Below you will find the sources used to construct the Wealth Inequality database, the first comprehensive compilation of cross-national time-series data on wealth inequality. The database utilizes data from academic research, government and private institutions (e.g., national statistical offices and central banks, international statistical institutions, and financial groups), and our own estimates from the available microdata. Links to technical documents and a description of the structure of the warehouse can be found on the Data and Documentation page.
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Distributional Financial Accounts. Federal Reserve. 2026.
@misc{FED_DWA_ineq,
title = {Distributional Financial Accounts},
author = {Federal Reserve},
year = {2026},
url = {https://www.federalreserve.gov/releases/z1/dataviz/dfa/index.html},
keywords = {Data Sources: Wealth Inequality}
}The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Development Research Group, Finance; and Private Sector Development Unit. World Bank, Development Data Group. 2025.
@misc{Findex_ineq,
title = {The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy},
author = {{Development Research Group, Finance and Private Sector Development Unit}},
year = {2025},
publisher = {World Bank, Development Data Group},
doi = {10.48529/BK9N-8R43},
url = {https://microdata.worldbank.org/index.php/catalog/study/WLD_2024_FINDEX_v02_M},
keywords = {Data Sources: Wealth Inequality}
}The Concentration of Personal Wealth in Italy 1995–2016. Acciari, Paolo; Alvaredo, Facundo; and Morelli, Salvatore. Journal of the European Economic Association. January 2024.
@article{Acciarietal2024,
title = {The Concentration of Personal Wealth in {{Italy}} 1995--2016},
author = {Acciari, Paolo and Alvaredo, Facundo and Morelli, Salvatore},
year = {2024},
month = {jan},
journal = {Journal of the European Economic Association},
doi = {10.1093/jeea/jvae002},
url = {https://doi.org/10.1093/jeea/jvae002},
abstract = {We estimate the distribution of wealth in Italy between 1995 and 2016 using a novel source of inheritance tax files, combined with surveys and national accounts. We find that the level of wealth concentration is in line with other European countries; however, its time trend appears more in line with the US, showing a significant increase over the period studied. The country exhibits one of the greatest declines in the wealth share of the bottom 50\%. The paper also shows that age plays a marginal role in explaining wealth concentration. Changes in savings, instead, are the predominant force behind the increase in wealth inequality, even at the top. Equity prices also account for a large share of wealth growth above the 99th percentile, whereas changes in house prices play only a minor role. Finally, we document the growing concentration of life-time wealth transfers, and their increasingly favorable tax treatment.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {jvae002},
url_file = {Acciarietal2024.pdf}
}We estimate the distribution of wealth in Italy between 1995 and 2016 using a novel source of inheritance tax files, combined with surveys and national accounts. We find that the level of wealth concentration is in line with other European countries; however, its time trend appears more in line with the US, showing a significant increase over the period studied. The country exhibits one of the greatest declines in the wealth share of the bottom 50%. The paper also shows that age plays a marginal role in explaining wealth concentration. Changes in savings, instead, are the predominant force behind the increase in wealth inequality, even at the top. Equity prices also account for a large share of wealth growth above the 99th percentile, whereas changes in house prices play only a minor role. Finally, we document the growing concentration of life-time wealth transfers, and their increasingly favorable tax treatment.
Online Appendix: The Concentration of Personal Wealth in Italy 1995–2016. Acciari, Paolo; Alvaredo, Facundo; and Morelli, Salvatore. January 2024.
@misc{Acciarietal2024app,
title = {Online Appendix: The Concentration of Personal Wealth in {{Italy}} 1995--2016},
author = {Acciari, Paolo and Alvaredo, Facundo and Morelli, Salvatore},
year = {2024},
month = {jan},
url = {https://doi.org/10.1093/jeea/jvae002},
keywords = {Data Sources: Wealth Inequality},
url_file = {Acciarietal2024app.pdf}
}Evidence from the dead: New estimates of wealth inequality using the distribution of estates. Alvaredo, Facundo; Berman, Yonatan; and Morelli, Salvatore. JSTOR. 2024.
@book{Alvaredo2024,
title = {Evidence from the dead: New estimates of wealth inequality using the distribution of estates},
author = {Alvaredo, Facundo and Berman, Yonatan and Morelli, Salvatore},
year = {2024},
publisher = {JSTOR},
url = {https://osf.io/preprints/socarxiv/a4frb_v2},
keywords = {Data Sources: Wealth Inequality}
}Experimental Distributional Wealth Accounts (DWA) for the Household Sector: Methodological Note. European Central Bank. January 2024.
@misc{EuropeanCentralBank2024_ExperimentalDistributionalWealthAccountsDWA,
title = {Experimental {{Distributional Wealth Accounts}} ({{DWA}}) for the Household Sector: Methodological Note},
author = {{European Central Bank}},
year = {2024},
month = {jan},
url = {https://data.ecb.europa.eu/sites/default/files/2024-01/DWA%20Methodological%20note_0.pdf},
urldate = {2024-09-06},
abstract = {The purpose of the Distributional Wealth Accounts (DWA), produced by the European System of Central Banks (ESCB), is to meet the growing interest in adding distributional information to macroeconomic sector accounts. This methodological note complements the Overview note (available on the ECB Data portal) summarising the data available, and provides more detailed information on how the Distributional Wealth Accounts are compiled.},
keywords = {Data Sources: Wealth Inequality},
url_file = {EuropeanCentralBank2024_ExperimentalDistributionalWealthAccountsDWA.pdf}
}The purpose of the Distributional Wealth Accounts (DWA), produced by the European System of Central Banks (ESCB), is to meet the growing interest in adding distributional information to macroeconomic sector accounts. This methodological note complements the Overview note (available on the ECB Data portal) summarising the data available, and provides more detailed information on how the Distributional Wealth Accounts are compiled.
Using Rich Lists to Study the Super-Rich and Top Wealth Inequality: Insights from Switzerland. Baselgia, Enea; and Martínez, Isabel Z. CESifo. March 2024.
@techreport{BaselgiaMartinez2024,
title = {Using Rich Lists to Study the Super-Rich and Top Wealth Inequality: Insights from {{Switzerland}}},
author = {Baselgia, Enea and Mart{\'i}nez, Isabel Z.},
year = {2024},
month = {mar},
number = {10993},
institution = {CESifo},
url = {https://doi.org/10.2139/ssrn.4756075},
abstract = {We present a new data set we built based on Swiss rich lists going back to 1989. We show, among other things, that 60\% of the super-rich are heirs---a fraction twice as large as in the US---and that wealth mobility at the very top has declined significantly. We find that top 0.01\% wealth shares are higher than previous estimates based on wealth tax statistics suggest. At the same time, we argue that rich list data lead to overestimating wealth inequality. While rich lists are valuable to study the super-rich, we recommend to use reported wealth figures with caution.},
keywords = {Data Sources: Wealth Inequality,Intergenerational Wealth,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_file = {BaselgiaMartinez2024.pdf}
}We present a new data set we built based on Swiss rich lists going back to 1989. We show, among other things, that 60% of the super-rich are heirs—a fraction twice as large as in the US—and that wealth mobility at the very top has declined significantly. We find that top 0.01% wealth shares are higher than previous estimates based on wealth tax statistics suggest. At the same time, we argue that rich list data lead to overestimating wealth inequality. While rich lists are valuable to study the super-rich, we recommend to use reported wealth figures with caution.
Kennickell (2021). Kennickell, Arthur. Review of Income and Wealth. 2024.
@misc{Kennickell2024,
title = {Kennickell (2021)},
author = {Kennickell, Arthur},
year = {2024},
journal = {Review of Income and Wealth},
doi = {10.1111/roiw.12696},
url = {https://doi.org/10.1111/roiw.12696},
abstract = {Since the work reported in Vermeulen (Review of Income and Wealth, 64(2), 357--387; 2018), a literature has developed using the simple Pareto distribution along with ``rich list'' information to improve estimates of the upper tail of the wealth distribution measured in surveys. Because the construction of such external data is typically opaque and subject to error, it may be best not to depend exclusively on this approach. This paper develops an alternative approach, using the generalized Pareto distribution (GPD), extending an estimation strategy developed by Castillo and Hadi (Journal of the American Statistical Association, 92(440), 1609--1620; 1997) in a novel way to survey data. The extension allows for addressing imperfections in the effective coverage of the upper tail of the wealth distribution, as well as allowing the imposition of an external measure of aggregate wealth as a constraint. The paper implements the method on Austrian survey data that has weak coverage of wealthy households. The results indicate that even with a range of plausible adjustments for data imperfections, relying only on the survey data to project the upper tail is insufficient to yield implied wealth aggregates in the range implied by aggregate figures. Imposing the implied aggregate as a constraint is necessary. The approach may be particularly useful in comparing survey-based inequality measures across and within countries and over time, as well as in constructing distributional financial accounts.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality}
}Since the work reported in Vermeulen (Review of Income and Wealth, 64(2), 357–387; 2018), a literature has developed using the simple Pareto distribution along with "rich list" information to improve estimates of the upper tail of the wealth distribution measured in surveys. Because the construction of such external data is typically opaque and subject to error, it may be best not to depend exclusively on this approach. This paper develops an alternative approach, using the generalized Pareto distribution (GPD), extending an estimation strategy developed by Castillo and Hadi (Journal of the American Statistical Association, 92(440), 1609–1620; 1997) in a novel way to survey data. The extension allows for addressing imperfections in the effective coverage of the upper tail of the wealth distribution, as well as allowing the imposition of an external measure of aggregate wealth as a constraint. The paper implements the method on Austrian survey data that has weak coverage of wealthy households. The results indicate that even with a range of plausible adjustments for data imperfections, relying only on the survey data to project the upper tail is insufficient to yield implied wealth aggregates in the range implied by aggregate figures. Imposing the implied aggregate as a constraint is necessary. The approach may be particularly useful in comparing survey-based inequality measures across and within countries and over time, as well as in constructing distributional financial accounts.
The Impact of Communist Party Membership on Wealth Distribution and Accumulation in Urban China. Targa, Matteo; and Yang, Li. World Development, 181. September 2024.
@article{TargaYang2024,
title = {The Impact of {{Communist Party}} Membership on Wealth Distribution and Accumulation in Urban {{China}}},
author = {Targa, Matteo and Yang, Li},
year = {2024},
month = {sep},
journal = {World Development},
volume = {181},
doi = {10.1016/j.worlddev.2024.106660},
url = {https://doi.org/10.1016/j.worlddev.2024.106660},
abstract = {This paper provides the first in-depth investigation into the evolution of the wealth gap between CCP and non-CCP households in urban China from 1995 to 2017. We apply unconditional quantile regression to analyze the variations in the premiums of party membership across the wealth distribution. Our results show that although the average wealth gap between CCP and non-CCP households remained substantial and consistent throughout the period, there have been significant shifts in the returns structure of party membership over time. Prior to the housing reform in the 1990s, the highest wealth premiums of CCP households were primarily concentrated in the middle of the distribution, but now they are concentrated at the bottom of the distribution. This is mainly attributed to the fact that CCP households at the lower end of the net wealth distribution are more inclined to possess housing assets, which tend to have higher value compared to those owned by non-CCP households. These effects fade out in the top half of the net wealth distribution, where the differences between CCP and non-CCP households become less apparent. Furthermore, by utilizing a balanced household panel from 2013 to 2017, we were able to track wealth accumulation at the household level. Our findings indicate that CCP households accumulate wealth faster than non-CCP households due to larger capital gains, and the differences between the two groups increase along the net wealth distribution.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {106660},
url_file = {TargaYang2024.pdf}
}This paper provides the first in-depth investigation into the evolution of the wealth gap between CCP and non-CCP households in urban China from 1995 to 2017. We apply unconditional quantile regression to analyze the variations in the premiums of party membership across the wealth distribution. Our results show that although the average wealth gap between CCP and non-CCP households remained substantial and consistent throughout the period, there have been significant shifts in the returns structure of party membership over time. Prior to the housing reform in the 1990s, the highest wealth premiums of CCP households were primarily concentrated in the middle of the distribution, but now they are concentrated at the bottom of the distribution. This is mainly attributed to the fact that CCP households at the lower end of the net wealth distribution are more inclined to possess housing assets, which tend to have higher value compared to those owned by non-CCP households. These effects fade out in the top half of the net wealth distribution, where the differences between CCP and non-CCP households become less apparent. Furthermore, by utilizing a balanced household panel from 2013 to 2017, we were able to track wealth accumulation at the household level. Our findings indicate that CCP households accumulate wealth faster than non-CCP households due to larger capital gains, and the differences between the two groups increase along the net wealth distribution.
Wealth Inequality Dynamics in Europe and the United States: Understanding the Determinants. Blanchet, Thomas; and Martínez-Toledano, Clara. Journal of Monetary Economics, 133: 25–43. January 2023.
@article{BlanchetMartinez-Toledano2023,
title = {Wealth Inequality Dynamics in {{Europe}} and the {{United States}}: Understanding the Determinants},
author = {Blanchet, Thomas and {Mart{\'i}nez-Toledano}, Clara},
year = {2023},
month = {jan},
journal = {Journal of Monetary Economics},
volume = {133},
pages = {25--43},
doi = {10.1016/j.jmoneco.2022.11.010},
url = {https://doi.org/10.1016/j.jmoneco.2022.11.010},
urldate = {2023-10-17},
abstract = {This paper studies the interaction between the long-term dynamics of aggregate household wealth and the wealth distribution in Europe and the United States. We do so by building the first Distributional Wealth Accounts for Europe, including households' assets, liabilities, investment flows, and the wealth distribution for most European countries from 1970--2020. We find that although aggregate household wealth to income ratios have followed a similar increasing pattern in both Europe and the United States since 1970, wealth concentration has increased much faster in the United States. Using wealth accumulation decompositions and counterfactual simulations, we show that the weaker rise in labor income inequality and the stronger rise in house prices relative to financial assets in Europe versus the United States appear to explain why Europe has experienced a more moderate rise in wealth concentration since the mid-1980s.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_working_paper = {https://bibbase.org/network/publication/blanchet-martineztoledano-wealthinequalitydynamicsineuropeandtheunitedstatesunderstandingthedeterminants-2022}
}This paper studies the interaction between the long-term dynamics of aggregate household wealth and the wealth distribution in Europe and the United States. We do so by building the first Distributional Wealth Accounts for Europe, including households' assets, liabilities, investment flows, and the wealth distribution for most European countries from 1970–2020. We find that although aggregate household wealth to income ratios have followed a similar increasing pattern in both Europe and the United States since 1970, wealth concentration has increased much faster in the United States. Using wealth accumulation decompositions and counterfactual simulations, we show that the weaker rise in labor income inequality and the stronger rise in house prices relative to financial assets in Europe versus the United States appear to explain why Europe has experienced a more moderate rise in wealth concentration since the mid-1980s.
Wealth Inequality in Latin America. Carranza, Rafael; De Rosa, Mauricio; and Flores, Ignacio. International Inequalities Institute. June 2023.
@techreport{Carranzaetal2023,
title = {Wealth Inequality in {{Latin America}}},
author = {Carranza, Rafael and De Rosa, Mauricio and Flores, Ignacio},
year = {2023},
month = {jun},
number = {108},
institution = {International Inequalities Institute},
url = {https://eprints.lse.ac.uk/119426/},
urldate = {2023-10-17},
abstract = {How wealth has accumulated in the region and how is it distributed across households? Despite being widely recognized for its extreme income inequality, reliable data on wealth is scarce, partial and oftentimes contradictory, making it difficult to answer these basic questions. In this study, we estimate aggregates based on macroeconomic data, and inequality based on recently available surveys. We contrast our results with the literature, with a handful of state-of-the-art estimates from administrative sources, and with more available but extrapolated estimates from Credit Suisse and wid.world. Considering all the evidence, we distinguish reliable facts from what can only be conjectured or speculated. We find that aggregate wealth increased over two decades in four countries, now ranging close to 3.5 the national income for market value estimates and 5-6 times at book values. We also find that wealth inequality is amongst the highest in the world were it can be measured. Given data limitations, one can only speculate about aggregates in opaque countries and about inequality trends in any country in the region. Although recent research in the developed world has focused in combining data sources to better understand wealth, the region lags behind and urgently requires more and better public information.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Trends in Aggregate Wealth and Wealth Inequality},
type = {{{III Working Paper}}},
url_file = {Carranzaetal2023.pdf}
}How wealth has accumulated in the region and how is it distributed across households? Despite being widely recognized for its extreme income inequality, reliable data on wealth is scarce, partial and oftentimes contradictory, making it difficult to answer these basic questions. In this study, we estimate aggregates based on macroeconomic data, and inequality based on recently available surveys. We contrast our results with the literature, with a handful of state-of-the-art estimates from administrative sources, and with more available but extrapolated estimates from Credit Suisse and wid.world. Considering all the evidence, we distinguish reliable facts from what can only be conjectured or speculated. We find that aggregate wealth increased over two decades in four countries, now ranging close to 3.5 the national income for market value estimates and 5-6 times at book values. We also find that wealth inequality is amongst the highest in the world were it can be measured. Given data limitations, one can only speculate about aggregates in opaque countries and about inequality trends in any country in the region. Although recent research in the developed world has focused in combining data sources to better understand wealth, the region lags behind and urgently requires more and better public information.
On Top of the Top: A Generalized Approach to the Estimation of Wealth Distributions. Disslbacher, Franziska; Ertl, Michael; List, Emanuel; Mokre, Patrick; and Schnetzer, Matthias. July 2023.
@unpublished{Disslbacheretal2023,
title = {On Top of the Top: A Generalized Approach to the Estimation of Wealth Distributions},
author = {Disslbacher, Franziska and Ertl, Michael and List, Emanuel and Mokre, Patrick and Schnetzer, Matthias},
year = {2023},
month = {jul},
doi = {10.2139/ssrn.4499915},
url = {https://doi.org/10.2139/ssrn.4499915},
abstract = {The wealth distribution is infamously top-heavy, while the decisive upper tail is missing from survey data on household wealth in European countries. We provide a novel quantile regression approach to estimate all parameters of the Pareto and Generalized Pareto distribution to adjust for the rich missing in survey data due to differential non-response and under-reporting. In contrast to existing Pareto-based adjustment routines, the generalized and rules-based method is scalable, flexible in the face of heterogeneities in data quality and wealth accumulation regimes, transparent, and prevents over-shooting of wealth aggregates and wealth concentration estimates. We apply the method to data on fourteen Eurozone countries by supplementing the Household Finance and Consumption Survey (HFCS) with a novel database on country-specific rich lists from the European Rich List Database (ERLDB) compiled from country-specific rich lists. The magnitude of the resulting upper-tail adjustments varies substantially across countries, highlighting the importance of the rules-based method developed here. In addition, while the results are highly stable across an extensive range of sensitivity tests addressing the opacities of ERLDB data, the resulting estimates vary substantially across parameters borrowed from prior work.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Trends in Aggregate Wealth and Wealth Inequality},
note = {Unpublished manuscript},
url_file = {Disslbacheretal2023.pdf}
}The wealth distribution is infamously top-heavy, while the decisive upper tail is missing from survey data on household wealth in European countries. We provide a novel quantile regression approach to estimate all parameters of the Pareto and Generalized Pareto distribution to adjust for the rich missing in survey data due to differential non-response and under-reporting. In contrast to existing Pareto-based adjustment routines, the generalized and rules-based method is scalable, flexible in the face of heterogeneities in data quality and wealth accumulation regimes, transparent, and prevents over-shooting of wealth aggregates and wealth concentration estimates. We apply the method to data on fourteen Eurozone countries by supplementing the Household Finance and Consumption Survey (HFCS) with a novel database on country-specific rich lists from the European Rich List Database (ERLDB) compiled from country-specific rich lists. The magnitude of the resulting upper-tail adjustments varies substantially across countries, highlighting the importance of the rules-based method developed here. In addition, while the results are highly stable across an extensive range of sensitivity tests addressing the opacities of ERLDB data, the resulting estimates vary substantially across parameters borrowed from prior work.
The Household Finance and Consumption Survey: Methodological Report for the 2021 Wave. Household Finance; and Consumption Network. European Central Bank. July 2023.
@techreport{HouseholdFinanceandConsumptionNetwork2023,
title = {The {{Household Finance}} and {{Consumption Survey}}: Methodological Report for the 2021 Wave},
author = {{Household Finance and Consumption Network}},
year = {2023},
month = {jul},
number = {45},
institution = {European Central Bank},
doi = {10.2866/970554},
url = {https://doi.org/10.2866/970554},
abstract = {This report summarises the methodologies used in the fourth wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in all 19 euro area countries, as well as in the Czech Republic, Croatia and Hungary. The total sample size is composed of more than 83,000 households. Although the survey does not refer to the same time period in all countries, the most common reference period for the data is 2021. The report presents the methodologies applied in areas such as data collection, sample design, weighting, imputation, and variance estimation. It also addresses statistical disclosure control issues and analyses issues that may have an effect on the comparability of the survey data across countries and across waves.},
keywords = {Data Sources: Wealth Inequality},
type = {{{ECB Statistics Paper Series}}},
url_data = {https://bibbase.org/network/publication/householdfinance-network-householdfinanceandconsumptionsurvey-2021},
url_file = {HouseholdFinanceandConsumptionNetwork2023.pdf}
}This report summarises the methodologies used in the fourth wave of the Eurosystem Household Finance and Consumption Survey, which provides household-level data collected in a harmonised way in all 19 euro area countries, as well as in the Czech Republic, Croatia and Hungary. The total sample size is composed of more than 83,000 households. Although the survey does not refer to the same time period in all countries, the most common reference period for the data is 2021. The report presents the methodologies applied in areas such as data collection, sample design, weighting, imputation, and variance estimation. It also addresses statistical disclosure control issues and analyses issues that may have an effect on the comparability of the survey data across countries and across waves.
A Micro Perspective on r $>$ g. Iacono, Roberto; and Palagi, Elisa. Economica, 90(358): 531–556. April 2023.
@article{IaconoPalagi2023,
title = {A Micro Perspective on r {$>$} g},
author = {Iacono, Roberto and Palagi, Elisa},
year = {2023},
month = {apr},
journal = {Economica},
volume = {90},
number = {358},
pages = {531--556},
doi = {10.1111/ecca.12464},
url = {https://doi.org/10.1111/ecca.12464},
abstract = {By exploiting large-scale administrative data on income and estimated personal wealth in Norway from 2010 to 2018, this paper establishes the first micro-level analysis of the difference between the real return on wealth and the real growth rate of total pre-tax income, across the entire net wealth distribution. We show that for the top 40\% of the distribution, the aggregate R-G of 1.8\% underestimates its micro counterpart r-g, while the opposite happens for the bottom 60\%. Moreover, for the bottom 50\% of the net wealth distribution, it is indeed the case that r},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_file = {IaconoPalagi2023.pdf}
}By exploiting large-scale administrative data on income and estimated personal wealth in Norway from 2010 to 2018, this paper establishes the first micro-level analysis of the difference between the real return on wealth and the real growth rate of total pre-tax income, across the entire net wealth distribution. We show that for the top 40% of the distribution, the aggregate R-G of 1.8% underestimates its micro counterpart r-g, while the opposite happens for the bottom 60%. Moreover, for the bottom 50% of the net wealth distribution, it is indeed the case that r
Welfare of Households; Key Figures. Statistics Netherlands. November 2023.
@misc{StatisticsNetherlands2023_WelfareHouseholdsKeyFigures,
title = {Welfare of Households; Key Figures},
author = {{Statistics Netherlands}},
year = {2023},
month = {nov},
url = {https://opendata.cbs.nl/statline/#/CBS/en/dataset/83739eng/table?ts=1581951486682},
urldate = {2024-03-19},
keywords = {Data Sources: Wealth Inequality},
note = {StatLine},
url_file = {StatisticsNetherlands2023_WelfareHouseholdsKeyFigures.csv}
}Global Wealth Databook 2023. Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Waldenström, Daniel. 2023.
@misc{Shorrocksetal2023,
title = {Global Wealth Databook 2023},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Waldenstr{\"o}m, Daniel},
year = {2023},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2024-10-04},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2023.pdf}
}Global Wealth Report 2023. Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Waldenström, Daniel. June 2023.
@misc{Shorrocksetal2023a,
title = {Global Wealth Report 2023},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Waldenstr{\"o}m, Daniel},
year = {2023},
month = {jun},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2024-10-04},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2023a.pdf}
}Top Wealth in America: New Estimates under Heterogeneous Returns. Smith, Matthew; Zidar, Owen; and Zwick, Eric. The Quarterly Journal of Economics, 138(1): 515–573. February 2023.
@article{Smithetal2023,
title = {Top Wealth in {{America}}: New Estimates under Heterogeneous Returns},
author = {Smith, Matthew and Zidar, Owen and Zwick, Eric},
year = {2023},
month = {feb},
journal = {The Quarterly Journal of Economics},
volume = {138},
number = {1},
pages = {515--573},
doi = {10.1093/qje/qjac033},
url = {https://doi.org/10.1093/qje/qjac033},
abstract = {This article uses administrative tax data to estimate top wealth in the United States. We assemble new data that link people to their sources of capital income and develop new methods to estimate the degree of return heterogeneity within asset classes. Disaggregated fixed-income data reveal that rich individuals earn much more of their interest income in higher-yielding forms and have much greater exposure to credit risk. Consequently, in recent years, the interest rate on fixed income at the top is approximately 3.5 times higher than the average. We value the population of U.S. firms using firm-level characteristics and apportion this wealth using firm-owner links. We combine this new data on fixed income and pass-through business returns with refined estimates of C-corporation equity, housing, and pension wealth to deliver new capitalized wealth estimates that build upon the methods of Saez and Zucman (2016a). From 1989 to 2016, the top 1\%, 0.1\%, and 0.01\% wealth shares increased by 6.6, 4.6, and 2.9 percentage points, respectively, to 33.7\%, 15.7\%, and 7.1\%. Overall, although we estimate a large degree of return heterogeneity, accounting for this heterogeneity does not change the fundamental story for top wealth shares and their growth---wealth inequality is high and has risen substantially over recent decades.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_2020_working_paper = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesandimplicationsfortaxingtherich-2020},
url_online_appendix = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesunderheterogeneousreturnsonlineappendix-2022},
url_replication_package = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesunderheterogeneousreturnsreplicationpackage-2022}
}This article uses administrative tax data to estimate top wealth in the United States. We assemble new data that link people to their sources of capital income and develop new methods to estimate the degree of return heterogeneity within asset classes. Disaggregated fixed-income data reveal that rich individuals earn much more of their interest income in higher-yielding forms and have much greater exposure to credit risk. Consequently, in recent years, the interest rate on fixed income at the top is approximately 3.5 times higher than the average. We value the population of U.S. firms using firm-level characteristics and apportion this wealth using firm-owner links. We combine this new data on fixed income and pass-through business returns with refined estimates of C-corporation equity, housing, and pension wealth to deliver new capitalized wealth estimates that build upon the methods of Saez and Zucman (2016a). From 1989 to 2016, the top 1%, 0.1%, and 0.01% wealth shares increased by 6.6, 4.6, and 2.9 percentage points, respectively, to 33.7%, 15.7%, and 7.1%. Overall, although we estimate a large degree of return heterogeneity, accounting for this heterogeneity does not change the fundamental story for top wealth shares and their growth—wealth inequality is high and has risen substantially over recent decades.
DFA: Distributional Financial Accounts. Board of Governors of the Federal Reserve System. June 2023.
@misc{BoardofGovernorsoftheFederalReserveSystem2023_DFADistributionalFinancialAccounts,
title = {{{DFA}}: {{Distributional Financial Accounts}}},
author = {{Board of Governors of the Federal Reserve System}},
year = {2023},
month = {jun},
url = {https://www.federalreserve.gov/releases/z1/dataviz/dfa/},
urldate = {2023-08-08},
keywords = {Data Sources: Wealth Inequality},
url_file = {BoardofGovernorsoftheFederalReserveSystem2023_DFADistributionalFinancialAccounts.zip}
}Data Appendix for Wealth and Its Distribution in Germany, 1895-2018. Albers, Thilo N. H.; Bartels, Charlotte; and Schularick, Moritz. April 2022.
@misc{Albersetal2022app,
title = {Data Appendix for Wealth and Its Distribution in {{Germany}}, 1895-2018},
author = {Albers, Thilo N. H. and Bartels, Charlotte and Schularick, Moritz},
year = {2022},
month = {apr},
url = {https://sites.google.com/site/charlottedsbartels/work-in-progress?authuser=0},
urldate = {2022-05-05},
abstract = {This Data Appendix supplements the paper 'Wealth and its distribution in Germany, 1895-2018'},
keywords = {Data Sources: Wealth Inequality},
url_file = {Albersetal2022app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/albers-bartels-schularick-wealthanditsdistributioningermany18952018-2022}
}This Data Appendix supplements the paper 'Wealth and its distribution in Germany, 1895-2018'
Wealth and Its Distribution in Germany, 1895-2018. Albers, Thilo N. H.; Bartels, Charlotte; and Schularick, Moritz. CESifo. May 2022.
@techreport{Albersetal2022,
title = {Wealth and Its Distribution in {{Germany}}, 1895-2018},
author = {Albers, Thilo N. H. and Bartels, Charlotte and Schularick, Moritz},
year = {2022},
month = {may},
number = {9739},
institution = {CESifo},
doi = {10.2139/ssrn.4103952},
url = {https://doi.org/10.2139/ssrn.4103952},
abstract = {German history over the past 125 years has been turbulent. Marked by two world wars, revolutions and major regime changes, as well as a hyperinflation and three currency reforms, expropriations and territorial divisions, it provides unique insights into the role of country-specific shocks in shaping long-run wealth dynamics. This paper presents the first comprehensive study of wealth and its distribution in Germany since the 19th century. We combine tax and archival data, household surveys, historical national accounts, and rich lists to analyze the evolution of the German wealth distribution over the long run. We show that the top 1\% wealth share has fallen by half, from close to 50\% in 1895 to 27\% today. Nearly all of this decline was the result of changes that occurred between 1914 and 1952. The interwar period and the wealth taxation in the aftermath of World War II stand out as the great equalizers in 20th century German history. After unification in 1990, two trends have left their mark on the German wealth distribution. Households at the top made substantial capital gains from rising business wealth while the middle-class had large capital gains in the housing market. The wealth share of the bottom 50\% halved since 1990. Our findings speak to the importance of historical shocks to the distribution and valuations of existing wealth in explaining the evolution of the wealth distribution over the long run.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_data_appendix = {https://bibbase.org/network/publication/albers-bartels-schularick-dataappendixforwealthanditsdistributioningermany18952018-2022},
url_data_files = {https://bibbase.org/network/publication/albers-bartels-schularick-wealthanditsdistributioningermany18952018datafiles-2022},
url_file = {Albersetal2022.pdf}
}German history over the past 125 years has been turbulent. Marked by two world wars, revolutions and major regime changes, as well as a hyperinflation and three currency reforms, expropriations and territorial divisions, it provides unique insights into the role of country-specific shocks in shaping long-run wealth dynamics. This paper presents the first comprehensive study of wealth and its distribution in Germany since the 19th century. We combine tax and archival data, household surveys, historical national accounts, and rich lists to analyze the evolution of the German wealth distribution over the long run. We show that the top 1% wealth share has fallen by half, from close to 50% in 1895 to 27% today. Nearly all of this decline was the result of changes that occurred between 1914 and 1952. The interwar period and the wealth taxation in the aftermath of World War II stand out as the great equalizers in 20th century German history. After unification in 1990, two trends have left their mark on the German wealth distribution. Households at the top made substantial capital gains from rising business wealth while the middle-class had large capital gains in the housing market. The wealth share of the bottom 50% halved since 1990. Our findings speak to the importance of historical shocks to the distribution and valuations of existing wealth in explaining the evolution of the wealth distribution over the long run.
Wealth and Its Distribution in Germany, 1895-2018: Data Files. Albers, Thilo N. H.; Bartels, Charlotte; and Schularick, Moritz. 2022.
@misc{Albersetal2022data,
title = {Wealth and Its Distribution in {{Germany}}, 1895-2018: Data Files},
author = {Albers, Thilo N. H. and Bartels, Charlotte and Schularick, Moritz},
year = {2022},
url = {https://bibbase.org/network/publication/albers-bartels-schularick-wealthanditsdistributioningermany18952018datafiles-2022},
abstract = {Received from the authors.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Albersetal2022data.zip},
url_parent_paper = {https://bibbase.org/network/publication/albers-bartels-schularick-wealthanditsdistributioningermany18952018-2022}
}Received from the authors.
The Sky and the Stratosphere: Concentrated Wealth in India during the `Lost Decade'. Anand, Ishan; and Kumar, Rishabh. February 2022.
@unpublished{AnandKumar2022,
title = {The Sky and the Stratosphere: Concentrated Wealth in {{India}} during the `Lost Decade'},
author = {Anand, Ishan and Kumar, Rishabh},
year = {2022},
month = {feb},
doi = {10.31235/osf.io/726c8},
url = {https://doi.org/10.31235/osf.io/726c8},
abstract = {Recently released official survey data show a decline in wealth inequality (measured by the Gini) and wealth concentration (shares of the top fractiles) over 2012-2018. We investigate a puzzling detail -- the rich hold equities, whose prices increased over 2012-2018, while the middle class holds precious metals, whose prices declined over the same period. The survey predicts the richest Indian to be worth Rs 244 million in 2018; according to glossy magazine covers, the richest Indian has, in fact, a net worth of Rs 2,560 billion. We correct this series using data from named rich lists and find that the decline in wealth inequality is more modest. More strikingly, we find a sharp increase in wealth concentration, with the share of the Top 0.001 percent doubling in size -- as of 2018, the wealth of the richest 7000 (approx.) Indians exceeds the wealth of the poorest 50 percent.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {Unpublished manuscript},
url_file = {AnandKumar2022.pdf},
url_published_version = {https://bibbase.org/network/publication/anand-kumar-theskyandthestratospherewealthconcentrationinindiaduringthelastlostdecade-2023},
url_supplementary_data = {https://bibbase.org/network/publication/anand-kumar-theskyandthestratosphereconcentratedwealthinindiaduringthelostdecadesupplementarydata-2022}
}Recently released official survey data show a decline in wealth inequality (measured by the Gini) and wealth concentration (shares of the top fractiles) over 2012-2018. We investigate a puzzling detail – the rich hold equities, whose prices increased over 2012-2018, while the middle class holds precious metals, whose prices declined over the same period. The survey predicts the richest Indian to be worth Rs 244 million in 2018; according to glossy magazine covers, the richest Indian has, in fact, a net worth of Rs 2,560 billion. We correct this series using data from named rich lists and find that the decline in wealth inequality is more modest. More strikingly, we find a sharp increase in wealth concentration, with the share of the Top 0.001 percent doubling in size – as of 2018, the wealth of the richest 7000 (approx.) Indians exceeds the wealth of the poorest 50 percent.
The Sky and the Stratosphere: Concentrated Wealth in India during the `Lost Decade': Supplementary Data. Anand, Ishan; and Kumar, Rishabh. 2022.
@misc{AnandKumar2022data,
title = {The Sky and the Stratosphere: Concentrated Wealth in {{India}} during the `Lost Decade': Supplementary Data},
author = {Anand, Ishan and Kumar, Rishabh},
year = {2022},
doi = {10.31235/osf.io/726c8},
url = {https://doi.org/10.31235/osf.io/726c8},
keywords = {Data Sources: Wealth Inequality},
url_file = {AnandKumar2022data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/anand-kumar-theskyandthestratosphereconcentratedwealthinindiaduringthelostdecade-2022},
url_published_version = {https://bibbase.org/network/publication/anand-kumar-theskyandthestratospherewealthconcentrationinindiaduringthelastlostdecade-2023}
}The Distributional Financial Accounts of the United States. Batty, Michael; Bricker, Jesse; Briggs, Joseph; Friedman, Sarah; Nemschoff, Danielle; Nielsen, Eric; Sommer, Kamila; and Volz, Alice Henriques. Measuring Distribution and Mobility of Income and Wealth, pp. 641–677. October 2022.
@inproceedings{Battyetal2022,
title = {The {{Distributional Financial Accounts}} of the {{United States}}},
author = {Batty, Michael and Bricker, Jesse and Briggs, Joseph and Friedman, Sarah and Nemschoff, Danielle and Nielsen, Eric and Sommer, Kamila and Volz, Alice Henriques},
year = {2022},
month = {oct},
booktitle = {Measuring Distribution and Mobility of Income and Wealth},
pages = {641--677},
publisher = {University of Chicago Press},
doi = {10.7208/chicago/9780226816043-025},
url = {https://www.nber.org/books-and-chapters/measuring-distribution-and-mobility-income-and-wealth/distributional-financial-accounts-united-states},
urldate = {2023-08-08},
abstract = {This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of US household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products---quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances---to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of US household wealth.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {Chapter 22},
address = {Chicago},
editor = {Chetty, Raj and Friedman, John N. and Gornick, Janet C. and Johnson, Barry and Kennickell, Arthur},
url_2019_working_paper = {https://bibbase.org/network/publication/batty-bricker-briggs-holmquist-mcintosh-moore-nielsen-reber-etal-introducingthedistributionalfinancialaccountsoftheunitedstates-2019},
url_2020_working_paper = {https://bibbase.org/network/publication/batty-bricker-briggs-friedman-nemschoff-nielsen-sommer-volz-thedistributionalfinancialaccountsoftheunitedstates-2020},
url_dfas = {https://bibbase.org/network/publication/boardofgovernorsofthefederalreservesystem-dfadistributionalfinancialaccounts-2023}
}This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of US household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products—quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances—to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of US household wealth.
Supplementary Online Appendix: Wealth Inequality in South Africa, 1993–2017. Chatterjee, Aroop; Czajka, Léo; and Gethin, Amory. February 2022.
@misc{Chatterjeeetal2022app,
title = {Supplementary Online Appendix: Wealth Inequality in {{South Africa}}, 1993--2017},
author = {Chatterjee, Aroop and Czajka, L{\'e}o and Gethin, Amory},
year = {2022},
month = {feb},
doi = {10.1093/wber/lhab012},
url = {https://doi.org/10.1093/wber/lhab012},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/chatterjee-czajka-gethin-wealthinequalityinsouthafrica19932017-2022}
}Wealth Inequality in South Africa, 1993–2017. Chatterjee, Aroop; Czajka, Léo; and Gethin, Amory. The World Bank Economic Review, 36(1): 19–36. February 2022.
@article{Chatterjeeetal2022,
title = {Wealth Inequality in {{South Africa}}, 1993--2017},
author = {Chatterjee, Aroop and Czajka, L{\'e}o and Gethin, Amory},
year = {2022},
month = {feb},
journal = {The World Bank Economic Review},
volume = {36},
number = {1},
pages = {19--36},
doi = {10.1093/wber/lhab012},
url = {https://doi.org/10.1093/wber/lhab012},
abstract = {This article estimates the distribution of personal wealth in South Africa by combining microdata covering the universe of income tax returns, household surveys, and macroeconomic balance sheet statistics. South Africa is characterized by unparalleled levels of wealth concentration. The top 10 percent own 86 percent of aggregate wealth and the top 0.1 percent close to one-third. The top 0.01 percent of the distribution (3,500 individuals) concentrate 15 percent of household net worth, more than the bottom 90 percent as a whole. Such levels of inequality can be accounted for in all forms of assets at the top end, including housing, pension funds, and financial assets. There has been no sign of decreasing inequality since the end of apartheid.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/chatterjee-czajka-gethin-wealthinequalityinsouthafrica19932017datafile-2022},
url_supplementary_online_appendix = {https://bibbase.org/network/publication/chatterjee-czajka-gethin-supplementaryonlineappendixwealthinequalityinsouthafrica19932017-2022}
}This article estimates the distribution of personal wealth in South Africa by combining microdata covering the universe of income tax returns, household surveys, and macroeconomic balance sheet statistics. South Africa is characterized by unparalleled levels of wealth concentration. The top 10 percent own 86 percent of aggregate wealth and the top 0.1 percent close to one-third. The top 0.01 percent of the distribution (3,500 individuals) concentrate 15 percent of household net worth, more than the bottom 90 percent as a whole. Such levels of inequality can be accounted for in all forms of assets at the top end, including housing, pension funds, and financial assets. There has been no sign of decreasing inequality since the end of apartheid.
Wealth Inequality in South Africa, 1993–2017: Data File. Chatterjee, Aroop; Czajka, Léo; and Gethin, Amory. 2022.
@misc{Chatterjeeetal2022data,
title = {Wealth Inequality in {{South Africa}}, 1993--2017: Data File},
author = {Chatterjee, Aroop and Czajka, L{\'e}o and Gethin, Amory},
year = {2022},
url = {https://wid.world/methodology/#library-raw-datasets},
keywords = {Data Sources: Wealth Inequality},
url_file = {Chatterjeeetal2022data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/chatterjee-czajka-gethin-wealthinequalityinsouthafrica19932017-2022}
}Documentation of Statistics Households' Assets. Statistics Finland. October 2022.
@misc{StatisticsFinland2021app,
title = {Documentation of Statistics Households' Assets},
author = {{Statistics Finland}},
year = {2022},
month = {oct},
url = {https://stat.fi/en/statistics/documentation/vtutk},
urldate = {2022-12-09},
keywords = {Data Sources: Wealth Inequality},
url_file = {StatisticsFinland2021app.pdf},
url_parent_data = {https://bibbase.org/network/publication/statisticsfinland-136zassetsliabilitiesandincomeofhouseholdsbynetwealthdecilegroupin19872019-2021}
}House Price Cycles, Wealth Inequality and Portfolio Reshuffling. Martínez-Toledano, Clara. August 2022.
@unpublished{Martinez-Toledano2022,
title = {House Price Cycles, Wealth Inequality and Portfolio Reshuffling},
author = {{Mart{\'i}nez-Toledano}, Clara},
year = {2022},
month = {aug},
url = {https://sites.google.com/view/claramartinez-toledanotoledano/research},
urldate = {2022-09-29},
abstract = {This paper studies the determinants of wealth inequality during housing booms and busts. I examine two episodes over the last four decades in Spain by combining fiscal data with household surveys and national accounts. I find that heterogeneity in capital gains is the main driver behind the fall in wealth inequality during housing booms, while heterogeneity in saving rates and portfolio choices are the main explanatory forces of the rise in wealth concentration during housing busts. Top wealth holders are better at timing the market and reshuffling their portfolios, as they appear to be subject to less portfolio adjustment frictions.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {Unpublished manuscript},
url_data_file = {https://bibbase.org/network/publication/martineztoledano-housepricecycleswealthinequalityandportfolioreshufflingdatafile-2022},
url_file = {Martinez-Toledano2022.pdf}
}This paper studies the determinants of wealth inequality during housing booms and busts. I examine two episodes over the last four decades in Spain by combining fiscal data with household surveys and national accounts. I find that heterogeneity in capital gains is the main driver behind the fall in wealth inequality during housing booms, while heterogeneity in saving rates and portfolio choices are the main explanatory forces of the rise in wealth concentration during housing busts. Top wealth holders are better at timing the market and reshuffling their portfolios, as they appear to be subject to less portfolio adjustment frictions.
House Price Cycles, Wealth Inequality and Portfolio Reshuffling: Data File. Martínez-Toledano, Clara. 2022.
@misc{Martinez-Toledano2022data,
title = {House Price Cycles, Wealth Inequality and Portfolio Reshuffling: Data File},
author = {{Mart{\'i}nez-Toledano}, Clara},
year = {2022},
url = {https://wid.world/document/house-price-cycles-wealth-inequality-and-portfolio-reshuffling-wid-world-working-paper-2020-02/},
keywords = {Data Sources: Wealth Inequality},
url_file = {Martinez-Toledano2022data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/martineztoledano-housepricecycleswealthinequalityandportfolioreshuffling-2022}
}10318: Share of Total Estimated Net Wealth, Average Estimated Net Wealth and Lowest Value in Decile for Households, by Decile 2010 - 2020. Statistics Norway. March 2022.
Income and Wealth Statistics for Households. Statistics Norway. September 2022.
@misc{StatisticsNorway2022app,
title = {Income and Wealth Statistics for Households},
author = {{Statistics Norway}},
year = {2022},
month = {sep},
url = {https://www.ssb.no/en/inntekt-og-forbruk/inntekt-og-formue/statistikk/inntekts-og-formuesstatistikk-for-husholdninger},
urldate = {2022-12-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {StatisticsNorway2022app.pdf},
url_parent_data = {https://bibbase.org/network/publication/statisticsnorway-10318shareoftotalestimatednetwealthaverageestimatednetwealthandlowestvalueindecileforhouseholdsbydecile20102020-2022}
}Income and Wealth Inequality in Hong Kong, 1981–2020: The Rise of Pluto-Communism? Piketty, Thomas; and Yang, Li. The World Bank Economic Review, 36(4): 803–834. November 2022.
@article{PikettyYang2022,
title = {Income and Wealth Inequality in {{Hong Kong}}, 1981--2020: The Rise of Pluto-Communism?},
author = {Piketty, Thomas and Yang, Li},
year = {2022},
month = {nov},
journal = {The World Bank Economic Review},
volume = {36},
number = {4},
pages = {803--834},
doi = {10.1093/wber/lhac019},
url = {https://doi.org/10.1093/wber/lhac019},
abstract = {The objective of this paper is to better understand the evolution and institutional roots of Hong Kong's growing economic inequality and political cleavages. By combining multiple sources of data (household surveys, fiscal data, wealth rankings, national accounts) and methodological innovations, two main findings are obtained. First, he evidence suggests a very large rise in income and wealth inequality in Hong Kong over the last four decades. Second, based on the latest opinion poll data, business elites, who carry disproportionate weight in Hong Kong's Legislative Council, are found to be more likely to vote for the pro-establishment camp (presumably to ensure that policies are passed that protect their political and economic interests). This paper argues that the unique alliance of government and business elites in a partially democratic political system is the plausible institutional root of Hong Kong's rising inequality and political cleavages.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality}
}The objective of this paper is to better understand the evolution and institutional roots of Hong Kong's growing economic inequality and political cleavages. By combining multiple sources of data (household surveys, fiscal data, wealth rankings, national accounts) and methodological innovations, two main findings are obtained. First, he evidence suggests a very large rise in income and wealth inequality in Hong Kong over the last four decades. Second, based on the latest opinion poll data, business elites, who carry disproportionate weight in Hong Kong's Legislative Council, are found to be more likely to vote for the pro-establishment camp (presumably to ensure that policies are passed that protect their political and economic interests). This paper argues that the unique alliance of government and business elites in a partially democratic political system is the plausible institutional root of Hong Kong's rising inequality and political cleavages.
Global Wealth Databook 2022. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. September 2022.
@misc{Shorrocksetal2022,
title = {Global Wealth Databook 2022},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2022},
month = {sep},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2024-10-04},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2022.pdf}
}Global Wealth Report 2022. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. September 2022.
@misc{Shorrocksetal2022a,
title = {Global Wealth Report 2022},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2022},
month = {sep},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2024-10-04},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2022a.pdf}
}Top Wealth in America: New Estimates under Heterogeneous Returns: Online Appendix. Smith, Matthew; Zidar, Owen; and Zwick, Eric. July 2022.
@misc{Smithetal2023app,
title = {Top Wealth in {{America}}: New Estimates under Heterogeneous Returns: Online Appendix},
author = {Smith, Matthew and Zidar, Owen and Zwick, Eric},
year = {2022},
month = {jul},
url = {http://ericzwick.com/},
keywords = {Data Sources: Wealth Inequality},
url_file = {Smithetal2023app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesunderheterogeneousreturns-2023}
}Top Wealth in America: New Estimates under Heterogeneous Returns: Replication Package. Smith, Matthew; Zidar, Owen; and Zwick, Eric. 2022.
@misc{Smithetal2023data,
title = {Top Wealth in {{America}}: New Estimates under Heterogeneous Returns: Replication Package},
author = {Smith, Matthew and Zidar, Owen and Zwick, Eric},
year = {2022},
url = {http://ericzwick.com/},
urldate = {2023-06-05},
keywords = {Data Sources: Wealth Inequality},
url_file = {Smithetal2023data.zip},
url_parent_paper = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesunderheterogeneousreturns-2023}
}Australian National Accounts: Distribution of Household Income, Consumption and Wealth. Australian Bureau of Statistics. December 2022.
@misc{AustralianBureauofStatistics2022_AustralianNationalAccountsDistributionHousehold,
title = {Australian {{National Accounts}}: Distribution of Household Income, Consumption and Wealth},
author = {{Australian Bureau of Statistics}},
year = {2022},
month = {dec},
url = {https://www.abs.gov.au/statistics/economy/national-accounts/australian-national-accounts-distribution-household-income-consumption-and-wealth/2021-22-financial-year},
urldate = {2023-01-25},
abstract = {Integrates ABS micro and macro data to produce distributional information of household income, consumption and wealth. The file we have utilized (attached) is "Table 2 Household (excluding non-profit institutions serving households) income, consumption and wealth, share of total household, by household distributional indicator, per cent", or "5204055011do002.xlsx".},
keywords = {Data Sources: Wealth Inequality},
url_2013_documentation = {https://bibbase.org/network/publication/australianbureauofstatistics-5204055009informationpaperaustraliannationalaccountsdistributionofhouseholdincomeconsumptionandwealth200910-2013},
url_file = {AustralianBureauofStatistics2022_AustralianNationalAccountsDistributionHousehold.xlsx}
}Integrates ABS micro and macro data to produce distributional information of household income, consumption and wealth. The file we have utilized (attached) is "Table 2 Household (excluding non-profit institutions serving households) income, consumption and wealth, share of total household, by household distributional indicator, per cent", or "5204055011do002.xlsx".
Household Net Worth Data Collection 2020/21. StatsNZ. June 2022.
@misc{StatsNZ2022_HouseholdNetWorthDataCollection,
title = {Household Net Worth Data Collection 2020/21},
author = {{StatsNZ}},
year = {2022},
month = {jun},
url = {https://datainfoplus.stats.govt.nz/item/nz.govt.stats/ba211f92-b4ad-4b3c-9630-662138009889#},
urldate = {2022-09-29},
keywords = {Data Sources: Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/statsnz-householdnetworthstatisticsyearendedjune2021-2022},
url_file = {StatsNZ2022_HouseholdNetWorthDataCollection.pdf}
}Household Net Worth Statistics: Year Ended June 2021. StatsNZ. March 2022.
@misc{StatsNZ2022_HouseholdNetWorthDataCollectiondata,
title = {Household Net Worth Statistics: Year Ended {{June}} 2021},
author = {{StatsNZ}},
year = {2022},
month = {mar},
url = {https://www.stats.govt.nz/information-releases/household-net-worth-statistics-year-ended-june-2021},
urldate = {2022-09-29},
keywords = {Data Sources: Wealth Inequality},
url_file = {StatsNZ2022_HouseholdNetWorthDataCollectiondata.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/statsnz-householdnetworthdatacollection202021-2022}
}Household Wealth and Its Distribution in the Netherlands, 1854-2019. Toussaint, Simon J.; de Vicq, Amaury; Moatsos, Michail; and van der Valk, Tim. World Inequality Lab. November 2022.
@techreport{Toussaintetal2022,
title = {Household Wealth and Its Distribution in the {{Netherlands}}, 1854-2019},
author = {Toussaint, Simon J. and {de Vicq}, Amaury and Moatsos, Michail and {van der Valk}, Tim},
year = {2022},
month = {nov},
number = {2022/19},
institution = {World Inequality Lab},
url = {https://wid.world/document/household-wealth-and-its-distribution-in-the-netherlands-1854-2019-world-inequality-lab-working-paper-2022-19/},
urldate = {2024-05-30},
abstract = {We analyze the evolution of aggregate household wealth, its composition, and top wealth shares since the mid-19th century for the Netherlands, a country which played a significant role in economic history. The main forces at play are the size and variation of colonial wealth up until WWII, and the introduction of a --particularly strong-- pension system thereafter. We show that the wealth-income ratio followed the familiar U-shaped pattern over the 20th century. The Netherlands, however, had the largest wealth-income ratio on record, growing since the mid-1850s, driven by industrialization and booming private foreign investments, to a peak of 900\% around 1880. In contrast to other countries, the wealth-income ratio remained high up until 1929. To better understand these trends, we construct the first series on colonial wealth and show that colonial and other foreign investment account for most of the gap with other countries in the pre-WWII period. The initial post-war decline in the ratio is driven by rapid income growth. The increase in the ratio since the 1970s has been mainly driven by the uniquely large capital-funded pension system. In contrast with other major countries, housing plays only a secondary role in net wealth accumulation due to significant mortgage debt. Methodologically, we are the first to compare historical national accounts, estate multiplier, and wealth tax data approaches to construct aggregate wealth. We find that the estate multiplier is a good alternative to the historical national accounts benchmark, while the use of wealth tax data results in unrealistically low estimates.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_file = {Toussaintetal2022.pdf}
}We analyze the evolution of aggregate household wealth, its composition, and top wealth shares since the mid-19th century for the Netherlands, a country which played a significant role in economic history. The main forces at play are the size and variation of colonial wealth up until WWII, and the introduction of a –particularly strong– pension system thereafter. We show that the wealth-income ratio followed the familiar U-shaped pattern over the 20th century. The Netherlands, however, had the largest wealth-income ratio on record, growing since the mid-1850s, driven by industrialization and booming private foreign investments, to a peak of 900% around 1880. In contrast to other countries, the wealth-income ratio remained high up until 1929. To better understand these trends, we construct the first series on colonial wealth and show that colonial and other foreign investment account for most of the gap with other countries in the pre-WWII period. The initial post-war decline in the ratio is driven by rapid income growth. The increase in the ratio since the 1970s has been mainly driven by the uniquely large capital-funded pension system. In contrast with other major countries, housing plays only a secondary role in net wealth accumulation due to significant mortgage debt. Methodologically, we are the first to compare historical national accounts, estate multiplier, and wealth tax data approaches to construct aggregate wealth. We find that the estate multiplier is a good alternative to the historical national accounts benchmark, while the use of wealth tax data results in unrealistically low estimates.
The UK's Wealth Distribution and Characteristics of High-Wealth Households. Advani, Arun; Bangham, George; and Leslie, Jack. Fiscal Studies, 42(3-4): 397–430. 2021.
@article{Advanietal2021,
title = {The {{UK}}'s Wealth Distribution and Characteristics of High-Wealth Households},
author = {Advani, Arun and Bangham, George and Leslie, Jack},
year = {2021},
journal = {Fiscal Studies},
volume = {42},
number = {3-4},
pages = {397--430},
doi = {10.1111/1475-5890.12286},
url = {https://doi.org/10.1111/1475-5890.12286},
abstract = {We show that wealth inequality in the UK is high and has increased slightly over the past decade as financial asset prices have increased in the wake of the financial crisis. But data deficiencies are a major barrier in understanding the true distribution, composition and size of household wealth. The most comprehensive survey of household wealth in the UK does a good job of capturing the vast majority of the wealth distribution, but nearly {\pounds}800 billion of wealth held by the very wealthiest UK households is missing. We also find tentative evidence that survey measures of high-wealth families undervalue their assets -- our central estimate of the true value of wealth held by households in the UK is 5 per cent higher than the survey data suggest.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/advani-bangham-leslie-theukswealthdistributionandcharacteristicsofhighwealthhouseholdsdatafile-2021},
url_file = {Advanietal2021.pdf},
url_online_appendix = {https://bibbase.org/network/publication/advani-bangham-leslie-theukswealthdistributionandcharacteristicsofhighwealthhouseholdsonlineappendix-2021}
}We show that wealth inequality in the UK is high and has increased slightly over the past decade as financial asset prices have increased in the wake of the financial crisis. But data deficiencies are a major barrier in understanding the true distribution, composition and size of household wealth. The most comprehensive survey of household wealth in the UK does a good job of capturing the vast majority of the wealth distribution, but nearly \pounds800 billion of wealth held by the very wealthiest UK households is missing. We also find tentative evidence that survey measures of high-wealth families undervalue their assets – our central estimate of the true value of wealth held by households in the UK is 5 per cent higher than the survey data suggest.
The UK's Wealth Distribution and Characteristics of High-Wealth Households: Data File. Advani, Arun; Bangham, George; and Leslie, Jack. 2021.
@misc{Advanietal2021data,
title = {The {{UK}}'s Wealth Distribution and Characteristics of High-Wealth Households: Data File},
author = {Advani, Arun and Bangham, George and Leslie, Jack},
year = {2021},
url = {https://arunadvani.com/research.html},
urldate = {2022-04-20},
keywords = {Data Sources: Wealth Inequality},
url_file = {Advanietal2021data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/advani-bangham-leslie-theukswealthdistributionandcharacteristicsofhighwealthhouseholds-2021}
}The UK's Wealth Distribution and Characteristics of High-Wealth Households: Online Appendix. Advani, Arun; Bangham, George; and Leslie, Jack. 2021.
@misc{Advanietal2021app,
title = {The {{UK}}'s Wealth Distribution and Characteristics of High-Wealth Households: Online Appendix},
author = {Advani, Arun and Bangham, George and Leslie, Jack},
year = {2021},
doi = {10.1111/1475-5890.12286},
url = {https://doi.org/10.1111/1475-5890.12286},
keywords = {Data Sources: Wealth Inequality},
url_file = {Advanietal2021app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/advani-bangham-leslie-theukswealthdistributionandcharacteristicsofhighwealthhouseholds-2021}
}Rethinking the Lebanese Economic Miracle: The Extreme Concentration of Income and Wealth in Lebanon 2005-2014. Assouad, Lydia. World Inequality Lab. February 2021.
@techreport{Assouad2021,
title = {Rethinking the {{Lebanese}} Economic Miracle: The Extreme Concentration of Income and Wealth in Lebanon 2005-2014},
author = {Assouad, Lydia},
year = {2021},
month = {feb},
number = {2017/13},
institution = {World Inequality Lab},
url = {https://wid.world/document/rethinking-lebanese-economic-miracle-extreme-concentration-income-wealth-lebanon-2005-2014-wid-world-working-paper-201713/},
urldate = {2022-04-01},
abstract = {I combine household surveys, national accounts and unique personal income tax records to produce the first estimates of the national income distribution in an Arab country, Lebanon. I find that income is extremely concentrated over the 2005-2014 period: The top 1 and 10 percent of the adult population received almost 25 and 55 percent of national income on average, placing Lebanon among the countries with the highest levels of income inequality in the world. Results are robust to sensitivity analysis and suggest that one should not give up on tracking the dynamics of wealth and income concentration in a developing country, as long as the the assumptions made are clearly and systematically stated. The extreme level on inequality found question the long-lasting narrative of the "Lebanese economic miracle" that showcases the country as a paragon of economic success in the Middle East. They also confirm results from a large literature that emphasizes how the Lebanese sectarian-based mode of governance has allowed the ruling elite to extract large rents on most economic activities in the last decades at the expense of the majority of citizens.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_data_files = {https://bibbase.org/network/publication/assouad-datafilestorethinkingthelebaneseeconomicmiracletheextremeconcentrationofincomeandwealthinlebanon20052014-2017},
url_file = {Assouad2021.pdf},
url_published_version = {https://bibbase.org/network/publication/assouad-rethinkingthelebaneseeconomicmiracletheextremeconcentrationofincomeandwealthinlebanon20052014-2023}
}I combine household surveys, national accounts and unique personal income tax records to produce the first estimates of the national income distribution in an Arab country, Lebanon. I find that income is extremely concentrated over the 2005-2014 period: The top 1 and 10 percent of the adult population received almost 25 and 55 percent of national income on average, placing Lebanon among the countries with the highest levels of income inequality in the world. Results are robust to sensitivity analysis and suggest that one should not give up on tracking the dynamics of wealth and income concentration in a developing country, as long as the the assumptions made are clearly and systematically stated. The extreme level on inequality found question the long-lasting narrative of the "Lebanese economic miracle" that showcases the country as a paragon of economic success in the Middle East. They also confirm results from a large literature that emphasizes how the Lebanese sectarian-based mode of governance has allowed the ruling elite to extract large rents on most economic activities in the last decades at the expense of the majority of citizens.
A Wealth of Information: Augmenting the Survey of Consumer Finances to Characterize the Full U.S. Wealth Distribution. Bricker, Jesse; Goodman, Sarena; Moore, Kevin B.; and Volz, Alice Henriques. Board of Governors of the Federal Reserve System. June 2021.
@techreport{Brickeretal2021,
title = {A Wealth of Information: Augmenting the Survey of Consumer Finances to Characterize the Full {{U}}.{{S}}. Wealth Distribution},
author = {Bricker, Jesse and Goodman, Sarena and Moore, Kevin B. and Volz, Alice Henriques},
year = {2021},
month = {jun},
number = {2021-053},
institution = {Board of Governors of the Federal Reserve System},
doi = {10.17016/FEDS.2021.053},
url = {https://doi.org/10.17016/FEDS.2021.053},
abstract = {We use the Survey of Consumer Finances (SCF) to advance U.S. wealth analysis along several dimensions. We develop a comprehensive framework that modifies the SCF to recover the wealth distribution over families, tax units, and individuals from 1989 to 2019. We show that, by ignoring unequal holdings within families, existing estimates considerably understate U.S. inequality across individuals. We find wealth concentration rose through the recent economic recovery, which differs from leading models that capitalize income into wealth even after aligning conceptual differences. We illustrate that private businesses are a growing impediment to accurately modeling wealth from income.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Finance and {{Economics Discussion Series}}},
url_accessible_version_of_figures = {https://bibbase.org/network/publication/bricker-goodman-moore-volz-awealthofinformationaugmentingthesurveyofconsumerfinancestocharacterizethefulluswealthdistributionaccessibleversionoffigures-2021},
url_file = {Brickeretal2021.pdf}
}We use the Survey of Consumer Finances (SCF) to advance U.S. wealth analysis along several dimensions. We develop a comprehensive framework that modifies the SCF to recover the wealth distribution over families, tax units, and individuals from 1989 to 2019. We show that, by ignoring unequal holdings within families, existing estimates considerably understate U.S. inequality across individuals. We find wealth concentration rose through the recent economic recovery, which differs from leading models that capitalize income into wealth even after aligning conceptual differences. We illustrate that private businesses are a growing impediment to accurately modeling wealth from income.
A Wealth of Information: Augmenting the Survey of Consumer Finances to Characterize the Full U.S. Wealth Distribution: Accessible Version of Figures. Bricker, Jesse; Goodman, Sarena; Moore, Kevin B.; and Volz, Alice Henriques. June 2021.
@misc{Brickeretal2021data,
title = {A Wealth of Information: Augmenting the Survey of Consumer Finances to Characterize the Full {{U}}.{{S}}. Wealth Distribution: Accessible Version of Figures},
author = {Bricker, Jesse and Goodman, Sarena and Moore, Kevin B. and Volz, Alice Henriques},
year = {2021},
month = {jun},
doi = {10.17016/FEDS.2021.053},
url = {https://doi.org/10.17016/FEDS.2021.053},
keywords = {Data Sources: Wealth Inequality},
url_file = {Brickeretal2021data.html},
url_parent_paper = {https://bibbase.org/network/publication/bricker-goodman-moore-volz-awealthofinformationaugmentingthesurveyofconsumerfinancestocharacterizethefulluswealthdistribution-2021}
}Social Security and Trends in Wealth Inequality. Catherine, Sylvain; Miller, Max; and Sarin, Natasha. August 2021.
@unpublished{Catherineetal2021,
title = {Social Security and Trends in Wealth Inequality},
author = {Catherine, Sylvain and Miller, Max and Sarin, Natasha},
year = {2021},
month = {aug},
doi = {10.2139/ssrn.3546668},
url = {https://doi.org/10.2139/ssrn.3546668},
abstract = {Recent influential work finds large increases in inequality in the U.S. based on measures of wealth concentration that notably exclude the value of social insurance programs. This paper revisits this conclusion by incorporating Social Security retirement benefits into measures of wealth inequality. We find that top wealth shares have not increased in the last three decades when Social Security is properly accounted for. This finding is robust to assumptions about how taxes and benefits may change in response to system financing concerns. When discounted at the risk-free rate, real Social Security wealth increased substantially from \$4.8 trillion in 1989 to \$41.3 trillion in 2016. When we adjust the discount rate for long-run macroeconomic risk, this increase remains sizable, growing from over \$3.9 trillion in 1989 to \$33.9 trillion in 2016. Consequently, by 2016, Social Security wealth represents 57\% of the wealth of the bottom 90\% of the wealth distribution.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {Unpublished manuscript},
url_data_files = {https://bibbase.org/network/publication/catherine-miller-sarin-socialsecurityandtrendsinwealthinequalitydatafiles-2021},
url_file = {Catherineetal2021.pdf}
}Recent influential work finds large increases in inequality in the U.S. based on measures of wealth concentration that notably exclude the value of social insurance programs. This paper revisits this conclusion by incorporating Social Security retirement benefits into measures of wealth inequality. We find that top wealth shares have not increased in the last three decades when Social Security is properly accounted for. This finding is robust to assumptions about how taxes and benefits may change in response to system financing concerns. When discounted at the risk-free rate, real Social Security wealth increased substantially from $4.8 trillion in 1989 to $41.3 trillion in 2016. When we adjust the discount rate for long-run macroeconomic risk, this increase remains sizable, growing from over $3.9 trillion in 1989 to $33.9 trillion in 2016. Consequently, by 2016, Social Security wealth represents 57% of the wealth of the bottom 90% of the wealth distribution.
Social Security and Trends in Wealth Inequality: Data Files. Catherine, Sylvain; Miller, Max; and Sarin, Natasha. 2021.
@misc{Catherineetal2021data,
title = {Social Security and Trends in Wealth Inequality: Data Files},
author = {Catherine, Sylvain and Miller, Max and Sarin, Natasha},
year = {2021},
url = {https://bibbase.org/network/publication/catherine-miller-sarin-socialsecurityandtrendsinwealthinequalitydatafiles-2021},
keywords = {Data Sources: Wealth Inequality},
url_file = {Catherineetal2021data.zip},
url_parent_paper = {https://bibbase.org/network/publication/catherine-miller-sarin-socialsecurityandtrendsinwealthinequality-2021}
}Long Run Canadian Wealth Inequality in International Context: Appendices. Davies, James B.; and Di Matteo, Livio. 2021.
@misc{DaviesDiMatteo2021app,
title = {Long Run {{Canadian}} Wealth Inequality in International Context: Appendices},
author = {Davies, James B. and Di Matteo, Livio},
year = {2021},
doi = {10.1111/roiw.12453},
url = {https://doi.org/10.1111/roiw.12453},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/davies-dimatteo-longruncanadianwealthinequalityininternationalcontext-2021}
}Household Finance and Consumption Survey. Household Finance; and Consumption Network. May 2021.
@misc{HouseholdFinanceandConsumptionNetwork2021,
title = {Household {{Finance}} and {{Consumption Survey}}},
author = {{Household Finance and Consumption Network}},
year = {2021},
month = {may},
url = {https://www.ecb.europa.eu/pub/economic-research/research-networks/html/researcher_hfcn.en.html},
urldate = {2022-07-12},
keywords = {Data Sources: Wealth Inequality,Data Sources: Wealth Topography},
note = {European Central Bank},
url_file = {HouseholdFinanceandConsumptionNetwork2021.zip},
url_methodological_report = {https://bibbase.org/network/publication/householdfinance-network-thehouseholdfinanceandconsumptionsurveymethodologicalreportforthe2021wave-2023}
}136z – Assets, Liabilities and Income of Households by Net Wealth Decile Group in, 1987-2019. Statistics Finland. June 2021.
@misc{StatisticsFinland2021_136zAssetsLiabilitiesIncomeHouseholds,
title = {136z -- Assets, Liabilities and Income of Households by Net Wealth Decile Group in, 1987-2019},
author = {{Statistics Finland}},
year = {2021},
month = {jun},
url = {https://pxdata.stat.fi/PxWeb/pxweb/en/StatFin/StatFin__vtutk/statfin_vtutk_pxt_136z.px/},
urldate = {2022-12-09},
keywords = {Data Sources: Wealth Inequality},
url_documentation = {https://bibbase.org/network/publication/statisticsfinland-documentationofstatisticshouseholdsassets-2022},
url_file = {StatisticsFinland2021_136zAssetsLiabilitiesIncomeHouseholds.xlsx}
}Accounting for Wealth-Inequality Dynamics: Methods, Estimates, and Simulations for France. Garbinti, Bertrand; Goupille-Lebret, Jonathan; and Piketty, Thomas. Journal of the European Economic Association, 19(1): 620–663. February 2021.
@article{Garbintietal2021,
title = {Accounting for Wealth-Inequality Dynamics: Methods, Estimates, and Simulations for {{France}}},
author = {Garbinti, Bertrand and {Goupille-Lebret}, Jonathan and Piketty, Thomas},
year = {2021},
month = {feb},
journal = {Journal of the European Economic Association},
volume = {19},
number = {1},
pages = {620--663},
doi = {10.1093/jeea/jvaa025},
url = {https://doi.org/10.1093/jeea/jvaa025},
abstract = {Measuring and understanding the evolution of wealth inequality is a key challenge for researchers, policy makers, and the general public. This paper breaks new ground on this topic by presenting a new method to estimate and study wealth inequality. This method combines fiscal data with household surveys and national accounts in order to provide annual wealth distribution series, with detailed breakdowns by percentiles, age, and assets. Using the case of France as an illustration, we show that the resulting series can be used to better analyze the evolution and the determinants of wealth-inequality dynamics over the 1970--2014 period. We show that the decline in wealth inequality ends in the early 1980s, marking the beginning of a rise in the top 1\% wealth share, though with significant fluctuations due largely to asset price movements. Rising inequality in savings rates coupled with highly stratified rates of returns has led to rising wealth concentration in spite of the opposing effect of house price increases. We develop a simple simulation model highlighting how changes in the combination of unequal savings rates, rates of return, and labor earnings that occurred in the early 1980s generated large multiplicative effects that led to radically different steady-state levels of wealth inequality. Taking advantage of the joint distribution of income and wealth, we show that top wealth holders are almost exclusively top capital earners, and increasingly fewer are made up of top labor earners; it has become increasingly difficult in recent decades to access top wealth groups with one's labor income only.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_2017_online_appendix = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfrance18002014appendix-2017},
url_appendix = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfranceappendix-2020},
url_data_appendix = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfrancedataappendix-2021},
url_file = {Garbintietal2021.pdf}
}Measuring and understanding the evolution of wealth inequality is a key challenge for researchers, policy makers, and the general public. This paper breaks new ground on this topic by presenting a new method to estimate and study wealth inequality. This method combines fiscal data with household surveys and national accounts in order to provide annual wealth distribution series, with detailed breakdowns by percentiles, age, and assets. Using the case of France as an illustration, we show that the resulting series can be used to better analyze the evolution and the determinants of wealth-inequality dynamics over the 1970–2014 period. We show that the decline in wealth inequality ends in the early 1980s, marking the beginning of a rise in the top 1% wealth share, though with significant fluctuations due largely to asset price movements. Rising inequality in savings rates coupled with highly stratified rates of returns has led to rising wealth concentration in spite of the opposing effect of house price increases. We develop a simple simulation model highlighting how changes in the combination of unequal savings rates, rates of return, and labor earnings that occurred in the early 1980s generated large multiplicative effects that led to radically different steady-state levels of wealth inequality. Taking advantage of the joint distribution of income and wealth, we show that top wealth holders are almost exclusively top capital earners, and increasingly fewer are made up of top labor earners; it has become increasingly difficult in recent decades to access top wealth groups with one's labor income only.
Accounting for Wealth-Inequality Dynamics: Methods, Estimates, and Simulations for France: Data Appendix. Garbinti, Bertrand; Goupille-Lebret, Jonathan; and Piketty, Thomas. February 2021.
@misc{Garbintietal2021data,
title = {Accounting for Wealth-Inequality Dynamics: Methods, Estimates, and Simulations for {{France}}: Data Appendix},
author = {Garbinti, Bertrand and {Goupille-Lebret}, Jonathan and Piketty, Thomas},
year = {2021},
month = {feb},
url = {https://sites.google.com/view/bertrandgarbinti/research},
urldate = {2022-03-08},
abstract = {Data appendix to version published in Journal of the European Economic Association.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Garbintietal2021data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfrance-2021}
}Data appendix to version published in Journal of the European Economic Association.
Instructions to Replicate "Wealth Concentration in the USA Using an Expanded Measure of Net Worth". Jacobs, Lindsay; Llanes, Elizabeth; Moore, Kevin; Thompson, Jeffrey; and Volz, Alice Henriques. October 2021.
@misc{Jacobsetal2021data,
title = {Instructions to Replicate "Wealth Concentration in the {{USA}} Using an Expanded Measure of Net Worth"},
author = {Jacobs, Lindsay and Llanes, Elizabeth and Moore, Kevin and Thompson, Jeffrey and Volz, Alice Henriques},
year = {2021},
month = {oct},
doi = {10.1093/oep/gpab054},
url = {https://doi.org/10.1093/oep/gpab054},
abstract = {Full replication files can be found at the URL provided.},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/jacobs-llanes-moore-thompson-volz-wealthconcentrationintheusausinganexpandedmeasureofnetworth-2021}
}Full replication files can be found at the URL provided.
Supplementary Appendix for: "Wealth Concentration in the USA Using an Expanded Measure of Net Worth". Jacobs, Lindsay; Llanes, Elizabeth; Moore, Kevin; Thompson, Jeffrey; and Volz, Alice Henriques. October 2021.
@misc{Jacobsetal2021app,
title = {Supplementary Appendix for: "Wealth Concentration in the {{USA}} Using an Expanded Measure of Net Worth"},
author = {Jacobs, Lindsay and Llanes, Elizabeth and Moore, Kevin and Thompson, Jeffrey and Volz, Alice Henriques},
year = {2021},
month = {oct},
doi = {10.1093/oep/gpab054},
url = {https://doi.org/10.1093/oep/gpab054},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/jacobs-llanes-moore-thompson-volz-wealthconcentrationintheusausinganexpandedmeasureofnetworth-2021}
}Wealth Concentration in the USA Using an Expanded Measure of Net Worth. Jacobs, Lindsay; Llanes, Elizabeth; Moore, Kevin; Thompson, Jeffrey; and Volz, Alice Henriques. Oxford Economic Papers. October 2021.
@article{Jacobsetal2021,
title = {Wealth Concentration in the {{USA}} Using an Expanded Measure of Net Worth},
author = {Jacobs, Lindsay and Llanes, Elizabeth and Moore, Kevin and Thompson, Jeffrey and Volz, Alice Henriques},
year = {2021},
month = {oct},
journal = {Oxford Economic Papers},
doi = {10.1093/oep/gpab054},
url = {https://doi.org/10.1093/oep/gpab054},
abstract = {Defined benefit (DB) pensions and Social Security are important resources for financing retirement in the USA. However, these illiquid, nonmarket forms of wealth are typically excluded from measures of net worth. To the extent that these broadly held resources substitute for savings, measures of wealth inequality that do not account for DB pensions and Social Security may be overstated. This article develops an alternative, expanded wealth concept, augmenting net worth data from the Survey of Consumer Finances with estimates of DB pension and expected Social Security wealth. We explore the concentration of wealth among households ages 40--59 and find that (i) including DB pension and Social Security results in markedly lower measures of wealth concentration and (ii) trends toward higher wealth inequality over time, while moderated, are still present. Simulation exercises show that reductions in Social Security benefits significantly increase wealth concentration for the youngest birth-year cohorts.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {gpab054},
url_replication_files = {https://bibbase.org/network/publication/jacobs-llanes-moore-thompson-volz-instructionstoreplicatewealthconcentrationintheusausinganexpandedmeasureofnetworth-2021},
url_supplementary_appendix = {https://bibbase.org/network/publication/jacobs-llanes-moore-thompson-volz-supplementaryappendixforwealthconcentrationintheusausinganexpandedmeasureofnetworth-2021}
}Defined benefit (DB) pensions and Social Security are important resources for financing retirement in the USA. However, these illiquid, nonmarket forms of wealth are typically excluded from measures of net worth. To the extent that these broadly held resources substitute for savings, measures of wealth inequality that do not account for DB pensions and Social Security may be overstated. This article develops an alternative, expanded wealth concept, augmenting net worth data from the Survey of Consumer Finances with estimates of DB pension and expected Social Security wealth. We explore the concentration of wealth among households ages 40–59 and find that (i) including DB pension and Social Security results in markedly lower measures of wealth concentration and (ii) trends toward higher wealth inequality over time, while moderated, are still present. Simulation exercises show that reductions in Social Security benefits significantly increase wealth concentration for the youngest birth-year cohorts.
Wealth Distribution Database. OECD. December 2021.
@misc{OECD2021_WealthDistributionDatabase,
title = {Wealth {{Distribution Database}}},
author = {{OECD}},
year = {2021},
month = {dec},
url = {https://stats.oecd.org/Index.aspx?DataSetCode=WEALTH},
abstract = {While much of the comparative evidence on inequalities that is currently available refers to household income, wealth is a critical dimension of households' economic well-being. How wealth is distributed is important for equity and inter-generational mobility, but also for the stability of the economic system and for its resilience to shocks. While the lack of comparative evidence in this field reflects the absence of an agreed standard that statistical offices could use when collecting this information, this gap has been addressed by the OECD with the release in 2013 of a set of statistical guidelines in this field. In 2013, the OECD issued a set of `Guidelines' for micro statistics on household wealth (OECD, 2013) and an increasing number of countries have engaged in the collection of micro statistics in this field (European Central Bank, 2013). Building on these initiatives as well as others, such as the Luxembourg Wealth Study (Sierminska et al, 2006) which have informed previous OECD analysis (Jantii et al., 2008), the OECD has updated the data on the distribution of household wealth for OECD countries, based on the set of conventions and classifications proposed in the 2013 OECD Guidelines.},
keywords = {Data Sources: Wealth Inequality},
note = {OECD Statistics},
url_file = {OECD2021_WealthDistributionDatabase.csv},
url_wdd_metadata = {https://bibbase.org/network/publication/oecd-wealthdistributiondatabasemetadatamainconcepts-2021},
url_wdd_sources_table = {https://bibbase.org/network/publication/oecd-wealthdistributiondatabasemetadatadatasourcesandcharacteristics-2021}
}While much of the comparative evidence on inequalities that is currently available refers to household income, wealth is a critical dimension of households' economic well-being. How wealth is distributed is important for equity and inter-generational mobility, but also for the stability of the economic system and for its resilience to shocks. While the lack of comparative evidence in this field reflects the absence of an agreed standard that statistical offices could use when collecting this information, this gap has been addressed by the OECD with the release in 2013 of a set of statistical guidelines in this field. In 2013, the OECD issued a set of `Guidelines' for micro statistics on household wealth (OECD, 2013) and an increasing number of countries have engaged in the collection of micro statistics in this field (European Central Bank, 2013). Building on these initiatives as well as others, such as the Luxembourg Wealth Study (Sierminska et al, 2006) which have informed previous OECD analysis (Jantii et al., 2008), the OECD has updated the data on the distribution of household wealth for OECD countries, based on the set of conventions and classifications proposed in the 2013 OECD Guidelines.
Wealth Distribution Database Metadata: Data Sources and Characteristics. OECD. 2021.
@misc{OECD2021_WealthDistributionDatabaseMetadataData,
title = {Wealth {{Distribution Database}} Metadata: Data Sources and Characteristics},
author = {{OECD}},
year = {2021},
url = {https://www.oecd.org/social/income-distribution-database.htm},
urldate = {2022-11-01},
keywords = {Data Sources: Wealth Inequality},
url_file = {OECD2021_WealthDistributionDatabaseMetadataData.pdf},
url_wealth_distribution_database = {https://bibbase.org/network/publication/oecd-wealthdistributiondatabase-2021}
}Wealth Distribution Database Metadata: Main Concepts. OECD. 2021.
@misc{OECD2021_WealthDistributionDatabaseMetadataMain,
title = {Wealth {{Distribution Database}} Metadata: Main Concepts},
author = {{OECD}},
year = {2021},
url = {https://www.oecd.org/social/income-distribution-database.htm},
urldate = {2022-11-01},
keywords = {Data Sources: Wealth Inequality},
url_file = {OECD2021_WealthDistributionDatabaseMetadataMain.pdf},
url_wealth_distribution_database = {https://bibbase.org/network/publication/oecd-wealthdistributiondatabase-2021}
}Income and Wealth Inequality in Hong Kong, 1981-2020: The Rise of Pluto-Communism? Appendix. Piketty, Thomas; and Yang, Li. World Inequality Lab. June 2021.
@techreport{PikettyYang2022app,
title = {Income and Wealth Inequality in {{Hong Kong}}, 1981-2020: The Rise of Pluto-Communism? Appendix},
author = {Piketty, Thomas and Yang, Li},
year = {2021},
month = {jun},
number = {2021/18},
institution = {World Inequality Lab},
url = {https://wid.world/document/appendix-to-income-and-wealth-inequality-in-hong-kong-1981-2020-the-rise-of-pluto-communism-world-inequality-lab-working-paper-2021-18/},
urldate = {2022-09-29},
keywords = {Data Sources: Wealth Inequality},
type = {Working {{Paper}}},
url_file = {PikettyYang2022app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/piketty-yang-incomeandwealthinequalityinhongkong19812020theriseofplutocommunism-2022}
}Income and Wealth Inequality in Hong Kong, 1981-2020: The Rise of Pluto-Communism? Data Files. Piketty, Thomas; and Yang, Li. 2021.
@misc{PikettyYang2022data,
title = {Income and Wealth Inequality in {{Hong Kong}}, 1981-2020: The Rise of Pluto-Communism? Data Files},
author = {Piketty, Thomas and Yang, Li},
year = {2021},
url = {https://wid.world/methodology/#library-raw-datasets},
urldate = {2022-09-29},
keywords = {Data Sources: Wealth Inequality},
url_file = {PikettyYang2022data.zip},
url_parent_paper = {https://bibbase.org/network/publication/piketty-yang-incomeandwealthinequalityinhongkong19812020theriseofplutocommunism-2022}
}Global Wealth Databook 2021. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. June 2021.
@misc{Shorrocksetal2021,
title = {Global Wealth Databook 2021},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2021},
month = {jun},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2023-04-25},
abstract = {For the past 12 years, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the ``wealth pyramid,'' covering 2.9 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who now comprise 1.1\% of the adult population and own 45.8\% of household wealth. During the 12 months up to end-2020, and in spite of the economic disruption caused by the COVID-19 pandemic, we estimate that aggregate global wealth has risen by USD 28.7 trillion (+7.4\%) to a combined total of USD 418.3 trillion. Wealth per adult grew by 6\% to a new record high of USD 79,952 per adult. The core reason for the apparent disconnect between the ongoing global recession in 2020 and household wealth is the pre-emptive action taken by governments and central banks, and the rapid development of COVID vaccines, which combined led to a strong rally in financial assets. While the Global Wealth Report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global Wealth Databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global Wealth Report and Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have -- or promise to have -- a global impact within and beyond the financial services industry. The Global Wealth Databook provides estimates for the level and distribution of wealth for over 200 countries for the period from 2000 to end-2020. It covers the pattern and trend of household wealth at both the regional and country levels. This year's report examines in more detail the development of wealth and wealth distribution in what has been a truly out of-the-ordinary year. Particular attention is paid to the continued growing importance of China and other emerging economies in global wealth creation, and to the differences across groups of countries that share a number of demographic and economic features.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2021.pdf}
}For the past 12 years, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," covering 2.9 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who now comprise 1.1% of the adult population and own 45.8% of household wealth. During the 12 months up to end-2020, and in spite of the economic disruption caused by the COVID-19 pandemic, we estimate that aggregate global wealth has risen by USD 28.7 trillion (+7.4%) to a combined total of USD 418.3 trillion. Wealth per adult grew by 6% to a new record high of USD 79,952 per adult. The core reason for the apparent disconnect between the ongoing global recession in 2020 and household wealth is the pre-emptive action taken by governments and central banks, and the rapid development of COVID vaccines, which combined led to a strong rally in financial assets. While the Global Wealth Report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global Wealth Databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global Wealth Report and Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have – or promise to have – a global impact within and beyond the financial services industry. The Global Wealth Databook provides estimates for the level and distribution of wealth for over 200 countries for the period from 2000 to end-2020. It covers the pattern and trend of household wealth at both the regional and country levels. This year's report examines in more detail the development of wealth and wealth distribution in what has been a truly out of-the-ordinary year. Particular attention is paid to the continued growing importance of China and other emerging economies in global wealth creation, and to the differences across groups of countries that share a number of demographic and economic features.
Global Wealth Report 2021. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. June 2021.
@misc{Shorrocksetal2021a,
title = {Global Wealth Report 2021},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2021},
month = {jun},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2023-04-25},
abstract = {Now in its twelfth year, I am proud to present to you the 2021 edition of the Credit Suisse Global Wealth Report. This report delivers a comprehensive analysis on available global household wealth, underpinned by unique insights from leading academics in the field, Anthony Shorrocks and James Davies. This year's edition digs deeper into the impact of the COVID-19 pandemic and the response of policymakers on global wealth and its distribution. Mindful of the important wealth differences that have built over the last year, our report also offers perspectives and, indeed, encouraging prospects, for wealth accumulation throughout the global wealth pyramid as we look to a world beyond the pandemic. I hope you find the insights of this edition of the Global Wealth Report to be of particular value in what remain unprecedented times.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2021a.pdf}
}Now in its twelfth year, I am proud to present to you the 2021 edition of the Credit Suisse Global Wealth Report. This report delivers a comprehensive analysis on available global household wealth, underpinned by unique insights from leading academics in the field, Anthony Shorrocks and James Davies. This year's edition digs deeper into the impact of the COVID-19 pandemic and the response of policymakers on global wealth and its distribution. Mindful of the important wealth differences that have built over the last year, our report also offers perspectives and, indeed, encouraging prospects, for wealth accumulation throughout the global wealth pyramid as we look to a world beyond the pandemic. I hope you find the insights of this edition of the Global Wealth Report to be of particular value in what remain unprecedented times.
Household Wealth Trends in the United States, 1962 to 2019: Median Wealth Rebounds... but Not Enough. Wolff, Edward N. National Bureau of Economic Research. January 2021.
@techreport{Wolff2021,
title = {Household Wealth Trends in the {{United States}}, 1962 to 2019: Median Wealth Rebounds... but Not Enough},
author = {Wolff, Edward N.},
year = {2021},
month = {jan},
number = {28383},
institution = {National Bureau of Economic Research},
doi = {10.3386/w28383},
url = {https://doi.org/10.3386/w28383},
abstract = {Median household wealth shot up by 21.2 percent in real terms between 2016 and 2019, as asset prices continued to rebound. However, 2007 still remains the watershed year, and median wealth was down 20.4 percent relative to 2007, though mean wealth more than fully recovered. There was a modest remission in wealth inequality, with the share of the top one percent down by 1.4 percentage points, that of the top 20 percent down by 1.0 percentage points, the Gini coefficient down by 0.008, and the mean wealth of the top one percent also down by 1.9 percent. The homeownership rate finally rebounded a bit, by 1.2 percentage points, to 64.9 percent. The stock ownership rate advanced by 0.4 percentage points to 49.6 percent, though still down from its 2001 peak. Though the mean debt of the middle class rose by 10.7 percent in real terms, the debt-income and debt-net worth ratios remained largely unchanged. The black-white gap in mean net worth remained unchanged, as did the Hispanic-white wealth gap. The wealth of households under age 35 continued to deteriorate in both absolute and relative terms between 2016 and 2019.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_file = {Wolff2021.pdf}
}Median household wealth shot up by 21.2 percent in real terms between 2016 and 2019, as asset prices continued to rebound. However, 2007 still remains the watershed year, and median wealth was down 20.4 percent relative to 2007, though mean wealth more than fully recovered. There was a modest remission in wealth inequality, with the share of the top one percent down by 1.4 percentage points, that of the top 20 percent down by 1.0 percentage points, the Gini coefficient down by 0.008, and the mean wealth of the top one percent also down by 1.9 percent. The homeownership rate finally rebounded a bit, by 1.2 percentage points, to 64.9 percent. The stock ownership rate advanced by 0.4 percentage points to 49.6 percent, though still down from its 2001 peak. Though the mean debt of the middle class rose by 10.7 percent in real terms, the debt-income and debt-net worth ratios remained largely unchanged. The black-white gap in mean net worth remained unchanged, as did the Hispanic-white wealth gap. The wealth of households under age 35 continued to deteriorate in both absolute and relative terms between 2016 and 2019.
The Distributional Financial Accounts of the United States. Batty, Michael; Bricker, Jesse; Briggs, Joseph; Friedman, Sarah; Nemschoff, Danielle; Nielsen, Eric; Sommer, Kamila; and Volz, Alice Henriques. December 2020.
@unpublished{Battyetal2022wp,
title = {The {{Distributional Financial Accounts}} of the {{United States}}},
author = {Batty, Michael and Bricker, Jesse and Briggs, Joseph and Friedman, Sarah and Nemschoff, Danielle and Nielsen, Eric and Sommer, Kamila and Volz, Alice Henriques},
year = {2020},
month = {dec},
url = {https://bibbase.org/network/publication/batty-bricker-briggs-friedman-nemschoff-nielsen-sommer-volz-thedistributionalfinancialaccountsoftheunitedstates-2020},
abstract = {This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of US household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products---quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances---to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of US household wealth.},
keywords = {Data Sources: Wealth Inequality},
note = {Unpublished manuscript},
collaborator = {Chetty, Raj and Friedman, John N. and Gornick, Janet C. and Johnson, Barry and Kennickell, Arthur},
url_2019_working_paper = {https://bibbase.org/network/publication/batty-bricker-briggs-holmquist-mcintosh-moore-nielsen-reber-etal-introducingthedistributionalfinancialaccountsoftheunitedstates-2019},
url_dfas = {https://bibbase.org/network/publication/boardofgovernorsofthefederalreservesystem-dfadistributionalfinancialaccounts-2023},
url_file = {Battyetal2022wp.pdf},
url_published_version = {https://bibbase.org/network/publication/batty-bricker-briggs-friedman-nemschoff-nielsen-sommer-volz-thedistributionalfinancialaccountsoftheunitedstates-2022}
}This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of US household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products—quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances—to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of US household wealth.
Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France: Appendix. Garbinti, Bertrand; Goupille-Lebret, Jonathan; and Piketty, Thomas. World Inequality Lab. March 2020.
@techreport{Garbintietal2021app,
title = {Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for {{France}}: Appendix},
author = {Garbinti, Bertrand and {Goupille-Lebret}, Jonathan and Piketty, Thomas},
year = {2020},
month = {mar},
number = {2020/05},
institution = {World Inequality Lab},
url = {https://wid.world/document/appendix-to-accounting-for-wealth-inequality-dynamics-methods-estimates-and-simulations-for-france-wid-world-working-paper-2020-05/},
urldate = {2022-03-08},
abstract = {Appendix to 2020 WID.world Working Paper Series (2020/05).},
keywords = {Data Sources: Wealth Inequality},
type = {{{WID}}.World {{Working Paper Series}}},
url_file = {Garbintietal2021app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfrance-2021}
}Appendix to 2020 WID.world Working Paper Series (2020/05).
Online Appendix for: Wealth Taxation and Wealth Accumulation: Theory and Evidence from Denmark. Jakobsen, Katrine; Jakobsen, Kristian; Kleven, Henrik; and Zucman, Gabriel. February 2020.
@misc{Jakobsenetal2020app,
title = {Online Appendix for: Wealth Taxation and Wealth Accumulation: Theory and Evidence from {{Denmark}}},
author = {Jakobsen, Katrine and Jakobsen, Kristian and Kleven, Henrik and Zucman, Gabriel},
year = {2020},
month = {feb},
doi = {10.1093/qje/qjz032},
url = {https://doi.org/10.1093/qje/qjz032},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/jakobsen-jakobsen-kleven-zucman-wealthtaxationandwealthaccumulationtheoryandevidencefromdenmark-2020}
}Wealth Taxation and Wealth Accumulation: Theory and Evidence from Denmark. Jakobsen, Katrine; Jakobsen, Kristian; Kleven, Henrik; and Zucman, Gabriel. The Quarterly Journal of Economics, 135(1): 329–388. February 2020.
@article{Jakobsenetal2020,
title = {Wealth Taxation and Wealth Accumulation: Theory and Evidence from {{Denmark}}},
author = {Jakobsen, Katrine and Jakobsen, Kristian and Kleven, Henrik and Zucman, Gabriel},
year = {2020},
month = {feb},
journal = {The Quarterly Journal of Economics},
volume = {135},
number = {1},
pages = {329--388},
doi = {10.1093/qje/qjz032},
url = {https://doi.org/10.1093/qje/qjz032},
abstract = {Using administrative wealth records from Denmark, we study the effects of wealth taxes on wealth accumulation. Denmark used to impose one of the world's highest marginal tax rates on wealth, but this tax was greatly reduced starting in 1989 and later abolished. Due to the specific design of the wealth tax, the 1989 reform provides a compelling quasi-experiment for understanding behavioral responses among the wealthiest segments of the population. We find clear reduced-form effects of wealth taxes in the short and medium run, with larger effects on the very wealthy than on the moderately wealthy. We develop a simple life cycle model with utility of residual wealth (bequests) allowing us to interpret the evidence in terms of structural primitives. We calibrate the model to the quasi-experimental moments and simulate the model forward to estimate the long-run effect of wealth taxes on wealth accumulation. Our simulations show that the long-run elasticity of taxable wealth with respect to the net-of-tax return is sizable at the top of the distribution.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
url_online_appendix = {https://bibbase.org/network/publication/jakobsen-jakobsen-kleven-zucman-onlineappendixforwealthtaxationandwealthaccumulationtheoryandevidencefromdenmark-2020},
url_replication_data = {https://bibbase.org/network/publication/jakobsen-jakobsen-kleven-zucman-replicationdataforwealthtaxationandwealthaccumulationtheoryandevidencefromdenmark-2019}
}Using administrative wealth records from Denmark, we study the effects of wealth taxes on wealth accumulation. Denmark used to impose one of the world's highest marginal tax rates on wealth, but this tax was greatly reduced starting in 1989 and later abolished. Due to the specific design of the wealth tax, the 1989 reform provides a compelling quasi-experiment for understanding behavioral responses among the wealthiest segments of the population. We find clear reduced-form effects of wealth taxes in the short and medium run, with larger effects on the very wealthy than on the moderately wealthy. We develop a simple life cycle model with utility of residual wealth (bequests) allowing us to interpret the evidence in terms of structural primitives. We calibrate the model to the quasi-experimental moments and simulate the model forward to estimate the long-run effect of wealth taxes on wealth accumulation. Our simulations show that the long-run elasticity of taxable wealth with respect to the net-of-tax return is sizable at the top of the distribution.
Income and Wealth Inequality in America, 1949-2016: Data Archive. Kuhn, Moritz; Schularick, Moritz; and Steins, Ulrike I. 2020.
@misc{Kuhnetal2020data,
title = {Income and Wealth Inequality in {{America}}, 1949-2016: Data Archive},
author = {Kuhn, Moritz and Schularick, Moritz and Steins, Ulrike I.},
year = {2020},
doi = {10.1086/708815},
url = {https://doi.org/10.1086/708815},
keywords = {Data Sources: Wealth Inequality},
url_published_paper = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2020},
url_working_paper = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2018}
}Income and Wealth Inequality in America, 1949–2016. Kuhn, Moritz; Schularick, Moritz; and Steins, Ulrike I. Journal of Political Economy, 128(9): 3469–3519. July 2020.
@article{Kuhnetal2020,
title = {Income and Wealth Inequality in {{America}}, 1949--2016},
author = {Kuhn, Moritz and Schularick, Moritz and Steins, Ulrike I.},
year = {2020},
month = {jul},
journal = {Journal of Political Economy},
volume = {128},
number = {9},
pages = {3469--3519},
doi = {10.1086/708815},
url = {https://doi.org/10.1086/708815},
abstract = {This paper introduces a new long-run data set based on archival data from historical waves of the Survey of Consumer Finances. Studying the joint distribution of household income and wealth, we expose the central importance of portfolio composition and asset prices for wealth dynamics in postwar America. Asset prices shift the wealth distribution because of systematic differences in household portfolios along the wealth distribution. Middle-class portfolios are dominated by housing, while rich households predominantly own business equity. Differential changes in equity and house prices shaped wealth dynamics in postwar America and decoupled the income and wealth distribution over extended periods.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality},
url_appendix = {https://bibbase.org/network/publication/kuhn-schularick-steins-appendixforonlinepublicationincomeandwealthinequalityinamerica19492016-2019},
url_data_archive = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016dataarchive-2020},
url_working_paper = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2018}
}This paper introduces a new long-run data set based on archival data from historical waves of the Survey of Consumer Finances. Studying the joint distribution of household income and wealth, we expose the central importance of portfolio composition and asset prices for wealth dynamics in postwar America. Asset prices shift the wealth distribution because of systematic differences in household portfolios along the wealth distribution. Middle-class portfolios are dominated by housing, while rich households predominantly own business equity. Differential changes in equity and house prices shaped wealth dynamics in postwar America and decoupled the income and wealth distribution over extended periods.
The Rise of Income and Wealth Inequality in America: Evidence from Distributional Macroeconomic Accounts. Saez, Emmanuel; and Zucman, Gabriel. Journal of Economic Perspectives, 34(4): 3–26. September 2020.
@article{SaezZucman2020a,
title = {The Rise of Income and Wealth Inequality in {{America}}: Evidence from Distributional Macroeconomic Accounts},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2020},
month = {sep},
journal = {Journal of Economic Perspectives},
volume = {34},
number = {4},
pages = {3--26},
doi = {10.1257/JEP.34.4.3},
url = {https://doi.org/10.1257/jep.34.4.3},
abstract = {This paper studies inequality in America through the lens of distributional macroeconomic accounts---comprehensive distributions of the aggregate amount of income and wealth recorded in the official macroeconomic accounts of the United States. We use these distributional macroeconomic accounts to quantify the rise of income and wealth concentration since the late 1970s, the change in tax progressivity, and the direct redistributive effects of government intervention in the economy. Between 1978 and 2018, the share of pre-tax income earned by the top 1 percent rose from 10 percent to about 19 percent, and the share of wealth owned by the top 0.1 percent rose from 7 percent to about 18 percent. In 2018, the tax system was regressive at the top-end; the top 400 wealthiest Americans paid a lower average tax rate than the macroeconomic tax rate of 29 percent. We confront our methods and findings with those of other studies, pinpoint the areas where more research is needed, and describe how additional data collection could improve inequality measurement.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Methods of Estimation of Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccountsdatafile-2020},
url_working_paper = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccountsworkingpaper-2020}
}This paper studies inequality in America through the lens of distributional macroeconomic accounts—comprehensive distributions of the aggregate amount of income and wealth recorded in the official macroeconomic accounts of the United States. We use these distributional macroeconomic accounts to quantify the rise of income and wealth concentration since the late 1970s, the change in tax progressivity, and the direct redistributive effects of government intervention in the economy. Between 1978 and 2018, the share of pre-tax income earned by the top 1 percent rose from 10 percent to about 19 percent, and the share of wealth owned by the top 0.1 percent rose from 7 percent to about 18 percent. In 2018, the tax system was regressive at the top-end; the top 400 wealthiest Americans paid a lower average tax rate than the macroeconomic tax rate of 29 percent. We confront our methods and findings with those of other studies, pinpoint the areas where more research is needed, and describe how additional data collection could improve inequality measurement.
The Rise of Income and Wealth Inequality in America: Evidence from Distributional Macroeconomic Accounts: Data File. Saez, Emmanuel; and Zucman, Gabriel. 2020.
@misc{SaezZucman2020adata,
title = {The Rise of Income and Wealth Inequality in {{America}}: Evidence from Distributional Macroeconomic Accounts: Data File},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2020},
url = {https://gabriel-zucman.eu/},
urldate = {2022-03-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {SaezZucman2020adata.xlsx},
url_published_paper = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccounts-2020},
url_working_paper = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccountsworkingpaper-2020}
}The Rise of Income and Wealth Inequality in America: Evidence from Distributional Macroeconomic Accounts [Working Paper]. Saez, Emmanuel; and Zucman, Gabriel. National Bureau of Economic Research. October 2020.
@techreport{SaezZucman2020awp,
title = {The Rise of Income and Wealth Inequality in {{America}}: Evidence from Distributional Macroeconomic Accounts [Working Paper]},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2020},
month = {oct},
number = {27922},
institution = {National Bureau of Economic Research},
doi = {10.3386/w27922},
url = {https://doi.org/10.3386/w27922},
abstract = {This paper studies inequality in America through the lens of distributional macroeconomic accounts---comprehensive distributions of the aggregate amount of income and wealth recorded in the official macroeconomic accounts of the United States. We use these distributional macroeconomic accounts to quantify the rise of income and wealth concentration since the late 1970s, the change in tax progressivity, and the direct redistributive effects of government intervention in the economy. Between 1978 and 2018, the share of pre-tax income earned by the top 1\% rose from 10\% to about 19\% and the share of wealth owned by the top 0.1\% rose from 7\% to about 18\%. In 2018, the tax system was regressive at the top end; the top 400 wealthiest Americans paid a lower average tax rate than the macroeconomic tax rate of 29\%. We confront our methods and findings with those of other studies, pinpoint the areas where more research is needed, and describe how additional data collection could improve inequality measurement.},
keywords = {Data Sources: Wealth Inequality},
type = {Working {{Paper}}},
url_data_file = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccountsdatafile-2020},
url_file = {SaezZucman2020awp.pdf},
url_published_version = {https://bibbase.org/network/publication/saez-zucman-theriseofincomeandwealthinequalityinamericaevidencefromdistributionalmacroeconomicaccounts-2020}
}This paper studies inequality in America through the lens of distributional macroeconomic accounts—comprehensive distributions of the aggregate amount of income and wealth recorded in the official macroeconomic accounts of the United States. We use these distributional macroeconomic accounts to quantify the rise of income and wealth concentration since the late 1970s, the change in tax progressivity, and the direct redistributive effects of government intervention in the economy. Between 1978 and 2018, the share of pre-tax income earned by the top 1% rose from 10% to about 19% and the share of wealth owned by the top 0.1% rose from 7% to about 18%. In 2018, the tax system was regressive at the top end; the top 400 wealthiest Americans paid a lower average tax rate than the macroeconomic tax rate of 29%. We confront our methods and findings with those of other studies, pinpoint the areas where more research is needed, and describe how additional data collection could improve inequality measurement.
Trends in US Income and Wealth Inequality: Revising after the Revisionists. Saez, Emmanuel; and Zucman, Gabriel. National Bureau of Economic Research. October 2020.
@techreport{SaezZucman2020b,
title = {Trends in {{US}} Income and Wealth Inequality: Revising after the Revisionists},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2020},
month = {oct},
number = {27921},
institution = {National Bureau of Economic Research},
doi = {10.3386/w27921},
url = {https://doi.org/10.3386/w27921},
abstract = {Recent studies argue that US inequality has increased less than previously thought, in particular due to a more modest rise of wealth and capital income at the top (Smith et al., 2019; Smith, Zidar and Zwick, 2020; Auten and Splinter, 2019). We examine the claims made in these papers point by point, separating genuine improvements from arguments that do not appear to us well grounded empirically or conceptually. Taking stock of this body of work, and factoring in other improvements, we provide a comprehensive update of our estimates of US income and wealth inequality. Although some of the points raised by the revisionists are valuable, the core quantitative findings of this literature do not appear to be supported by the data. The low capital share of private business income estimated in Smith et al. (2019) is not consistent with the large capital stock of these businesses. In Smith, Zidar and Zwick (2020), the interest rate assigned to the wealthy is higher than in the datasets where both income and wealth can be observed, leading to downward biased top wealth shares; capitalizing equities using almost only dividends dramatically underestimates the wealth of billionaires relative to the Forbes 400. In Auten and Splinter (2019), business profits earned by the top 1\% but not taxable (due in particular to generous depreciation rules) are classified as tax evasion; tax evasion is then allocated to the bottom 99\% based on an erroneous reading of random audit data. Our revised series show a rise of inequality similar to Saez and Zucman (2016) and Piketty, Saez, and Zucman (2018) while allowing for a more granular depiction of the composition of wealth and income at the top.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_data_file = {https://bibbase.org/network/publication/saez-zucman-trendsinusincomeandwealthinequalityrevisingaftertherevisionistsdatafile-2020},
url_file = {SaezZucman2020b.pdf}
}Recent studies argue that US inequality has increased less than previously thought, in particular due to a more modest rise of wealth and capital income at the top (Smith et al., 2019; Smith, Zidar and Zwick, 2020; Auten and Splinter, 2019). We examine the claims made in these papers point by point, separating genuine improvements from arguments that do not appear to us well grounded empirically or conceptually. Taking stock of this body of work, and factoring in other improvements, we provide a comprehensive update of our estimates of US income and wealth inequality. Although some of the points raised by the revisionists are valuable, the core quantitative findings of this literature do not appear to be supported by the data. The low capital share of private business income estimated in Smith et al. (2019) is not consistent with the large capital stock of these businesses. In Smith, Zidar and Zwick (2020), the interest rate assigned to the wealthy is higher than in the datasets where both income and wealth can be observed, leading to downward biased top wealth shares; capitalizing equities using almost only dividends dramatically underestimates the wealth of billionaires relative to the Forbes 400. In Auten and Splinter (2019), business profits earned by the top 1% but not taxable (due in particular to generous depreciation rules) are classified as tax evasion; tax evasion is then allocated to the bottom 99% based on an erroneous reading of random audit data. Our revised series show a rise of inequality similar to Saez and Zucman (2016) and Piketty, Saez, and Zucman (2018) while allowing for a more granular depiction of the composition of wealth and income at the top.
Trends in US Income and Wealth Inequality: Revising after the Revisionists: Data File. Saez, Emmanuel; and Zucman, Gabriel. October 2020.
@misc{SaezZucman2020bdata,
title = {Trends in {{US}} Income and Wealth Inequality: Revising after the Revisionists: Data File},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2020},
month = {oct},
url = {https://gabriel-zucman.eu/},
urldate = {2022-03-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {SaezZucman2020bdata.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/saez-zucman-trendsinusincomeandwealthinequalityrevisingaftertherevisionists-2020}
}Global Wealth Report 2020. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2020.
@misc{Shorrocksetal2020,
title = {Global Wealth Report 2020},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2020},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2023-04-25},
abstract = {The COVID-19 pandemic has had a huge impact on regions all around the globe and affected people's lives in countless ways. How it has impacted wealth and the distribution of wealth is the subject of this special Credit Suisse Global Wealth Report 2020. Given the difficulties encountered in assembling our full dataset in these turbulent times, we have chosen to publish an interim edition of the Global Wealth Report for 2020. We will publish a full edition in the second quarter of 2021, providing further insights into the impact of the pandemic on global wealth. Whereas 2019 was a year of tremendous wealth creation -- total global wealth rose by USD 36.3 trillion during the year -- our experts estimate total household wealth dropped by USD 17.5 trillion between January and March. From March onward, stock markets have rebounded and house prices have soared, and the data available for Q2 2020 suggests that household wealth is roughly back to the level at the end of last year. Lower economic growth for some time and changes in corporate and consumer behavior will result not only in lost output, but also in redundant facilities as well as sectoral changes that may restrain household wealth accumulation for many years. Thus our authors believe that household wealth will, at best, recover slowly from the pandemic throughout 2021. Among major economies, only China is projected to see material gains in wealth over the period. Without the pandemic, our experts' best estimate of global wealth per adult would have risen from USD 77,309 at the start of the year to USD 78,376 at end-June. Instead, the pandemic has caused average wealth to drop to USD 76,984. The most adversely affected region was Latin America, where currency devaluations reinforced reductions in gross domestic product (GDP) to result in a 12.8\% decline in total wealth in US dollar terms. The pandemic eradicated the expected growth in North America and caused losses in every other region, except China and India. Among the major global economies, the United Kingdom has seen the most notable relative erosion of wealth. The worldwide impact on wealth distribution within countries has been remarkably small given the substantial pandemic-related GDP losses. Indeed, there is no firm evidence that the pandemic has systematically favored broad higher wealth groups over lower-wealth groups or vice versa. Although it is too early to fully assess the impact of the COVID-19 pandemic on global wealth distribution, it is notable that the latest data indicate that overall wealth inequality has declined in at least one key country -- the United States. Nevertheless, we are likely to see a differential impact on low-skilled labor, women, minorities and young workers that will require the attention of policymakers. Importantly, the worldwide distribution of wealth will change in response to the changing pattern of household wealth across countries and regions, with China very likely to be among the countries to benefit most. Wealth plays an essential role in household financial resilience and serves as a foundation for broader economic development, especially during times of crisis. We at Credit Suisse remain committed to delivering our financial expertise and experience to all of our clients and stakeholders. I hope readers find the insights of this edition of the Global Wealth Report to be of particular relevance in present times.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2020.pdf}
}The COVID-19 pandemic has had a huge impact on regions all around the globe and affected people's lives in countless ways. How it has impacted wealth and the distribution of wealth is the subject of this special Credit Suisse Global Wealth Report 2020. Given the difficulties encountered in assembling our full dataset in these turbulent times, we have chosen to publish an interim edition of the Global Wealth Report for 2020. We will publish a full edition in the second quarter of 2021, providing further insights into the impact of the pandemic on global wealth. Whereas 2019 was a year of tremendous wealth creation – total global wealth rose by USD 36.3 trillion during the year – our experts estimate total household wealth dropped by USD 17.5 trillion between January and March. From March onward, stock markets have rebounded and house prices have soared, and the data available for Q2 2020 suggests that household wealth is roughly back to the level at the end of last year. Lower economic growth for some time and changes in corporate and consumer behavior will result not only in lost output, but also in redundant facilities as well as sectoral changes that may restrain household wealth accumulation for many years. Thus our authors believe that household wealth will, at best, recover slowly from the pandemic throughout 2021. Among major economies, only China is projected to see material gains in wealth over the period. Without the pandemic, our experts' best estimate of global wealth per adult would have risen from USD 77,309 at the start of the year to USD 78,376 at end-June. Instead, the pandemic has caused average wealth to drop to USD 76,984. The most adversely affected region was Latin America, where currency devaluations reinforced reductions in gross domestic product (GDP) to result in a 12.8% decline in total wealth in US dollar terms. The pandemic eradicated the expected growth in North America and caused losses in every other region, except China and India. Among the major global economies, the United Kingdom has seen the most notable relative erosion of wealth. The worldwide impact on wealth distribution within countries has been remarkably small given the substantial pandemic-related GDP losses. Indeed, there is no firm evidence that the pandemic has systematically favored broad higher wealth groups over lower-wealth groups or vice versa. Although it is too early to fully assess the impact of the COVID-19 pandemic on global wealth distribution, it is notable that the latest data indicate that overall wealth inequality has declined in at least one key country – the United States. Nevertheless, we are likely to see a differential impact on low-skilled labor, women, minorities and young workers that will require the attention of policymakers. Importantly, the worldwide distribution of wealth will change in response to the changing pattern of household wealth across countries and regions, with China very likely to be among the countries to benefit most. Wealth plays an essential role in household financial resilience and serves as a foundation for broader economic development, especially during times of crisis. We at Credit Suisse remain committed to delivering our financial expertise and experience to all of our clients and stakeholders. I hope readers find the insights of this edition of the Global Wealth Report to be of particular relevance in present times.
Top Wealth in America: New Estimates and Implications for Taxing the Rich. Smith, Matthew; Zidar, Owen; and Zwick, Eric. April 2020.
@unpublished{Smithetal2020,
title = {Top Wealth in {{America}}: New Estimates and Implications for Taxing the Rich},
author = {Smith, Matthew and Zidar, Owen and Zwick, Eric},
year = {2020},
month = {apr},
url = {http://ericzwick.com/},
abstract = {This paper uses administrative tax data to estimate top wealth in the United States. We build on the capitalization approach in Saez and Zucman (2016) while accounting for heterogeneity within asset classes when mapping income flows to wealth. Our approach reduces bias in wealth estimates because wealth and rates of return are correlated. We find that the top 0.1\% share of wealth increased from 7\% to 14\% from 1978 to 2016. While this rise is half as large as prior estimates, wealth is very concentrated: the top 1\% holds nearly as much wealth as the bottom 90\%. However, the "P90-99" class holds more wealth than either group after accounting for heterogeneity. Private business and public equity wealth are the primary sources of wealth at the top, and pension and housing wealth account for almost all wealth of the bottom 90\%. Our approach substantially reduces estimates of mechanical wealth tax revenue and top capital income in distributional national accounts, which depend on well-measured estimates of top wealth. From 1980 to 2014, capital income accounts for 2.4 out of 8.1 percentage points of the rise of the top 1\% income share.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
note = {Unpublished manuscript},
url_file = {Smithetal2020.pdf},
url_published_version = {https://bibbase.org/network/publication/smith-zidar-zwick-topwealthinamericanewestimatesunderheterogeneousreturns-2023}
}This paper uses administrative tax data to estimate top wealth in the United States. We build on the capitalization approach in Saez and Zucman (2016) while accounting for heterogeneity within asset classes when mapping income flows to wealth. Our approach reduces bias in wealth estimates because wealth and rates of return are correlated. We find that the top 0.1% share of wealth increased from 7% to 14% from 1978 to 2016. While this rise is half as large as prior estimates, wealth is very concentrated: the top 1% holds nearly as much wealth as the bottom 90%. However, the "P90-99" class holds more wealth than either group after accounting for heterogeneity. Private business and public equity wealth are the primary sources of wealth at the top, and pension and housing wealth account for almost all wealth of the bottom 90%. Our approach substantially reduces estimates of mechanical wealth tax revenue and top capital income in distributional national accounts, which depend on well-measured estimates of top wealth. From 1980 to 2014, capital income accounts for 2.4 out of 8.1 percentage points of the rise of the top 1% income share.
Wealth Inequality and Financial Inclusion: Evidence from South African Tax and Survey Records. von Fintel, Dieter; and Orthofer, Anna. Economic Modelling, 91: 568–578. September 2020.
@article{vonFintelOrthofer2020,
title = {Wealth Inequality and Financial Inclusion: Evidence from {{South African}} Tax and Survey Records},
author = {{von Fintel}, Dieter and Orthofer, Anna},
year = {2020},
month = {sep},
journal = {Economic Modelling},
volume = {91},
pages = {568--578},
doi = {10.1016/j.econmod.2020.02.001},
url = {https://doi.org/10.1016/j.econmod.2020.02.001},
abstract = {Theoretical models show that financial inclusion reduces wealth inequality. Existing empirical models are restricted to estimates using income inequality because of a lack of cross country wealth inequality data. We used 2010-11 and 2014-5 waves of the National Income Dynamics Study combined with South African tax records to estimate wealth and income inequality. Using Re-centered Influence Function regressions on the micro-level records, we confirmed the negative cross-country relationship between financial inclusion and income inequality. Wealth inequality is different. Financial inclusion improved wealth shares of only the middle class. Because of predatory lending, expansion of credit reduced the wealth share of the poor. Improved savings by the middle class, providing better oversight over financial services targeted at the poor and removing impediments to the small business sector are pre-conditions for financial inclusion to reduce wealth inequality.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_online_supplementary_materials = {https://bibbase.org/network/publication/vonfintel-orthofer-wealthinequalityandfinancialinclusionevidencefromsouthafricantaxandsurveyrecordsonlinesupplementarymaterials-2020}
}Theoretical models show that financial inclusion reduces wealth inequality. Existing empirical models are restricted to estimates using income inequality because of a lack of cross country wealth inequality data. We used 2010-11 and 2014-5 waves of the National Income Dynamics Study combined with South African tax records to estimate wealth and income inequality. Using Re-centered Influence Function regressions on the micro-level records, we confirmed the negative cross-country relationship between financial inclusion and income inequality. Wealth inequality is different. Financial inclusion improved wealth shares of only the middle class. Because of predatory lending, expansion of credit reduced the wealth share of the poor. Improved savings by the middle class, providing better oversight over financial services targeted at the poor and removing impediments to the small business sector are pre-conditions for financial inclusion to reduce wealth inequality.
Wealth Inequality and Financial Inclusion: Evidence from South African Tax and Survey Records: Online Supplementary Materials. von Fintel, Dieter; and Orthofer, Anna. July 2020.
@misc{vonFintelOrthofer2020app,
title = {Wealth Inequality and Financial Inclusion: Evidence from {{South African}} Tax and Survey Records: Online Supplementary Materials},
author = {{von Fintel}, Dieter and Orthofer, Anna},
year = {2020},
month = {jul},
url = {https://doi.org/10.1016/j.econmod.2020.02.001},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/vonfintel-orthofer-wealthinequalityandfinancialinclusionevidencefromsouthafricantaxandsurveyrecords-2020}
}Introducing the Distributional Financial Accounts of the United States. Batty, Michael; Bricker, Jesse; Briggs, Joseph; Holmquist, Elizabeth; McIntosh, Susan; Moore, Kevin; Nielsen, Eric; et al. Board of Governors of the Federal Reserve System. March 2019.
@techreport{Battyetal2019,
title = {Introducing the {{Distributional Financial Accounts}} of the {{United States}}},
author = {Batty, Michael and Bricker, Jesse and Briggs, Joseph and Holmquist, Elizabeth and McIntosh, Susan and Moore, Kevin and Nielsen, Eric and Reber, Sarah and Shatto, Molly and Sommer, Kamila and Sweeney, Tom and Volz, Alice Henriques},
year = {2019},
month = {mar},
number = {2019-017},
institution = {Board of Governors of the Federal Reserve System},
doi = {10.17016/feds.2019.017},
url = {https://doi.org/10.17016/feds.2019.017},
abstract = {This paper describes the construction of the Distributional Financial Accounts (DFAs), a new dataset containing quarterly estimates of the distribution of U.S. household wealth since 1989, and provides the first look at the resulting data. The DFAs build on two existing Federal Reserve Board statistical products-quarterly aggregate measures of household wealth from the Financial Accounts of the United States and triennial wealth distribution measures from the Survey of Consumer Finances-to incorporate distributional information into a national accounting framework. The DFAs complement other existing sources of data on the wealth distribution by using a more comprehensive measure of household wealth and by providing quarterly data on a timely basis. We encourage policymakers, researchers, and other interested parties to use the DFAs to help understand issues related to the distribution of U.S. household wealth.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Finance and {{Economics Discussion Series}}},
url_2020_working_paper = {https://bibbase.org/network/publication/batty-bricker-briggs-friedman-nemschoff-nielsen-sommer-volz-thedistributionalfinancialaccountsoftheunitedstates-2020},
url_dfas = {https://bibbase.org/network/publication/boardofgovernorsofthefederalreservesystem-dfadistributionalfinancialaccounts-2023},
url_file = {Battyetal2019.pdf},
url_published_version = {https://bibbase.org/network/publication/batty-bricker-briggs-friedman-nemschoff-nielsen-sommer-volz-thedistributionalfinancialaccountsoftheunitedstates-2022}
}This paper describes the construction of the Distributional Financial Accounts (DFAs), a new dataset containing quarterly estimates of the distribution of U.S. household wealth since 1989, and provides the first look at the resulting data. The DFAs build on two existing Federal Reserve Board statistical products-quarterly aggregate measures of household wealth from the Financial Accounts of the United States and triennial wealth distribution measures from the Survey of Consumer Finances-to incorporate distributional information into a national accounting framework. The DFAs complement other existing sources of data on the wealth distribution by using a more comprehensive measure of household wealth and by providing quarterly data on a timely basis. We encourage policymakers, researchers, and other interested parties to use the DFAs to help understand issues related to the distribution of U.S. household wealth.
Replication Data for: 'Wealth Taxation and Wealth Accumulation: Theory and Evidence from Denmark'. Jakobsen, Katrine; Jakobsen, Kristian; Kleven, Henrik; and Zucman, Gabriel. October 2019.
@misc{Jakobsenetal2020data,
title = {Replication Data for: 'Wealth Taxation and Wealth Accumulation: Theory and Evidence from {{Denmark}}'},
author = {Jakobsen, Katrine and Jakobsen, Kristian and Kleven, Henrik and Zucman, Gabriel},
year = {2019},
month = {oct},
doi = {10.7910/DVN/PFQU4R},
url = {https://doi.org/10.7910/DVN/PFQU4R},
keywords = {Data Sources: Wealth Inequality},
note = {Harvard Dataverse},
url_file = {Jakobsenetal2020data.zip},
url_parent_paper = {https://bibbase.org/network/publication/jakobsen-jakobsen-kleven-zucman-wealthtaxationandwealthaccumulationtheoryandevidencefromdenmark-2020}
}Dimensions of Inequality in Japan: Distributions of Earnings, Income and Wealth between 1984 and 2014. Kitao, Sagiri; and Yamada, Tomoaki. Centre for Applied Macroeconomic Analysis. June 2019.
@techreport{KitaoYamada2019,
title = {Dimensions of Inequality in {{Japan}}: Distributions of Earnings, Income and Wealth between 1984 and 2014},
author = {Kitao, Sagiri and Yamada, Tomoaki},
year = {2019},
month = {jun},
number = {36/2019},
institution = {Centre for Applied Macroeconomic Analysis},
url = {https://cama.crawford.anu.edu.au/publication/cama-working-paper-series/14348/dimensions-inequality-japan-distributions-earnings},
abstract = {Inequality has become a central policy issue across the world. We study trends of inequality in earnings, income and wealth across households in Japan, using the National Survey of Family Income and Expenditure (NSFIE) from 1984 to 2014. We focus on the transition of inequality unconditionally and conditionally across various dimensions of household heterogeneity such as age, cohort, employment and marital status of household heads, sources of income, family size, etc. Inequality in earnings, income and wealth all increased during the last three decades. Changes in earnings and income inequality were mostly driven by demographic shift in the population towards the elderly, who tend to have higher inequality. Wealth inequality rose not only in the aggregate but also among the young, and this is due to a major increase in the fraction of households who own zero or very low wealth across all age groups. Critical factors in understanding inequality trends in Japan that we identified are aging demographics, changes in typical household structure, and macroeconomic trends of the past decades including the financial bubble period and a decades-long slow-down thereafter.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {{{CAMA Working Paper}}},
url_file = {KitaoYamada2019.pdf}
}Inequality has become a central policy issue across the world. We study trends of inequality in earnings, income and wealth across households in Japan, using the National Survey of Family Income and Expenditure (NSFIE) from 1984 to 2014. We focus on the transition of inequality unconditionally and conditionally across various dimensions of household heterogeneity such as age, cohort, employment and marital status of household heads, sources of income, family size, etc. Inequality in earnings, income and wealth all increased during the last three decades. Changes in earnings and income inequality were mostly driven by demographic shift in the population towards the elderly, who tend to have higher inequality. Wealth inequality rose not only in the aggregate but also among the young, and this is due to a major increase in the fraction of households who own zero or very low wealth across all age groups. Critical factors in understanding inequality trends in Japan that we identified are aging demographics, changes in typical household structure, and macroeconomic trends of the past decades including the financial bubble period and a decades-long slow-down thereafter.
Appendix for Online Publication: Income and Wealth Inequality in America, 1949-2016. Kuhn, Moritz; Schularick, Moritz; and Steins, Ulrike I. December 2019.
@misc{Kuhnetal2020app,
title = {Appendix for Online Publication: Income and Wealth Inequality in {{America}}, 1949-2016},
author = {Kuhn, Moritz and Schularick, Moritz and Steins, Ulrike I.},
year = {2019},
month = {dec},
doi = {10.1086/708815},
url = {https://doi.org/10.1086/708815},
abstract = {This appendix accompanies the paper Income and Wealth Inequality in America, 1949-2016. Section A provides further details on the SCF+ data and its construction. We also explain how we implement the approaches for demographic adjustment and how we identify hand-to-mouth households in the data. Section B discusses the coverage of the SCF+ at the top of the income and wealth distribution. Section C discusses evidence on mobility between wealth groups based on Panel Study of Income Dynamics (PSID) data. Section D provides sensitivity tests for Gini coefficients excluding negative wealth or income observations and for imputing rental income from owner-occupied housing. Section E provides additional results on Gini coefficients for different asset classes, a decomposition of house price exposure for different wealth groups over time, and presents time series for income and wealth shares, Gini coefficients for income and wealth, and for the portfolio composition along the wealth distribution.},
keywords = {Data Sources: Wealth Inequality},
url_published_paper = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2020},
url_working_paper = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2018}
}This appendix accompanies the paper Income and Wealth Inequality in America, 1949-2016. Section A provides further details on the SCF+ data and its construction. We also explain how we implement the approaches for demographic adjustment and how we identify hand-to-mouth households in the data. Section B discusses the coverage of the SCF+ at the top of the income and wealth distribution. Section C discusses evidence on mobility between wealth groups based on Panel Study of Income Dynamics (PSID) data. Section D provides sensitivity tests for Gini coefficients excluding negative wealth or income observations and for imputing rental income from owner-occupied housing. Section E provides additional results on Gini coefficients for different asset classes, a decomposition of house price exposure for different wealth groups over time, and presents time series for income and wealth shares, Gini coefficients for income and wealth, and for the portfolio composition along the wealth distribution.
Capital Accumulation, Private Property, and Rising Inequality in China, 1978–2015. Piketty, Thomas; Yang, Li; and Zucman, Gabriel. American Economic Review, 109(7): 2469–2496. July 2019.
@article{Pikettyetal2019,
title = {Capital Accumulation, Private Property, and Rising Inequality in {{China}}, 1978--2015},
author = {Piketty, Thomas and Yang, Li and Zucman, Gabriel},
year = {2019},
month = {jul},
journal = {American Economic Review},
volume = {109},
number = {7},
pages = {2469--2496},
doi = {10.1257/aer.20170973},
url = {https://doi.org/10.1257/aer.20170973},
abstract = {We combine national accounts, surveys, and new tax data to study the accumulation and distribution of income and wealth in China from 1978 to 2015. The national wealth-income ratio increased from 350 percent in 1978 to 700 percent in 2015, while the share of public property in national wealth declined from 70 percent to 30 percent. We provide sharp upward revision of official inequality estimates. The top 10 percent income share rose from 27 percent to 41 percent between 1978 and 2015; the bottom 50 percent share dropped from 27 percent to 15 percent. China's inequality levels used to be close to Nordic countries and are now approaching US levels.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Impacts of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
url_data_files = {https://bibbase.org/network/publication/piketty-yang-zucman-capitalaccumulationprivatepropertyandrisinginequalityinchina19782015datafiles-2018},
url_online_appendix = {https://bibbase.org/network/publication/piketty-yang-zucman-capitalaccumulationprivatepropertyandrisinginequalityinchina19782015onlineappendix-2018}
}We combine national accounts, surveys, and new tax data to study the accumulation and distribution of income and wealth in China from 1978 to 2015. The national wealth-income ratio increased from 350 percent in 1978 to 700 percent in 2015, while the share of public property in national wealth declined from 70 percent to 30 percent. We provide sharp upward revision of official inequality estimates. The top 10 percent income share rose from 27 percent to 41 percent between 1978 and 2015; the bottom 50 percent share dropped from 27 percent to 15 percent. China's inequality levels used to be close to Nordic countries and are now approaching US levels.
Progressive Wealth Taxation. Saez, Emmanuel; and Zucman, Gabriel. Brookings Paper on Economic Activity, Fall: 437–533. 2019.
@article{SaezZucman2019,
title = {Progressive Wealth Taxation},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2019},
journal = {Brookings Paper on Economic Activity},
volume = {Fall},
pages = {437--533},
doi = {10.1353/eca.2019.0017},
url = {https://doi.org/10.1353/eca.2019.0017},
abstract = {This paper discusses the progressive taxation of household wealth. We first discuss what wealth is, how it is distributed, and how much revenue a progressive wealth tax could generate in the United States. We try to reconcile discrepancies across wealth data sources. Second, we discuss the role a wealth tax can play to increase the overall progressivity of the U.S. tax system. Third, we discuss the empirical evidence on wealth tax avoidance and evasion as well as tax enforcement policies. We summarize the key elements needed to make a U.S. wealth tax work in light of the experience of other countries. Fourth, we discuss the real economic effects of wealth taxation on inequality, the capital stock, and economic activity. Fifth, we present a simple tractable model of the taxation of billionaires' wealth that can be applied to the Forbes list of the four hundred richest Americans since 1982 to illustrate the long-run effects of concrete wealth tax proposals on top fortunes.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
url_data_file = {https://bibbase.org/network/publication/saez-zucman-progressivewealthtaxationdatafile-2019}
}This paper discusses the progressive taxation of household wealth. We first discuss what wealth is, how it is distributed, and how much revenue a progressive wealth tax could generate in the United States. We try to reconcile discrepancies across wealth data sources. Second, we discuss the role a wealth tax can play to increase the overall progressivity of the U.S. tax system. Third, we discuss the empirical evidence on wealth tax avoidance and evasion as well as tax enforcement policies. We summarize the key elements needed to make a U.S. wealth tax work in light of the experience of other countries. Fourth, we discuss the real economic effects of wealth taxation on inequality, the capital stock, and economic activity. Fifth, we present a simple tractable model of the taxation of billionaires' wealth that can be applied to the Forbes list of the four hundred richest Americans since 1982 to illustrate the long-run effects of concrete wealth tax proposals on top fortunes.
Progressive Wealth Taxation: Data File. Saez, Emmanuel; and Zucman, Gabriel. 2019.
@misc{SaezZucman2019data,
title = {Progressive Wealth Taxation: Data File},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2019},
url = {https://gabriel-zucman.eu/},
urldate = {2022-03-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {SaezZucman2019data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/saez-zucman-progressivewealthtaxation-2019}
}Top Incomes, Income and Wealth Inequality in the Netherlands: The First 100 Years 1914–2014 – What's Next? Salverda, Wiemer. World Inequality Database. May 2019.
@techreport{Salverda2019,
title = {Top Incomes, Income and Wealth Inequality in the {{Netherlands}}: The First 100 Years 1914--2014 -- What's Next?},
author = {Salverda, Wiemer},
year = {2019},
month = {may},
number = {2019/02},
institution = {World Inequality Database},
url = {https://wid.world/document/top-incomes-income-and-wealth-inequality-in-the-netherlands-the-first-100-years-1914-2014-whats-next-wid-world-wp-2-2019/},
urldate = {2024-05-30},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {{{WID}}.World {{Working Paper}}},
url_data_file = {https://bibbase.org/network/publication/salverda-topincomesincomeandwealthinequalityinthenetherlandsthefirst100years19142014whatsnextdatafile-2019},
url_file = {Salverda2019.pdf}
}Top Incomes, Income and Wealth Inequality in the Netherlands: The First 100 Years 1914–2014 – What's next? Data File. Salverda, Wiemer. 2019.
@misc{Salverda2019data,
title = {Top Incomes, Income and Wealth Inequality in the {{Netherlands}}: The First 100 Years 1914--2014 -- What's next? Data File},
author = {Salverda, Wiemer},
year = {2019},
url = {https://bibbase.org/network/publication/salverda-topincomesincomeandwealthinequalityinthenetherlandsthefirst100years19142014whatsnextdatafile-2019},
keywords = {Data Sources: Wealth Inequality},
url_file = {Salverda2019data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/salverda-topincomesincomeandwealthinequalityinthenetherlandsthefirst100years19142014whatsnext-2019}
}Global Wealth Databook 2019. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2019.
@misc{Shorrocksetal2019,
title = {Global Wealth Databook 2019},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2019},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {For the past ten years, the Credit Suisse Research Institute's Global wealth report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the ``wealth pyramid,'' covering 2.9 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who comprise less than 1\% of the adult population, but own 44\% of household wealth. During the 12 months to mid-2019, aggregate global wealth rose by USD 9.1 trillion (2.6\%) to a combined total of USD 361 trillion. Wealth per adult grew by a modest 1.2\%, although global average wealth achieved yet another record high of USD 70,850 per adult. While the Global wealth report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global wealth databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global wealth report and Global wealth databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have -- or promise to have -- a global impact within and beyond the financial services industry. The Global wealth databook provides estimates for the level and distribution of wealth for over 200 countries for the period 2000 to mid-2019. It covers the pattern and trend of household wealth at both the regional and country levels. To mark its tenth anniversary, this year's report examines in more detail the underlying factors which help explain the evolution of wealth levels and wealth distribution. Particular attention is paid to the growing importance of China and other emerging economies, especially in the period since the global financial crisis when they became the dominant contributor to global wealth creation.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2019.pdf}
}For the past ten years, the Credit Suisse Research Institute's Global wealth report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," covering 2.9 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who comprise less than 1% of the adult population, but own 44% of household wealth. During the 12 months to mid-2019, aggregate global wealth rose by USD 9.1 trillion (2.6%) to a combined total of USD 361 trillion. Wealth per adult grew by a modest 1.2%, although global average wealth achieved yet another record high of USD 70,850 per adult. While the Global wealth report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global wealth databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global wealth report and Global wealth databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have – or promise to have – a global impact within and beyond the financial services industry. The Global wealth databook provides estimates for the level and distribution of wealth for over 200 countries for the period 2000 to mid-2019. It covers the pattern and trend of household wealth at both the regional and country levels. To mark its tenth anniversary, this year's report examines in more detail the underlying factors which help explain the evolution of wealth levels and wealth distribution. Particular attention is paid to the growing importance of China and other emerging economies, especially in the period since the global financial crisis when they became the dominant contributor to global wealth creation.
Global Wealth Report 2019. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2019.
@misc{Shorrocksetal2019a,
title = {Global Wealth Report 2019},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2019},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Ten years ago, the Credit Suisse Research Institute launched the first Global wealth report providing the most comprehensive and up-to date survey of household wealth. Since then the Global wealth report has become the standard reference point to monitor wealth growth across countries and the extent to which wealth inequalities are widening or narrowing. For the past decade, global wealth creation has centered around China and the United States. This year, the United States extended its unbroken spell of wealth gains, which began after the global financial crisis in 2008. The United States also accounts for 40\% of dollar millionaires worldwide and for 40\% of those in the top 1\% of global wealth distribution. Wealth in China started the century from a lower base, but grew at a much faster pace during the early years. It was one of the few countries to avoid the impact of the global financial crisis. China's progress has enabled it to replace Europe as the principal source of global wealth growth and to replace Japan as the country with the second-largest number of millionaires. More tellingly, China overtook the United States this year to become the country with most people in the top 10\% of global wealth distribution. The rest of the world has not stood still. Other emerging markets -- India in particular -- have made a steady contribution, which we expect to continue over the next five years. However, overall worldwide growth was modest in the 12 months up to mid-2019. Aggregate global wealth rose by USD 9.1 trillion to USD 360.6 trillion, representing a growth rate of 2.6\%. Wealth per adult grew by just 1.2\% to USD 70,850 per adult in mid-2019. The number of new millionaires was also relatively modest, up 1.1 million to 46.8 million. The United States added 675,000 newcomers, more than half of the global total. Japan and China each contributed more than 150,000, but Australia lost 124,000 millionaires following a fall in average wealth. To mark its tenth anniversary, this year's report examines in more detail the underlying factors for the evolution of wealth levels and wealth distribution. The growth records of countries can be quite different depending on whether wealth is measured in US dollars or domestic currencies, or in nominal or inflation-adjusted units. In the longer term, the most successful countries are those that succeed in raising wealth as a multiple of Gross Domestic Product (GDP) by addressing institutional and financial-sector deficiencies. This can result in a virtuous cycle in which higher wealth stimulates GDP growth, which in turn raises aggregate wealth. China, India and Vietnam provide examples of this virtuous cycle in action. Second, the report looks at the evolution of wealth inequality. The bottom half of wealth holders collectively accounted for less than 1\% of total global wealth in mid-2019, while the richest 10\% own 82\% of global wealth and the top 1\% alone own 45\%. Global inequality fell during the first part of this century when a narrowing of gaps between countries was reinforced by declining inequality within countries. While advances by emerging markets continued to narrow the gaps between countries, inequality within countries grew as economies recovered after the global financial crisis. As a result, the top 1\% of wealth holders increased their share of world wealth. This trend appears to have abated in 2016 and global inequality is now likely to edge downward in the immediate future. Given some of this year's intriguing findings, we hope you will find the Global wealth report 2019 a valuable source of information and wish you interesting reading.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2019a.pdf}
}Ten years ago, the Credit Suisse Research Institute launched the first Global wealth report providing the most comprehensive and up-to date survey of household wealth. Since then the Global wealth report has become the standard reference point to monitor wealth growth across countries and the extent to which wealth inequalities are widening or narrowing. For the past decade, global wealth creation has centered around China and the United States. This year, the United States extended its unbroken spell of wealth gains, which began after the global financial crisis in 2008. The United States also accounts for 40% of dollar millionaires worldwide and for 40% of those in the top 1% of global wealth distribution. Wealth in China started the century from a lower base, but grew at a much faster pace during the early years. It was one of the few countries to avoid the impact of the global financial crisis. China's progress has enabled it to replace Europe as the principal source of global wealth growth and to replace Japan as the country with the second-largest number of millionaires. More tellingly, China overtook the United States this year to become the country with most people in the top 10% of global wealth distribution. The rest of the world has not stood still. Other emerging markets – India in particular – have made a steady contribution, which we expect to continue over the next five years. However, overall worldwide growth was modest in the 12 months up to mid-2019. Aggregate global wealth rose by USD 9.1 trillion to USD 360.6 trillion, representing a growth rate of 2.6%. Wealth per adult grew by just 1.2% to USD 70,850 per adult in mid-2019. The number of new millionaires was also relatively modest, up 1.1 million to 46.8 million. The United States added 675,000 newcomers, more than half of the global total. Japan and China each contributed more than 150,000, but Australia lost 124,000 millionaires following a fall in average wealth. To mark its tenth anniversary, this year's report examines in more detail the underlying factors for the evolution of wealth levels and wealth distribution. The growth records of countries can be quite different depending on whether wealth is measured in US dollars or domestic currencies, or in nominal or inflation-adjusted units. In the longer term, the most successful countries are those that succeed in raising wealth as a multiple of Gross Domestic Product (GDP) by addressing institutional and financial-sector deficiencies. This can result in a virtuous cycle in which higher wealth stimulates GDP growth, which in turn raises aggregate wealth. China, India and Vietnam provide examples of this virtuous cycle in action. Second, the report looks at the evolution of wealth inequality. The bottom half of wealth holders collectively accounted for less than 1% of total global wealth in mid-2019, while the richest 10% own 82% of global wealth and the top 1% alone own 45%. Global inequality fell during the first part of this century when a narrowing of gaps between countries was reinforced by declining inequality within countries. While advances by emerging markets continued to narrow the gaps between countries, inequality within countries grew as economies recovered after the global financial crisis. As a result, the top 1% of wealth holders increased their share of world wealth. This trend appears to have abated in 2016 and global inequality is now likely to edge downward in the immediate future. Given some of this year's intriguing findings, we hope you will find the Global wealth report 2019 a valuable source of information and wish you interesting reading.
Codebook for 2019 Survey of Consumer Finances. Board of Governors of the Federal Reserve System. 2019.
@misc{FederalReserve2019_Codebook2019SurveyConsumerFinances,
title = {Codebook for 2019 {{Survey}} of {{Consumer Finances}}},
author = {{Board of Governors of the Federal Reserve System}},
year = {2019},
url = {https://www.federalreserve.gov/econres/files/codebk2019.txt},
urldate = {2022-06-27},
keywords = {Data Sources: Wealth Inequality},
url_file = {FederalReserve2019_Codebook2019SurveyConsumerFinances.txt}
}Global Wealth Inequality. Zucman, Gabriel. Annual Review of Economics, 11: 109–138. August 2019.
@article{Zucman2019,
title = {Global Wealth Inequality},
author = {Zucman, Gabriel},
year = {2019},
month = {aug},
journal = {Annual Review of Economics},
volume = {11},
pages = {109--138},
doi = {10.1146/annurev-economics-080218-025852},
url = {https://doi.org/10.1146/annurev-economics-080218-025852},
abstract = {This article reviews the recent literature on the dynamics of global wealth inequality. I first reconcile available estimates of wealth inequality in the United States. Both surveys and tax data show that wealth inequality has increased dramatically since the 1980s, with a top 1\% wealth share of approximately 40\% in 2016 versus 25--30\% in the 1980s. Second, I discuss the fast-growing literature on wealth inequality across the world. Evidence points toward a rise in global wealth concentration: For China, Europe, and the United States combined, the top 1\% wealth share has increased from 28\% in 1980 to 33\% today, while the bottom 75\% share hovered around 10\%. Recent studies, however, may underestimate the level and rise of inequality, as financial globalization makes it increasingly hard to measure wealth at the top. I discuss how new data sources (leaks from financial institutions, tax amnesties, and macroeconomic statistics of tax havens) can be leveraged to better capture the wealth of the rich.},
keywords = {Data Sources: Wealth Inequality,Impacts of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/zucman-globalwealthinequalitydatafile-2019}
}This article reviews the recent literature on the dynamics of global wealth inequality. I first reconcile available estimates of wealth inequality in the United States. Both surveys and tax data show that wealth inequality has increased dramatically since the 1980s, with a top 1% wealth share of approximately 40% in 2016 versus 25–30% in the 1980s. Second, I discuss the fast-growing literature on wealth inequality across the world. Evidence points toward a rise in global wealth concentration: For China, Europe, and the United States combined, the top 1% wealth share has increased from 28% in 1980 to 33% today, while the bottom 75% share hovered around 10%. Recent studies, however, may underestimate the level and rise of inequality, as financial globalization makes it increasingly hard to measure wealth at the top. I discuss how new data sources (leaks from financial institutions, tax amnesties, and macroeconomic statistics of tax havens) can be leveraged to better capture the wealth of the rich.
Global Wealth Inequality: Data File. Zucman, Gabriel. 2019.
@misc{Zucman2019data,
title = {Global Wealth Inequality: Data File},
author = {Zucman, Gabriel},
year = {2019},
url = {https://gabriel-zucman.eu/},
urldate = {2022-03-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {Zucman2019data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/zucman-globalwealthinequality-2019}
}Top Wealth Shares in the UK over More than a Century. Alvaredo, Facundo; Atkinson, Anthony B.; and Morelli, Salvatore. Journal of Public Economics, 162: 26–47. June 2018.
@article{Alvaredoetal2018,
title = {Top Wealth Shares in the {{UK}} over More than a Century},
author = {Alvaredo, Facundo and Atkinson, Anthony B. and Morelli, Salvatore},
year = {2018},
month = {jun},
journal = {Journal of Public Economics},
volume = {162},
pages = {26--47},
doi = {10.1016/j.jpubeco.2018.02.008},
url = {https://doi.org/10.1016/j.jpubeco.2018.02.008},
abstract = {Recent research highlighted controversy about the evolution of concentration of personal wealth. In this paper we provide new evidence about the long-run evolution of top wealth shares for the United Kingdom. The new series covers a long period -- from 1895 to the present -- and has a different point of departure from the previous literature: we start with the analysis of the distribution of estates left at death. We find that the application to the estate data of mortality multipliers to yield estimates of wealth among the living does not substantially change the degree of concentration over much of the period both in the UK and US, allowing inferences to be made for years when this method cannot be applied. The results show that wealth concentration in the UK remained relatively constant during the first wave of globalization, but then decreased dramatically in the period from 1914 to 1979. The UK went from being more unequal in terms of wealth than the US to being less unequal. However, the decline in UK wealth concentration came to an end around 1980, and since then there is evidence of an increase in top shares, notably in the distribution of wealth excluding housing in recent years. We investigate the triangulating evidence provided by data on capital income concentration and on reported super fortunes.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
note = {Special issue: honoring the work of Sir Anthony B. Atkinson (1944--2017)},
url_data_file = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacenturydatafile-2018},
url_online_appendix = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacenturyappendicesforonlinepublication-2018},
url_working_paper = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacentury-2017}
}Recent research highlighted controversy about the evolution of concentration of personal wealth. In this paper we provide new evidence about the long-run evolution of top wealth shares for the United Kingdom. The new series covers a long period – from 1895 to the present – and has a different point of departure from the previous literature: we start with the analysis of the distribution of estates left at death. We find that the application to the estate data of mortality multipliers to yield estimates of wealth among the living does not substantially change the degree of concentration over much of the period both in the UK and US, allowing inferences to be made for years when this method cannot be applied. The results show that wealth concentration in the UK remained relatively constant during the first wave of globalization, but then decreased dramatically in the period from 1914 to 1979. The UK went from being more unequal in terms of wealth than the US to being less unequal. However, the decline in UK wealth concentration came to an end around 1980, and since then there is evidence of an increase in top shares, notably in the distribution of wealth excluding housing in recent years. We investigate the triangulating evidence provided by data on capital income concentration and on reported super fortunes.
Top Wealth Shares in the UK over More than a Century: Appendices for on Line Publication. Alvaredo, Facundo; Atkinson, Anthony B.; and Morelli, Salvatore. June 2018.
@misc{Alvaredoetal2018app,
title = {Top Wealth Shares in the {{UK}} over More than a Century: Appendices for on Line Publication},
author = {Alvaredo, Facundo and Atkinson, Anthony B. and Morelli, Salvatore},
year = {2018},
month = {jun},
url = {https://doi.org/10.1016/j.jpubeco.2018.02.008},
abstract = {Appendices for version published in Journal of Public Economics.},
keywords = {Data Sources: Wealth Inequality},
url_published_paper = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacentury-2018},
url_working_paper = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacentury-2017}
}Appendices for version published in Journal of Public Economics.
Top Wealth Shares in the UK over More than a Century: Data File. Alvaredo, Facundo; Atkinson, Anthony B.; and Morelli, Salvatore. June 2018.
@misc{Alvaredoetal2018data,
title = {Top Wealth Shares in the {{UK}} over More than a Century: Data File},
author = {Alvaredo, Facundo and Atkinson, Anthony B. and Morelli, Salvatore},
year = {2018},
month = {jun},
url = {https://doi.org/10.1016/j.jpubeco.2018.02.008},
abstract = {Data file for version published in Journal of Public Economics.},
keywords = {Data Sources: Wealth Inequality},
url_published_paper = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacentury-2018},
url_working_paper = {https://bibbase.org/network/publication/alvaredo-atkinson-morelli-topwealthsharesintheukovermorethanacentury-2017}
}Data file for version published in Journal of Public Economics.
Wealth Inequality, Class and Caste in India, 1961-2012. Bharti, Nitin Kumar. World Inequality Database. 2018.
@techreport{Bharti2018,
title = {Wealth Inequality, Class and Caste in {{India}}, 1961-2012},
author = {Bharti, Nitin Kumar},
year = {2018},
number = {2018/14},
institution = {World Inequality Database},
url = {https://wid.world/document/n-k-bharti-wealth-inequality-class-and-caste-in-india-1961-2012/},
urldate = {2022-04-01},
abstract = {This research makes two main contributions. First, I combine data from wealth surveys (NSS-AIDIS) and millionaire lists to produce wealth inequality series for India over the 1961-2012 period. I find a strong rise in wealth concentration in recent decades, in line with recent research using income data. E.g. the top 10\% wealth share rose from 45\% in year 1981 to 68\% in 2012, while the top 1\% share rose from 27\% to 41\%. Next, I gather information from censuses and surveys (NSS AIDIS and consumption, IHDS, NFHS) in order to explore the changing relationship between class and caste in India and the mechanisms behind rising inequality. Assortative mating appears to be very high in India, both at the caste level and at the education level (though not hugely larger than than in Western countries at the education level). I stress the limits of our knowledge and indicate possible lines of future research, particularly regarding the interplay between assortative mating and inequality dynamics.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {{{WID}}.World {{Working Paper}}},
url_file = {Bharti2018.pdf}
}This research makes two main contributions. First, I combine data from wealth surveys (NSS-AIDIS) and millionaire lists to produce wealth inequality series for India over the 1961-2012 period. I find a strong rise in wealth concentration in recent decades, in line with recent research using income data. E.g. the top 10% wealth share rose from 45% in year 1981 to 68% in 2012, while the top 1% share rose from 27% to 41%. Next, I gather information from censuses and surveys (NSS AIDIS and consumption, IHDS, NFHS) in order to explore the changing relationship between class and caste in India and the mechanisms behind rising inequality. Assortative mating appears to be very high in India, both at the caste level and at the education level (though not hugely larger than than in Western countries at the education level). I stress the limits of our knowledge and indicate possible lines of future research, particularly regarding the interplay between assortative mating and inequality dynamics.
How Much Has Wealth Concentration Grown in the United States? A Re-Examination of Data from 2001-2013. Bricker, Jesse; Henriques, Alice; and Hansen, Peter. Board of Governors of the Federal Reserve System. April 2018.
@techreport{Brickeretal2018,
title = {How Much Has Wealth Concentration Grown in the {{United States}}? {{A}} Re-Examination of Data from 2001-2013},
author = {Bricker, Jesse and Henriques, Alice and Hansen, Peter},
year = {2018},
month = {apr},
number = {2018-024},
institution = {Board of Governors of the Federal Reserve System},
doi = {10.17016/feds.2018.024},
url = {https://doi.org/10.17016/FEDS.2018.024},
abstract = {Well known research based on capitalized income tax data shows robust growth in wealth concentration in the late 2000s. We show that these robust growth estimates rely on an assumption---homogeneous rates of return across the wealth distribution---that is not supported by data. When the capitalization model incorporates heterogeneous rates of return (on just interest-bearing assets), wealth concentration estimates in 2011 fall from 40.5\% to 33.9\%. These estimates are consistent in levels and trend with other micro wealth data and show that wealth concentration increases until the Great Recession, then declines before increasing again.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Finance and {{Economics Discussion Series}}},
url_accessible_figures = {https://bibbase.org/network/publication/bricker-henriques-hansen-howmuchhaswealthconcentrationgrownintheunitedstatesareexaminationofdatafrom20012013accessiblefigures-2018},
url_file = {Brickeretal2018.pdf}
}Well known research based on capitalized income tax data shows robust growth in wealth concentration in the late 2000s. We show that these robust growth estimates rely on an assumption—homogeneous rates of return across the wealth distribution—that is not supported by data. When the capitalization model incorporates heterogeneous rates of return (on just interest-bearing assets), wealth concentration estimates in 2011 fall from 40.5% to 33.9%. These estimates are consistent in levels and trend with other micro wealth data and show that wealth concentration increases until the Great Recession, then declines before increasing again.
How Much Has Wealth Concentration Grown in the United States? A Re-Examination of Data from 2001-2013: Accessible Figures. Bricker, Jesse; Henriques, Alice; and Hansen, Peter. Board of Governors of the Federal Reserve System. April 2018.
@misc{Brickeretal2018data,
title = {How Much Has Wealth Concentration Grown in the {{United States}}? {{A}} Re-Examination of Data from 2001-2013: Accessible Figures},
author = {Bricker, Jesse and Henriques, Alice and Hansen, Peter},
year = {2018},
month = {apr},
publisher = {Board of Governors of the Federal Reserve System},
doi = {10.17016/feds.2018.024},
url = {https://doi.org/10.17016/FEDS.2018.024},
abstract = {Well known research based on capitalized income tax data shows robust growth in wealth concentration in the late 2000s. We show that these robust growth estimates rely on an assumption---homogeneous rates of return across the wealth distribution---that is not supported by data. When the capitalization model incorporates heterogeneous rates of return (on just interest-bearing assets), wealth concentration estimates in 2011 fall from 40.5\% to 33.9\%. These estimates are consistent in levels and trend with other micro wealth data and show that wealth concentration increases until the Great Recession, then declines before increasing again.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Brickeretal2018data.html},
url_parent_paper = {https://bibbase.org/network/publication/bricker-henriques-hansen-howmuchhaswealthconcentrationgrownintheunitedstatesareexaminationofdatafrom20012013-2018}
}Well known research based on capitalized income tax data shows robust growth in wealth concentration in the late 2000s. We show that these robust growth estimates rely on an assumption—homogeneous rates of return across the wealth distribution—that is not supported by data. When the capitalization model incorporates heterogeneous rates of return (on just interest-bearing assets), wealth concentration estimates in 2011 fall from 40.5% to 33.9%. These estimates are consistent in levels and trend with other micro wealth data and show that wealth concentration increases until the Great Recession, then declines before increasing again.
Wealth Inequality in Italy: A Reconstruction of 1968-1975 Data and a Comparison with Recent Estimates. Cannari, Luigi; and D'Alessio, Giovanni. Rivista di Storia Economica, XXXIV(3): 357–396. December 2018.
@article{CannariDAlessio2018,
title = {Wealth Inequality in {{Italy}}: {{A}} Reconstruction of 1968-1975 Data and a Comparison with Recent Estimates},
author = {Cannari, Luigi and D'Alessio, Giovanni},
year = {2018},
month = {dec},
journal = {Rivista di Storia Economica},
volume = {XXXIV},
number = {3},
pages = {357--396},
doi = {10.1410/94752},
url = {https://www.rivisteweb.it/doi/10.1410/94752},
urldate = {2022-02-15},
abstract = {This paper provides a reconstruction of the joint distribution of income and wealth among Italians in the years ranging from 1968 to 1975. By exploiting the information available in some historical reports recently published by the Bank of Italy, the paper reconstructs synthetic microdata compatible with the aggregate results of sample surveys carried out in those years. In this way, inequality and poverty can be estimated by using the same statistical criteria that are used today, making possible an intertemporal comparison of the estimates. The concentration of household wealth shows a downward trend in the 1970s and 1980s, an increase in the years following the 1992-1993 crisis and a relative stability in the new century. In the period 1968-1975 the concentration of wealth turns out to have been higher than in recent years. The estimates of relative poverty, calculated by using both indicators of equivalent income and indicators that combine income and wealth, show a decreasing trend until the 1990s and a subsequent increase; the upward trend of these indicators in recent years is steeper than that of the concentration indices. The poverty indicators that take wealth into account have reached levels similar to those observed in the period 1968-1975. Migration flows have significantly contributed to the recent growth in the poverty indices.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality}
}This paper provides a reconstruction of the joint distribution of income and wealth among Italians in the years ranging from 1968 to 1975. By exploiting the information available in some historical reports recently published by the Bank of Italy, the paper reconstructs synthetic microdata compatible with the aggregate results of sample surveys carried out in those years. In this way, inequality and poverty can be estimated by using the same statistical criteria that are used today, making possible an intertemporal comparison of the estimates. The concentration of household wealth shows a downward trend in the 1970s and 1980s, an increase in the years following the 1992-1993 crisis and a relative stability in the new century. In the period 1968-1975 the concentration of wealth turns out to have been higher than in recent years. The estimates of relative poverty, calculated by using both indicators of equivalent income and indicators that combine income and wealth, show a decreasing trend until the 1990s and a subsequent increase; the upward trend of these indicators in recent years is steeper than that of the concentration indices. The poverty indicators that take wealth into account have reached levels similar to those observed in the period 1968-1975. Migration flows have significantly contributed to the recent growth in the poverty indices.
Wealth Inequality in Korea, 2000–2013: Evidence from Inheritance Tax Statistics. Kim, Nak Nyeon. Journal of the Korean Welfare State and Social Policy, 2(1): 26–57. 2018.
@article{Kim2018,
title = {Wealth Inequality in {{Korea}}, 2000--2013: Evidence from Inheritance Tax Statistics},
author = {Kim, Nak Nyeon},
year = {2018},
journal = {Journal of the Korean Welfare State and Social Policy},
volume = {2},
number = {1},
pages = {26--57},
url = {http://www.welfarestate.re.kr/beluxe_wtFu73/5421},
urldate = {2022-04-01},
abstract = {This paper estimates the individual wealth distribution since 2000 by applying the estate multiplier method to the inheritance tax statistics. Based on these estimates, the main findings are as follows. First, the top 1\% (or 10\%) of the adult population aged 20 and above owned 24\% (or 63\%) of total wealth for 2000--2007 and 25\% (or 66\%) for 2010--2013. Wealth concentration was much higher than income concentration, which was 12.1\% (or 44.1\%). Second, the wealth concentration in South Korea was lower than Anglo Saxon countries but somewhat higher than European continental countries such as France, falling in the middle of these two groups. A similar international status was true of income concentration. Third, Statistics Korea's Survey of Household Finances and Living Conditions does not adequately cover the financial assets of the top wealth brackets and consequently underestimates wealth inequality.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Trends in Aggregate Wealth and Wealth Inequality}
}This paper estimates the individual wealth distribution since 2000 by applying the estate multiplier method to the inheritance tax statistics. Based on these estimates, the main findings are as follows. First, the top 1% (or 10%) of the adult population aged 20 and above owned 24% (or 63%) of total wealth for 2000–2007 and 25% (or 66%) for 2010–2013. Wealth concentration was much higher than income concentration, which was 12.1% (or 44.1%). Second, the wealth concentration in South Korea was lower than Anglo Saxon countries but somewhat higher than European continental countries such as France, falling in the middle of these two groups. A similar international status was true of income concentration. Third, Statistics Korea's Survey of Household Finances and Living Conditions does not adequately cover the financial assets of the top wealth brackets and consequently underestimates wealth inequality.
Income and Wealth Inequality in America, 1949-2016. Kuhn, Moritz; Schularick, Moritz; and Steins, Ulrike I. Opportunity and Inclusive Growth Institute. June 2018.
@techreport{Kuhnetal2020wp,
title = {Income and Wealth Inequality in {{America}}, 1949-2016},
author = {Kuhn, Moritz and Schularick, Moritz and Steins, Ulrike I.},
year = {2018},
month = {jun},
number = {9},
institution = {{Opportunity and Inclusive Growth Institute}},
doi = {10.21034/iwp.9},
url = {https://doi.org/10.21034/iwp.9},
abstract = {This paper introduces a new long-run dataset based on archival data from historical waves of the Survey of Consumer Finances. The household-level data allow us to study the joint distributions of household income and wealth since 1949. We expose the central importance of portfolio composition and asset prices for wealth dynamics in postwar America. Asset prices shift the wealth distribution because the composition and leverage of household portfolios differ systematically along the wealth distribution. Middle-class portfolios are dominated by housing, while rich households predominantly own equity. An important consequence is that the top and the middle of the distribution are affected differentially by changes in equity and house prices. Housing booms lead to substantial wealth gains for leveraged middle-class households and tend to decrease wealth inequality, all else equal. Stock market booms primarily boost the wealth of households at the top of the distribution. This race between the equity market and the housing market shaped wealth dynamics in postwar America and decoupled the income and wealth distribution over extended periods. The historical data also reveal that no progress has been made in reducing income and wealth inequalities between black and white households over the past 70 years, and that close to half of all American households have less wealth today in real terms than the median household had in 1970.},
keywords = {Data Sources: Wealth Inequality},
type = {Institute {{Working Paper}}},
url_appendix = {https://bibbase.org/network/publication/kuhn-schularick-steins-appendixforonlinepublicationincomeandwealthinequalityinamerica19492016-2019},
url_data_archive = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016dataarchive-2020},
url_file = {Kuhnetal2020wp.pdf},
url_published_version = {https://bibbase.org/network/publication/kuhn-schularick-steins-incomeandwealthinequalityinamerica19492016-2020}
}This paper introduces a new long-run dataset based on archival data from historical waves of the Survey of Consumer Finances. The household-level data allow us to study the joint distributions of household income and wealth since 1949. We expose the central importance of portfolio composition and asset prices for wealth dynamics in postwar America. Asset prices shift the wealth distribution because the composition and leverage of household portfolios differ systematically along the wealth distribution. Middle-class portfolios are dominated by housing, while rich households predominantly own equity. An important consequence is that the top and the middle of the distribution are affected differentially by changes in equity and house prices. Housing booms lead to substantial wealth gains for leveraged middle-class households and tend to decrease wealth inequality, all else equal. Stock market booms primarily boost the wealth of households at the top of the distribution. This race between the equity market and the housing market shaped wealth dynamics in postwar America and decoupled the income and wealth distribution over extended periods. The historical data also reveal that no progress has been made in reducing income and wealth inequalities between black and white households over the past 70 years, and that close to half of all American households have less wealth today in real terms than the median household had in 1970.
Wealth Inequality in Sweden: What Can We Learn from Capitalized Income Tax Data? Lundberg, Jacob; and Waldenström, Daniel. Review of Income and Wealth, 64(3): 517–541. September 2018.
@article{LundbergWaldenstrom2018,
title = {Wealth Inequality in {{Sweden}}: What Can We Learn from Capitalized Income Tax Data?},
author = {Lundberg, Jacob and Waldenstr{\"o}m, Daniel},
year = {2018},
month = {sep},
journal = {Review of Income and Wealth},
volume = {64},
number = {3},
pages = {517--541},
doi = {10.1111/roiw.12294},
url = {https://doi.org/10.1111/roiw.12294},
abstract = {This paper presents new estimates of wealth inequality in Sweden during 2000--2012, linking wealth register data up to 2007 and individually capitalized wealth based on income and property tax registers for the period thereafter when a repeal of the wealth tax stopped the collection of individual wealth statistics. We find that wealth inequality increased after 2007 and that more unequal bank holdings and housing appear to be important drivers. We also evaluate the performance of the capitalization method by contrasting its estimates and their dispersion with observed stocks in register data up to 2007. The goodness-of-fit varies tremendously across assets and we conclude that although capitalized wealth estimates may well approximate overall inequality levels and trends, they are highly sensitive to assumptions and the quality of the underlying data sources.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_appendix = {https://bibbase.org/network/publication/lundberg-waldenstrm-wealthinequalityinswedenwhatcanwelearnfromcapitalizedincometaxdataappendix-2018}
}This paper presents new estimates of wealth inequality in Sweden during 2000–2012, linking wealth register data up to 2007 and individually capitalized wealth based on income and property tax registers for the period thereafter when a repeal of the wealth tax stopped the collection of individual wealth statistics. We find that wealth inequality increased after 2007 and that more unequal bank holdings and housing appear to be important drivers. We also evaluate the performance of the capitalization method by contrasting its estimates and their dispersion with observed stocks in register data up to 2007. The goodness-of-fit varies tremendously across assets and we conclude that although capitalized wealth estimates may well approximate overall inequality levels and trends, they are highly sensitive to assumptions and the quality of the underlying data sources.
Wealth Inequality in Sweden: What Can We Learn from Capitalized Income Tax Data? Appendix. Lundberg, Jacob; and Waldenström, Daniel. 2018.
@misc{LundbergWaldenstrom2018app,
title = {Wealth Inequality in {{Sweden}}: What Can We Learn from Capitalized Income Tax Data? Appendix},
author = {Lundberg, Jacob and Waldenstr{\"o}m, Daniel},
year = {2018},
doi = {10.1111/roiw.12294},
url = {https://doi.org/10.1111/roiw.12294},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/lundberg-waldenstrm-wealthinequalityinswedenwhatcanwelearnfromcapitalizedincometaxdata-2018}
}From Soviets to Oligarchs: Inequality and Property in Russia 1905-2016. Novokmet, Filip; Piketty, Thomas; and Zucman, Gabriel. Journal of Economic Inequality, 16(2): 189–223. 2018.
@article{Novokmetetal2018,
title = {From {{Soviets}} to Oligarchs: Inequality and Property in {{Russia}} 1905-2016},
author = {Novokmet, Filip and Piketty, Thomas and Zucman, Gabriel},
year = {2018},
journal = {Journal of Economic Inequality},
volume = {16},
number = {2},
pages = {189--223},
doi = {10.1007/s10888-018-9383-0},
url = {https://doi.org/10.1007/s10888-018-9383-0},
abstract = {This paper combines national accounts, survey, wealth and fiscal data (including recently released tax data on high-income taxpayers) in order to provide consistent series on the accumulation and distribution of income and wealth in Russia from the Soviet period until the present day. We find that official survey-based measures vastly under-estimate the rise of inequality since 1990. According to our benchmark estimates, top income shares are now similar to (or higher than) the levels observed in the United States. We also find that inequality has increased substantially more in Russia than in China and other ex-communist countries in Eastern Europe. We relate this finding to the specific transition strategy followed in Russia. According to our benchmark estimates, the wealth held offshore by rich Russians is about three times larger than official net foreign reserves, and is comparable in magnitude to total household financial assets held in Russia.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Impacts of Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_appendix = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016appendix-2017},
url_main_figures_and_tables = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016mainfiguresandtables-2018},
url_working_paper = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016workingpaper-2018}
}This paper combines national accounts, survey, wealth and fiscal data (including recently released tax data on high-income taxpayers) in order to provide consistent series on the accumulation and distribution of income and wealth in Russia from the Soviet period until the present day. We find that official survey-based measures vastly under-estimate the rise of inequality since 1990. According to our benchmark estimates, top income shares are now similar to (or higher than) the levels observed in the United States. We also find that inequality has increased substantially more in Russia than in China and other ex-communist countries in Eastern Europe. We relate this finding to the specific transition strategy followed in Russia. According to our benchmark estimates, the wealth held offshore by rich Russians is about three times larger than official net foreign reserves, and is comparable in magnitude to total household financial assets held in Russia.
From Soviets to Oligarchs: Inequality and Property in Russia 1905-2016: Data Files. Novokmet, Filip; Piketty, Thomas; and Zucman, Gabriel. 2018.
@misc{Novokmetetal2018data,
title = {From {{Soviets}} to Oligarchs: Inequality and Property in {{Russia}} 1905-2016: Data Files},
author = {Novokmet, Filip and Piketty, Thomas and Zucman, Gabriel},
year = {2018},
url = {https://gabriel-zucman.eu/russia/},
urldate = {2022-03-09},
abstract = {Includes main figures and tables and appendix A data. Complete data, including distributional series files, are available at the URL provided.},
keywords = {Data Sources: Wealth Inequality},
annotation = {tex.url\_published\_paper https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016-2018},
url_file = {Novokmetetal2018data.zip},
url_working_paper = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016workingpaper-2018}
}Includes main figures and tables and appendix A data. Complete data, including distributional series files, are available at the URL provided.
Capital Accumulation, Private Property, and Rising Inequality in China, 1978-2015: Data Files. Piketty, Thomas; Yang, Li; and Zucman, Gabriel. October 2018.
@misc{Pikettyetal2019data,
title = {Capital Accumulation, Private Property, and Rising Inequality in {{China}}, 1978-2015: Data Files},
author = {Piketty, Thomas and Yang, Li and Zucman, Gabriel},
year = {2018},
month = {oct},
url = {https://gabriel-zucman.eu/china/},
urldate = {2022-03-10},
abstract = {The attached file includes the main figures and tables (PYZ2017MainFiguresTables.xlsx) as well as the data for Appendix A, the national accounts series (PYZ2017NationalAccountsDataMainFiles.zip). Data for Appendix B (distributional files), as well as a complete replication archive and raw files can be found at the URL provided.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Pikettyetal2019data.zip},
url_parent_paper = {https://bibbase.org/network/publication/piketty-yang-zucman-capitalaccumulationprivatepropertyandrisinginequalityinchina19782015-2019}
}The attached file includes the main figures and tables (PYZ2017MainFiguresTables.xlsx) as well as the data for Appendix A, the national accounts series (PYZ2017NationalAccountsDataMainFiles.zip). Data for Appendix B (distributional files), as well as a complete replication archive and raw files can be found at the URL provided.
Capital Accumulation, Private Property and Rising Inequality in China, 1978-2015 Online Appendix. Piketty, Thomas; Yang, Li; and Zucman, Gabriel. October 2018.
@misc{Pikettyetal2019app,
title = {Capital Accumulation, Private Property and Rising Inequality in {{China}}, 1978-2015 Online Appendix},
author = {Piketty, Thomas and Yang, Li and Zucman, Gabriel},
year = {2018},
month = {oct},
doi = {10.1257/aer.20170973},
url = {https://doi.org/10.1257/aer.20170973},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/piketty-yang-zucman-capitalaccumulationprivatepropertyandrisinginequalityinchina19782015-2019}
}Global Wealth Databook 2018. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2018.
@misc{Shorrocksetal2018,
title = {Global Wealth Databook 2018},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2018},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Since 2010, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the "wealth pyramid," capturing 3.2 billion adults with wealth below USD 10,000 to those at the apex of the wealth pyramid with USD 1 million or more who comprise less than 1\% of the adult population, but own 45\% of household wealth. During the 12 months to mid-2018, aggregate global wealth rose by USD 14.0 trillion (4.6\%) to a total of USD 317 trillion, outpacing population growth. Wealth per adult grew by 3.2\%, raising global mean wealth to a record high of USD 63,100 per adult. While the Global Wealth Report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global Wealth Databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global Wealth Report and Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have -- or promise to have -- a global impact within and beyond the financial services industry. The Global Wealth Databook provides estimates for the level and distribution of wealth for over 200 countries for the period 2000 to mid-2018. It covers the evolution of household wealth at both the regional and country levels. This year's Databook also presents findings on female wealth holdings, in particular on gender differences with males. Women nowadays account for an estimated 40\% of global wealth overall, with most of the rise in their share of wealth having occurred in the 20th century.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2018.pdf}
}Since 2010, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," capturing 3.2 billion adults with wealth below USD 10,000 to those at the apex of the wealth pyramid with USD 1 million or more who comprise less than 1% of the adult population, but own 45% of household wealth. During the 12 months to mid-2018, aggregate global wealth rose by USD 14.0 trillion (4.6%) to a total of USD 317 trillion, outpacing population growth. Wealth per adult grew by 3.2%, raising global mean wealth to a record high of USD 63,100 per adult. While the Global Wealth Report highlights the main features of global wealth holdings in recent years, the Credit Suisse Research Institute's Global Wealth Databook provides a great deal more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the published results. This level of detail sets it apart from other reports in this field. Research for the Global Wealth Report and Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, assisted by Dr. Rodrigo Lluberas. The Credit Suisse Research Institute is Credit Suisse's in-house think tank. The Institute was established in the aftermath of the 2008 financial crisis with the objective of studying long-term economic developments, which have – or promise to have – a global impact within and beyond the financial services industry. The Global Wealth Databook provides estimates for the level and distribution of wealth for over 200 countries for the period 2000 to mid-2018. It covers the evolution of household wealth at both the regional and country levels. This year's Databook also presents findings on female wealth holdings, in particular on gender differences with males. Women nowadays account for an estimated 40% of global wealth overall, with most of the rise in their share of wealth having occurred in the 20th century.
Global Wealth Report 2018. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2018.
@misc{Shorrocksetal2018a,
title = {Global Wealth Report 2018},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2018},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {The Credit Suisse Global Wealth Report is the most extensive and current source of information on global household wealth. Now in its ninth edition, the report not only provides insights into the wealth development of regions and segments, but for the first time it also focuses on the most recent evidence on female wealth holdings, in particular on gender differences with males. During the 12 months since our last report to mid-2018, aggregate global wealth rose by USD 14 trillion to USD 317 trillion, which represents a growth rate of approximately 4.6\%. This growth rate was lower than last year, but higher than the average growth rate in the post-2008 era. This was sufficient to outpace population growth, so that wealth per adult grew by approximately 3.2\%, a record high. Looking at the number of millionaires, we see that there are 42.2 million millionaires worldwide, which is up 2.3 million over the previous 12 months. Our research indicates that the United States added 878,000 new millionaires -- representing around 40\% of the global increase -- to its already sizable stock, whereas the number of newcomers in France, Germany, the United Kingdom and Italy was around 200,000 each. In China, the number of millionaires rose by a modest 186,000 and in Japan 94,000. The main explanation for these increases in millionaire numbers within countries lies in the real wealth growth, rather than in exchange-rate movements. Millionaire numbers fell in very few countries (such as Turkey and Brazil), and by relatively small amounts, the main driver being currency depreciation. The key finding of this year's new wealth valuation is for many observers not surprising -- China is now clearly established second place in the world wealth hierarchy. The country overtook Japan with respect to the number of ultra-high net worth (UHNW) individuals in 2009, total wealth in 2011 and the number of millionaires in 2014. Nevertheless, the data shows that mean wealth per adult in China (USD 47,810 in mid-2018) remains far below the level in Japan (USD 227,240). Turning our interest to the lower level of the wealth distribution, we see that 3.2 billion adults or about 64\% of the adult population lives with a wealth below USD 10,000, which corresponds to only 1.9\% of the global wealth. Those with low wealth are disproportionately found among the younger age groups, those who live in regions where prospects for wealth creation are very limited (most notably Africa) and where opportunities are sometimes constrained. The wealth of women has been receiving increasing attention and we estimate that women account for about 40\% of global wealth overall. During the 20th century, their share of wealth rose considerably and, since the year 2000, the level of women's wealth has risen along with all household wealth, especially in Asia alongside the rise of China's wealth. The tendency shows that more self-made women are succeeding in business and are entering the highest wealth ranks. Despite this trend, even in those countries where progress is the strongest, some categories of women -- such as single mothers and divorcees -- remain disadvantaged. While more is required to be done to ensure that women have an equal opportunity to build up, inherit and share in wealth, there are signs that progress has been happening in many parts of the world. Given some of this year's intriguing findings, we hope you find the 2018 edition of the Global Wealth Report a valuable source of insight and wish you interesting reading.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2018a.pdf}
}The Credit Suisse Global Wealth Report is the most extensive and current source of information on global household wealth. Now in its ninth edition, the report not only provides insights into the wealth development of regions and segments, but for the first time it also focuses on the most recent evidence on female wealth holdings, in particular on gender differences with males. During the 12 months since our last report to mid-2018, aggregate global wealth rose by USD 14 trillion to USD 317 trillion, which represents a growth rate of approximately 4.6%. This growth rate was lower than last year, but higher than the average growth rate in the post-2008 era. This was sufficient to outpace population growth, so that wealth per adult grew by approximately 3.2%, a record high. Looking at the number of millionaires, we see that there are 42.2 million millionaires worldwide, which is up 2.3 million over the previous 12 months. Our research indicates that the United States added 878,000 new millionaires – representing around 40% of the global increase – to its already sizable stock, whereas the number of newcomers in France, Germany, the United Kingdom and Italy was around 200,000 each. In China, the number of millionaires rose by a modest 186,000 and in Japan 94,000. The main explanation for these increases in millionaire numbers within countries lies in the real wealth growth, rather than in exchange-rate movements. Millionaire numbers fell in very few countries (such as Turkey and Brazil), and by relatively small amounts, the main driver being currency depreciation. The key finding of this year's new wealth valuation is for many observers not surprising – China is now clearly established second place in the world wealth hierarchy. The country overtook Japan with respect to the number of ultra-high net worth (UHNW) individuals in 2009, total wealth in 2011 and the number of millionaires in 2014. Nevertheless, the data shows that mean wealth per adult in China (USD 47,810 in mid-2018) remains far below the level in Japan (USD 227,240). Turning our interest to the lower level of the wealth distribution, we see that 3.2 billion adults or about 64% of the adult population lives with a wealth below USD 10,000, which corresponds to only 1.9% of the global wealth. Those with low wealth are disproportionately found among the younger age groups, those who live in regions where prospects for wealth creation are very limited (most notably Africa) and where opportunities are sometimes constrained. The wealth of women has been receiving increasing attention and we estimate that women account for about 40% of global wealth overall. During the 20th century, their share of wealth rose considerably and, since the year 2000, the level of women's wealth has risen along with all household wealth, especially in Asia alongside the rise of China's wealth. The tendency shows that more self-made women are succeeding in business and are entering the highest wealth ranks. Despite this trend, even in those countries where progress is the strongest, some categories of women – such as single mothers and divorcees – remain disadvantaged. While more is required to be done to ensure that women have an equal opportunity to build up, inherit and share in wealth, there are signs that progress has been happening in many parts of the world. Given some of this year's intriguing findings, we hope you find the 2018 edition of the Global Wealth Report a valuable source of insight and wish you interesting reading.
How Fat Is the Top Tail of the Wealth Distribution? Vermeulen, Philip. Review of Income and Wealth, 64(2): 357–387. 2018.
@article{Vermeulen2018,
title = {How Fat Is the Top Tail of the Wealth Distribution?},
author = {Vermeulen, Philip},
year = {2018},
journal = {Review of Income and Wealth},
volume = {64},
number = {2},
pages = {357--387},
doi = {10.1111/roiw.12279},
url = {https://doi.org/10.1111/roiw.12279},
abstract = {Differential unit non-response in household wealth surveys biases estimates of top tail wealth shares downward. Using Monte Carlo evidence, I show that adding only a few extreme observations to wealth surveys is sufficient to remove the downward bias. Combining extreme wealth observations from Forbes World's billionaires with the Survey of Consumer Finances, the Wealth and Assets Survey, and the Household Finance and Consumption Survey, I provide new improved estimates of top tail wealth in the United States, the United Kingdom, and nine euro area countries. These new estimates indicate significantly higher top wealth shares than those calculated from the wealth surveys alone.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality}
}Differential unit non-response in household wealth surveys biases estimates of top tail wealth shares downward. Using Monte Carlo evidence, I show that adding only a few extreme observations to wealth surveys is sufficient to remove the downward bias. Combining extreme wealth observations from Forbes World's billionaires with the Survey of Consumer Finances, the Wealth and Assets Survey, and the Household Finance and Consumption Survey, I provide new improved estimates of top tail wealth in the United States, the United Kingdom, and nine euro area countries. These new estimates indicate significantly higher top wealth shares than those calculated from the wealth surveys alone.
Data Files to "Rethinking the Lebanese Economic Miracle: The Extreme Concentration of Income and Wealth in Lebanon 2005-2014". Assouad, Lydia. World Inequality Lab. 2017.
@misc{Assouad2021data,
title = {Data Files to "Rethinking the {{Lebanese}} Economic Miracle: The Extreme Concentration of Income and Wealth in Lebanon 2005-2014"},
author = {Assouad, Lydia},
year = {2017},
publisher = {World Inequality Lab},
url = {https://wid.world/methodology/#library-browse-by-country-lebanon},
urldate = {2022-04-01},
abstract = {Full replication files available at the URL provided.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Assouad2021data.zip},
url_parent_paper = {https://bibbase.org/network/publication/assouad-rethinkingthelebaneseeconomicmiracletheextremeconcentrationofincomeandwealthinlebanon20052014-2021}
}Full replication files available at the URL provided.
Prices and Currency Conversions in WID.World. Blanchet, Thomas. World Wealth & Income Database. August 2017.
@techreport{Blanchet2017,
title = {Prices and Currency Conversions in {{WID}}.World},
author = {Blanchet, Thomas},
year = {2017},
month = {aug},
number = {2017/3},
institution = {World Wealth \& Income Database},
url = {https://wid.world/document/convert-wid-world-series/},
urldate = {2023-09-22},
abstract = {This technical note reviews the issues surrounding the use of price indexes and currency conversion factors in WID.world. We explain some of the main issues surrounding the measurement and construction of these data, we describe how the data in WID.world was constructed, and finally we clarify how to properly compare income and wealth levels in WID.world between countries and periods.},
keywords = {Data Sources: Wealth Inequality},
type = {{{WID}}.World {{Technical Note Series}}},
url_file = {Blanchet2017.pdf}
}This technical note reviews the issues surrounding the use of price indexes and currency conversion factors in WID.world. We explain some of the main issues surrounding the measurement and construction of these data, we describe how the data in WID.world was constructed, and finally we clarify how to properly compare income and wealth levels in WID.world between countries and periods.
Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France (1800-2014): Appendix. Garbinti, Bertrand; Goupille-Lebret, Jonathan; and Piketty, Thomas. World Wealth & Income Database. January 2017.
@techreport{Garbintietal2021app2,
title = {Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for {{France}} (1800-2014): Appendix},
author = {Garbinti, Bertrand and {Goupille-Lebret}, Jonathan and Piketty, Thomas},
year = {2017},
month = {jan},
number = {2016/6},
institution = {World Wealth \& Income Database},
url = {https://wid.world/document/b-garbinti-j-goupille-t-piketty-appendix-wealth-concentration-france-1800-2014-methods-estimates-simulations-2016/},
urldate = {2022-05-03},
abstract = {This data appendix provides methodological details and complete data series for our paper ``Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France (1800-2014)''. It is supplemented by a set of data files and computer codes (GGP2016Wealth.zip). [Editor's note: this is the appendix to the 2017 version of the WID.world Working Paper (2016/6). The most up to date appendix can be found in the parent paper.]},
keywords = {Data Sources: Wealth Inequality},
type = {{{WID}}.World {{Working Paper Series}}},
url_file = {Garbintietal2021app2.pdf},
url_parent_paper = {https://bibbase.org/network/publication/garbinti-goupillelebret-piketty-accountingforwealthinequalitydynamicsmethodsestimatesandsimulationsforfrance-2021}
}This data appendix provides methodological details and complete data series for our paper "Accounting for Wealth Inequality Dynamics: Methods, Estimates and Simulations for France (1800-2014)". It is supplemented by a set of data files and computer codes (GGP2016Wealth.zip). [Editor's note: this is the appendix to the 2017 version of the WID.world Working Paper (2016/6). The most up to date appendix can be found in the parent paper.]
From Soviets to Oligarchs: Inequality and Property in Russia 1905-2016: Appendix. Novokmet, Filip; Piketty, Thomas; and Zucman, Gabriel. World Wealth & Income Database. December 2017.
@techreport{Novokmetetal2018app,
title = {From {{Soviets}} to Oligarchs: Inequality and Property in {{Russia}} 1905-2016: Appendix},
author = {Novokmet, Filip and Piketty, Thomas and Zucman, Gabriel},
year = {2017},
month = {dec},
number = {2017/10},
institution = {World Wealth \& Income Database},
url = {https://wid.world/document/appendix-soviets-oligarchs-inequality-property-russia-1905-2016-wid-world-working-paper-201710/},
abstract = {This appendix supplements our paper and describes the full set of data files and computer codes (NPZ2017.zip) that were used to construct the series. [Editor's note: This is the appendix to the 2017 WID.world working paper version.]},
keywords = {Data Sources: Wealth Inequality},
type = {{{WID}}.World {{Working Paper Series}}},
url_file = {Novokmetetal2018app.pdf},
url_published_paper = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016-2018},
url_working_paper = {https://bibbase.org/network/publication/novokmet-piketty-zucman-fromsovietstooligarchsinequalityandpropertyinrussia19052016workingpaper-2018}
}This appendix supplements our paper and describes the full set of data files and computer codes (NPZ2017.zip) that were used to construct the series. [Editor's note: This is the appendix to the 2017 WID.world working paper version.]
Global Wealth Databook 2017. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. November 2017.
@misc{Shorrocksetal2017,
title = {Global Wealth Databook 2017},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2017},
month = {nov},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Since 2010, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the ``wealth pyramid,'' capturing 3.5 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who account for a small part of the world's population, but yet own a significant share of its wealth. Research for the Credit Suisse Research Institute's Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Dr. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Research Institute's Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Global Wealth Report highlights the main findings of our study, the Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2017 at both the regional and country levels. It presents our estimates on the distribution of wealth for over 200 countries. This year's Databook presents findings on the Millennials' wealth position and provides a comparison with earlier generations.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2017.pdf}
}Since 2010, the Credit Suisse Research Institute's Global Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," capturing 3.5 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who account for a small part of the world's population, but yet own a significant share of its wealth. Research for the Credit Suisse Research Institute's Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Dr. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Research Institute's Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Global Wealth Report highlights the main findings of our study, the Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2017 at both the regional and country levels. It presents our estimates on the distribution of wealth for over 200 countries. This year's Databook presents findings on the Millennials' wealth position and provides a comparison with earlier generations.
Global Wealth Report 2017. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. November 2017.
@misc{Shorrocksetal2017a,
title = {Global Wealth Report 2017},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2017},
month = {nov},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2017a.pdf}
}Wealth Inequality in the Netherlands, c. 1950-2015. the Paradox of a Northern European Welfare State. van Bavel, Bas; and Frankema, Ewout. TSEG - The Low Countries Journal of Social and Economic History, 14(2): 29–62. 2017.
@article{vanBavelFrankema2017,
title = {Wealth Inequality in the {{Netherlands}}, c. 1950-2015. the Paradox of a Northern {{European}} Welfare State},
author = {{van Bavel}, Bas and Frankema, Ewout},
year = {2017},
journal = {TSEG - The Low Countries Journal of Social and Economic History},
volume = {14},
number = {2},
pages = {29--62},
doi = {10.18352/tseg.916},
url = {https://doi.org/10.18352/tseg.916},
abstract = {This paper reviews the available evidence on post-war trends in Dutch private wealth inequality using a range of scattered sources. Wealth tax records suggest a substantial decline in inequality to the 1970s and, more tentatively, a gradual rise thereafter. In the post-1990 years, Gini-coefficients of private wealth inequality range from 0.8 to 0.9, which is at the high end of the international comparison. Such high levels of private wealth inequality contrast with relatively low levels of net income inequality; a paradox that the Netherlands share with other Northern European welfare states. We hypothesise that publicly funded life-time income security limits the wealth-formation by ordinary Dutch households, while the redistributive taxes required to finance this system are targeting income rather than wealth.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_file = {vanBavelFrankema2017.pdf}
}This paper reviews the available evidence on post-war trends in Dutch private wealth inequality using a range of scattered sources. Wealth tax records suggest a substantial decline in inequality to the 1970s and, more tentatively, a gradual rise thereafter. In the post-1990 years, Gini-coefficients of private wealth inequality range from 0.8 to 0.9, which is at the high end of the international comparison. Such high levels of private wealth inequality contrast with relatively low levels of net income inequality; a paradox that the Netherlands share with other Northern European welfare states. We hypothesise that publicly funded life-time income security limits the wealth-formation by ordinary Dutch households, while the redistributive taxes required to finance this system are targeting income rather than wealth.
Household Wealth Trends in the United States, 1962 to 2016: Has Middle Class Wealth Recovered? Wolff, Edward N. National Bureau of Economic Research. November 2017.
@techreport{Wolff2017,
title = {Household Wealth Trends in the {{United States}}, 1962 to 2016: Has Middle Class Wealth Recovered?},
author = {Wolff, Edward N.},
year = {2017},
month = {nov},
number = {24085},
institution = {National Bureau of Economic Research},
doi = {10.3386/w24085},
url = {https://doi.org/10.3386/w24085},
abstract = {Asset prices plunged between 2007 and 2010 but then rebounded from 2010 to 2016. The most telling finding is that median wealth plummeted by 44 percent over years 2007 to 2010. The inequality of net worth, after almost two decades of little movement, went up sharply from 2007 to 2010, and relative indebtedness for the middle class expanded. The sharp fall in median net worth and the rise in overall wealth inequality over these years are largely traceable to the high leverage of middle class families and the high share of homes in their portfolio. Mean and median wealth rebounded from 2010 to 2016, by 17 and 28 percent, respectively. While mean wealth surpassed its previous peak in 2007, median wealth was still down by 34 percent. More than 100 percent of the recovery in both was due to a high return on wealth but this factor was offset by negative savings. Relative indebtedness continued to fall for the middle class from 2010 to 2016, and wealth inequality increased somewhat. The racial and ethnic disparity in wealth holdings widened considerably between 2007 and 2016, and the wealth of households under age 45 declined in relative terms.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
type = {Working {{Paper}}},
url_file = {Wolff2017.pdf}
}Asset prices plunged between 2007 and 2010 but then rebounded from 2010 to 2016. The most telling finding is that median wealth plummeted by 44 percent over years 2007 to 2010. The inequality of net worth, after almost two decades of little movement, went up sharply from 2007 to 2010, and relative indebtedness for the middle class expanded. The sharp fall in median net worth and the rise in overall wealth inequality over these years are largely traceable to the high leverage of middle class families and the high share of homes in their portfolio. Mean and median wealth rebounded from 2010 to 2016, by 17 and 28 percent, respectively. While mean wealth surpassed its previous peak in 2007, median wealth was still down by 34 percent. More than 100 percent of the recovery in both was due to a high return on wealth but this factor was offset by negative savings. Relative indebtedness continued to fall for the middle class from 2010 to 2016, and wealth inequality increased somewhat. The racial and ethnic disparity in wealth holdings widened considerably between 2007 and 2016, and the wealth of households under age 45 declined in relative terms.
National Accounts Series Methodology. Blanchet, Thomas; and Chancel, Lucas. World Wealth & Income Database. September 2016.
@techreport{BlanchetChancel2016,
title = {National Accounts Series Methodology},
author = {Blanchet, Thomas and Chancel, Lucas},
year = {2016},
month = {sep},
number = {2016/1},
institution = {World Wealth \& Income Database},
url = {https://wid.world/document/1676/},
urldate = {2023-09-22},
abstract = {This methodological note presents the methodology followed to construct homogeneous series of national accounts presented on WID.world (i.e. series of net national income, gross domestic product, net foreign income, consumption of fixed capital and population) covering (almost) all countries in the world, from at least 1950 to today.},
keywords = {Data Sources: Wealth Inequality},
type = {{{WID}}.World {{Working Paper Series}}},
url_file = {BlanchetChancel2016.pdf}
}This methodological note presents the methodology followed to construct homogeneous series of national accounts presented on WID.world (i.e. series of net national income, gross domestic product, net foreign income, consumption of fixed capital and population) covering (almost) all countries in the world, from at least 1950 to today.
Measuring Income and Wealth at the Top Using Administrative and Survey Data. Bricker, Jesse; Henriques, Alice; Krimmel, Jacob; and Sabelhaus, John. Brookings Papers on Economic Activity, Spring: 261–331. 2016.
@article{Brickeretal2016,
title = {Measuring Income and Wealth at the Top Using Administrative and Survey Data},
author = {Bricker, Jesse and Henriques, Alice and Krimmel, Jacob and Sabelhaus, John},
year = {2016},
journal = {Brookings Papers on Economic Activity},
volume = {Spring},
pages = {261--331},
doi = {10.1353/eca.2016.0016},
url = {https://www.brookings.edu/bpea-articles/measuring-income-and-wealth-at-the-top-using-administrative-and-survey-data/},
urldate = {2023-06-05},
abstract = {Most available estimates of U.S. wealth and income concentration indicate that the top shares are high and have been rising in recent decades, but there is some disagreement about specific levels and trends. Household surveys are the traditional data source used to measure the top shares, but recent studies using administrative tax records suggest that these survey-based top share estimates may not be capturing all of the increasing concentration. In this paper, we reconcile the divergent top share estimates, showing how the choices of data sets and methodological decisions affect levels and trends. Relative to the new and most widely cited top share estimates based on administrative tax data alone, our preferred estimates for both wealth and income concentration are lower and have been rising less rapidly in recent years.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_appendix = {https://bibbase.org/network/publication/bricker-henriques-krimmel-sabelhaus-onlineappendixformeasuringincomeandwealthatthetopusingadministrativeandsurveydata-2016},
url_figures = {https://bibbase.org/network/publication/bricker-henriques-krimmel-sabelhaus-measuringincomeandwealthatthetopusingadministrativeandsurveydatafigures-2016},
url_file = {Brickeretal2016.pdf}
}Most available estimates of U.S. wealth and income concentration indicate that the top shares are high and have been rising in recent decades, but there is some disagreement about specific levels and trends. Household surveys are the traditional data source used to measure the top shares, but recent studies using administrative tax records suggest that these survey-based top share estimates may not be capturing all of the increasing concentration. In this paper, we reconcile the divergent top share estimates, showing how the choices of data sets and methodological decisions affect levels and trends. Relative to the new and most widely cited top share estimates based on administrative tax data alone, our preferred estimates for both wealth and income concentration are lower and have been rising less rapidly in recent years.
Measuring Income and Wealth at the Top Using Administrative and Survey Data: Figures. Bricker, Jesse; Henriques, Alice; Krimmel, Jacob; and Sabelhaus, John. 2016.
@misc{Brickeretal2016data,
title = {Measuring Income and Wealth at the Top Using Administrative and Survey Data: Figures},
author = {Bricker, Jesse and Henriques, Alice and Krimmel, Jacob and Sabelhaus, John},
year = {2016},
url = {https://www.brookings.edu/bpea-articles/measuring-income-and-wealth-at-the-top-using-administrative-and-survey-data/},
urldate = {2023-06-05},
abstract = {Full data and programs can be found at the URL provided.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Brickeretal2016data.xlsx},
url_parent_paper = {https://bibbase.org/network/publication/bricker-henriques-krimmel-sabelhaus-measuringincomeandwealthatthetopusingadministrativeandsurveydata-2016}
}Full data and programs can be found at the URL provided.
On-Line Appendix for: Measuring Income and Wealth at the Top Using Administrative and Survey Data. Bricker, Jesse; Henriques, Alice; Krimmel, Jacob; and Sabelhaus, John. 2016.
@misc{Brickeretal2016app,
title = {On-Line Appendix for: Measuring Income and Wealth at the Top Using Administrative and Survey Data},
author = {Bricker, Jesse and Henriques, Alice and Krimmel, Jacob and Sabelhaus, John},
year = {2016},
doi = {10.1353/eca.2016.0016},
url = {https://www.brookings.edu/bpea-articles/measuring-income-and-wealth-at-the-top-using-administrative-and-survey-data/},
urldate = {2023-06-05},
keywords = {Data Sources: Wealth Inequality},
url_file = {Brickeretal2016app.pdf},
url_parent_paper = {https://bibbase.org/network/publication/bricker-henriques-krimmel-sabelhaus-measuringincomeandwealthatthetopusingadministrativeandsurveydata-2016}
}Wealth Distribution in Australia: Evidence from Income Capitalization. Galiana, Lino. Paris School of Economics. August 2016.
@mastersthesis{Galiana2016,
title = {Wealth Distribution in {{Australia}}: Evidence from Income Capitalization},
author = {Galiana, Lino},
year = {2016},
month = {aug},
url = {http://www.piketty.pse.ens.fr/fr/enseignement/10-page-statique/19-memoires},
urldate = {2022-04-01},
abstract = {Australian wealth shares have known large fluctuations due to asset pricing volatility on Australian financial and housing markets. This paper intends to analyze those fluctuations through the relatively innovative approach that consists in drawing individual income data from aggregated fiscal data and in applying the income capitalization method to derive household wealth. First of all, we show that after an initial drop of top wealth shares up to 1996, the upward housing price dynamic triggered off a sharp increase in top wealth shares in 2003-2004 and a second one in 2006-2007. At the acme, the 1\% wealthiest individuals owned 20\% of the total wealth. Secondly, we argue that this period of housing price growth has been marked by the penetration of home-owners in top-wealth groups, which initially included mostly owners of financial assets. Nonetheless, homeowners are no longer present in top-wealth groups above P99. Then, we intend to show that financial instruments, especially stocks, and business assets constitute between 70 and 90\% of the wealth of the people belonging to the top 0.01\%. Finally,using the household survey HILDA, we show through non-parametric techniques that the behavior of Australian households is consistent with the life-cycle theory.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
school = {Paris School of Economics}
}Australian wealth shares have known large fluctuations due to asset pricing volatility on Australian financial and housing markets. This paper intends to analyze those fluctuations through the relatively innovative approach that consists in drawing individual income data from aggregated fiscal data and in applying the income capitalization method to derive household wealth. First of all, we show that after an initial drop of top wealth shares up to 1996, the upward housing price dynamic triggered off a sharp increase in top wealth shares in 2003-2004 and a second one in 2006-2007. At the acme, the 1% wealthiest individuals owned 20% of the total wealth. Secondly, we argue that this period of housing price growth has been marked by the penetration of home-owners in top-wealth groups, which initially included mostly owners of financial assets. Nonetheless, homeowners are no longer present in top-wealth groups above P99. Then, we intend to show that financial instruments, especially stocks, and business assets constitute between 70 and 90% of the wealth of the people belonging to the top 0.01%. Finally,using the household survey HILDA, we show through non-parametric techniques that the behavior of Australian households is consistent with the life-cycle theory.
Top Wealth Shares in Australia 1915–2012. Katic, Pamela; and Leigh, Andrew. Review of Income and Wealth, 62(2): 209–222. June 2016.
@article{KaticLeigh2016,
title = {Top Wealth Shares in {{Australia}} 1915--2012},
author = {Katic, Pamela and Leigh, Andrew},
year = {2016},
month = {jun},
journal = {Review of Income and Wealth},
volume = {62},
number = {2},
pages = {209--222},
doi = {10.1111/roiw.12177},
url = {https://doi.org/10.1111/roiw.12177},
abstract = {Combining data from surveys, inheritance tax records, and rich lists, we estimate top wealth shares for Australia from World War I until the present day. We find that the top 1 percent share declined by two-thirds from 1915 until the late 1960s, and rose from the late 1970s to 2010. The recent increase is sharpest at the top of the distribution, with the top 0.001 percent wealth share tripling from 1984 to 2012. The trend in top wealth shares is similar to that in Australian top income shares (though the drop in the first half of the twentieth century is larger for wealth than income shares). Since the early twentieth century, top wealth shares in Australia have been lower than in the U.K. and U.S.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_supporting_information = {https://bibbase.org/network/publication/katic-leigh-topwealthsharesinaustralia19152012supportinginformation-2016}
}Combining data from surveys, inheritance tax records, and rich lists, we estimate top wealth shares for Australia from World War I until the present day. We find that the top 1 percent share declined by two-thirds from 1915 until the late 1960s, and rose from the late 1970s to 2010. The recent increase is sharpest at the top of the distribution, with the top 0.001 percent wealth share tripling from 1984 to 2012. The trend in top wealth shares is similar to that in Australian top income shares (though the drop in the first half of the twentieth century is larger for wealth than income shares). Since the early twentieth century, top wealth shares in Australia have been lower than in the U.K. and U.S.
Top Wealth Shares in Australia 1915–2012: Supporting Information. Katic, Pamela; and Leigh, Andrew. June 2016.
@misc{KaticLeigh2016app,
title = {Top Wealth Shares in {{Australia}} 1915--2012: Supporting Information},
author = {Katic, Pamela and Leigh, Andrew},
year = {2016},
month = {jun},
doi = {10.1111/roiw.12177},
url = {https://doi.org/10.1111/roiw.12177},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/katic-leigh-topwealthsharesinaustralia19152012-2016}
}Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data. Saez, Emmanuel; and Zucman, Gabriel. The Quarterly Journal of Economics, 131(2): 519–578. May 2016.
@article{SaezZucman2016,
title = {Wealth Inequality in the {{United States}} since 1913: Evidence from Capitalized Income Tax Data},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2016},
month = {may},
journal = {The Quarterly Journal of Economics},
volume = {131},
number = {2},
pages = {519--578},
doi = {10.1093/qje/qjw004},
url = {https://doi.org/10.1093/qje/qjw004},
abstract = {This paper combines income tax returns with macroeconomic household balance sheets to estimate the distribution of wealth in the United States since 1913. We estimate wealth by capitalizing the incomes reported by individual taxpayers, accounting for assets that do not generate taxable income. We successfully test our capitalization method in three micro datasets where we can observe both income and wealth: the Survey of Consumer Finance, linked estate and income tax returns, and foundations' tax records. We find that wealth concentration was high in the beginning of the twentieth century, fell from 1929 to 1978, and has continuously increased since then. The top 0.1\% wealth share has risen from 7\% in 1978 to 22\% in 2012, a level almost as high as in 1929. Top wealth-holders are younger today than in the 1960s and earn a higher fraction of the economy's labor income. The bottom 90\% wealth share first increased up to the mid-1980s and then steadily declined. The increase in wealth inequality in recent decades is due to the upsurge of top incomes combined with an increase in saving rate inequality. We explain how our findings can be reconciled with Survey of Consumer Finances and estate tax data.},
keywords = {Data Sources: Wealth Inequality,Impacts of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
url_main_data = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdatamaindata-2015},
url_online_appendix = {https://bibbase.org/network/publication/saez-zucman-onlineappendixofwealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2015},
url_working_paper = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2014}
}This paper combines income tax returns with macroeconomic household balance sheets to estimate the distribution of wealth in the United States since 1913. We estimate wealth by capitalizing the incomes reported by individual taxpayers, accounting for assets that do not generate taxable income. We successfully test our capitalization method in three micro datasets where we can observe both income and wealth: the Survey of Consumer Finance, linked estate and income tax returns, and foundations' tax records. We find that wealth concentration was high in the beginning of the twentieth century, fell from 1929 to 1978, and has continuously increased since then. The top 0.1% wealth share has risen from 7% in 1978 to 22% in 2012, a level almost as high as in 1929. Top wealth-holders are younger today than in the 1960s and earn a higher fraction of the economy's labor income. The bottom 90% wealth share first increased up to the mid-1980s and then steadily declined. The increase in wealth inequality in recent decades is due to the upsurge of top incomes combined with an increase in saving rate inequality. We explain how our findings can be reconciled with Survey of Consumer Finances and estate tax data.
Global Wealth Databook 2016. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. November 2016.
@misc{Shorrocksetal2016,
title = {Global Wealth Databook 2016},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2016},
month = {nov},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Since 2010, the Credit Suisse Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the "wealth pyramid," capturing 3.5 billion adults with wealth below USD 10,000, to those at the apex, who account for a small part of the world's population, yet own a significant share of its wealth. Research for the Credit Suisse Global Wealth Databook was undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," (Oxford University Press, 2008). Rodrigo Lluberas was also a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world, for the period since 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this Databook includes the full extent of our analysis. More importantly, it sets out in detail the data used in our Global Wealth project, the methodology for calculating estimates of wealth, and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels during the period from 2000 to mid-2016, on both a regional and a country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich set of data, this year's Databook presents findings on the most significant trends at the bottom of the global wealth pyramid.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2016.pdf}
}Since 2010, the Credit Suisse Wealth Report has been the leading reference on global household wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," capturing 3.5 billion adults with wealth below USD 10,000, to those at the apex, who account for a small part of the world's population, yet own a significant share of its wealth. Research for the Credit Suisse Global Wealth Databook was undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," (Oxford University Press, 2008). Rodrigo Lluberas was also a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world, for the period since 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this Databook includes the full extent of our analysis. More importantly, it sets out in detail the data used in our Global Wealth project, the methodology for calculating estimates of wealth, and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels during the period from 2000 to mid-2016, on both a regional and a country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich set of data, this year's Databook presents findings on the most significant trends at the bottom of the global wealth pyramid.
Global Wealth Report 2016. Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. November 2016.
@misc{Shorrocksetal2016a,
title = {Global Wealth Report 2016},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2016},
month = {nov},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Despite their significance for economic activity, precise and comprehensive insights into the levels and the global distribution of wealth remain scarce. The Global Wealth Report, issued annually by the Credit Suisse Research Institute, is one of the key sources of intelligence in relation to global wealth development, and delivers extensive estimates of global household wealth levels, covering all regions and population segments. Our seventh edition of the Global Wealth Report confirms a course of the weak global wealth growth. In the course the past 12 months, global wealth has risen by USD 3.5 trillion to USD 256 trillion, which represents an increase of 1.4\%. However, wealth creation has merely kept pace with population growth. As a result, in 2016, wealth per adult was unchanged for the first time since 2008, at approximately USD 52,800. Among the major economies, the USA and Japan were able to generate substantial additional wealth, while the United Kingdom recorded a significant decline as a result of currency depreciation. Since 2008, we have reported on gains in household wealth being driven by an increase in financial assets. Interestingly, we are observing a shift in 2016, as the share of non-financial assets increased for the first time. In total, USD 4.9 trillion were added to real assets, compared to a USD 330 billion rise in financial assets. We have further established that wealth inequality, measured by the share of the wealthiest 1\% and wealthiest 10\% of adults, as compared to the rest of the world's adult population, continues to rise. While the bottom half collectively own less than 1\% of total wealth, the wealthiest top 10\% own 89\% of all global assets. Since the beginning of the century, emerging economies have significantly influenced the global allocation of wealth. In 2000, emerging economies accounted for a mere 12\% of global wealth, but have contributed nearly 25\% towards global growth since. Today, emerging nations are home to 18\% of the world's ultra-high net worth population. China alone accounts for 9\% of the top decile of global wealth holders, which is well above France, Germany, Italy, and the United Kingdom. Besides the recurring themes, our 2016 edition of the Global Wealth Report sheds light on the most significant trends at the bottom of the global wealth pyramid. Currently, an estimated 9\% of adults globally are net debtors, which is without a doubt a worrying development. In our report, we provide insights into the regional composition of this segment, explore structural factors associated with poverty, and estimate the assets owned by the lower wealth segments. We trust that you will find our report insightful.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2016a.pdf}
}Despite their significance for economic activity, precise and comprehensive insights into the levels and the global distribution of wealth remain scarce. The Global Wealth Report, issued annually by the Credit Suisse Research Institute, is one of the key sources of intelligence in relation to global wealth development, and delivers extensive estimates of global household wealth levels, covering all regions and population segments. Our seventh edition of the Global Wealth Report confirms a course of the weak global wealth growth. In the course the past 12 months, global wealth has risen by USD 3.5 trillion to USD 256 trillion, which represents an increase of 1.4%. However, wealth creation has merely kept pace with population growth. As a result, in 2016, wealth per adult was unchanged for the first time since 2008, at approximately USD 52,800. Among the major economies, the USA and Japan were able to generate substantial additional wealth, while the United Kingdom recorded a significant decline as a result of currency depreciation. Since 2008, we have reported on gains in household wealth being driven by an increase in financial assets. Interestingly, we are observing a shift in 2016, as the share of non-financial assets increased for the first time. In total, USD 4.9 trillion were added to real assets, compared to a USD 330 billion rise in financial assets. We have further established that wealth inequality, measured by the share of the wealthiest 1% and wealthiest 10% of adults, as compared to the rest of the world's adult population, continues to rise. While the bottom half collectively own less than 1% of total wealth, the wealthiest top 10% own 89% of all global assets. Since the beginning of the century, emerging economies have significantly influenced the global allocation of wealth. In 2000, emerging economies accounted for a mere 12% of global wealth, but have contributed nearly 25% towards global growth since. Today, emerging nations are home to 18% of the world's ultra-high net worth population. China alone accounts for 9% of the top decile of global wealth holders, which is well above France, Germany, Italy, and the United Kingdom. Besides the recurring themes, our 2016 edition of the Global Wealth Report sheds light on the most significant trends at the bottom of the global wealth pyramid. Currently, an estimated 9% of adults globally are net debtors, which is without a doubt a worrying development. In our report, we provide insights into the regional composition of this segment, explore structural factors associated with poverty, and estimate the assets owned by the lower wealth segments. We trust that you will find our report insightful.
Long-Run Trends in the Distribution of Income and Wealth. Roine, Jesper; and Waldenström, Daniel. Handbook of Income Distribution, 2: 469–592. 2015.
@incollection{RoineWaldenstrom2015,
title = {Long-Run Trends in the Distribution of Income and Wealth},
author = {Roine, Jesper and Waldenstr{\"o}m, Daniel},
year = {2015},
booktitle = {Handbook of Income Distribution},
volume = {2},
pages = {469--592},
publisher = {North-Holland},
doi = {10.1016/B978-0-444-59428-0.00008-4},
url = {https://doi.org/10.1016/B978-0-444-59428-0.00008-4},
abstract = {This chapter reviews the long-run developments in the distribution of personal income and wealth. It also discusses suggested explanations for the observed patterns. We try to answer questions such as: What do we know, and how do we know, about the distribution of income and wealth over time? Are there common trends across countries or over the path of development? How do the facts relate to proposed theories about changes in inequality? We present the main inequality trends, in some cases starting as early as in the late eighteenth century, combining previous research with recent findings in the so-called top income literature and new evidence on wealth concentration. The picture that emerges shows that inequality was historically high almost everywhere at the beginning of the twentieth century. In some countries this situation was preceded by increasing concentration, but in most cases inequality seems to have been relatively constant at a high level in the nineteenth century. Over the twentieth century inequality decreased almost everywhere for the first 80 years, largely due to decreasing wealth concentration and decreasing capital incomes in the top of the distribution. Thereafter trends became more divergent across countries and also different across income and wealth distributions. Econometric evidence over the long run suggests that top shares increase in periods of above-average growth, whereas democracy and high marginal tax rates are associated with lower top shares.},
keywords = {Data Sources: Wealth Inequality,Cross-National Comparisons,Determinants of Wealth and Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
address = {Amsterdam},
chapter = {7},
editor = {Atkinson, Anthony B. and Bourguignon, Fran{\c c}ois},
isbn = {978-0-444-59430-3},
url_data_files = {https://bibbase.org/network/publication/roine-waldenstrm-longruntrendsinthedistributionofincomeandwealthdatafiles-2015}
}This chapter reviews the long-run developments in the distribution of personal income and wealth. It also discusses suggested explanations for the observed patterns. We try to answer questions such as: What do we know, and how do we know, about the distribution of income and wealth over time? Are there common trends across countries or over the path of development? How do the facts relate to proposed theories about changes in inequality? We present the main inequality trends, in some cases starting as early as in the late eighteenth century, combining previous research with recent findings in the so-called top income literature and new evidence on wealth concentration. The picture that emerges shows that inequality was historically high almost everywhere at the beginning of the twentieth century. In some countries this situation was preceded by increasing concentration, but in most cases inequality seems to have been relatively constant at a high level in the nineteenth century. Over the twentieth century inequality decreased almost everywhere for the first 80 years, largely due to decreasing wealth concentration and decreasing capital incomes in the top of the distribution. Thereafter trends became more divergent across countries and also different across income and wealth distributions. Econometric evidence over the long run suggests that top shares increase in periods of above-average growth, whereas democracy and high marginal tax rates are associated with lower top shares.
Long-Run Trends in the Distribution of Income and Wealth: Data Files. Roine, Jesper; and Waldenström, Daniel. 2015.
@misc{RoineWaldenstrom2015data,
title = {Long-Run Trends in the Distribution of Income and Wealth: Data Files},
author = {Roine, Jesper and Waldenstr{\"o}m, Daniel},
year = {2015},
url = {https://sites.google.com/view/danielwaldenstrom/data-programs},
urldate = {2022-03-15},
keywords = {Data Sources: Wealth Inequality},
url_file = {RoineWaldenstrom2015data.zip},
url_parent_book_chapter = {https://bibbase.org/network/publication/roine-waldenstrm-longruntrendsinthedistributionofincomeandwealth-2015}
}Online Appendix of Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data. Saez, Emmanuel; and Zucman, Gabriel. October 2015.
@misc{SaezZucman2016app,
title = {Online Appendix of Wealth Inequality in the {{United States}} since 1913: Evidence from Capitalized Income Tax Data},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2015},
month = {oct},
doi = {10.1093/qje/qjw004},
url = {https://doi.org/10.1093/qje/qjw004},
keywords = {Data Sources: Wealth Inequality},
url_file = {SaezZucman2016app.pdf},
url_published_paper = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2016},
url_working_paper = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2014}
}Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data: Main Data. Saez, Emmanuel; and Zucman, Gabriel. 2015.
@misc{SaezZucman2016data,
title = {Wealth Inequality in the {{United States}} since 1913: Evidence from Capitalized Income Tax Data: Main Data},
author = {Saez, Emmanuel and Zucman, Gabriel},
year = {2015},
url = {https://gabriel-zucman.eu/uswealth/},
urldate = {2022-03-10},
abstract = {Tables and figures included in the paper (.xlsx).},
keywords = {Data Sources: Wealth Inequality},
url_file = {SaezZucman2016data.xlsx},
url_published_paper = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2016},
url_working_paper = {https://bibbase.org/network/publication/saez-zucman-wealthinequalityintheunitedstatessince1913evidencefromcapitalizedincometaxdata-2014}
}Tables and figures included in the paper (.xlsx).
Global Wealth Databook 2015. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2015.
@misc{Shorrocksetal2015,
title = {Global Wealth Databook 2015},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2015},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Since 2010, the Credit Suisse Wealth Report has been the leading reference on global wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the ``wealth pyramid,'' capturing 3.4 billion adults with wealth below USD 10,000, to the millionaires, who account for 0.7\% of adult population, but yet own 45.2\% of global wealth. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 158-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2015 at both the regional and country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich data, the Databook presents findings on the global middle class, its size and how it fared over time.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2015.pdf}
}Since 2010, the Credit Suisse Wealth Report has been the leading reference on global wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," capturing 3.4 billion adults with wealth below USD 10,000, to the millionaires, who account for 0.7% of adult population, but yet own 45.2% of global wealth. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 158-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2015 at both the regional and country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich data, the Databook presents findings on the global middle class, its size and how it fared over time.
Global Wealth Report 2015. Stierli, Markus; Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. October 2015.
@misc{Stierlietal2015,
title = {Global Wealth Report 2015},
author = {Stierli, Markus and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2015},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Stierlietal2015.pdf}
}Global Wealth Databook 2014. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2014.
@misc{Shorrocksetal2014,
title = {Global Wealth Databook 2014},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2014},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Since 2010, the Credit Suisse Wealth Report has been the leading reference on global wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum -- from the very base of the ``wealth pyramid,'' capturing 3.3 billion adults with wealth below USD 10,000, to the millionaires, who account for 0.7\% of adult population, but yet own 44\% of global wealth. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 156-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2014 at both the regional and country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich data, the Databook presents findings on wealth inequality in developed countries and emerging markets.},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2014.pdf}
}Since 2010, the Credit Suisse Wealth Report has been the leading reference on global wealth. It contains the most comprehensive and up-to-date findings on global wealth across the entire wealth spectrum – from the very base of the "wealth pyramid," capturing 3.3 billion adults with wealth below USD 10,000, to the millionaires, who account for 0.7% of adult population, but yet own 44% of global wealth. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 156-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook provides detailed information on the evolution of household wealth levels through the period 2000 to mid-2014 at both the regional and country level. It presents our estimates on the distribution of wealth for over 200 countries. Based on this rich data, the Databook presents findings on wealth inequality in developed countries and emerging markets.
Global Wealth Report 2014. Stierli, Markus; Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. October 2014.
@misc{Stierlietal2014,
title = {Global Wealth Report 2014},
author = {Stierli, Markus and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2014},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Stierlietal2014.pdf}
}European System of Accounts: ESA 2010. Eurostat. December 2013.
@misc{Eurostat2013_EuropeanSystemAccountsESA2010,
title = {European {{System}} of {{Accounts}}: {{ESA}} 2010},
author = {{Eurostat}},
year = {2013},
month = {dec},
url = {https://doi.org/10.2785/16644},
abstract = {The European System of Accounts (hereinafter referred to as `the ESA 2010' or `the ESA') is an internationally compatible accounting framework for a systematic and detailed description of a total economy (that is, a region, country or group of countries), its components and its relations with other total economies.},
keywords = {Data Sources: Wealth Inequality},
url_file = {Eurostat2013_EuropeanSystemAccountsESA2010.pdf}
}The European System of Accounts (hereinafter referred to as `the ESA 2010' or `the ESA') is an internationally compatible accounting framework for a systematic and detailed description of a total economy (that is, a region, country or group of countries), its components and its relations with other total economies.
Global Wealth Report 2013. Keating, Giles; O'Sullivan, Michael; Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. October 2013.
@misc{Keatingetal2013,
title = {Global Wealth Report 2013},
author = {Keating, Giles and O'Sullivan, Michael and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2013},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Keatingetal2013.pdf}
}Global Wealth Databook 2013. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2013.
@misc{Shorrocksetal2013,
title = {Global Wealth Databook 2013},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2013},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {This is now the fourth edition of the Credit Suisse Global Wealth Databook -- an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.7 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 155-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to mid2013, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 216 countries. This rich data set has enabled our investigation of wealth holdings in the Eurozone area in Chapter 2 of the Wealth Report and provides background for the study of wealth mobility in Chapter 4 of the Wealth Report. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series and the composition of household portfolios (assets and debts).},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2013.pdf}
}This is now the fourth edition of the Credit Suisse Global Wealth Databook – an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.7 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 155-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to mid2013, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 216 countries. This rich data set has enabled our investigation of wealth holdings in the Eurozone area in Chapter 2 of the Wealth Report and provides background for the study of wealth mobility in Chapter 4 of the Wealth Report. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series and the composition of household portfolios (assets and debts).
5204.0.55.009 - Information Paper: Australian National Accounts, Distribution of Household Income, Consumption and Wealth, 2009-10. Australian Bureau of Statistics. August 2013.
@misc{AustralianBureauofStatistics2022app,
title = {5204.0.55.009 - {{Information Paper}}: {{Australian National Accounts}}, Distribution of Household Income, Consumption and Wealth, 2009-10},
author = {{Australian Bureau of Statistics}},
year = {2013},
month = {aug},
url = {https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/5204.0.55.009Main+Features12009-10?OpenDocument},
urldate = {2023-01-31},
keywords = {Data Sources: Wealth Inequality},
url_file = {AustralianBureauofStatistics2022app.pdf},
url_parent_data = {https://bibbase.org/network/publication/australianbureauofstatistics-australiannationalaccountsdistributionofhouseholdincomeconsumptionandwealth-2022}
}Global Wealth Report 2012. Keating, Giles; O'Sullivan, Michael; Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. October 2012.
@misc{Keatingetal2012,
title = {Global Wealth Report 2012},
author = {Keating, Giles and O'Sullivan, Michael and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2012},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Keatingetal2012.pdf}
}Global Wealth Databook 2012. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2012.
@misc{Shorrocksetal2012,
title = {Global Wealth Databook 2012},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2012},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {This is now the third edition of the Credit Suisse Global Wealth Databook -- an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.6 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 159-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to mid2012, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 216 countries. This rich data set has enabled our in-depth study of household indebtedness in Chapter 4 of the Wealth Report. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series, inheritance and age effects and the composition of household portfolios (assets and debts).},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2012.pdf}
}This is now the third edition of the Credit Suisse Global Wealth Databook – an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.6 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 159-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to mid2012, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 216 countries. This rich data set has enabled our in-depth study of household indebtedness in Chapter 4 of the Wealth Report. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series, inheritance and age effects and the composition of household portfolios (assets and debts).
Global Wealth Report 2011. Keating, Giles; O'Sullivan, Michael; Shorrocks, Anthony; Davies, James B.; Lluberas, Rodrigo; and Koutsoukis, Antonios. October 2011.
@misc{Keatingetal2011,
title = {Global Wealth Report 2011},
author = {Keating, Giles and O'Sullivan, Michael and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo and Koutsoukis, Antonios},
year = {2011},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Keatingetal2011.pdf}
}Global Wealth Databook 2011. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2011.
@misc{Shorrocksetal2011,
title = {Global Wealth Databook 2011},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2011},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {This is the second edition of the Credit Suisse Global Wealth Databook -- an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.5 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 155-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to 2011, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 160 countries. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series, age effects and the composition of household portfolios (assets and debts).},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2011.pdf}
}This is the second edition of the Credit Suisse Global Wealth Databook – an in-depth project that offers investors the most comprehensive study of world wealth, and which remains the only study that analyzes the wealth of all the world's 4.5 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. Rodrigo Lluberas has also been a very significant contributor to the project. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, this 155-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to 2011, providing data at both regional and country level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 160 countries. Finally, the Databook presents detailed data on relatively under-researched areas, such as the historical wealth series, age effects and the composition of household portfolios (assets and debts).
Income and Wealth Concentration in Spain in a Historical and Fiscal Perspective. Alvaredo, Facundo; and Saez, Emmanuel. Top Incomes: A Global Perspective, pp. 482–559. May 2010.
@incollection{AlvaredoSaez2010,
title = {Income and Wealth Concentration in {{Spain}} in a Historical and Fiscal Perspective},
author = {Alvaredo, Facundo and Saez, Emmanuel},
year = {2010},
month = {may},
booktitle = {Top Incomes: A Global Perspective},
pages = {482--559},
publisher = {Oxford University Press},
url = {https://global.oup.com/academic/product/top-incomes-9780199286898?cc=us&lang=en&#},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
address = {New York},
chapter = {10},
editor = {Atkinson, A. B. and Piketty, T.},
isbn = {978-0-19-928689-8},
url_article_version = {https://bibbase.org/network/publication/alvaredo-saez-incomeandwealthconcentrationinspainfromahistoricalandfiscalperspective-2009},
url_data_file = {https://bibbase.org/network/publication/alvaredo-saez-incomeandwealthconcentrationinspaininahistoricalandfiscalperspectivedatafile-2010}
}Income and Wealth Concentration in Spain in a Historical and Fiscal Perspective: Data File. Alvaredo, Facundo; and Saez, Emmanuel. 2010.
@misc{AlvaredoSaez2010data,
title = {Income and Wealth Concentration in {{Spain}} in a Historical and Fiscal Perspective: Data File},
author = {Alvaredo, Facundo and Saez, Emmanuel},
year = {2010},
url = {https://eml.berkeley.edu/~saez/},
urldate = {2022-03-09},
abstract = {Tables and figures in Excel format.},
keywords = {Data Sources: Wealth Inequality},
url_article = {https://bibbase.org/network/publication/alvaredo-saez-incomeandwealthconcentrationinspainfromahistoricalandfiscalperspective-2009},
url_book_chapter = {https://bibbase.org/network/publication/alvaredo-saez-incomeandwealthconcentrationinspaininahistoricalandfiscalperspective-2010},
url_file = {AlvaredoSaez2010data.xls}
}Tables and figures in Excel format.
Die verteilung der vermögen in Deutschland: empirische analysen für personen und haushalte. Frick, Joachim R.; Grabka, Markus M.; and Hauser, Richard. Hans-Böckler-Stiftung, 118. 2010.
@book{Fricketal2010,
title = {{Die verteilung der verm{\"o}gen in Deutschland: empirische analysen f{\"u}r personen und haushalte}},
author = {Frick, Joachim R. and Grabka, Markus M. and Hauser, Richard},
year = {2010},
volume = {118},
publisher = {Hans-B{\"o}ckler-Stiftung},
doi = {10.5771/9783845269412},
url = {https://doi.org/10.5771/9783845269412},
abstract = {Die Nettoverm{\"o}gen sind viel ungleichm{\"a}{\ss}iger verteilt als die Nettoeinkommen. In den letzten Jahren hat die Ungleichheit der Verm{\"o}gensverteilung noch weiter zugenommen. Dies ergeben die beiden Verm{\"o}genserhebungen des Sozio-oekonomischen Panels (SOEP) von 2002 und 2007, auf deren Grundlage die Autoren in diesem Band eine Reihe von innovativen Analysen rund um die Verm{\"o}gensverteilung pr{\"a}sentieren. Sie widmen sich u.a. der -- erstaunlicherweise nicht sehr stringenten -- Korrelation zwischen Nettoeinkommen und -verm{\"o}gen, der langfristigen Entwicklung des Gesamtverm{\"o}gens des Haushaltssektors mit den Auf- und Abstiegen in der Verm{\"o}genshierarchie sowie der Verm{\"o}gensverteilung nach Bildungsstand, beruflicher Stellung und Migrationshintergrund. Indem die Untersuchung auch die rechtlichen Eigent{\"u}mer erfasst, erlaubt sie einen Einblick in die geschlechtsspezifischen Verm{\"o}gensverh{\"a}ltnisse -- mit dem Ergebnis, dass M{\"a}nner erwartungsgem{\"a}{\ss} deutlich verm{\"o}gender sind als Frauen. Erstmals beziehen die Autoren auch die Anwartschaften an Renten und Pensionen in die erweiterte Verm{\"o}gensrechnung ein. Das Anwartschaftsverm{\"o}gen ist wesentlich weniger ungleich verteilt als das Geld-, Sach- und Beteiligungsverm{\"o}gen; die Ungleichheit wird dadurch abgeschw{\"a}cht, aber sie bleibt insgesamt eklatant. -- Mit einem Vorwort von Sir Anthony Atkinson.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
address = {D{\"u}sseldorf, Germany},
isbn = {978-3-8360-8718-6},
langid = {german},
series = {{Forschung aus der Hans-B{\"o}ckler-Stiftung (HBS)}}
}Die Nettovermögen sind viel ungleichmäßiger verteilt als die Nettoeinkommen. In den letzten Jahren hat die Ungleichheit der Vermögensverteilung noch weiter zugenommen. Dies ergeben die beiden Vermögenserhebungen des Sozio-oekonomischen Panels (SOEP) von 2002 und 2007, auf deren Grundlage die Autoren in diesem Band eine Reihe von innovativen Analysen rund um die Vermögensverteilung präsentieren. Sie widmen sich u.a. der – erstaunlicherweise nicht sehr stringenten – Korrelation zwischen Nettoeinkommen und -vermögen, der langfristigen Entwicklung des Gesamtvermögens des Haushaltssektors mit den Auf- und Abstiegen in der Vermögenshierarchie sowie der Vermögensverteilung nach Bildungsstand, beruflicher Stellung und Migrationshintergrund. Indem die Untersuchung auch die rechtlichen Eigentümer erfasst, erlaubt sie einen Einblick in die geschlechtsspezifischen Vermögensverhältnisse – mit dem Ergebnis, dass Männer erwartungsgemäß deutlich vermögender sind als Frauen. Erstmals beziehen die Autoren auch die Anwartschaften an Renten und Pensionen in die erweiterte Vermögensrechnung ein. Das Anwartschaftsvermögen ist wesentlich weniger ungleich verteilt als das Geld-, Sach- und Beteiligungsvermögen; die Ungleichheit wird dadurch abgeschwächt, aber sie bleibt insgesamt eklatant. – Mit einem Vorwort von Sir Anthony Atkinson.
Global Wealth Report 2010. Keating, Giles; O'Sullivan, Michael; Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2010.
@misc{Keatingetal2010,
title = {Global Wealth Report 2010},
author = {Keating, Giles and O'Sullivan, Michael and Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2010},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Keatingetal2010.pdf}
}Global Wealth Databook 2010. Shorrocks, Anthony; Davies, James B.; and Lluberas, Rodrigo. October 2010.
@misc{Shorrocksetal2010,
title = {Global Wealth Databook 2010},
author = {Shorrocks, Anthony and Davies, James B. and Lluberas, Rodrigo},
year = {2010},
month = {oct},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
abstract = {Credit Suisse Research Institute is proud to launch the Credit Suisse Global Wealth Databook 2010, which offers investors the most comprehensive study of world wealth -- it is the first study to analyze the wealth of all the world's 4.4 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, the 128-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to 2010, providing data at the regional level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 160 countries. Finally, the Databook presents detailed data on relatively under-researched areas such as gender and the composition of household portfolios (assets and debts).},
keywords = {Data Sources: Wealth Inequality},
note = {Credit Suisse Research Institute},
url_file = {Shorrocksetal2010.pdf}
}Credit Suisse Research Institute is proud to launch the Credit Suisse Global Wealth Databook 2010, which offers investors the most comprehensive study of world wealth – it is the first study to analyze the wealth of all the world's 4.4 billion adults. Research for the Credit Suisse Global Wealth Databook has been undertaken on behalf of the Credit Suisse Research Institute by Professors Anthony Shorrocks and Jim Davies, recognized authorities on this topic, and the architects and principal authors of "Personal Wealth from a Global Perspective," Oxford University Press, 2008. The aim of the Credit Suisse Global Wealth project is to provide the best available estimates of the wealth holdings of households around the world for the period since the year 2000. While the Credit Suisse Global Wealth Report highlights the main findings of our study, the 128-page Databook underlines the extent of our analysis. More importantly, it sets out in detail the data employed in our Global Wealth project, the methodology used to calculate estimates of wealth and how this may differ from other reports in this field. The Credit Suisse Global Wealth Databook also details the evolution of household wealth levels through the period 2000 to 2010, providing data at the regional level on high net worth individuals, and highlighting the wealth pyramid in addition to wealth analysis for 160 countries. Finally, the Databook presents detailed data on relatively under-researched areas such as gender and the composition of household portfolios (assets and debts).
Wealth Concentration over the Path of Development: Sweden, 1873–2006. Roine, Jesper; and Waldenström, Daniel. The Scandinavian Journal of Economics, 111(1): 151–187. March 2009.
@article{RoineWaldenstrom2009,
title = {Wealth Concentration over the Path of Development: {{Sweden}}, 1873--2006},
author = {Roine, Jesper and Waldenstr{\"o}m, Daniel},
year = {2009},
month = {mar},
journal = {The Scandinavian Journal of Economics},
volume = {111},
number = {1},
pages = {151--187},
doi = {10.1111/j.1467-9442.2008.01558.x},
url = {https://doi.org/10.1111/j.1467-9442.2008.01558.x},
abstract = {We study wealth concentration in Sweden over 130 years, from the beginning of industrialization until the present day. Our series are based on new evidence from estate and wealth tax data, foreign and domestic family firm-wealth, and pension wealth estimates. We find that Swedish wealth concentration was high in the agrarian state, and changed little during early industrialization. From World War I until about 1950, the richest percentile lost ground to high-income earners in the rest of the top-wealth decile. This equalization continued postwar; the entire top decile lost-out relative to the rest of the population. Around 1980, wealth compression stopped and inequality increased. We approximate the effects of international flows and find that the recent increase in wealth inequality is probably larger than what official estimates suggest.},
keywords = {Data Sources: Wealth Inequality,Methods of Estimation of Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality}
}We study wealth concentration in Sweden over 130 years, from the beginning of industrialization until the present day. Our series are based on new evidence from estate and wealth tax data, foreign and domestic family firm-wealth, and pension wealth estimates. We find that Swedish wealth concentration was high in the agrarian state, and changed little during early industrialization. From World War I until about 1950, the richest percentile lost ground to high-income earners in the rest of the top-wealth decile. This equalization continued postwar; the entire top decile lost-out relative to the rest of the population. Around 1980, wealth compression stopped and inequality increased. We approximate the effects of international flows and find that the recent increase in wealth inequality is probably larger than what official estimates suggest.
Income and Wealth Concentration in Switzerland over the Twentieth Century. Dell, F.; Piketty, T.; and Saez, E. Top Incomes over the Twentieth Century: A Contrast between Continental European and English-speaking Countries. 2007.
@incollection{Delletal2007,
title = {Income and Wealth Concentration in {{Switzerland}} over the Twentieth Century},
author = {Dell, F. and Piketty, T. and Saez, E.},
year = {2007},
booktitle = {Top Incomes over the Twentieth Century: A Contrast between Continental {{European}} and {{English-speaking}} Countries},
publisher = {Oxford University Press},
doi = {https://doi.org/10.1093/oso/9780199286881.003.0011},
url = {https://global.oup.com/academic/product/top-incomes-over-the-twentieth-century-9780198727750?lang=en&cc=us},
urldate = {2022-03-24},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
address = {New York},
editor = {Atkinson, A. B. and Piketty, T.},
isbn = {978-0-19-872775-0},
url_data_series = {https://bibbase.org/network/publication/dell-piketty-saez-incomeandwealthconcentrationinswitzerlandoverthe20thcenturydataseries-2005}
}Household Wealth Distribution in Italy in the 1990s. Brandolini, Andrea; Cannari, Luigi; D'Alessio, Giovanni; and Faiella, Ivan. International Perspectives on Household Wealth, pp. 225–275. October 2006.
@incollection{Brandolinietal2006,
title = {Household Wealth Distribution in {{Italy}} in the 1990s},
author = {Brandolini, Andrea and Cannari, Luigi and D'Alessio, Giovanni and Faiella, Ivan},
year = {2006},
month = {oct},
booktitle = {International Perspectives on Household Wealth},
pages = {225--275},
publisher = {Edward Elgar Publishing},
doi = {10.4337/9781847203175.00015},
url = {https://doi.org/10.4337/9781847203175.00015},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
address = {Cheltenham, UK},
chapter = {7},
editor = {Wolff, Edward N.},
isbn = {978-1-84720-317-5},
url_working_paper = {https://bibbase.org/network/publication/brandolini-cannari-dalessio-faiella-householdwealthdistributioninitalyinthe1990s-2004}
}Wealth Concentration in a Developing Economy: Paris and France, 1807–1994. Piketty, Thomas; Postel-Vinay, Gilles; and Rosenthal, Jean-Laurent. American Economic Review, 96(1): 236–256. March 2006.
@article{Pikettyetal2006,
title = {Wealth Concentration in a Developing Economy: {{Paris}} and {{France}}, 1807--1994},
author = {Piketty, Thomas and {Postel-Vinay}, Gilles and Rosenthal, Jean-Laurent},
year = {2006},
month = {mar},
journal = {American Economic Review},
volume = {96},
number = {1},
pages = {236--256},
doi = {10.1257/000282806776157614},
url = {https://doi.org/10.1257/000282806776157614},
abstract = {Using large samples of estate tax returns, we construct new series on wealth concentration in Paris and France from 1807 to 1994. Inequality increased until 1914 because industrial and financial estates grew dramatically. Then, adverse shocks, rather than a Kuznets-type process, led to a massive decline in inequality. The very high wealth concentration prior to 1914 benefited retired individuals living off capital income (rentiers) rather than entrepreneurs. The very rich were in their seventies and eighties, whereas they had been in their fifties a half century earlier and would be so again after World War II. Our results shed new light on ongoing debates about wealth inequality and growth.},
keywords = {Data Sources: Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality,Wealth Taxation},
url_replication_files = {https://bibbase.org/network/publication/piketty-postelvinay-rosenthal-wealthconcentrationinadevelopingeconomyparisandfrance18071994replicationfiles-2005}
}Using large samples of estate tax returns, we construct new series on wealth concentration in Paris and France from 1807 to 1994. Inequality increased until 1914 because industrial and financial estates grew dramatically. Then, adverse shocks, rather than a Kuznets-type process, led to a massive decline in inequality. The very high wealth concentration prior to 1914 benefited retired individuals living off capital income (rentiers) rather than entrepreneurs. The very rich were in their seventies and eighties, whereas they had been in their fifties a half century earlier and would be so again after World War II. Our results shed new light on ongoing debates about wealth inequality and growth.
Income and Wealth Concentration in Switzerland over the 20th Century: Data Series. Dell, Fabian; Piketty, Thomas; and Saez, Emmanuel. 2005.
@misc{Delletal2007data,
title = {Income and Wealth Concentration in {{Switzerland}} over the 20th Century: Data Series},
author = {Dell, Fabian and Piketty, Thomas and Saez, Emmanuel},
year = {2005},
url = {http://piketty.pse.ens.fr/fr/publications},
urldate = {2022-03-09},
keywords = {Data Sources: Wealth Inequality},
url_file = {Delletal2007data.xls},
url_parent_book_chapter = {https://bibbase.org/network/publication/dell-piketty-saez-incomeandwealthconcentrationinswitzerlandoverthetwentiethcentury-2007}
}Wealth Concentration in a Developing Economy: Paris and France, 1807–1994: Replication Files. Piketty, Thomas; Postel-Vinay, Gilles; and Rosenthal, Jean-Laurent. October 2005.
@misc{Pikettyetal2006data,
title = {Wealth Concentration in a Developing Economy: {{Paris}} and {{France}}, 1807--1994: Replication Files},
author = {Piketty, Thomas and {Postel-Vinay}, Gilles and Rosenthal, Jean-Laurent},
year = {2005},
month = {oct},
url = {http://piketty.pse.ens.fr/fr/publications},
urldate = {2022-03-10},
keywords = {Data Sources: Wealth Inequality},
url_parent_paper = {https://bibbase.org/network/publication/piketty-postelvinay-rosenthal-wealthconcentrationinadevelopingeconomyparisandfrance18071994-2006}
}Household Wealth Distribution in Italy in the 1990s. Brandolini, Andrea; Cannari, Luigi; D'Alessio, Giovanni; and Faiella, Ivan. Bank of Italy. December 2004.
@techreport{Brandolinietal2006wp,
title = {Household Wealth Distribution in {{Italy}} in the 1990s},
author = {Brandolini, Andrea and Cannari, Luigi and D'Alessio, Giovanni and Faiella, Ivan},
year = {2004},
month = {dec},
number = {530},
institution = {Bank of Italy},
url = {https://www.bancaditalia.it/pubblicazioni/temi-discussione/2004/2004-0530/},
urldate = {2022-04-01},
abstract = {This paper describes the composition and distribution of household wealth in Italy. First, the evolution of household portfolios over the last forty years is described on the basis of newly reconstructed aggregate balance sheets. Second, the characteristics and quality of the main statistical source on wealth distribution, the Bank of Italy's Survey of Household Income and Wealth, are examined to-gether with the statistical procedures used to adjust for non-response, non-reporting and under-reporting. The distribution of household net worth is then studied using both adjusted and unad-justed data. Wealth inequality is found to have risen steadily during the 1990s. The increased con-centration of financial wealth was an important factor in determining this path.},
keywords = {Data Sources: Wealth Inequality},
type = {Working {{Paper}}},
url_file = {Brandolinietal2006wp.pdf},
url_published_version = {https://bibbase.org/network/publication/brandolini-cannari-dalessio-faiella-householdwealthdistributioninitalyinthe1990s-2006}
}This paper describes the composition and distribution of household wealth in Italy. First, the evolution of household portfolios over the last forty years is described on the basis of newly reconstructed aggregate balance sheets. Second, the characteristics and quality of the main statistical source on wealth distribution, the Bank of Italy's Survey of Household Income and Wealth, are examined to-gether with the statistical procedures used to adjust for non-response, non-reporting and under-reporting. The distribution of household net worth is then studied using both adjusted and unad-justed data. Wealth inequality is found to have risen steadily during the 1990s. The increased con-centration of financial wealth was an important factor in determining this path.
Top Wealth Shares in the United States, 1916-2000: Evidence from Estate Tax Returns: Data File. Kopczuk, Wojciech; and Saez, Emmanuel. 2004.
@misc{KopczukSaez2004data,
title = {Top Wealth Shares in the {{United States}}, 1916-2000: Evidence from Estate Tax Returns: Data File},
author = {Kopczuk, Wojciech and Saez, Emmanuel},
year = {2004},
url = {https://eml.berkeley.edu/~saez/},
urldate = {2022-03-09},
abstract = {File includes data for all figures and tables in Excel format, including those only in the NBER working paper version.},
keywords = {Data Sources: Wealth Inequality},
url_file = {KopczukSaez2004data.xls},
url_published_paper = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturns-2004},
url_working_paper = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturnsworkingpaper-2004}
}File includes data for all figures and tables in Excel format, including those only in the NBER working paper version.
Top Wealth Shares in the United States, 1916-2000: Evidence from Estate Tax Returns [Working Paper]. Kopczuk, Wojciech; and Saez, Emmanuel. National Bureau of Economic Research. March 2004.
@techreport{KopczukSaez2004wp,
title = {Top Wealth Shares in the {{United States}}, 1916-2000: Evidence from Estate Tax Returns [Working Paper]},
author = {Kopczuk, Wojciech and Saez, Emmanuel},
year = {2004},
month = {mar},
number = {10399},
institution = {National Bureau of Economic Research},
doi = {10.3386/w10399},
url = {https://doi.org/10.3386/w10399},
abstract = {This paper presents new homogeneous series on top wealth shares from 1916 to 2000 in the United States using estate tax return data. Top wealth shares were very high at the beginning of the period but have been hit sharply by the Great Depression, the New Deal, and World War II shocks. Those shocks have had permanent effects. Following a decline in the 1970s, top wealth shares recovered in the early 1980s, but they are still much lower in 2000 than in the early decades of the century. Most of the changes we document are concentrated among the very top wealth holders with much smaller movements for groups below the top 0.1\%. Consistent with the Survey of Consumer Finances results, top wealth shares estimated from Estate Tax Returns display no significant increase since 1995. Evidence from the Forbes 400 richest Americans suggests that only the super-rich have experienced significant gains relative to the average over the last decade. Our results are consistent with the decreased importance of capital income at the top of the income distribution documented by Piketty and Saez (2003) and suggest that the rentier class of the early century is not yet reconstituted. The most plausible explanations for the facts are perhaps the development of progressive income and estate taxation which has dramatically impaired the ability of large wealth holders to maintain their fortunes, and the democratization of stock ownership which now spreads stock market gains and losses much more widely than in the past.},
keywords = {Data Sources: Wealth Inequality},
type = {Working {{Paper}}},
url_data_file = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturnsdatafile-2004},
url_file = {KopczukSaez2004wp.pdf},
url_published_version = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturns-2004}
}This paper presents new homogeneous series on top wealth shares from 1916 to 2000 in the United States using estate tax return data. Top wealth shares were very high at the beginning of the period but have been hit sharply by the Great Depression, the New Deal, and World War II shocks. Those shocks have had permanent effects. Following a decline in the 1970s, top wealth shares recovered in the early 1980s, but they are still much lower in 2000 than in the early decades of the century. Most of the changes we document are concentrated among the very top wealth holders with much smaller movements for groups below the top 0.1%. Consistent with the Survey of Consumer Finances results, top wealth shares estimated from Estate Tax Returns display no significant increase since 1995. Evidence from the Forbes 400 richest Americans suggests that only the super-rich have experienced significant gains relative to the average over the last decade. Our results are consistent with the decreased importance of capital income at the top of the income distribution documented by Piketty and Saez (2003) and suggest that the rentier class of the early century is not yet reconstituted. The most plausible explanations for the facts are perhaps the development of progressive income and estate taxation which has dramatically impaired the ability of large wealth holders to maintain their fortunes, and the democratization of stock ownership which now spreads stock market gains and losses much more widely than in the past.
Top Wealth Shares in the United States, 1916–2000: Evidence from Estate Tax Returns. Kopczuk, Wojciech; and Saez, Emmanuel. National Tax Journal, 57(2): 445–487. 2004.
@article{KopczukSaez2004,
title = {Top Wealth Shares in the {{United States}}, 1916--2000: Evidence from Estate Tax Returns},
author = {Kopczuk, Wojciech and Saez, Emmanuel},
year = {2004},
journal = {National Tax Journal},
volume = {57},
number = {2},
pages = {445--487},
doi = {10.17310/ntj.2004.2S.05},
url = {http://doi.org/10.17310/ntj.2004.2S.05},
abstract = {This paper presents new homogeneous series on top wealth shares from 1916 to 2000 in the United States using estate tax return data. Top wealth shares were very high at the beginning of the period but have been hit sharply by the Great Depression, the New Deal, and World War II shocks. Those shocks have had permanent effects. Following a decline in the 1970s, top wealth shares recovered in the early 1980s, but they are still much lower in 2000 than in the early decades of the century. Most of the changes we document are concentrated among the very top wealth holders with much smaller movements for groups below the top 0.1 percent. Consistent with the Survey of Consumer Finances results, top wealth shares estimated from Estate Tax Returns display no significant increase since 1995. Evidence from the Forbes 400 richest Americans suggests that only the super--rich have experienced significant gains relative to the average over the last decade. Our results are consistent with the decreased importance of capital incomes at the top of the income distribution documented by Piketty and Saez (2003), and suggest that the rentier class of the early century is not yet reconstituted. The paper proposes several tentative explanations to account for the facts.},
keywords = {Data Sources: Wealth Inequality,Determinants of Wealth and Wealth Inequality,Trends in Aggregate Wealth and Wealth Inequality},
url_data_file = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturnsdatafile-2004},
url_working_paper = {https://bibbase.org/network/publication/kopczuk-saez-topwealthsharesintheunitedstates19162000evidencefromestatetaxreturnsworkingpaper-2004}
}This paper presents new homogeneous series on top wealth shares from 1916 to 2000 in the United States using estate tax return data. Top wealth shares were very high at the beginning of the period but have been hit sharply by the Great Depression, the New Deal, and World War II shocks. Those shocks have had permanent effects. Following a decline in the 1970s, top wealth shares recovered in the early 1980s, but they are still much lower in 2000 than in the early decades of the century. Most of the changes we document are concentrated among the very top wealth holders with much smaller movements for groups below the top 0.1 percent. Consistent with the Survey of Consumer Finances results, top wealth shares estimated from Estate Tax Returns display no significant increase since 1995. Evidence from the Forbes 400 richest Americans suggests that only the super–rich have experienced significant gains relative to the average over the last decade. Our results are consistent with the decreased importance of capital incomes at the top of the income distribution documented by Piketty and Saez (2003), and suggest that the rentier class of the early century is not yet reconstituted. The paper proposes several tentative explanations to account for the facts.
Codebook for 1962 Survey of Financial Characteristics of Consumers and 1963 Changes in Family Finances. Board of Governors of the Federal Reserve System. September 1997.
@misc{FederalReserve1997_Codebook1962SurveyFinancialCharacteristics,
title = {Codebook for 1962 {{Survey}} of {{Financial Characteristics}} of {{Consumers}} and 1963 {{Changes}} in {{Family Finances}}},
author = {{Board of Governors of the Federal Reserve System}},
year = {1997},
month = {sep},
url = {https://www.federalreserve.gov/econres/files/6263_codebk6263.txt},
urldate = {2022-09-10},
keywords = {Data Sources: Wealth Inequality},
url_file = {FederalReserve1997_Codebook1962SurveyFinancialCharacteristics.txt}
}Data. World Inequality Database. 1900.
@misc{WorldInequalityDatabase_Data,
title = {Data},
author = {{World Inequality Database}},
year = {1900},
url = {https://wid.world/data/},
urldate = {2022-05-30},
keywords = {Data Sources: Wealth Inequality,Data Sources: Wealth Topography}
}Luxembourg Wealth Study Database. LIS. 1900.
@misc{LIS_LuxembourgWealthStudyDatabase,
title = {Luxembourg {{Wealth Study Database}}},
author = {{LIS}},
year = {1900},
url = {https://www.lisdatacenter.org/our-data/lws-database/},
urldate = {2022-02-07},
keywords = {Data Sources: Wealth Inequality,Data Sources: Wealth Topography}
}Credit Suisse Global Wealth Report. Credit Suisse. 1900.
@misc{CreditSuisse_CreditSuisseGlobalWealthReport,
title = {Credit {{Suisse}} Global Wealth Report},
author = {{Credit Suisse}},
year = {1900},
url = {https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html},
urldate = {2022-02-17},
keywords = {Data Sources: Wealth Inequality,Data Sources: Wealth Topography}
}Demographic and Health Surveys (own estimates). 1900.
@misc{dhs_various,
title = {Demographic and Health Surveys (own estimates)},
author = {Unknown},
year = {1900},
url = {https://dhsprogram.com/data/},
keywords = {Data Sources: Wealth Inequality}
}European Central Bank Distributional Wealth Accounts. 1900.
@misc{EuropeanCentralBank2024_DistributionalWealthAccounts,
title = {European Central Bank Distributional Wealth Accounts},
author = {Unknown},
year = {1900},
url = {https://data.ecb.europa.eu/data/datasets/DWA},
keywords = {Data Sources: Wealth Inequality,Data Sources: Wealth Topography}
}Living Standards Measurement Study (own estimates). 1900.
@misc{lsms_various,
title = {Living Standards Measurement Study (own estimates)},
author = {Unknown},
year = {1900},
url = {https://www.worldbank.org/en/programs/lsms},
keywords = {Data Sources: Wealth Inequality}
}WAEMU Harmonized Household Living Conditions Surveys (own estimates). 1900.
@misc{phmecv_various,
title = {WAEMU Harmonized Household Living Conditions Surveys (own estimates)},
author = {Unknown},
year = {1900},
url = {https://phmecv.uemoa.int/},
keywords = {Data Sources: Wealth Inequality}
}