2018
DOI: 10.1257/jel.20161390
|View full text |Cite
|
Sign up to set email alerts
|

Skewed Wealth Distributions: Theory and Empirics

Abstract: Invariably, across a cross-section of countries and time periods, wealth distributions are skewed to the right displaying thick upper tails, that is, large and slowly declining top wealth shares. In this survey, we categorize the theoretical studies on the distribution of wealth in terms of the underlying economic mechanisms generating skewness and thick tails. Further, we show how these mechanisms can be micro-founded by the consumption–savings decisions of rational agents in specific economic and demographic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

9
122
1
1

Year Published

2019
2019
2021
2021

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 200 publications
(133 citation statements)
references
References 143 publications
9
122
1
1
Order By: Relevance
“…Heterogeneity in returns to wealth may solve the puzzle of why two countries with very different levels of concentration of income at the top may nevertheless have similar levels of wealth concentration at the top. Surveying the theories of skewed wealth distributions, Benhabib and Bisin () revisit and put in a novel perspective two theorems, one by Grey () and another by Kesten (). Grey's theorem asserts that, in an economy with homogeneous returns to wealth and heterogeneous income, the wealth distribution inherits the properties of the income distribution, including the thickness of its tails.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Heterogeneity in returns to wealth may solve the puzzle of why two countries with very different levels of concentration of income at the top may nevertheless have similar levels of wealth concentration at the top. Surveying the theories of skewed wealth distributions, Benhabib and Bisin () revisit and put in a novel perspective two theorems, one by Grey () and another by Kesten (). Grey's theorem asserts that, in an economy with homogeneous returns to wealth and heterogeneous income, the wealth distribution inherits the properties of the income distribution, including the thickness of its tails.…”
Section: Discussionmentioning
confidence: 99%
“… For instance, while the calibrated model of Kindermann and Krueger () comes close to matching the distribution of wealth in the US, it requires the top 0.25% of income earners to earn 400 to 600 times more than the median earner; in the data the income of the top 0.25% is at most 34 times median income (Benhabib and Bisin ()). …”
mentioning
confidence: 99%
“…For example, Fagiolo et al (2010) report that consumption expenditures obey the AEP distribution, while Bottazzi et al (2014) and Reichstein and Jensen (2005) discuss applications to the firm size and growth rate distribution, respectively. Skewed and thick-tailed distributions are also observed for earnings and wealth (Benhabib and Bisin, 2018) as well as for the returns to total wealth, and it would certainly be worthwhile to investigate the implication of the distributional regularity in the latter on the dynamics of inequality. This would require to study the process governing the returns under the observed asymmetry.…”
Section: Discussionmentioning
confidence: 99%
“…The distribution becomes more skewed, because agents that escape from the nonparticipation threshold at a young age accumulate wealth at a faster rate than those that have to exit asset markets occasionally and those that begin to participate persistently at a later stage, despite of rebalancing their portfolios towards safer assets as financial wealth increases. Interestingly, the model therefore provides an intuitive explanation for both the disproportionately high share of wealth held by financial market participants highlighted in Guvenen () and the skew of the wealth distribution discussed in Benhabib and Bisin (). The mode of the wealth distribution shifts slightly faster in the model than in the data, however, the evolution of the mean is almost precisely captured as can be seen from Figure .…”
Section: Simulationsmentioning
confidence: 93%