Estimating the Top Tail of the Wealth Distribution

Vermeulen, Philip

doi:10.1257/aer.p20161021

Cited by 67 publications

(73 citation statements)

References 4 publications

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“…The tails of the distribution could contain measurement errors, as their inclusion causes unpredictable swings in inequality measures which could drive results in an empirical analysis (Brewer and Wren-Lewis, 2016). In addition, wealth measurement at the upper tail of the distribution is biased due to nonresponse and underreporting (Vermeulen, 2016). A crude way to deal with this issue is to disregard the top and bottom 1% of distribution, if included in the primary data source (Mumtaz and Theophilopoulou, 2017) or use surveys that already exclude the very upper end of the distribution (Coibion et al, 2017;Inui et al, 2017).…”

Section: Data Challenges: Measuring Inequalitymentioning

confidence: 99%

Central Bank Policies and Income and Wealth Inequality: A Survey

Colciago

Samarina

Haan

2019

Journal of Economic Surveys

137

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This paper reviews recent research on the relationship between central bank policies and inequality. A new paradigm which integrates sticky‐prices, incomplete markets, and heterogeneity among households is emerging, which allows for the joint study of how inequality shapes macroeconomic aggregates and how macroeconomic shocks and policies affect inequality. The new paradigm features multiple distributional channels of monetary policy. Most empirical studies, however, analyze each potential channel of redistribution in isolation. Our review suggests that empirical research on the effects of conventional monetary policy on income and wealth inequality yields mixed findings, although there seems to be a consensus that higher inflation, at least above some threshold, increases inequality. In contrast to common wisdom, conclusions concerning the impact of unconventional monetary policies on inequality are also not clear cut. To better understand policy effects on inequality, future research should focus on the estimation of General Equilibrium models with heterogeneous agents.

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Section: Data Challenges: Measuring Inequalitymentioning

confidence: 99%

Central Bank Policies and Income and Wealth Inequality: A Survey

Colciago

Samarina

Haan

2019

Journal of Economic Surveys

137

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“…7 Due to non-response, the most affluent households are likely to be underrepresented in the HFCS. This issue can be addressed by assuming that the upper tail of the wealth distribution approximates a Pareto distribution (Vermeulen 2016). However, this approach is not applicable for subordinate wealth components such as real estate.…”

Section: Methodology Of Statistical Matchingmentioning

confidence: 99%

Distributional and revenue effects of a tax shift from labor to property

Paetzold

Tiefenbacher

2018

Int Tax Public Finance

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Contrary to frequent recommendations of the public finance literature and international institutions, a persistently high tax wedge on labor is observed in Europe. Simultaneously, the scope for shifting taxes to more growth-friendly revenue sources appears underused. This motivates our simulation of a tax shift from labor to property for Germany, a country where property tax revenues are particularly low and the tax wedge on labor income is among the highest in industrialized countries. We simulate a reform where property is no longer taxed by its (often) outdated cadastral value but by its market value, using the additional revenue to reduce social insurance contributions (SIC). To make such a simulation possible, we match property-related information with the input data of the tax-benefit microsimulation model EUROMOD. We find a considerable increase in property tax revenues, allowing to reduce the implicit tax rate on labor from 37.2 to 36.5%. Distributive effects tend to be modest and depend on the design of the SIC reduction. Overall, our results suggest that more households would gain than lose from the tax shift, with gainers mostly situated in the middle of the income distribution.

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“…However, with respect to the top wealth distribution, household surveys have inherent, crucial drawbacks: non-response and under-reporting (Vermeulen 2016a(Vermeulen , 2018. Generally, personal wealth is considerably more concentrated than income and it is difficult to capture the top wealth distribution through small-scale voluntary surveys.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, non-response bias is probable as response rates tend to decrease with high income and wealth, especially at the top (Vermeulen 2018). The bias because of under-reporting is striking when comparing survey data with national accounts (Vermeulen 2016a;Chakraborty and Waltl 2018).…”

Section: Introductionmentioning

confidence: 99%

Looking for the missing rich: tracing the top tail of the wealth distribution

Bach

Thiemann

Zucco

2019

Int Tax Public Finance

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We analyse the top tail of the wealth distribution in France, Germany, and Spain using the first and second waves of the Household Finance and Consumption Survey (HFCS). Since top wealth is likely to be under-represented in household surveys, we integrate big fortunes from rich lists, estimate a Pareto distribution, and impute the missing rich. In addition to the Forbes list, we rely on national rich lists since they represent a broader base of the big fortunes in those countries. As a result, the top 1% wealth share increases notably for the three selected countries after imputing the top wealth. We find that national rich lists can improve the estimation of the Pareto coefficient in particular when the list of national USD billionaires is short.

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Estimating the Top Tail of the Wealth Distribution

Cited by 67 publications

References 4 publications

Central Bank Policies and Income and Wealth Inequality: A Survey

Central Bank Policies and Income and Wealth Inequality: A Survey

Distributional and revenue effects of a tax shift from labor to property

Looking for the missing rich: tracing the top tail of the wealth distribution

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