Top Wealth Shares in Australia 1915–2012

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.     

Wealth Inequality in Sweden: What can we Learn from Capitalized Income Tax Data?

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.     

The Gender Wealth Gap in Europe: Application of Machine Learning to Predict Individual-level Wealth

This article provides comparative estimates of the gender wealth gaps for 22 European countries, employing data from the Household Finance and Consumption Survey. The data on wealth are collected at the household level, while individual-level data are needed for the estimates of gender wealth gaps. We propose a novel approach using machine learning and model averaging methods to predict individual-level wealth data for multi-person households. Our results suggest that random forest performs best as the predicting tool for this exercise, outperforming elastic net and Bayesian model averaging. The estimated gender wealth gaps tend to be in favor of men, especially at the top of the wealth distribution. Men have 24 percent more wealth than women on average. We also find that a high home ownership rate is associated with a smaller country-level gender wealth gap. Our estimates suggest that the individual-level wealth inequality is on average 3 pp higher than the household-level wealth inequality in multi-member households.     

Wealth inequality in Central and Eastern Europe: Evidence from household survey and rich lists’ data combined*

We study how the problem of the ‘missing rich’, the underrepresentation of the wealthiest in household surveys, affects wealth inequality estimates for the post‐socialist countries of Central and Eastern Europe (CEE). The survey data from the second wave of the Household Finance and Consumption Survey (HFCS) are joined with the data from the national rich lists for Estonia, Hungary, Latvia, Poland and Slovakia. Pareto distribution is fitted to the joined survey and rich lists’ data to impute the missing observations for the largest wealth values. We provide the first estimates of the top‐corrected wealth inequality for the CEE region in 2013/2014. Despite a short period of wealth accumulation during the post‐1989 market economy period, our adjustment procedure reveals that wealth inequality in the Baltic countries is comparable to that of Germany (one of the most wealth‐unequal countries in Europe), while in Poland and Hungary it has reached levels observed in France or Spain. We discuss possible explanations of these findings with reference to the speed and range of privatization processes, extent of income inequality, and the role of inheritances and wealth taxes in the region.     

Older or Wealthier? The Impact of Age Adjustment on Wealth Inequality*

Differences in individual wealth holdings are widely viewed as a driving force of economic inequality. However, as this finding relies on cross‐sectional data, a concern is that older is confused with wealthier. We propose a new method to adjust for age effects in cross‐sections, which eliminates wealth inequality due to age, yet preserves inequality arising from other factors. Using a new cross‐country comparable database, we examine the impact of age adjustments on wealth inequality across countries and over time. We find that the most widely used method yields a substantially different picture of age‐adjusted wealth inequality than our method.     

How Fat is the Top Tail of the Wealth Distribution?

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.     

Perceptions of inequality

Individual perceptions of (income or wealth) inequality have strong effects on their decisions as economic agents or voters. It is therefore important to know more about the relation between perceived and measured inequality. We present a novel formal framework that is based on the assumption that people typically do not observe the entire income (wealth) distribution and that their guesses about the extent of inequality are based on “self-centered” reference groups. This framework predicts that perceptions of inequality will change along positions in the income distribution and that for a specific position various dimensions of inequality perception are related to each other. First, low (high) income individuals overestimate (underestimate) their own position. Second, subjective estimates of average earnings increase with the own income position. Third, high or low income people have different perceptions about the skewness and the “shape” of the income distribution (e.g. pyramid or diamond). Fourth, the subjective perception of inequality is lower for high-income individuals. Survey data from 40 countries provide strong support for the framework.     

The Long‐Run History of Income Inequality in Denmark

We use historical publications and micro data from tax returns to construct internationally comparable estimates of the development in income inequality in Denmark over the last 140 years. The study shows that income inequality and top income shares have declined during several distinct phases in between periods of stability. Furthermore, the quality of the Danish data allows us to analyse not only the development in top income shares but also broader inequality measures such as the Gini coefficient. These analyses show that top income shares are a good proxy for the underlying development in inequality.     

Distribution of wealth and incomplete markets: Theory and empirical evidence

This paper analyses the equilibrium distribution of wealth in an economy where firms’ productivities are subject to idiosyncratic shocks, returns on factors are determined in competitive markets, households have linear consumption functions and government imposes taxes on capital and labour incomes and equally redistributes the collected resources to households. The equilibrium distribution of wealth is explicitly calculated and its shape crucially depends on market incompleteness. With incomplete markets it follows a Paretian law in the top tail and the Pareto exponent depends on the saving rate, on the net return on capital, on the growth rate of population, and on portfolio diversification. The characteristics of the labour market crucially affects the bottom tail, but not the upper tail of the distribution of wealth in the case of completely decentralized labour market. The analysis also suggests a positive relationship between growth and wealth inequality. The theoretical predictions find a corroboration in the empirical evidence of United States in the period 1989-2004.     

The Impact of Inheritance on the Distribution of Wealth: Evidence from Great Britain

Using the British Household Panel Survey, we investigate the role of inheritance in shaping the distribution of household wealth in Great Britain during 1995–2005a period characterized by a substantial increase in wealth and an equally important decrease in wealth inequality. Abstracting from behavioral effects, we find that inheritances received during this period accounted for 30 percent of the increase in wealth of inheritors. Regression estimates of the effect of inheritance on wealth accumulation suggest that households spend 30 percent of their inheritances on average, and that there is substantial heterogeneity in household responses. Households that accumulated more wealth saved a larger share of their inheritances, as did middle aged households and those with lower initial wealth. Although inheritances are highly unequal they had a small impact on overall wealth inequality. This mainly reflected the fact that their size relative to other sources of wealth was very small.     

Income Inequality and Political Polarization: Time Series Evidence Over Nine Decades

Rising income inequality and political polarization have led some to hypothesize that the two are causally linked. Properly interpreting such correlations is complicated by multiple factors driving these phenomena, potential feedback between inequality and polarization, measurement issues, and the statistical challenges of modeling non‐stationary variables. We find that a more precise measure of inequality (the inverted Pareto–Lorenz coefficient) is more consistently and statistically related to polarization in the short and long runs than the less precise top 1 percent share of income. We find bi‐directional causality between polarization and inequality, consistent with theoretical conjecture and less formal evidence in previous studies.     

Distributional Consequences of Commodity Price Shocks: Australia Over A Century

This paper studies the distributional impact of commodity price shocks over the short and the very long run. Using a GARCH model, we find that Australia experienced more volatility than many commodity exporting developing countries over the periods 1865–1940 and 1960–2008. We conduct cointegration tests to assess the commodity price shock inequality nexus. A single equation error correction model suggests that commodity price shocks increase the income share of the top 1, 0.05, and 0.01 percent in the short run. The very top end of the income distribution benefits from commodity booms disproportionately more than the rest of the society. The short run effect is mainly driven by wool and mining and not agricultural commodities. A sustained increase in the price of renewables (wool) reduces inequality whereas the same for non‐renewable resources (minerals) increases inequality. We expect that the initial distribution of land and mineral resources explains the asymmetric result.     

The distributional effects of progressive capital taxes

Rising inequality since the 1980s has spurred much research examining the underlying causes and potential policy responses. Among the more controversial, One of the more controversial policy proposals is a progressive capital tax in response to rising top wealth shares around the world proposes a progressive capital tax in response to rising top wealth shares around the world. This paper introduces rank-based econometric methods for dynamic power laws as a tool for estimating the effect of progressive capital taxes on the distribution of wealth under different assumptions about the impact of these taxes on household behavior. In most scenarios, we find that a small tax levied on 1% of households would substantially reshape the US wealth distribution and reduce inequality.     

Wealth inequality and financial inclusion: Evidence from South African tax and survey records

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.     

The Effect of Labor's Bargaining Power on Wealth Inequality in the UK,USA, And France

This paper analyses the determinants of wealth inequality, measured as the share of wealth owned by the top 1 percent wealthiest individuals. We find that labor's bargaining power is a significant and important determinant of top wealth shares. Using a semi-structural vector autoregression (SVAR) model for the period 1970–2019, we estimate that shocks to labor's bargaining power explain 32 percent, 8 percent and 32 percent of the variation around the long-term trend in wealth inequality in the UK, USA and France, respectively.     

Network effects and the dynamics of migration and inequality: Theory and evidence from Mexico

International migration is costly and initially only the middle class of the wealth distribution may have both the means and incentives to migrate, which can increase inequality in the sending community. However, the migration networks formed lower the costs for future migrants, which can in turn lower inequality. This paper shows both theoretically and empirically that wealth has a nonlinear effect on migration, and then examines the empirical evidence for an inverse U-shaped relationship between emigration and inequality in rural sending communities in Mexico. After instrumenting, we find that the overall impact of migration is to reduce inequality across communities with relatively high levels of past migration. We also find some suggestive evidence for an inverse U-shaped relationship among communities with a wider range of migration experiences.     

TRENDS IN HOUSEHOLD WEALTH IN THE UNITED STATES, 1962–83 AND 1983–89

Using the 1983 and 1989 Surveys of Consumer Finances, I find evidence of sharply increasing house-hold wealth inequality over this period. Whereas mean wealth increased by 23 percent in real terms, median wealth grew by only 8 percent. The share of the top one-half percentile rose by five percentage points, while the wealth of the bottom two quintiles showed an absolute decline. The Gini coefficient increased from 0.80 to 0.84. Almost all the growth in real wealth accrued to the top 20 percent of wealthholders. In contrast, the degree of wealth inequality was almost identical in 1983 as in 1962, and real wealth growth was more evenly distributed across the wealth distribution. There is also evidence that the sharp increase in wealth inequality from 1983 to 1989 was due to a correspondingly sharp rise in income inequality, the increase of stock prices relative to housing prices, and relatively slow inflation.     

“Fair go” for all? Wealth and Risk Aversion of Australian Households*

A mean‐variance framework is applied to Australian household financial portfolios in order to provide estimates of relative risk aversion in the economy. Controlling for various socio‐economic characteristics, we explore whether risk aversion heterogeneity is a function of wealth heterogeneity. In contrast to most studies, we find evidence of very high risk aversion amongst the majority of households of poor households but vastly lower risk aversion amongst the high percentiles in the wealth distribution. Applying a first differences model across three survey waves spanning 2002 to 2010, we find that risk tolerance increases significantly with wealth. Risk tolerance is positively associated with mortgage payments, but rental payments have no relationship. In addition, we found no evidence that holding a university education has any discernible impact on risk aversion. Lastly, we present some preliminary findings as to the impact of financial advice on observed risk aversion. Financial advice is found to accentuating risk aversion, particularly amongst the wealthiest households. The findings have potential implications for the distribution of wealth in Australia that has received renewed interest recently.     

Indian Income Inequality, 1922‐2015: From British Raj to Billionaire Raj?

We combine household surveys and national accounts, as well as recently released tax data to track the dynamics of Indian income inequality from 1922 to 2015. According to our benchmark estimates, the top 1 percent of earners captured less than 21 percent of total income in the late 1930s, before dropping to 6 percent in the early 1980s and rising to 22 percent in the recent period. Our results appear to be robust to a range of alternative assumptions seeking to address numerous data limitations. These findings suggest that much more can be done to promote inclusive growth in India. We also stress the need for more transparency on income and wealth statistics, which is key to allow an informed democratic debate on inequality.     

ON THE ROLE OF CAPITAL GAINS IN SWEDISH INCOME INEQUALITY

Realized capital gains are typically disregarded in the study of income inequality. We show that in the case of Sweden this severely underestimates the actual increase in inequality and, in particular, top income shares during recent decades. Using micro panel data to average incomes over longer periods and re‐rank individuals according to income excluding capital gains, we show that capital gains indeed are a reoccurring addition to rather than a transitory component in top incomes. Doing the same for lower income groups, however, makes virtually no difference. We also try to find the roots of the recent surge in capital gains‐driven inequality in Sweden since the 1980s. While there are no evident changes in terms of who earns these gains (high wage earners vs. top capital income earners), the primary driver instead seems to be the drastic asset price increases on the post‐1980 deregulated financial markets.