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The distribution of income and wealth are generally regarded as key performance indicators of a society. Cross-sectional analyses of Australian income and wealth distributions at various points in time have found that both are highly unequal. However, lifetime distributions may be quite different. This paper provides some insight into the differences for one of these distributions – wealth.

A dynamic microsimulation model of the Australian population is used to project the cross-sectional and lifetime asset holdings of a 5-year birth cohort over a period of 40 years. The annual personal net worth of this birth cohort are analysed in regard to age and net worth, the changing wealth distribution within the cohort, wealth mobility, and a comparison of lifetime and cross-sectional distributions.

This paper considers a parametric model for the joint distribution of income and wealth. The model is used to analyze income and wealth inequality in five OECD countries using comparable household-level survey data. We focus on the dependence parameter between the two variables and study whether accounting for wealth and income jointly reveals a different pattern of social inequality than the traditional “income only” approach. We find that cross-country variations in the dependence parameter effectively account only for a small fraction of cross-country differences in a bivariate measure of inequality. The index appears primarily driven by differences in inequality in the wealth distribution.

The study of the upper tail of the income and wealth distributions is important to the understanding of economic inequality. By means of the ‘isograph’, a new tool to describe income or wealth distributions, the authors compare wealth and income and wealth-to-income ratios in 16 European countries and the United States using data for years 2013/2014 from the Eurozone Household Finance and Consumption Survey and the US Survey on Consumer Finance. Focussing on the top half of the distribution, the authors find that for households in the top income quintile, wealth-to-income ratios generally increase rapidly with income; the association between high wealth and high incomes is highest among the highest percentiles. There is generally a positive relationship between median wealth in the country and the wealth of the top 1%. However, the United States is an outlier where the median wealth is relatively low but the wealth of the top 1% is extremely high.

Based on empirical patterns of annual earnings and saving from new micro-data covering a large sample of American workers around a hundred years ago, we develop a model for simulating the cross-section distribution of wealth at the turn of the twentieth century. Our methodology allows for a direct comparison with the wealth distribution from a sample of families in a comparable part of the contemporary income distribution. Our primary finding is that patterns of wealth accumulation among American workers at the turn of the century bear a striking resemblance to contemporary profiles.

Using harmonized wealth data and a novel decomposition approach in this literature, we show that cohort effects exist in the income profiles of asset and debt portfolios for a sample of European countries, the United States, and Canada. We find that the association between household wealth portfolios at the intensive margin (the level of assets) and household characteristics is different from that found at the extensive margin (the decision to own). Characteristics explain most of the cross-country differences in asset and debt levels, except for housing wealth, which displays large unexplained differences for both the under-50 and over-50 populations. However, there are cohort differences in the drivers of wealth levels. We observe that younger households’ levels of wealth, given participation, may be more responsive to the institutional setting than mature households. Our findings have important implications, indicating a scope for policies which can promote or redirect investment in housing for both cohorts and which promote optimal portfolio allocation for mature households.

The 2007–2009 financial crisis initially appeared to have destroyed a huge amount of wealth in the United States. Housing prices dropped about 21% across the country and as much as 50% in some places, and the stock market dropped by nearly 50% as well. This chapter examines how the financial crisis differentially affected households at different parts of the income and wealth distributions. Our results show that all households lost about the same percentage of their wealth in that period. But because households in the top 10% of the wealth distribution owned many different kinds of assets, their wealth soon recovered. The bottom 80% of the wealth distribution had more of their wealth tied up in housing. We show that financial distress, indexed by foreclosures, being behind in mortgage payments, and changes in house prices were particularly concentrated in households in the bottom 80% of the wealth distribution. These households lost a large part of their wealth and have not yet recovered. Households that were most deeply affected were those who entered the housing market late and took out subprime loans. African American and Hispanic households were particularly susceptible as they bought houses late in the price bubble often with subprime loans.

It is not easy to get a long perspective on the distribution of wealth in Sweden because there is no single data source that gives a consistent view for a long period of time. The early estimates of the distribution of wealth were based on the concept of tax-assessed wealth which is the basis of the wealth tax. This definition has the disadvantage of not including assets that were not taxed, and no or very unreliable data were given for the majority of the tax payers who were below the taxation threshold. Furthermore, this variable was defined for individuals and for jointly taxed individuals, but no economically meaningful household concept was available. Register data have since then improved, in particular after the late 1990s when data became available directly from banks, brokers, and insurance companies without the filtering of the tax payers. The problem with the household definition remains, but in SESIM we have made corrections to get a useful definition (see Chapter 3). A relatively large survey (HEK) run by Statistics Sweden which combines survey information about the household with register data on assets estimates the median household wealth to 156000 SEK in 1999 and 197000 SEK in 2003.² The latter estimate is in the 1999 price level.³ These estimates apply to all households independent of age. As will be shown below, the level of wealth depends very much on age.

It is well known that taxes on the transfer of wealth typically raise very little revenue. However, this does not mean that they are ineffective as tools for redistribution. In this chapter, we show how important such taxes can be in the long-run distribution of wealth, reducing equilibrium inequality (the “predistribution” effect) by a much larger amount than what is apparent in terms of the immediate impact of the tax (the “redistribution” effect).

The impact of the “Great Recession” on inequality is unclear. Because the crises in the housing and stock markets and mass job loss affect incomes across the entire distribution, the overall impact on inequality is difficult to determine. Early speculation using a variety of narrow measures of earnings, income, and consumption yield contradictory results. In this chapter, we develop new estimates of income inequality based on “more complete income” (MCI), which augments standard income measures with those that are accrued from the ownership of wealth. We use the 1989–2007 Surveys of Consumer Finances, and also construct MCI measures for 2009 based on projections of assets, income, and earnings.

We investigate the level and trend in MCI inequality and compare it to other estimates of overall and “high incomes” in the literature. Compared to standard measures of income, MCI suggests higher levels of inequality and slightly larger increases in inequality over time. Several MCI-based inequality measures peaked in 2007 at their highest levels in 20 years. The combined impact of the Great Recession on the housing, stock, and labor markets after 2007 has reduced some measures of income inequality at the top of the MCI distribution. Despite declining from the 2007 peak, however, inequality remains as high as levels experienced earlier in the decade, and much higher than most points over the last 20 years. In the middle of the income distribution, the declines in income from wealth after 2007 were the result of diminished value of residential real estate; at the top of the distribution, declines in the value of business assets had the greatest impact.

We also assess the level and trend in the functional distribution of income between capital and labor, and find a rising share of income accruing to real capital or wealth from 1989 to 2007. The recent economic crisis has diminished the capital share back to levels from 2004. Contrary to the findings of other researchers, we find that the labor share of income among high-income groups declined between 1992 and 2007.