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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.

I find that median wealth plummeted over the years 2007–2010, and by 2010 was at its lowest level since 1969. The inequality of net worth, after almost two decades of little movement, was up sharply from 2007 to 2010. Relative indebtedness continued to expand from 2007 to 2010, particularly for the middle class, though the proximate causes were declining net worth and income rather than an increase in absolute indebtedness. In fact, the average debt of the middle class actually fell in real terms by 25 percent. The sharp fall in median wealth and the rise in inequality in the late 2000s are traceable to the high leverage of middle-class families in 2007 and the high share of homes in their portfolio. The racial and ethnic disparity in wealth holdings, after remaining more or less stable from 1983 to 2007, widened considerably between 2007 and 2010. Hispanics, in particular, got hammered by the Great Recession in terms of net worth and net equity in their homes. Households under age 45 also got pummeled by the Great Recession, as their relative and absolute wealth declined sharply from 2007 to 2010.

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.

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.

During the last two decades the share of foreign-born residents in Italy has grown considerably, from just over 1 percent to about 8 percent. This chapter seeks to clarify the status of immigrants in Italy by examining the evolution of their economic situation and, in particular, the presence of economic hardship. Poverty is measured by considering not only the usual income-based indicators but also others that take into account households’ real and financial wealth. The picture that emerges is one of a higher incidence of economic hardship among immigrant households that strongly affects the dynamics of poverty nationwide. The economic gap with respect to natives appears to increase in the years considered, but the condition of poverty is not more persistent for immigrants than for Italians.

In the wake of the Stiglitz Commission, we assess German economic well-being by considering income, wealth and consumption. A decomposition approach is used to test for corresponding inequality differences of these well-being dimensions. Total inequality is decomposed into within- and between-group inequality (via a normalised coefficient of variation). The decompositions are categorised into those that refer to socio-demographic characteristics (place of residence, age, household type) and those belonging to different well-being (sub-)categories (potential and net income, expenditure and wealth categories). The empirical analyses are performed for Germany using the 2008 German Sample Survey of Income and Expenditure. By decomposing German well-being inequality in great detail, we shed light on its dimensions. Our analyses illustrate that it is necessary to consider all well-being dimensions to make statements about the material well-being of private households or individuals.

Industrial feudalism is a socio-economic formation of advanced capitalist countries in which society becomes stratified into closed, hierarchically-defined social groups. In the writings of Ludwik Krzywicki and Oskar Lange, industrial feudalism is associated with the dominance of monopoly finance capital. The chapter extends this analysis of twenty-first century capitalism in which social groups are differentiated by the kind of property that they own and hence the kind of credit to which they have access to prevent becoming déclassé. However asset inflation then inhibits upward social mobility, confining households to their inherited social class. This inhibits labour mobility. But the availability of credit for the propertied classes also defines attitudes towards state welfare provision.

Purpose – In this chapter, we advance research on the socioeconomic ranking of religious groups by using both income and wealth to document the rankings of the six major religious groups in the United States – Jews, Catholics, mainline Protestants, evangelical Protestants, black Protestants, and the religiously unaffiliated – during 2001–2007, a period marked by both catastrophic economic losses and widespread economic gain.

Design/Methodology/Approach – Drawing from the Panel Study on Income Dynamics (PSID), we provide descriptive statistics to explore the socioeconomic differences among the six major religious groups. In addition, we note their ownership rates and changes in wealth and income during 2001–2007.

Findings – Overall, these findings point to enduring stratification in the U.S. religious landscape. Based on median net worth, leading into the Great Recession, the six major religious groups ranked in the following order: Jews, Catholics, mainline Protestants, evangelical Protestants, the unaffiliated, and black Protestants. At the same time, these findings point to the upward mobility of white Catholics, who increased their income and made the greatest increase in net worth between 2001 and 2007. These data also suggest a decline in the socioeconomic status of the religiously unaffiliated as compared to previous studies.

Research implications – These findings illustrate the degree to which certain religious groups have access to wealth and other resources, and have implications for how the years leading into the Great Recession may have influenced households’ vulnerability to financial shocks.

Originality/Value – We use both income and wealth to examine whether different religious groups experienced any changes in income and wealth leading into the 2008 economic downturn.

This paper uses a sample of school age children from the Nepal Demographic Health Survey (NDHS) to examine the relationship between maternal education and child schooling in Nepal. Taking advantage of the two-stage stratified sample design, we estimate a sample selection model controlling for cluster fixed effects. These results are then compared to OLS and Tobit models. Our analysis shows that being male significantly increases the likelihood of attending school and for those children attending school, it also affects the years of schooling. Parental education has a similarly positive effect on child school, but interestingly we find maternal education having a relatively greater effect on the schooling of girls. Our results also point to household wealth as having a positive effect on both the probability of schooling and the years of schooling in all our models, with the magnitude of these effects being similar for male and female children. Finally, a comparison of our results with a model ignoring cluster fixed effects produces results that are statistically different both in signs and in the levels of significance.