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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.

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.

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.

The structural change of the dairy industry has been a long-term process with fewer, larger dairy herds in all regions. The purpose of this paper is to evaluate whether this structural change is leading to less income and wealth equality across dairy farms and how these factors differ across the USA.

Income and wealth inequality of US dairy farms was estimated by Gini coefficients using data from the 2000 and 2010 ARMS dairy costs and returns data. A population-level quantile regression was estimated at decile increments to determine the factors that affect net farm income (NFI) and net worth (NETW) and if they changed across the time periods.

Adjusted-Gini coefficients were estimated and indicated that income inequality was greater than wealth inequality across US dairy farms. Results of the quantile regressions confirm regional differences exist with dairy farms in Mountain regions consistently having lower NFI and NETW relative to farms in the Lake States region when factors such as herd size were equal. Life cycle effects were not observed for NFI, but present within NETW estimates across the ten years.

This analysis estimates industry-specific-adjusted Gini coefficients to determine if income and wealth inequality exist.

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.

Purpose – The purpose of this chapter is to assess the role of the wealth-to-income ratio in forecasting housing risk premium.

Methodology/approach – To investigate this issue, the chapter uses the residuals of the trend relationship among asset wealth and labor income to predict future real housing returns. It shows that deviations of asset wealth from its cointegrating relationship with labor income, wy, track time-variation in expected housing returns.

Findings – Using data for a set of industrialized countries, this chapter finds that if agents are hit by a shock that generates a fall in the wealth-to-income ratio, they will demand (i) a higher housing risk premium when housing assets are complements of financial assets and (ii) a lower housing risk premium when housing assets are substitutes of financial assets.

Originality/value of chapter – The findings of this chapter are novel in the field of alternative finance and, in particular, durable (housing) finance. Indeed, they build on a representative agent's theoretical model to infer about the degree of substitution or complementarity between financial and housing assets, which, in turn, can be useful at developing investment strategies for hedging against the risk of unfavorable housing fluctuations. Additionally, they open a new research avenue for understanding the determinants of housing risk premium by linking the dynamics of asset wealth and labor income with the behavior of future housing returns.

Purpose – The purpose of this chapter is to assess the role of collateralizable wealth and systemic risk in explaining future asset returns.

Methodology/approach – To test this hypothesis, the chapter uses the residuals of the trend relationship among housing wealth and labor income to predict both stock returns and government bond yields. Specifically, it shows that nonlinear deviations of housing wealth from its cointegrating relationship with labor income, hwy, forecast expected future returns.

Findings – Using data for a set of industrialized countries, the chapter finds that when the housing wealth-to-income ratio falls, investors demand a higher risk premium for stocks. As for government bond returns: (i) when they are seen as a component of asset wealth, investors react in the same manner and (ii) if, however, investors perceive the increase in government bond returns as signaling a future rise in taxes or a deterioration of public finances, then they interpret the fall in the housing wealth-to-income ratio as a fall in future bond premia. Finally, this work shows that the occurrence of crisis episodes amplifies the transmission of housing market shocks to financial markets.

Originality/value of chapter – These findings are novel. They also open new and challenging avenues for understanding the dynamics of the relationship between the housing sector, stock market and government bond developments, and the banking system.

The purpose of this study is to estimate the housing wealth effect on non-durable consumption using data from the Spanish Survey of Household Finances (Encuesta Financiera de las Familias, SHF) for the period 2002–2017.

The authors aim at identifying the effect of anticipated and unanticipated housing wealth changes on consumption with the sample of homeowners, following Paiella and Pistaferri (2017).

Results of this study lead us to conclude that there exists a strong housing wealth effect on consumption for the Spanish households.

The authors provide evidence against the permanent income model. They also analyse how the results change with income expectations, age and the household indebtedness rate. Finally, they detect a strong excess sensitivity to income.