The propensity to become a business owner is a nonlinear function of wealth. The relationship between wealth and entry into entrepreneurship is essentially flat over the majority of the wealth distribution. It is only at the top of the wealth distributionafter the ninety-fifth percentilethat a positive relationship can be found. Segmenting businesses into industries with high and lowstarting capital requirements, we find no evidence that wealth matters more for businesses requiring higher initial capital. When using inheritances as an instrument for wealth, we find that both past and future inheritances predict current business entry, showing that inheritances capture more than simply liquidity. We further exploit the regional variation in house prices and find that households that lived in regions in which housing prices appreciated strongly were no more likely to start a business than households in other regions.

A large literature shows that the self-employed underreport their income to tax authorities. In this paper, we quantify the extent to which the self-employed also systematically underreport their income in U.S. household surveys. We use the Engel curve describing the relationship between income and expenditures of wage and salary workers to infer the actual income, and thus the reporting gap, of the self-employed based on their reported expenditures. On average, the self-employed underreport their income by about 25%. We show that failing to account for such income underreporting leads to biased conclusions in a variety of settings.

Regional shocks are an important feature of the US economy. Households' ability to self-insure against these shocks depends on how they affect local interest rates. In the United States, most borrowing occurs through the mortgage market and is influenced by the presence of government-sponsored enterprises (GSE). We establish that despite large regional variation in predictable default risk, GSE mortgage rates for otherwise identical loans do not vary spatially. In contrast, the private market does set interest rates which vary with local risk. We use a spatial model of collateralized borrowing to show that the national interest rate policy substantially affects welfare by redistributing resources across regions.

We explore the impact of rising incomes at the top of the distribution on spatial sorting patterns within large U.S. cities. We develop and quantify a spatial model of a city with heterogeneous agents and non-homothetic preferences for neighbourhoods with endogenous amenity quality. As the rich get richer, demand increases for the high-quality amenities available in downtown neighbourhoods. Rising demand drives up house prices and spurs the development of higher quality neighbourhoods downtown. This gentrification of downtowns makes poor incumbents worse off, as they are either displaced to the suburbs or pay higher rents for amenities that they do not value as much. We quantify the corresponding impact on well-being inequality. Through the lens of the quantified model, the change in the income distribution between 1990 and 2014 led to neighbourhood change and spatial resorting within urban areas that increased the welfare of richer households relative to that of poorer households, above and beyond rising nominal income inequality.

Using nationally representative data on consumption, we show that Blacks and Hispanics devote larger shares of their expenditure bundles to visible goods (clothing, jewelry, and cars) than do comparable Whites. These differences exist among virtually all subpopulations, are relatively constant over time, and are economically large. Although racial differences in utility preference parameters might account for a portion of these consumption differences, we emphasize instead a model of status seeking in which conspicuous consumption is used as a costly indicator of a household's economic position. Using merged data on race- and state-level income, we demonstrate that a key prediction of the status-signaling model—that visible consumption should be declining in reference group income—is strongly borne out in the data for each racial group. Moreover, we show that accounting for differences in reference group income characteristics explains most of the racial difference in visible consumption.

In 1960, 94 percent of doctors and lawyers were white men. By 2010, the fraction was just 62 percent. Similar changes in other highly‐skilled occupations have occurred throughout the U.S. economy during the last 50 years. Given that the innate talent for these professions is unlikely to have changed differently across groups, the change in the occupational distribution since 1960 suggests that a substantial pool of innately talented women and black men in 1960 were not pursuing their comparative advantage. We examine the effect on aggregate productivity of the convergence in the occupational distribution between 1960 and 2010 through the prism of a Roy model. Across our various specifications, between 20% and 40% of growth in aggregate market output per person can be explained by the improved allocation of talent.

Using administrative payroll data from the largest US payroll processing company, we measure the extent of nominal wage rigidity in the United States. The data allow us to define a worker’s per-period base contract wage separately from other forms of compensation such as overtime premiums and bonuses. We provide evidence that firms use base wages to cyclically adjust the marginal cost of their workers. Nominal base wage declines are much rarer than previously thought with only 2 percent of job-stayers receiving a nominal base wage cut during a given year. Approximately 35 percent of workers receive no base wage change year over year. We document strong evidence of both time and state dependence in nominal base wage adjustments. In addition, we provide evidence that the flexibility of new hire base wages is similar to that of existing workers. Collectively, our results can be used to discipline models of nominal wage rigidity.

Using data from the American Time Use Survey between 2003 and 2010, we document that home production absorbs roughly 30 percent of foregone market work hours at business cycle frequencies. Leisure absorbs roughly 50 percent of foregone market work hours, with sleeping and television watching accounting for most of this increase. We document significant increases in time spent on shopping, child care, education, and health. Job search absorbs between 2 and 6 percent of foregone market work hours. We discuss the implications of our results for business cycle models with home production and non-separable preferences.

Using time use survey data we document a hump-shaped profile of job search time in the United States across the life-cycle. The middle-aged unemployed spend roughly three times as much time in job search as the youngest group of unemployed. The hump-shaped profile of job search time is relatively stable across demographic groups. However, the profile of job search time appears to be declining in non-US countries. We discuss how standard life-cycle models with incomplete markets have difficulty in accounting for the hump-shaped profile found in the US data.

When a city experiences a decline in income or population, do all neighborhoods within the city decline equally? Or, do some neighborhoods decline more than others? What are the characteristics of the neighborhoods that decline the most? We answer these questions by looking at what happened to neighborhoods within Detroit as Detroit experienced a sharp decline in income and population from the 1980s to the late 2000s. We find patterns of changes in income and population that are consistent with the model and empirical patterns of gentrification presented in Guerrieri, Hartley, and Hurst (2011), only playing out in reverse.