We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time.

The board independence requirements enacted in conjunction with the Sarbanes Oxley Act of 2002 (SOX) provided motivation for firms that were already compliant with the regulations to alter their board structure. We consider actual board changes made by compliant firms and how such changes affect the monitoring efficiency of the boards. We find that the majority of compliant firms (approximately 56%) add independent directors following SOX. However, we find a nontrivial number of firms (approximately 26%) actually decrease the number of independent directors to move closer to the stated 50% requirement. For firms that decrease independence, the CEO turnover performance sensitivity significantly decreases following SOX. We also find that large board independence changes seem to be most detrimental to the monitoring function of the board. Our results highlight that SOX may have had unintended consequences.

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. (JEL E24, E32, J31, J41)

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. (JEL D31, E32, J22)

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.

The (S, s) model has enjoyed tremendous popularity over the past decade. It has been employed almost everywhere that discrete adjustment is observed. Today microeconomic rigidities are seen as an important influence on aggregate dynamics. In this paper we quickly characterize the microeconomic evidence for the model. To narrow the scope of our discussion, we will focus our attention on real variables, and we will comment on price inertia where appropriate. We conclude that, in spite of its popularity, the evidence for the importance of the (S, s) adjustment is surprisingly weak. We argue that discrete adjustment is, in and of itself, of little macroeconomic interest. To be important these frictions must coordinate agents to act together, thereby exacerbating deviations from the neoclassical benchmark. To date there have been few attempts at empirically identifying such interactions. In the last section, we present some results of our own. We test one of the main implications of (S, s) adjustment, that a greater variance in the forcing process leads to more frequent adjustment. Using data on automobiles from the Consumer Expenditure Survey, we find that more variable income leads to less frequent adjustment. We speculate that this correlation is indicative of a link between discrete adjustment and imperfect capital markets. This interaction could provide an important role for (S, s) frictions.

We study how the recent housing boom and bust affected college enrollment during the 2000s. We exploit cross-city variation in local housing booms, which improved labor market opportunities for young men and women. We find that the boom lowered college enrollment, with effects concentrated at two-year colleges. The decline in enrollment during the boom was generally reversed during the bust; however, attainment remains persistently low for particular cohorts, suggesting that reduced educational attainment is an enduring effect of the recent housing cycle. The housing boom can account for approximately 25 percent of the recent slowdown in college attainment. (JEL I23, I25, J24, J31, R21, R31)

Not properly accounting for differences between business owners and nonbusiness owners in studies of household wealth can lead to erroneous conclusions about the significance of different saving motives. Using data from the Panel Study of Income Dynamics from the 1980s and 1990s, we show that within samples of both business owners and non–business owners, the amount of precautionary savings with respect to labor income risk is modest and accounts for less than 10% of total household wealth. Previous large estimates of the size of precautionary balances resulted from pooling these two groups together. Such pooling is inappropriate given that business owners face higher labor risk and accumulate more wealth than non–business owners for reasons unrelated to precautionary motives.

We propose a methodology exploiting time diary data and “leisure Engel curves” to infer quality changes across leisure activities and measure the effects on the marginal return to leisure. We study leisure returns for men aged 21–30, who have shifted leisure toward video gaming and recreational computing and have had larger market work hour declines than older men or women since 2004. We show that recreational computing is distinctly a leisure luxury for younger men. By increasing the value of time, innovations to this leisure technology have lowered young men's work hours by 2%, or much of their work hours decline compared to older men's.