Research Database

We document that declining hours worked are the primary driver of widening inequality in the bottom half of the male labor earnings distribution in the United States over the past 52 years. This decline in hours is heavily concentrated in recessions: hours and earnings at the bottom fall sharply in recessions and do not fully recover in subsequent expansions. Motivated by this evidence, we build a structural model to explore the possibility that recessions cause persistent increases in inequality; that is, that the cycle drives the trend. The model features skill-biased technical change, which implies a trend decline in low-skill wages relative to the value of non-market activities. With this adverse trend in the background, recessions imply a potential double-whammy for low skilled men. This group is disproportionately likely to experience unemployment, which further reduces skills and potential earnings via a scarring effect. As unemployed low skilled men give up job search, recessions generate surges in non-participation. Because non-participation is highly persistent, earnings inequality remains elevated long after the recession ends.

We show that occupational licensing has significant negative effects on labor market fluidity defined as cross-occupation mobility. Using a balanced panel of workers constructed from the CPS and SIPP data, we analyze the link between occupational licensing and labor market outcomes. We find that workers with a government-issued occupational license experience churn rates significantly lower than those of non-licensed workers. Specifically, licensed workers are 24% less likely to switch occupations and 3% less likely to become unemployed in the following year. Moreover, occupational licensing represents barriers to entry for both non-employed workers and employed ones. The effect is more prominent for employed workers relative to those entering from non-employment, because the opportunity cost of acquiring a license is much higher for employed individuals. Lastly, we find that average wage growth is higher for licensed workers than non-licensed workers, whether they stay in the same occupation in the next year or switch occupations. We find significant heterogeneity in the licensing effect across different occupation groups. These results hold across various data sources, time spans, and indicators of being licensed. Overall, licensing could account for almost 8% of the total decline in monthly occupational mobility over the past two decades

We address this question in a heterogeneous-agent incomplete-markets model featuring exogenous idiosyncratic risk, endogenous skill investment, and flexible labor supply. The tax and transfer schedule is restricted to be log-linear in income, a good description of the US system. Rising inequality is modeled as a combination of skill-biased technical change and growth in residual wage dispersion. When facing shifts in the income distribution like those observed in the US, a utilitarian planner chooses higher progressivity in response to larger residual inequality but lower progressivity in response to widening skill price dispersion reflecting technical change. Overall, optimal progressivity is approximately unchanged between 1980 and 2016. We document that the progressivity of the actual US tax and transfer system has similarly changed little since 1980, in line with the model prescription.

We show that cities with higher population density specialize in high-skill service jobs that can be done remotely. The urban and industry bias of remote work potential shaped the recent pandemic’s economic impact. Many high-skill service workers started to work remotely, withdrawing spending from big-city consumer service industries dependent on their demand. As a result, low-skill service workers in big cities bore most of the recent pandemic’s economic impact. Our findings have broader implications for the distributional consequences of the U.S. economy’s transition to more remote work.

This paper studies the short- and long-run effects of large firms on economic development. We use evidence from one of the largest multinationals of the 20th century: the United Fruit Company (UFCo). The firm was given a large land concession in Costa Rica—one of the so-called "Banana Republics"—from 1899 to 1984. Using administrative census data with census-block geo-references from 1973 to 2011, we implement a geographic regression discontinuity design that exploits a quasi-random assignment of land. We find that the firm had a positive and persistent effect on living standards. Company documents explain that a key concern at the time was to attract and maintain a sizable workforce, which induced the firm to invest heavily in local amenities that can account for our result. Consistent with this mechanism, we show, empirically and through a proposed model, that the firm's welfare effect is increasing in worker mobility.

To measure labor market power in the US economy, we develop a tractable quantitative, general equilibrium, oligopsony model of the labor market. We estimate key model parameters by matching the firm-level relationship between labor market share and employment size and wage responses to state corporate tax changes. The model quantitatively replicates quasi-experimental evidence on (i) imperfect productivity-wage pass-through, (ii) strategic behavior of dominant employers, and (iii) the local labor market impact of mergers. We then measure welfare losses relative to the efficient allocation. Accounting for transition dynamics, we quantify welfare losses from labor market power relative to the efficient allocation as roughly 6 percent of lifetime consumption. An analytical decomposition attributes equal parts to dead-weight losses and misallocation. Lastly, we find that declining local concentration added 4 ppt to labor's share of income between 1977 and 2013.

This paper aims at an improved understanding of the relationship between monetary policy and racial inequality. We investigate the distributional effects of monetary policy in a unified framework, linking monetary policy shocks both to earnings and wealth differentials between black and white households. Specifically, we show that, although a more accommodative monetary policy increases employment of black households more than white households, the overall effects are small. At the same time, an accommodative monetary policy shock exacerbates the wealth difference between black and white households, because black households own less financial assets that appreciate in value. Over multi-year time horizons, the employment effects are substantially smaller than the countervailing portfolio effects. We conclude that there is little reason to think that accommodative monetary policy plays a significant role in reducing racial inequities in the way often discussed. On the contrary, it may well accentuate inequalities for extended periods.

COVID symptom screening, a new workplace practice, is likely to affect many millions of American workers in the coming months. Eleven states already require and federal guidance recommends frequent screening of employees for infection symptoms. This paper provides some of the first empirical work exploring the tradeoffs employers face in using daily symptom screening. First, we find that common symptom checkers will likely screen out up to 7 percent of workers each day, depending on the measure used. Second, we find that the measures used will matter for three reasons: many respondents report any given symptom, survey design affects responses, and demographic groups report symptoms at different rates, even absent fluctuations in likely COVID exposure. This last pattern can potentially lead to disparate impacts, and is important from an equity standpoint.

We examine the determinants of COVID-19 risk exposure in the context of the initial wave in New York City. During the beginning of the first wave of the pandemic, out-of-home activity related to commuting was strongly associated with COVID-19 cases at the ZIP code level and hospitalization at an individual level. After layoffs of workers decreased commuting, case growth continued through household crowding. A larger share of individuals in crowded housing, or commuting to essential and frontline work, are Black, Hispanic, and lower-income—which contributes to disparities in disease risk. As a result, our paper shows that structural socio-economic inequalities help determine the cross-section of COVID-19 risk exposure in urban areas.

We use panel data covering 118 million homes in the United States, merged with geolocation detail for 75,000 taxing entities, to document a nationwide "assessment gap" which leads local governments to place a disproportionate fiscal burden on racial and ethnic minorities. We show that holding jurisdictions and property tax rates fixed, black and Hispanic residents nonetheless face a 10-13% higher tax burden for the same bundle of public services. This assessment gap arises through two channels. First, property assessments are less sensitive to neighborhood attributes than market prices are. This generates racially correlated spatial variation in tax burden within jurisdiction. Second, appeals behavior and appeals outcomes differ by race. This results in higher assessment growth rates for minority residents. We propose an alternate approach for constructing assessments based on small-geography home price indexes, and show that this reduces inequality by at least 55-70%.