Reconsidering the Consequences of Worker Displacements: Firm versus Worker Perspective

Prior literature has established that displaced workers suffer persistent earnings losses by following workers in administrative data after mass layoffs. This literature assumes that these are involuntary separations owing to economic distress. This paper examines this assumption by matching survey data on worker-supplied reasons for separations with administrative data. Workers exhibit substantially different earnings dynamics in mass layoffs depending on the reason for separation. Using a new methodology to account for the increased separation rates across all survey responses during a mass layoff, the paper finds earnings loss estimates that are surprisingly close to those using only administrative data. (JEL E32, J31, J63, J64, J65)

Spillover Effects of Mass Layoffs

Using administrative data on firms and workers in Germany, we quantify the spillover effects of mass layoffs. Our empirical strategy combines matching with an event study approach to trace employment and wages in regions hit by a mass layoff relative to suitable control regions. We find sizable and persistent negative spillover effects on the regional economy: regions, and especially firms producing in the same broad industry as the layoff plant, lose many more jobs than in the initial layoff. In contrast, negative employment effects on workers employed in the region at the time of the mass layoff are considerably smaller. Strikingly, workers younger than 50 suffer no employment losses, as geographic mobility fully shields them from the decline in local employment opportunities.

Revisiting the Link Between Economic Distress, Race, and Domestic Violence

Male unemployment may decrease the incidence of domestic violence, due to loss of economic power in the relationship, or increase the incidence of domestic violence, due to emotional outbursts fueled by increased stress. We hypothesize that Black men may face a greater loss of expected future earnings after an unemployment shock due to a more unfavorable labor market relative to White men. Consequently, we would expect that Black men would, on net, exhibit a greater reduction (or a smaller increase) in incidences of domestic violence following an employment shock. This study uses mass layoff events reported by the Bureau of Labor Statistics (BLS) at the county level ( N = 3,377) for the years 2003-2008. Mass layoff events occur when a firm lays off at least 50 workers and are uncorrelated with individual-level characteristics ( N = 28,939 events, affecting N = 5,337,481 individuals). Domestic violence data are taken from the National Archive of Criminal Justice and defined as occurring when an accused perpetrator is charged, but not necessarily convicted. We use a multivariate regression model to estimate how differences in the change in reported incidences of domestic violence by race correlate with changes in mass layoffs by race. We control for the poverty rate, real per capita income, percent Black, percent women, and percent of females laid off. The standard errors are clustered at the county level and include county and time dummies to account for regional and time specific trends. We observe that an increase in the number of Blacks subject to a mass layoff event do exert a negative associated influence on domestic violence while layoffs of White men exert a positive influence. Our results shed light on how the influence of economic uncertainty on incidences of domestic violence has been found to be positive in some previous research but negative in other research.

Earnings Losses of Displaced Workers Revisited

Earnings losses of Connecticut workers affected by mass layoff are calculated using administrative data. Estimated reductions are initially more than 30 percent and six years later, as much as 15 percent. The Connecticut estimates are smaller than comparable ones from Pennsylvania administrative data but similar to those from the Panel Study of Income Dynamics (PSID) and Department of Workforce Services (DWS). Earnings reductions in Connecticut and Pennsylvania are concentrated among Unemployment Insurance recipients. An unusually high proportion of Unemployment Insurance beneficiaries in Pennsylvania explains the larger estimated losses relative to other studies. Fixed-effects, random growth, and matching estimators produced similar earnings loss estimates suggesting each is relatively unbiased in this context.