Richard Alan Sessa, M.Sci.

Academic Research

Job Market Paper
Title: Local Labor Market Conditions and the Transition Out of Unemployment: The Importance of Prior-Industry Demand
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Abstract: Most research investigating the effects of local labor market conditions on unemployment summarize those conditions in the form of Bartik’s (1991) index. Such studies overlook an important component of local demand conditions, namely, the fortunes in workers’ prior industries. This paper examines the effects of local own- and other-industry labor demand on the probability that jobseekers exit unemployment. To the extent that workers are tied to their prior lines of production, it becomes useful to distinguish between labor demand in their previous industry and the level of aggregate labor demand for their locale. After combining several U.S. datasets spanning the years 2003-2015, I find that a 10-percentage point increase in labor demand within an individual’s prior local industry increases the probability of exiting unemployment by 2.7-percentage points after controlling for aggregate demand. Moreover, I document that the magnitude of this effect increases with a jobseeker’s age and level of educational attainment. These findings suggest that, in addition to overall labor market conditions, prior-industry demand is an important determinant of unemployment transitions.
   
Working Papers
Title: Local Labor Demand and the Earnings Losses of (Some) Displaced Workers (with Dr. Mallika Pung)
Abstract: This paper studies the impact of local labor demand on the earnings losses of displaced workers. We combine data from Displaced Workers Surveys (DWS) and the Bureau of Economic Analysis (BEA) to construct a novel dataset linking displaced workers to measures of local labor demand. Using a generalized difference-in- difference approach, our estimates suggest that a one standard deviation increase in local labor demand reduces the mean earnings loss associated with job displacement by 13 percentage points, after controlling for national business cycle fluctuations. Using a quantile regression (QR) approach, we document significant heterogeneity in the effect of predicted demand shocks across the earnings loss distribution. The effect of labor demand is strongest in the lower region of the distribution with little or no effect in the upper region.
Work in Progress

“Sectoral Labor Reallocation in Recessions and Recoveries.” March 2017.