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Abandoning the Sinking Ship: The Composition of Worker Flows Prior to Displacement

August 2002

Working Paper Number:

tp-2002-11

Abstract

declines experienced by workers several years before displacement occurs. Little attention, however, has been paid to other changes in compensation and employment in firms prior to the actual displacement event. This paper examines changes in the composition of job and worker flows before displacement, and compares the "quality" distribution of workers leaving distressed firms to that of all movers in general. More specifically, we exploit a unique dataset that contains observations on all workers over an extended period of time in a number of US states, combined with survey data, to decompose different jobflow statistics according to skill group and number of periods before displacement. Furthermore, we use quantile regression techniques to analyze changes in the skill profile of workers leaving distressed firms. Throughout the paper, our measure for worker skill is derived from person fixed effects estimated using the wage regression techniques pioneered by Abowd, Kramarz, and Margolis (1999) in conjunction with the standard specification for displaced worker studies (Jacobson, LaLonde, and Sullivan 1993). We find that there are significant changes to all measures of job and worker flows prior to displacement. In particular, churning rates increase for all skill groups, but retention rates drop for high-skilled workers. The quantile regressions reveal a right-shift in the distribution of worker quality at the time of displacement as compared to average firm exit flows. In the periods prior to displacement, the patterns are consistent with both discouraged high-skilled workers leaving the firm, and management actions to layoff low-skilled workers.

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employed, employ, labor, longitudinal, retirement, tenure, workforce, worker, household, welfare, census bureau, research census, employer household, aging, moving

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Bureau of Labor Statistics, National Science Foundation, Ordinary Least Squares, University of Maryland, Current Population Survey, Cornell University, New York University, Journal of Economic Literature, Department of Labor, Longitudinal Employer Household Dynamics, Alfred P Sloan Foundation, National Institute on Aging, Cornell Institute for Social and Economic Research, PSID

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