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Empirical Analyses of Job Displacements and Productivity
|dc.description||Committee Chairperson: John Abowd; Other Committee Members: George Jakubson and Kosali Simon.||en_US|
|dc.description.abstract||The first chapter of this dissertation integrates the existing literatures on displacement and health by examining the enduring effects of job dislocations that are induced by employment shocks. A joint estimation of hourly wage rates and weekly hours illuminates the disparities in these economic outcomes that exist between those who have reestablished themselves in the workplace subsequent to a layoff and those who have returned to work following the onset of a disability relative to those with uninterrupted job histories. As an extension of these ideas, employment transitions and workplace adjustments are modeled to capture spousal reactions to these shocks. Multiple indicators of health from the Survey of Income and Program Participation and Social Security Administrative benefits records are incorporated into the analyses of those with impairments that prompted job loss. These measures allow knowledge to be gleaned regarding the qualitative differences in the lasting impacts of job cessation resulting from medically diagnosed illnesses as compared to estimates uncovered using survey data sources alone. By considering time durations following these periods of separation in light of these indicators of well-being, a more comprehensive understanding of the long-run repercussions of employee-employer separation is acquired. The second and third chapters, representing joint work with John M. Abowd and Kevin L. McKinney, address the research and data work that is part of a larger Bureau of Labor Statistics and Bureau of the Census project. We examine the manner in which changes in the composition of the labor force impact productivity by exploiting measures of human capital, or skill. The BLS has previously employed a multifactor productivity to explore changes in the index of labor composition using categories within industry division and year by education, work experience, and gender. We choose to use the centiles of the nationally-weighted human capital distribution from the estimation of a wage equation that includes both person and firm fixed effects to partition the sample of workers into more refined cells. The knowledge of the estimated density function of human capital for each sector enables us to characterize how differences in labor force composition affect labor quality within and between industry divisions over time.||en_US|
|dc.title||Empirical Analyses of Job Displacements and Productivity||en_US|
|dc.type||dissertation or thesis||en_US|