{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/85562"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/85562","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Three Essays on Worker Displacement","abstract":"Chapter 1 examines the effect of job displacement on the distribution of earnings. I utilize a novel technique, quantile fixed effect regression, in order to examine how the overall distribution of earnings changes while controlling for unobserved heterogeneity in worker quality. I find that while mean income falls by approximately 22% in the year of displacement, displacement does not affect all workers equally. The 5th percentile of the income distribution falls 45%. Much of the negative mean effect is accounted for by a small group of displaced workers who end up with poor job matches. In contrast, 39% of workers experience income gains following displacement. Chapter 2 simulates an on-the-job search model to match the finding that 39% of workers earn more after displacement. I first examine an on-the-job search model under the assumption that workers know the distribution of earnings and I find evidence of substantial on-the-job search costs. Next, I relax the assumption that workers know the distribution of earnings. In a model where workers learn about the wage distribution from wage offers, I find that 75% lower on-the-job search costs match the empirical data. Chapter 3 documents three problems associated with measuring the wage gains from internal migration. First, earnings losses associated with job displacement may overwhelm gains from migration when different types of job separations are pooled. Second, even in a sample of workers that quit, temporary losses in job specific human capital can dominate migration gains. Third, I find large heterogeneity in the outcomes for workers that quit their jobs. I employ quantile fixed effect estimation and examine how the entire distribution of earnings differs for quitters that move and quitters that stay in the same location. I show that the effect at the lower tail of the distribution is positive, but the effect for the rest of the distribution varies. This suggests that because of the costs associated with moving, workers will not quit and take the lowest paying jobs in another market.","abstract_html":"Chapter 1 examines the effect of job displacement on the distribution of earnings. I utilize a novel technique, quantile fixed effect regression, in order to examine how the overall distribution of earnings changes while controlling for unobserved heterogeneity in worker quality. I find that while mean income falls by approximately 22% in the year of displacement, displacement does not affect all workers equally. The 5th percentile of the income distribution falls 45%. Much of the negative mean effect is accounted for by a small group of displaced workers who end up with poor job matches. In contrast, 39% of workers experience income gains following displacement. Chapter 2 simulates an on-the-job search model to match the finding that 39% of workers earn more after displacement. I first examine an on-the-job search model under the assumption that workers know the distribution of earnings and I find evidence of substantial on-the-job search costs. Next, I relax the assumption that workers know the distribution of earnings. In a model where workers learn about the wage distribution from wage offers, I find that 75% lower on-the-job search costs match the empirical data. Chapter 3 documents three problems associated with measuring the wage gains from internal migration. First, earnings losses associated with job displacement may overwhelm gains from migration when different types of job separations are pooled. Second, even in a sample of workers that quit, temporary losses in job specific human capital can dominate migration gains. Third, I find large heterogeneity in the outcomes for workers that quit their jobs. I employ quantile fixed effect estimation and examine how the entire distribution of earnings differs for quitters that move and quitters that stay in the same location. I show that the effect at the lower tail of the distribution is positive, but the effect for the rest of the distribution varies. This suggests that because of the costs associated with moving, workers will not quit and take the lowest paying jobs in another market.","abstract_has_math":false,"creators":["Hanner, Dan L."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Todd Elder"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T22:47:24Z","date_published":"2015-09-25T22:47:24Z","updated_at":"2026-07-22T22:26:25Z","subjects":["Economics, Labor"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3202102"],"render_values":[{"text":"(MiAaPQ)AAI3202102","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/85562","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Todd Elder"]},{"key":"dc:creator","label":"Author","values":["Hanner, Dan L."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T22:47:24Z","10000-01-01","2005"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Economics, Labor"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/85562","(MiAaPQ)AAI3202102"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Chapter 1 examines the effect of job displacement on the distribution of earnings. I utilize a novel technique, quantile fixed effect regression, in order to examine how the overall distribution of earnings changes while controlling for unobserved heterogeneity in worker quality. I find that while mean income falls by approximately 22% in the year of displacement, displacement does not affect all workers equally. The 5th percentile of the income distribution falls 45%. Much of the negative mean effect is accounted for by a small group of displaced workers who end up with poor job matches. In contrast, 39% of workers experience income gains following displacement. Chapter 2 simulates an on-the-job search model to match the finding that 39% of workers earn more after displacement. I first examine an on-the-job search model under the assumption that workers know the distribution of earnings and I find evidence of substantial on-the-job search costs. Next, I relax the assumption that workers know the distribution of earnings. In a model where workers learn about the wage distribution from wage offers, I find that 75% lower on-the-job search costs match the empirical data. Chapter 3 documents three problems associated with measuring the wage gains from internal migration. First, earnings losses associated with job displacement may overwhelm gains from migration when different types of job separations are pooled. Second, even in a sample of workers that quit, temporary losses in job specific human capital can dominate migration gains. Third, I find large heterogeneity in the outcomes for workers that quit their jobs. I employ quantile fixed effect estimation and examine how the entire distribution of earnings differs for quitters that move and quitters that stay in the same location. I show that the effect at the lower tail of the distribution is positive, but the effect for the rest of the distribution varies. 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I utilize a novel technique, quantile fixed effect regression, in order to examine how the overall distribution of earnings changes while controlling for unobserved heterogeneity in worker quality. I find that while mean income falls by approximately 22% in the year of displacement, displacement does not affect all workers equally. The 5th percentile of the income distribution falls 45%. Much of the negative mean effect is accounted for by a small group of displaced workers who end up with poor job matches. In contrast, 39% of workers experience income gains following displacement. Chapter 2 simulates an on-the-job search model to match the finding that 39% of workers earn more after displacement. I first examine an on-the-job search model under the assumption that workers know the distribution of earnings and I find evidence of substantial on-the-job search costs. Next, I relax the assumption that workers know the distribution of earnings. In a model where workers learn about the wage distribution from wage offers, I find that 75% lower on-the-job search costs match the empirical data. Chapter 3 documents three problems associated with measuring the wage gains from internal migration. First, earnings losses associated with job displacement may overwhelm gains from migration when different types of job separations are pooled. Second, even in a sample of workers that quit, temporary losses in job specific human capital can dominate migration gains. Third, I find large heterogeneity in the outcomes for workers that quit their jobs. I employ quantile fixed effect estimation and examine how the entire distribution of earnings differs for quitters that move and quitters that stay in the same location. I show that the effect at the lower tail of the distribution is positive, but the effect for the rest of the distribution varies. 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