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We estimate and report life-cycle transition probabilities between employment, unemployment and inactivity for male and female workers using Current Population Survey monthly files. We assess the relative importance of each probability in explaining the life-cycle profiles of participation and unemployment rates using a novel decomposition method. A key robust finding is that most differences in participation and unemployment over the life-cycle can be attributed to the probability of leaving employment and the probability of transiting from inactivity to unemployment, while transitions from unemployment to employment (the job finding probability) play secondary roles. We conclude that search models that seek to explain life-cycle work patterns should not ignore transitions to and from inactivity.
Although the link between household size and consumption has a strong empirical support, there is no consistent way in which demographics are dealt with in standard life-cycle models. We study the relationship between the predictions of the Single Agent model (the standard in the literature) versus a simple model extension where deterministic changes in household size and composition affect optimal consumption decisions. We provide theoretical results comparing both approaches and quantify the differences in predictions across models.
Artículo de publicación ISIWe estimate life-cycle transition probabilities among employment, unemployment and inactivity for US workers. We assess the importance of each worker flow to account for participation and unemployment rates over the life cycle. We find that inactivity exit and entry matter but the empirically relevant margins defy conventional wisdom: high youth unemployment is due to high employment exit probabilities, while low labour force entry probabilities substantially account for low participation and unemployment among older workers. Our results remain intact under several forms of heterogeneity, time-aggregation bias and misclassification errors.Spanish Ministry of Economy and Competitiveness
ECO2012-32392
Severo Ochoa Programme for Centres of Excellence in RD
SEV-2011-0075
Fondecyt
1120593
1111045
We use online job board data to document novel facts regarding unemployment and on-the-job searches. We define a relevant set of job ads using the bipartite network between ads and applicants and show how applications are affected by demographics such as gender, age, and marital status as well as timing variables like unemployment duration, job tenure, and cyclical conditions. We also study the selective margin, i.e., how the posted-expected wage gap and the applicant fit into ad requirements such as education, experience, location, and occupation affect applications. This evidence can help discipline current and future search theories.
JEL Codes: E24, J40, J64
We use an unusually rich data from a Chilean job board to document novel facts regarding job search for unemployed and employed seekers. We show how application behavior is influenced by (1) demographics such as gender, age, and marital status, (2) alignment between applicant wage expectations and wage offers, (3) applicant fit into ad requirements such as education, experience, job location and occupation (4) timing variables, including unemployment duration, job tenure (for on-the-job searchers) and business cycle conditions. This empirical evidence can discipline current and future search-theoretical frameworks.
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