Document Type


Date of Degree


Degree Name

PhD (Doctor of Philosophy)

Degree In


First Advisor

John Geweke

First Committee Member

Kung-Sik Chan

Second Committee Member

Beth Ingram

Third Committee Member

George Neumann

Fourth Committee Member

Elena Pastorino


This dissertation quantitatively evaluates selected labor market policies in a search-matching model with skill heterogeneity where high-skilled workers can take temporary jobs with skill requirements below their skill levels. The joint posterior distribution of structural parameters of the theoretical model is obtained conditional on the data on labor markets histories of the NLSY79 respondents. The information on AFQT scores of individuals and the skill requirements of occupations is utilized to identify the skill levels of workers and complexity levels of jobs in the job-worker matches realized in the data. The model and the data are used to simulate the posterior distributions of impacts of labor market policies on the endogenous variables of interest to a policy-maker, including unemployment rates, durations and wages of low- and high-skilled workers. In particular, the effects of the following policies are analyzed: increase in proportion of high-skilled workers, subsidies for employing or hiring high- and low-skilled workers and increase in unemployment income.


Bayesian Inference, Matching Models, MCMC, NLSY79


ix,135 pages


Includes bibliographical references (pages 133-135).


Copyright 2007 Olena Stavrunova

Included in

Economics Commons