Statistical Discrimination, Employer Learning, and Employment Differentials by Race, Gender, and Education
2014/06/24
研討會日期 : 2014-06-24
時間 : 14:30
主講人 : Professor Seik Kim
地點 : Conference Room C103
演講者簡介 : Professor Kim received his Ph.D. in Economics from Yale University at 2008. He is currently an Associate Professor at Korea University. His research fields are Labor Economics, Applied Microeconomics, and Econometrics
演講摘要 : Previous papers on testing for statistical discrimination and employer learning require variables that employers do not observe directly, but are observed by researchers or data on employer-provided performance measures. This paper develops a test that does not rely on these specific variables. The proposed test can be performed with individual-level cross-section data on employment status, experience, and some variables on which discrimination is based, such as race, gender, and education. Evidence from analysis using the March Current Population Survey for 1977-2010 supports statistical discrimination and employer learning. The empirical findings are not explained by alternative hypotheses, such as human capital theory, search and matching models, and the theory of taste-based discrimination.
