Model uncertainty and race and gender heterogeneity in the college entry decision
This paper uses a flexible modeling strategy to examine the roles of measured ability, family characteristics and proxies for secondary schooling quality as determinants of the decision to enter college. While previous work on this topic has been careful to determine which explanatory variables to include when modeling college entry decisions, few studies have been concerned about appropriate distributional assumptions, (i.e. choice of link function). In this paper, I extend my binary choice analysis to the class of Student-t link functions, which enables me to approximately regard the often-used probit and logit models as special cases. Unconditional estimates which average over competing models and integrate out model uncertainty are also obtained. Using NLSY data, I apply these methods and find that the link functions and estimated impacts of ability and family characteristics on the probabilities of enrolling in college are not constant across race and gender groups.
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