No abstract

I show how to identify and estimate the average partial effect of explanatory variables in a model where unobserved heterogeneity interacts with the explanatory variables and may be unconditionally correlated with the explanatory variables. To identify the population-averaged effects, I use extensions of ignorability assumptions that are used for estimating linear models with additive heterogeneity and for estimating average treatment effects. New estimators are obtained for estimating the unconditional average partial effect as well as the average partial effect conditional on functions of observed covariates.

This paper shows that the bootstrap does not consistently estimate the asymptotic distribution of the maximum score estimator. The theory developed also applies to other estimators within a cube-root convergence class. For some single-parameter estimators in this class, the results suggest a simple method for inference based upon the bootstrap. Copyright The Econometric Society 2005.

We offer evidence of gender selection within the United States. Analysis of comprehensive birth data shows unusually high boy-birth percentages after 1980 among later children (most notably third and fourth children) born to Chinese and Asian Indian mothers. Based upon linked data from California, Asian Indian mothers are found to be significantly more likely to have a terminated pregnancy and to give birth to a boy when they have previously only given birth to girls. The observed boy-birth percentages are consistent with over 2,000 "missing" Chinese and Indian girls in the United States between 1991 and 2004. (JEL J11, J16)