Simplified Implementation of the Heckman Estimator of the Dynamic Probit Model and a Comparison with Alternative Estimators*

This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynamic random effects probit model and other dynamic nonlinear panel data models using standard software. It then compares the estimators proposed by Heckman, Orme and Wooldridge, based on three alternative approximations, first in an empirical model for the probability of unemployment and then in a set of simulation experiments. The results indicate that none of the three estimators dominates the other two in all cases. In most cases, all three estimators display satisfactory performance, except when the number of time periods is very small.     

Gender and ethnic differences in factors that influence food intake

Abstract The objective of this research was to ascertain the gender-and ethnic-related factors that influence what one eats. This survey was conducted using a validated, pilot-tested questionnaire in 11 states and the District of Columbia, which were participating in the W-182 Western Regional Research project. The results indicated that the factors that influence what one eats differ by gender and ethnicity. Men were very much influenced by likes and dislikes, and by their spouse or significant other. Women were influenced by likes and dislikes, and health. Food likes/dislikes and concerns about health and weight were among the leading four factors for all ethnic groups. Food likes/dislikes were the top factor influencing what is eaten by 51% or more of Asians, Pacific Islanders, Caucasians and Hispanics. Concern about health was the top factor for 62% and 58%, respectively, of African Americans and Native Americans.