Gender Differences of Immigrant Scientists/Engineers Earnings: A Random-Effect Growth Curve Model

Yuying Tong, University of North Carolina at Chapel Hill

In this paper, we employ a random-effect growth curve model on a longitudinal data set of scientists/engineers to model the earning differences between males and females among the immigrant scientists/engineers. Four waves of SESTAT data were arranged into a pooled-cross section time series so that repeated measures of scientists/engineers for each individual in a two-year interval could be used for analysis. Our results show that an unobserved random effect explained nearly 30 percent of the variance on the overall earning differences across individuals. We also find that foreign-born scientists are not necessarily at a disadvantage for both overall earning and earning growth rate. Citizenship status, however, plays a significant role on foreign-born scientists/engineers’ overall earning disadvantage, but not in the growth rate. Although women do experience disadvantages in both overall earning and on earning growth rate, there is no evidence to support the position that foreign-born woman scientists are more disadvantaged than their native counterparts.