The impacts of industry wage premiums and education levels on gender inequality : evidence from five developed countries

In contrast to most prior studies of gender inequality focusing on a specific country or a specific year, this paper uses cross-nationally comparable data from the Luxembourg Income Study (LIS) to examine the impacts of wage premiums in male- and female-dominated industries and education levels on gender inequality in five developed countries- the United States, the United Kingdom, Germany, Ireland, and Belgium from 2004 to 2017. To the best of our knowledge, there are no attempts in the prior empirical literature studying the effects of wage premiums in male- and female-dominated industries on gender inequality. To guarantee continuity and stability, we run the regression year by year separately for 14 consecutive periods for each of five advanced countries. The timeline covers the before, during, and after the great recession to rule out the possible effects of historical contingency. Thus, this is the first empirical paper to investigate the causal relationship between male- and female-dominated industries and gender inequality across counties over a continuous period. We raise and answer three research questions: (1) Do the wage premiums among male- and female-dominated industries affect the gender wage gap? (2) Is there a cross-country variation in the relationship between education levels and the gender wage gap? (3) Is there an impact of education levels on the gender employment gap? As for empirical analysis, for the first two questions, we run the multivariate linear regression; for the third question, we estimate the probit model, marginal effects, and the delta method standard errors. We find that: 1) There is a significant correlation between the wage premiums in female- and male-dominated industries and gender wage gap; 2) There is a crosscountry variation in the relationship between education levels and the gender wage gap; 3) There is also a cross-country variation in the relationship between education levels and the gender employment gap.