Bootstrapping statistical inferences of decomposition methods for gender earnings differentials

Applying the standard bootstrapping technique with corrections for heteroskedasticity for a sample of the 1997 Urban Household Survey in China, the present article attempts to test (1) whether the commonly used decomposition methods for gender earnings differentials give significantly different results and (2) whether the explained component is significantly different from the unexplained component (which is commonly referred to as discrimination) within each decomposition method. Based on a national data set, the empirical results indicated some significant differences in both tests. The implication of the results is that the proposed bootstrapping technique can be regarded as a guideline on applying which approach to decompose gender earnings differentials among different methods without losing important information, and on evaluating the relative importance of the decomposition components for any chosen method.