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Tools of the Trade

Tools of the Trade: Beyond mean decompositions (with an application to the gender wage gap in China)

Jed Friedman's picture

Suppose you were investigating the observed wage gap in urban China, where men are paid approximately 30% more than women. The first thing you would like to know is whether the higher wages paid to men are a result of the greater average years of schooling and years in the labor force that men have or whether, instead, men are paid more even after accounting for education and experience. If the latter situation is the case then the difference in wages may at least in part be due to labor market discrimination.

Tools of the Trade: estimating correct standard errors in small sample cluster studies, another take

Jed Friedman's picture

For many years, researchers have recognized the need to correct standard error estimates for observational dependence within clusters. An earlier post contrasted the typical approach to this matter, the cluster robust standard error (CRSE), and various methods to cluster bootstrap the standard error.

Tools of the Trade: Getting those standard errors correct in small sample cluster studies

Jed Friedman's picture

Some of the earliest posts on this blog concerned the inferential challenges of cluster randomized trials when clusters are few in number (see here and here for two examples of discussion). Today’s post continues this theme with a focus on better practice in the treatment of standard errors.