Direct and indirect effects in a logit model

In this article, I discuss a method by Erikson et al. (2005, Proceedings of the National Academy of Science 102: 9730–9733) for decomposing a total effect in a logit model into direct and indirect effects. Moreover, I extend this method in three ways. First, in the original method the variable through which the indirect effect occurs is assumed to be normally distributed. In this article, the method is generalized by allowing this variable to have any distribution. Second, the original method did not provide standard errors for the estimates. In this article, the bootstrap is proposed as a method of providing those. Third, I show how to include control variables in this decomposition, which was not allowed in the original method. The original method and these extensions are implemented in the ldecomp command. Copyright 2010 by StataCorp LP.