Estimation of fixed effects dynamic panel data models: linear differencing or conditional expectation

This is the authors' abstract. We don't add key points for this paper.

This note discusses the pros and cons of using the conditional mean approach of Mundlak and Chamberlain and the linear difference approach to deal with the incidental parameters issue in estimating fixed effects dynamic panel data models. The importance of the data generating process of the explanatory variables and the proper treatment of initial values for either approach to get asymptotically unbiased estimators are demonstrated both analytically and through Monte Carlo studies.