Panel data methods for microeconometrics using Stata

This presentation provides an overview of the subset of methods for panel data and the associated Stata xt commands most commonly used by microeconometricians. First, attention is focused on a short panel, meaning data on many individual units and few time periods. Examples include longitudinal surveys of many individuals and panel datasets on many firms. Then the data can be viewed as being clustered on the individual unit and panel methods used are also applicable to other forms of clustered data such as cross-section data from individual-level surveys conducted at many villages with clustering at the village level. Second, emphasis is placed on using the repeated measures aspect of panel data to estimate key marginal effects that can be interpreted as measuring causation rather than mere correlation. The leading methods assume time-invariant individual-specific effects (or “fixed effects”). Instrumental variables (IV) methods can also be used, with data from periods other than the current year potentially serving as instruments. Third, some analyses use dynamic models rather than static models. Particular interest lies in fitting models with both lagged dependent variables and fixed effects. The paper additionally surveys other panel methods used in econometrics, such as those for nonlinear models and those for dynamic panels with many periods of data.