This course in panel data econometrics, presented mainly from a microeconometrics perspective, will cover linear and nonlinear panel data models with unobserved heterogeneity, including discussions of the strengths and weaknesses of the various estimation methods.
Basic estimation methods include random effects, correlated random effects, fixed effects, and first differencing. Instrumental variables estimation of models without strictly exogenous explanatory variables will also be covered, including those that contain contemporaneously endogenous variables and those that contain lagged dependent variables. Estimation of linear models with heterogeneous trends and heterogeneous slopes will also be covered. Special considerations with unbalanced panels will be discussed, including how to test for sample selection and attrition bias.
We will also cover how one does inference for large-T panels with cross-sectional correlation. The final topic is nonlinear panel data models for binary, fractional, and nonnegative responses.
The statistical package Stata will be used to illustrate the methods during lectures and in obtaining hands-on experience during the practical work.
Participants should have good working knowledge of ordinary least squares and two stage least squares in a cross-sectional environment, at the level of the “Introductory Microeconometrics” training course.
The course will be presented at a level below my book Econometric Analysis of Cross Section and Panel Data, second edition. MIT Press, 2010.