- Publicado: 21 Febrero 2014
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This course provides a thorough analytical and experimental analysis of the qualities of inference when modeling dynamic and possibly simultaneous relationships on the basis of panel data. The focus is on establishing causal relationships for non- discrete dependent variables on the basis of short balanced panels of independent individual cross-section units (small T, moderate or large N). For such micro- econometric panels the (non)stationarity of the time-series is not an issue, but certain aspects of the initial conditions of the involved dynamic processes certainly are. Special attention will be paid to specializing GMM (generalized method of moments) inference methods for this type of model, leading to a methodology to classify transformations of both explanatory and non-explanatory variables as either endogenous or potential instruments. The course is supplemented by computer illustrations on the basis of actual empirical data using Stata. In addition, relevant simulation results will be discussed to acquire insights in the contrasts between the limiting and the actual finite sample distributions of parameter estimators and test statistics on the tenability of parametric restrictions and of moment conditions.
