Two-Step And Related Estimators In Contemporary Rational-Expectations Models: An Analysis Of Small-Sample Properties

This article examines the performance of ordinary least squares, generalized least squares, and Pagan’s (1986) double-length estimator (DLE) in several rational-expectations models. The three approaches are equivalent in the simplest of models but may differ appreciably in models typically encountered in applied work. Small-sample properties of the estimators are examined in several contemporary macroeconomic models. The following conclusions are reached: (a) All estimators exhibit similar sampling distributions in a monetary-neutrality framework, (b) the least squares procedures maintain smaller sampling variance and deliver more reliable tests in a permanent- income model in very small samples, (c) DLE generally delivers superior performance in a nonlinear aggregate-supply model with unanticipated “shock” regressors, and (d) overall, DLE outperforms the LS alternatives except in the smallest of samples.