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

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Abstract

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.

Original languageEnglish (US)
Pages (from-to)51-61
Number of pages11
JournalJournal of Business and Economic Statistics
Volume9
Issue number1
DOIs
StatePublished - Jan 1991

Keywords

  • Generalized least squares
  • Generated regressors
  • Monte Carlo simulation
  • Nonlinear estimation

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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