Small sample properties of estimators of non-linear models of covariance structure

Todd Clark

No 95-01, Research Working Paper from Federal Reserve Bank of Kansas City

Abstract: This study examines the small sample properties of GMM and ML estimators of non-linear models of covariance structure. The study focuses on the properties of parameter estimates and the Hansen (1982) and Newey (1985) model specification test. It use Monte Carlo simulations to consider the properties of estimates for some simple factor models, the Hall and Mishkin (1982) model of consumption and income changes, and a simple Bernanke (1986) decomposition model. This analysis establishes and seeks to explain a number of results. Most importantly, optimally weighted GMM estimation yields some biased parameter estimates, and GMM estimation yields a model specification test with size substantially greater than the asymptotic size.

Keywords: Econometric models; Sampling (Statistics) (search for similar items in EconPapers)
Date: 1995
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Journal Article: Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure (1996)
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