Finite-Sample Properties of Some Alternative GMM Estimators
- 1 July 1996
- journal article
- research article
- Published by Taylor & Francis in Journal of Business & Economic Statistics
- Vol. 14 (3), 262-280
- https://doi.org/10.1080/07350015.1996.10524656
Abstract
We investigate the small-sample properties of three alternative generalized method of moments (GMM) estimators of asset-pricing models. The estimators that we consider include ones in which the weighting matrix is iterated to convergence and ones in which the weighting matrix is changed with each choice of the parameters. Particular attention is devoted to assessing the performance of the asymptotic theory for making inferences based directly on the deterioration of GMM criterion functions.Keywords
All Related Versions
This publication has 33 references indexed in Scilit:
- Finite sample properties of the generalized method of moments in tests of conditional asset pricing modelsJournal of Financial Economics, 1994
- Asset Prices in an Exchange Economy with Habit FormationEconometrica, 1991
- Habit persistence and durability in aggregate consumption: Empirical testsJournal of Financial Economics, 1991
- Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: An Empirical AnalysisJournal of Political Economy, 1991
- Habit Formation: A Resolution of the Equity Premium PuzzleJournal of Political Economy, 1990
- Estimating Models with Intertemporal Substitution Using Aggregate Time Series DataJournal of Business & Economic Statistics, 1990
- A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice under UncertaintyThe Quarterly Journal of Economics, 1988
- Modeling the term structure of interest rates under non-separable utility and durability of goodsJournal of Financial Economics, 1986
- Evaluation of the Distribution Function of the Limited Information Maximum Likelihood EstimatorEconometrica, 1982
- The Fitting of Time-Series ModelsRevue de l'Institut International de Statistique / Review of the International Statistical Institute, 1960