Abstract
GMM estimators are now widely used in econometric and financial analysis. Their asymptotic properties are well known, but we have little knowledge of their small sample properties or their rate of convergence to their limiting distribution. This paper reports small sample Monte Carlo evidence which helps discriminate between the many GMM estimators proposed in the literature. We add a new GMM estimator which delivers better finite sample properties. We also test whether biases in the parameter estimates are either significant or significantly different between estimators. We conclude that they are, with both relative and absolute biases depending on sample size, fitting criterion, non-normality of disturbances, and parameter size.
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© 1994 Springer Science+Business Media Dordrecht
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Hallett, A.J.H., Ma, Y. (1994). On the Accuracy and Efficiency of GMM Estimators: A Monte Carlo Study. In: Belsley, D.A. (eds) Computational Techniques for Econometrics and Economic Analysis. Advances in Computational Economics, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8372-5_2
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DOI: https://doi.org/10.1007/978-94-015-8372-5_2
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4290-3
Online ISBN: 978-94-015-8372-5
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