System GMM Estimation With A Small Sample

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System GMM Estimation With A Small Sample

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Marcelo Soto ()

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Marcelo Soto

Abstract

Properties of GMM estimators for panel data, which have become very popular in the empirical economic growth literature, are not well known when the number of individuals is small. This paper analyses through Monte Carlo simulations the properties of various GMM and other estimators when the number of individuals is the one typically available in country growth studies. It is found that, provided that some persistency is present in the series, the system GMM estimator has a lower bias and higher efficiency than all the other estimators analysed, including the standard first-differences GMM estimator.

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Publisher Info
Paper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 780.09.

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Length: 27
Date of creation: 01 Sep 2009
Date of revision:
Handle: RePEc:aub:autbar:780.09

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
O11 - Economic Development, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

This paper has been announced in the following NEP Reports:

NEP-ALL-2009-09-05 (All new papers)
NEP-ECM-2009-09-05 (Econometrics)

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This page was last updated on 2009-12-4.

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