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Nonlinear models and small sample performance of the generalized method of moments

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Abstract

In this paper I explore the issue of nonlinearity (both in the data generation process and in the functional form that establishes the relationship between the parameters and the data) regarding the poor performance of the Generalized Method of Moments (GMM) in small samples. To this purpose I build a sequence of models starting with a simple linear model and enlarging it progressively until I approximate a standard (nonlinear) neoclassical growth model. I then use simulation techniques to find the small sample distribution of the GMM estimators in each of the models.

Suggested Citation

  • Eva Ventura, 1996. "Nonlinear models and small sample performance of the generalized method of moments," Economics Working Papers 186, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:186
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    More about this item

    Keywords

    GMM; small sample; simulation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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