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Gmm Estimation Of A Production Function With Panel Data: An Application To Spanish Manufacturing Firms

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César Alonso-Borrego ()
Rocío Sánchez-Mangas ()

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Abstract

In this paper we consider the estimation of a Cobb-Douglas production function using a panel dataset of Spanish manufacturing firms. As it is stressed in the econometric literature, the use of standard GMM first differences estimators to eliminate the unobserved firm-specific effects may yield imprecise estimates, particularly in the case of the estimation of the production function. The reason is that the high persistence of output and inputs involved in the estimation of production functions make that their lagged levels to be weak instruments for the first differences of these series. The extended GMM estimator proposed by Arellano and Bover (1995) considers further orthogonality conditions based on lagged differences as instruments for the equation in levels. This approach has been applied to the estimation of technological parameters by Blundell and Bond (1999). Our estimation results, based on this approach, confirm the better performance of the extended GMM estimator compared to the standard first-differenced GMM estimator

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws015527.

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Date of creation: Dec 2001
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Handle: RePEc:cte:wsrepe:ws015527

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  1. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Blackwell Publishing, vol. 58(2), pages 277-97, April. [Downloadable!] (restricted)
  2. Bronwyn H. Hall & Jacques Mairesse & Benoit Mulkay & Jacques Mairesse, 1999. "Firm Level Investment in France and the United States: An Exploration of What We Have Learned in Twenty Years," Econometrics 9902001, EconWPA. [Downloadable!]
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  3. Richard Blundell & Steve Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies. [Downloadable!]
  4. Richard Blundell & Steve Bond, 1999. "GMM estimation with persistent panel data: an application to production functions," IFS Working Papers W99/04, Institute for Fiscal Studies. [Downloadable!]
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Rocío Sánchez-Mangas, 2001. "Estimation Of A Dynamic Discrete Choice Model Of Irreversible Investment," Statistics and Econometrics Working Papers ws015628, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
  2. Housung Jung & Hyeog Ug Kwon, 2007. "An Alternative System GMM Estimation in Dynamic Panel Models," Hi-Stat Discussion Paper Series d07-217, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
  3. Álvaro Escribano Sáez & Rodolfo Stucchi, 2008. "Catching up in total factor productivity through the business cycle : evidence from Spanish manufacturing surveys," Economics Working Papers we085125, Universidad Carlos III, Departamento de Economía. [Downloadable!]
  4. Aguirregabiria, Victor, 2009. "Econometric Issues and Methods in the Estimation of Production Functions," MPRA Paper 15973, University Library of Munich, Germany. [Downloadable!]
  5. Carmine Ornaghi, 2006. "Assessing the effects of measurement errors on the estimation of production functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 879-891. [Downloadable!]
  6. Rocío Sánchez-Mangas, 2002. "Pseudo-Maximum Likelihood Estimation Of A Dynamic Structural Investment Model," Statistics and Econometrics Working Papers ws026218, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
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