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

  • César Alonso-Borrego

    ()

  • Rocío Sánchez-Mangas

    ()

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. Jacques Mairesse & Bronwyn H. Hall & Benoit Mulkay, 1999. "Firm-Level Investment in France and the United States: An Exploration of What We Have Learned in Twenty Years," NBER Working Papers 7437, National Bureau of Economic Research, Inc.
  2. 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.
  3. 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, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  4. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  5. 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.
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