The Sensitivity of Productivity Estimates
Researchers interested in estimating productivity can choose from an array of methodologies, each with its strengths and weaknesses. This study compares productivity estimates and evaluates the extent to which the conclusions of three important productivity debates in the economic development literature are sensitive to the choice of estimation method. Five widely used techniques are considered, two nonparametric and three parametric: index numbers, data envelopment analysis, instrumental variables estimation, stochastic frontiers, and semiparametric estimation. Using data on manufacturing firms in two developing countries, Colombia and Zimbabwe, we find that the different methods produce surprisingly similar productivity estimates when the measures are compared directly, even though the estimated input elasticities vary widely. Furthermore, the methods reach the same conclusions on two of the debates, supporting endogenous growth effects and showing that firm-level productivity changes are an important contributor to aggregate productivity growth. On the third debate, only with the parametric productivity measures is there evidence of learning by exporting.
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Volume (Year): 26 (2008)
Issue (Month): ()
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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.:
- R Blundell & Steven Bond, .
"Initial conditions and moment restrictions in dynamic panel data model,"
W14&104., Economics Group, Nuffield College, University of Oxford.
- Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
- Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
- Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
- Acemoglu, D. & Zilibotti, F., 1998.
660, Stockholm - International Economic Studies.
- Acemoglu, Daron & Zilibotti, Fabrizio, 2000. "Productivity Differences," CEPR Discussion Papers 2498, C.E.P.R. Discussion Papers.
- Acemoglu, Daron & Zilibotti, Fabrizio, 1998. "Productivity Differences," Seminar Papers 660, Stockholm University, Institute for International Economic Studies.
- Daron Acemoglu & Fabrizio Zilbotti, 1999. "Productivity Differences," NBER Working Papers 6879, National Bureau of Economic Research, Inc.
- Andrew B. Bernard & J. Bradford Jensen, 1997.
"Exceptional Exporter Performance: Cause, Effect, or Both?,"
NBER Working Papers
6272, National Bureau of Economic Research, Inc.
- Bernard, Andrew B. & Bradford Jensen, J., 1999. "Exceptional exporter performance: cause, effect, or both?," Journal of International Economics, Elsevier, vol. 47(1), pages 1-25, February.
- Bernard, A., 1997. "Exceptional Exporter Performance: Cause, Effect, or Both?," Working papers 97-21, Massachusetts Institute of Technology (MIT), Department of Economics.
- Erik Brynjolfsson & Lorin M. Hitt, 2003.
"Computing Productivity: Firm-Level Evidence,"
The Review of Economics and Statistics,
MIT Press, vol. 85(4), pages 793-808, November.
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
- Richard Blundell & Stephen Bond, 2000.
"GMM Estimation with persistent panel data: an application to production functions,"
Taylor & Francis Journals, vol. 19(3), pages 321-340.
- 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.
- Aw, Bee Yan & Chen, Xiaomin & Roberts, Mark J., 2001. "Firm-level evidence on productivity differentials and turnover in Taiwanese manufacturing," Journal of Development Economics, Elsevier, vol. 66(1), pages 51-86, October.
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