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R&D and productivity: Estimating production functions when productivity is endogenous

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Author Info
Doraszelski, Ulrich
Jaumandreu, Jordi

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Abstract

We develop a simple estimator for production functions in the presence of endogenous productivity change that allows us to retrieve productivity and its relationship with R&D at the firm level. Our dynamic investment model can be viewed as a generalization of the knowledge capital model (Griliches 1979) that has remained a cornerstone of the productivity literature for more than 25 years. We relax the assumptions on the R&D process and examine the impact of the investment in knowledge on the productivity of firms. We illustrate our approach on an unbalanced panel of more than 1800 Spanish man- ufacturing firms in nine industries during the 1990s. Our ¯ndings indicate that the link between R&D and productivity is subject to a high degree of uncertainty, nonlinearity, and heterogeneity across firms. Abstracting from uncertainty and nonlinearity, as is done in the knowledge capital model, or assuming an exogenous process for productiv- ity, as is done in the recent literature on structural estimation of production functions, overlooks some of its most interesting features.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1246.

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Date of creation: 2006
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Handle: RePEc:pra:mprapa:1246

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Keywords: production function knowledge capital productivity R&D

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O3 - Economic Development, Technological Change, and Growth - - Technological Change

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  2. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January. [Downloadable!] (restricted)
  3. Ornaghi, Carmine, 2006. "Spillovers in product and process innovation: Evidence from manufacturing firms," International Journal of Industrial Organization, Elsevier, vol. 24(2), pages 349-380, March. [Downloadable!] (restricted)
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  9. Griffith, Rachel & Harrison, Rupert & Van Reenen, John, 2004. "How Special is the Special Relationship? Using the Impact of US R&D Spillovers on UK Firms as a Test of Technology Sourcing," CEPR Discussion Papers 4698, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  10. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-54, July. [Downloadable!] (restricted)
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  12. Rachel Griffith & Stephen Redding & John Van Reenen, 2000. "Mapping the two faces of R&D: productivity growth in a panel of OECD industries," IFS Working Papers W00/02, Institute for Fiscal Studies. [Downloadable!]
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  13. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Blackwell Publishing, vol. 70(2), pages 317-341, 04. [Downloadable!] (restricted)
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  14. Juan J Dolado & Carlos Garcia--Serrano & Juan F. Jimeno, 2002. "Drawing Lessons From The Boom Of Temporary Jobs In Spain," Economic Journal, Royal Economic Society, vol. 112(721), pages F270-F295, June. [Downloadable!] (restricted)
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  15. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June. [Downloadable!] (restricted)
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  17. Pavcnik, Nina, 2002. "Trade Liberalization, Exit, and Productivity Improvement: Evidence from Chilean Plants," Review of Economic Studies, Blackwell Publishing, vol. 69(1), pages 245-76, January.
  18. Huergo, Elena & Jaumandreu, Jordi, 2004. "Firms' age, process innovation and productivity growth," International Journal of Industrial Organization, Elsevier, vol. 22(4), pages 541-559, April. [Downloadable!] (restricted)
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