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Modelling and measuring the effects of public subsidies on business R&D: theoretical and econometric issues

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Author Info
Cerulli Giovanni () (Ceris - Institute for Economic Research on Firms and Growth, Rome, Italy)

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Abstract

It is the aim of this paper to review the principal econometric models used so far to measure the effect of government’s support to private R&D expenditure; in order to reach this task, we first present a basic theoretical framework to identify the effects of public subsidies on business R&D, going on by extending it to the case of dynamic complementarities and presence of subsidy spillovers. The review of the econometric models, the core of the paper, starts from section 4. We first classify econometric models according to three dimensions: 1. structural (based on a system of equations) and non-structural (based on a reduced-form equation and, possibly, a counterfactual) models; 2. models using the subsidy variable in a continuous or in a binary form; and finally, 3. studies exploiting a cross-section versus a longitudinal (panel data) structure. The final part of the paper is an original contribution providing some guidelines to implement R&D policy evaluation in a dynamic subsidization setting.

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Publisher Info
Paper provided by Institute for Economic Research on Firms and Growth - Moncalieri (TO) in its series CERIS Working Paper with number 200803.

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Length: 49 pages
Date of creation: Jun 2008
Date of revision:
Handle: RePEc:csc:cerisp:200803

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Related research
Keywords: business R&D; public incentives; econometric evaluation; dynamic treatment;

Find related papers by JEL classification:
O32 - Economic Development, Technological Change, and Growth - - Technological Change - - - Management of Technological Innovation and R&D
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
O38 - Economic Development, Technological Change, and Growth - - Technological Change - - - Government Policy

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References listed on IDEAS
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  1. Klette, Tor Jakob & Moen, Jarle & Griliches, Zvi, 2000. "Do subsidies to commercial R&D reduce market failures? Microeconometric evaluation studies1," Research Policy, Elsevier, vol. 29(4-5), pages 471-495, April. [Downloadable!] (restricted)
    Other versions:
  2. James J. Heckman & Sergio Urzua & Edward J. Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," NBER Working Papers 12574, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  3. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  4. Xulia González & Jordi Jaumandreu & Consuelo Pazo, 2005. "Barriers to Innovation and Subsidy Effectiveness," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 930-949, Winter.
  5. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February. [Downloadable!] (restricted)
    Other versions:
  6. DUGUET Emmanuel, 2004. "Are R&D subsidies a substitute or a complement to privately funded R&D? Evidence from France using propensity score methods for non- experimental data," Public Economics 0411007, EconWPA. [Downloadable!]
  7. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, 08. [Downloadable!] (restricted)
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  9. Heshmati, Almas & Loof, Hans, 2005. "The Impact of Public Funds on Private R&D Investment: New Evidence from a Firm Level Innovation Study," Discussion Papers 11862, MTT Agrifood Research Finland. [Downloadable!]
  10. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-59, July. [Downloadable!] (restricted)
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  11. Paul A. David & Bronwyn H. Hall, 2000. "Heart of Darkness: Modeling Public-Private Funding Interactions Inside the R&D Black Box," NBER Working Papers 7538, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  12. M. Ishaq Nadiri, 1993. "Innovations and Technological Spillovers," NBER Working Papers 4423, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  13. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November. [Downloadable!]
  14. Martin, Stephen & Scott, John T., 2000. "The nature of innovation market failure and the design of public support for private innovation," Research Policy, Elsevier, vol. 29(4-5), pages 437-447, April. [Downloadable!] (restricted)
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  15. Michael Lechner, 1999. "Identification and Estimation of Causal Effects of Multiple Treatments Under the Conditional Independence Assumption," IZA Discussion Papers 91, Institute for the Study of Labor (IZA). [Downloadable!]
  16. Nadiri, M.I., 1993. "Innovations and Technological Spillovers," Working Papers 93-31, C.V. Starr Center for Applied Economics, New York University. [Downloadable!]
  17. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages S71-102, October. [Downloadable!] (restricted)
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