Characteristics and Heterogeneity of the Impact of r&d Subsidies

Author/s Marusca De Castris, Guido Pellegrini
Publishing Year 2015 Issue 2015/3 Suppl. Language Italian
Pages 19 P. 61-79 File size 193 KB
DOI 10.3280/SCRE2015-S03004
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The aim of this study is to measure the influence of different firm characteristics on the impact of the policy instruments, that can be heterogeneous. The empirical analysis is based on the policy instruments directed to subsidize private projects on R&D in Italy. We develop a new methodological framework for testing if firm characteristics can modify the sign and the level of the effects of public policy; we use a counterfactual approach and nonparametric methods able to identify and test the presence of heterogeneity of the effects compared to some specific dimensions of analysis. The results show that, although overall the policy instruments have modest efficacy, some features, such as to be an exporting firms or to have a internal research unit, affect the magnitude of the effects of the intervention.

Keywords: R&d; subsidies; heterogeneous treatment effects

Jel codes: L52, O31, O38

  1. Angrist J., 2004, «Treatment Effect Heterogeneity in Theory and Practice». Economic Journal, 114, 494: C52-C83. DOI: 10.1111/j.0013-0133.2003.00195.x
  2. Becker S.O., Ichino A., 2002, «Estimation of Average Treatment Effects Based on Propensity Scores». The Stata Journal, 2, 4: 358-377.
  3. Becker S.O., Egger P.H., von Ehrlich M., 2013, «Absorptive Capacity and the Growth and Investment Effects of Regional Transfers: A Regression Discontinuity Design with Heterogeneous Treatment Effects». American Economic Journal: Economic Policy, 5, 4: 29-77. DOI: 10.1257/pol.5.4.29.
  4. Brand J.E., Xie Y., 2010, «Who Benefits Most From College? Evidence for Negative Selection in Heterogeneous Economic Returns to Higher Education». American Sociological Review, 75, 2: 273-302. DOI: 10.1177%2F0003122410363567
  5. Bronzini R., Iachini E., 2014, «Are Incentives for r&d Effective? Evidence from a Regression Discontinuity Approach». American Economic Journal: Economic Policy, 6, 4: 100-134. DOI: 10.1257/pol.6.4.100
  6. Brownie C., Boos D.D., Hughes-Oliver J. 1990, «Modifying the t and anova F Tests when Treatment is Expected to Increase Variability Relative to Controls ». Biometrics, 46, 1: 259-266. DOI: 10.2307/2531650
  7. Cerulli G., Poti B., 2008, Evaluating the Effect of Public Subsidies on firm r&d Activity: An Application to Italy Using the Community Innovation Survey. Ceris-Cnr, W.P. n. 9.
  8. Crump R., Hotz V., Imbens G.W., Mitnik O.A., 2008, «Non Parametric Tests for Treatment Effect Heterogeneity». The Review of Economics and Statistics, 90, 3: 389-405. DOI: 10.3386/t0324
  9. David P.A., Hall B., Toole A., 2000, «Is Public r&d a Complement or Substitute for Private r&d? A Review of the Econometric Evidence». Research Policy, 29, 4-5: 497-529. DOI: 10.3386/w7373
  10. De Blasio G., Fantino D., Pellegrini G., 2014, «Evaluating the Impact of Innovation Incentives: Evidence from an Unexpected Shortage of Funds». Industrial and Corporate Change. DOI: 10.1093/icc/dtu027
  11. Djebbari H., Smith J., 2008, «Heterogeneous Impacts in progresa». Journal of Econometrics, 145, 1-2: 64-80. DOI: 10.1016/j.jeconom.2008.05.012
  12. Fantino D., Cannone G., 2013, Evaluating the Efficacy of European Regional Funds for r&d. Banca d’Italia: Temi di Discussione n. 902, February.
  13. Fink G., McConnell M., Vollmer S., 2010, «Testing for Heterogeneous Treatment Effects in Experimental Data: False Discovery Risks and Correction Procedures». Journal of Development Effectiveness, 6, 1: 44-57. DOI: 10.1080/19439342.2013.875054
  14. Merito M., Giannangeli S., Bonaccorsi A., 2007, «Gli incentivi per la ricerca e lo sviluppo industriale stimolano la produttivita della ricerca e la crescita delle imprese?». l’Industria, 27, 2: 221-241. DOI: 10.1430/24638
  15. Rosenbaum P., Rubin D., 1983, «The Central Role of the Propensity Score in Observational Studies for Causal Effects». Biometrika, 70, 1: 41-55. DOI: 10.1093/biomet/70.1.41
  16. Rosenbaum P., Rubin D., 1985, «Constructing a Control Group Using Multivariate Matched Sampling Methods that Incorporate the Propensity Score». The American Statistician, 39, 1: 33-38. DOI: 10.1080/00031305.1985.10479383
  17. Rubin D., 1974, «Estimating Causal Effects of Treatements in Randomized and Nonrandomized Studies». Journal of Educational Psychology, 66, 5: 688-701. DOI: 10.1037/h003735

Marusca De Castris, Guido Pellegrini, Caratteristiche delle imprese ed eterogeneità degli effetti degli incentivi alla r&s in "SCIENZE REGIONALI " 3 Suppl./2015, pp 61-79, DOI: 10.3280/SCRE2015-S03004