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Assessment of the public tools used to promote R&D investment in Spanish SMEs

Abstract

In this paper, we identify the potential determinants of firm R&D to understand the effectiveness of public policies. Our results suggest a considerably low impact of tax credits and public grants on the R&D investment of the Spanish manufacturing firms. Tax credits are mainly considered by large firms that use them as a reduction in the tax burden in the corporate tax, while SMEs use public grants to alleviate financial constraints. This evidence leads to discuss alternatives to the current design of the public policies analyzed.

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Notes

  1. 1.

    Spain has failed to improve its relative position and remains in the group of the moderate innovators according to the EU Innovation Scoreboard (EU 2012). EU Scoreboard data show investment in R&D by the top 1,000 EU companies and places Spain 19th of 27 EU countries in terms of innovation performance.

  2. 2.

    Although, academic and policy makers have made considerable effort in analyzing the input additional effects of public instruments, there is also a growing interest in the study of output additionality (e.g., increase in growth/employment/number of patents) and on behavioral additionality. This is the case when the public tools may induce changes in the firm behavior, or may change the behavior of other firms or institutions toward that firm (e.g., by receiving a type of public support, the government may certify firms and confer a halo or certification effect to private investors and/or banks (see Meuleman and De Maeseneire 2012).

  3. 3.

    Corchuelo and Martínez-Ros (2008) show that tax incentives are little known by Spanish firms and may be used only randomly by SMEs.

  4. 4.

    This latter figure is, for example, slightly higher than the same figure in Germany and lower than the one in Finland where the proportion of R&D investment in terms of GDP is greater in both cases than in Spain.

  5. 5.

    In this group, 46 firms were formed in 1995 or later. In other words, only 6.5 % of the firms that invest less or equal than 10 years are aged fewer than 10. In fact, the average age of firms investing in R & D over 10 years is 37.18. The average age of firms investing < 10 years is 30.19.

  6. 6.

    A value > 100 % can be obtained in those cases where the entire public grant is received in a year although the duration of the investment project is greater than a year.

  7. 7.

    Three alternative estimation techniques are applied to the panel: pooled OLS, IV two-step OLS and two-step GMM first differences. These results are available from the authors upon request.

  8. 8.

    We use the Hausman F test to contrast endogeneity in average productivity, interest rate, external debt, tax credits and public grants, with statistic values (an p values in brackets) of F(1,546) = 1,391.81 [0.00], F(1,487) = 0.67 [0.41], F(1,500) = 1.59 [0.21], F(1,549) = 0.80 [0.37] and F(1,417) = 0.24 [0.63], respectively. The null hypothesis is that these variables are exogenous. This hypothesis can be rejected at the 5 % level in case of average productivity, which implies that average productivity is endogenous.

  9. 9.

    Stock and Yogo (2005) classify a group of instruments as weak, or “performing poorly”, if the bias of IV estimator relative to the bias of the OLS, or alternatively the statistic, could exceed several relative thresholds (in this study we use 10 and 15 % maximal IV size). The instrumental variable estimator relative bias is < 10/15 %.

  10. 10.

    Under the null hypothesis that the instrumental variables are valid, the Hansen test is distributed as a chi square with degrees of freedom equal to the number of over identifying restrictions.

  11. 11.

    From expression (13), we exclude marginal productivity taking into account the possible existence of multicollinearity. Otherwise, the results with this variable were not different from the results presented in Tables 3 and 4. These results are available from the authors upon request.

  12. 12.

    But our evidence differs from Berubé and Mohen (2009) in their analysis, focused on innovation output measures, conclude that firms using tax credits and public grants are more effective than firms using only tax credits, but firm size is not a relevant variable for the analysis.

  13. 13.

    The repealing of this deduction would increase corporate tax revenues in 2013 by 1.5 % (about 280 million Euros).

  14. 14.

    This is a reasonable assumption taken into account the estimations by Meghir et al. (1996), where highly innovative firms face essentially zero adjustment costs.

  15. 15.

    The results for the endogeneity test for average productivity, interest rate, external debt, tax credits and public grants are, respectively, the following: (p values in brackets) F(1,545) = 1,369.92 [0.00], F(1,486) = 0.07 [0.79], F(1,499) = 1.64 [0.20], F(1,548) = 0.54 [0.46], F(1,416) = 0.58 [0.45].

  16. 16.

    The results for the endogeneity test for average productivity, interest rate, external debt, tax credits and public grants are, respectively, the following: (p values in brackets) F(1,537) = 1,350.10 [0.00], F(1,478) = 0.02 [0.88], F(1,491) = 1.24 [0.27], F(1,540) = 0.28 [0.59], F(1,408) = 0.72 [0.39].

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Correspondence to Inmaculada Álvarez-Ayuso.

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Romero-Jordán, D., Delgado-Rodríguez, M.J., Álvarez-Ayuso, I. et al. Assessment of the public tools used to promote R&D investment in Spanish SMEs. Small Bus Econ 43, 959–976 (2014). https://doi.org/10.1007/s11187-014-9575-3

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Keywords

  • R&D
  • Tax credits
  • Public grants
  • Effectiveness
  • Panel data

JEL Classifications

  • C26
  • H32
  • O38
  • L26
  • L60