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Does R&D protect SMEs from the hardness of the cycle? Evidence from Spanish SMEs (1990-2009)

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Abstract

This paper analyses whether undertaking R&D activities allows SMEs to attenuate the negative impact of recessions on productivity. In contrast to other studies we use a firm level indicator of the cycle based on firms’ own perceptions, while total factor productivity is obtained using a control function methodology in which we recognise the potential role that R&D experience might have in shaping future firms’ productivity. The analysis is performed using a representative sample of Spanish SMEs for the period 1990–2009. Results show both that R&D activities render positive productivity returns, and that performing R&D helps to alleviate the negative effects of downturns on productivity. Additionally, R&D seems to have a countercyclical effect upon SME’s productivity over the business cycle, as we find that SMEs R&D productivity premium in recessions doubles that of expansions.

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Fig. 1
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Notes

  1. SMEs account for over 78 % of the employment and 68 % of the value added of the Spanish economy (Eurostat, 2005).

  2. See Griliches (1990), Barlevy (2004) and (Comin and Gertler 2006).

  3. Barlevy (2007) and Aghion et al. (2012).

  4. Ouyang (2011) also claims that the observed pro-cyclicality of R&D is partly due to an aggregation bias.

  5. Similar results are found by Bonha-Padilla et al. (2009) and, at industry level, in Ouyang (2011).

  6. The empirical literature has shown important productivity gains form R&D at macro (Coe and Helpman, 1993), industry (Bernstein 1998; Añón Higón 2007) and firm level (Griliches 1980). See Hall et al. (2010) for a survey.

  7. Moreover, R&D activities are the essence of survival since only those companies that are able to successfully innovate are able to establish and maintain a competitive advantage in the market (Audretsch and Mahmood 1995).

  8. See http://www.fundacionsepi.es/esee/sp/pesentacion.asp for further details.

  9. We do not use any observation for 1990, as we cannot compute productivity for this year in this survey.

  10. Klepper (1997) in a related but different approach makes a similar point: the firms’ perception of the market might capture the way many industries evolve.

  11. This result should be taken with caution as financial constraints are an important determinant of the relationship between R&D and the cycle, see Aghion et al. (2013), and in this regression we do not take into account whether firms are credit constrained.

  12. As pointed out by De Loecker (2007, 2010) for exporting, this might be an important refinement in the analysis of the effects of performing R&D on productivity.

  13. The law of motion for capital follows a deterministic dynamic process according to which k it  = (1 − δ)k it − 1 + I it − 1. Thus, it is assumed that the capital the firm uses in period t was actually decided in period t-1 (it takes a full production period for the capital to be ordered, received and installed by the firm before it becomes operative). Labour and materials (unlike capital) are chosen in period t, the period they actually get used (and, therefore, they can be a function of ω it ). These timing assumptions make them non-dynamic inputs, in the sense that (and again unlike capital) current choices for them have no impact on future choices.

  14. Both the investment of capital demand function and the demand for intermediate materials are assumed to be strictly increasing in ω it (in the case of the investment of capital this is assumed in the region in which i it  > 0). That is, conditional on k it , a firm with higher ω it optimally invests more (or demands more materials).

  15. Following Doraszelski and Jaumandreu (2013) we group the 20 industries in which the ESEE classifies firms into 10 industries. The aim is to get enough observations to carry out industry-by-industry estimations. The coefficients estimated at industry level are reported in Table 5 in the Appendix.

  16. We lag this variable 2 periods to avoid potential endogeneity problems. Our main conclusions largely hold, however, if we use a dummy variable that takes value 1 if the firm performs R&D in period t-1 (rather than in period t-2). This is also the case if we use a dummy variable that takes the value 1 if the firm declares that in year t-1 (rather than in period t) its main market was in recession.

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Acknowledgment

We acknowledge financial support from Ministerio de Ciencia e Innovación (projects ECO2011-25033, ECO2011-30323-C03-02 and SEJ2010-19088/ECON), the Generalitat Valenciana (project PROMETEO/068), and the "Xarxa de Referència d’R+D+I en Economia i Polítiques Públiques" and the SGR Programme (2009-SGR-322) of the Catalan Government. Usual disclaimers apply.

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Correspondence to Juan A. Mañez.

Appendix

Appendix

Table 5 Production function estimates (by industry)

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Añón-Higón, D., Manjón-Antolin, M., Mañez, J.A. et al. Does R&D protect SMEs from the hardness of the cycle? Evidence from Spanish SMEs (1990-2009). Int Entrep Manag J 11, 361–376 (2015). https://doi.org/10.1007/s11365-014-0329-0

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