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Assessing the relationship between R&D subsidy, R&D cooperation and absorptive capacity: an investigation on the manufacturing Spanish case

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Abstract

Private companies want to eliminate outgoing spillovers while policymakers seek to maximize them. With subsidized R&D cooperation agreements both agents partially achieve their objectives. For this reason, in Europe, policymakers grant subsidies for R&D activities with the condition of establishing R&D cooperation agreements. This study explores the relationship of complementarity between R&D subsidy, R&D cooperation and absorptive capacity in the context of its contribution to labor productivity of enterprises. The data used comes from the Technological Innovation Panel (PITEC), managed by the Spanish National Statistics Institute. We selected manufacturing companies in the period 2008–2013. We evaluate the existence of complementarity through the systems approach and the interaction approach. The econometric technique that we used to estimate the coefficients of our empirical model was maximum-likelihood random effects. As a consequence of the low absorptive capacity of Spanish manufacturing firms we find that R&D subsidies and R&D cooperation agreements are not complementary variables, i.e., receiving public subsidies as a result of establishing R&D cooperation agreements has a lower impact on productivity than the sum of the individual impacts of R&D cooperation and R&D subsidies. In consequence, this result calls into question the convenience of using subsidized R&D cooperation agreements as a tool for promoting innovation in EU countries as there are notable differences between the companies in these countries in terms of absorption capacity.

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Notes

  1. A large number of R&D cooperation agreements are taking place between companies that have a high potential to take advantage of spillovers generated by other companies. Thus, the partners mutually internalize their outgoing spillovers. In general, it is assumed that non-partner companies do not have such high potential, so they will not be in a position to benefit from spillovers generated by the partners.

  2. In 2009, Spanish R&D intensity was 1.38%, while in Finland, Germany, Austria and France it was 3.93%, 2.82%, 2.79% and 2.21% respectively (European Commission, 2011b). In this study we use R&D intensity as a proxy for absorptive capacity. Many previous studies have used the same proxy variable (e.g. Belderbos et al, 2004a; Cassiman and Veugelers, 2002; Cohen and Levinthal, 1990).

  3. We test the relationship between R&D cooperation and R&D subsidy variables in two different subsamples. One is formed by companies that have low absorptive capacity; the other is formed by companies that have a high capacity for absorption (of course, the concepts “high” and “low” refer to the Spanish reality). Clearly, our hypothesis is unconditional as we assume that the relationship between the variables analysed in both subsamples is that of substitution. Therefore, this substitution relationship is not conditioned by the existence of companies with high or low absorptive capacity.

  4. That is, we assume that the test that analyses the relationship between R&D cooperation and absorptive capacity in the two subsamples constructed from the third variable (companies receiving subsidies and companies not receiving subsidies) is substitutive. Therefore, a priori, in this second hypothesis we assume that the relation analysed is not conditioned by the value of the R&D subsidy variable. Our hypothesis is that the relationship is also unconditionally substitutive.

  5. Originally, our panel data contained 4536 manufacturing companies. However, as our goal is to work with a strongly balanced sample, we eliminated all the incorporations in the PITEC database that took place after 2008 (10 firms) and those companies that disappeared from PITEC between 2009 and 2013 (147 firms). Thus, our panel data set is made up of 4379 firms.

  6. For panel data and linear models, Stata provides five different model estimators. Three of these estimators do not allow suppression of the constant of the model, so they cannot be used in the systems approach. The complementarity tests in the systems approach and the interaction approach of the two other estimators (the ML random-effects and population-average estimators) provide the same results. We expose the corresponding data to the ML random-effects estimator.

  7. The population under analysis is made up of manufacturing companies with very different characteristics. It is therefore necessary to control this diversity (Cassiman and Veugelers, 2006). To this end, we include industry dummies at the two-digit industry classification level. These dummy variables are time invariant. However, invariant regressors are dropped in some models (for example, in GMM for the dynamic panel model and the fixed-effects model) because they are eliminated after first-differencing. Therefore, some models cannot be used to perform the complementarity tests as they do not allow suppression of the constant and/or do not allow the correct specification of our empirical model (that is to say, they cannot incorporate invariant regressors).

  8. From a different perspective, but with similar consequences, Hinloopen (2001) notes that in the case of optimally subsidizing cooperative or non-cooperative R&D, ‘sustaining R&D collaboratives is a redundant industrial policy, all else equal’.

  9. In the field of innovation literature there is a general perception that large companies are better positioned to capture the benefits of R&D cooperation. Larger firms have a greater and better capacity to internalize knowledge-intensive activities (Rammer et al. 2009). Many empirical studies have highlighted that large firms have a higher propensity to cooperate because they have a high absorptive capacity (e.g. Faems et al, 2010; López, 2008). However, it should be noted that this greater absorptive capacity comes mainly from their greater R&D (e.g. Ebersberger and Herstad, 2013).

References

  • Aerts, K., & Czarnitzki, D. (2006). The impact of public R&D-funding in Flanders. Brussels: IWT Study No. 54.

  • Athey, S., & Stern, S. (1998). An empirical framework for testing theories about complementarity in organizational design. Cambridge, MA: National Bureau of Economic Research.

    Book  Google Scholar 

  • Badillo, E. R., & Moreno, R. (2014). Does absorptive capacity determine collaborative research returns to innovation? A geographical dimension. Working Paper 2014/28 1/36, Research Institute of Applied Economics, University of Barcelona, Spain.

  • Bayona-Sáez, C., & García-Marco, T. (2010). Assessing the effectiveness of the Eureka program. Res. Policy, 39(10), 1375–1386.

    Article  Google Scholar 

  • Belderbos, R., Carree, M. A., Diederen, B., Lokshin, B., & Veugelers, R. (2004a). Heterogeneity in R&D cooperation strategies. Int. J. Ind. Organ., 22(8/9), 1137–1263.

    Google Scholar 

  • Belderbos, R., Carree, M., & Lokshin, B. (2004b). Cooperative R&D and firm performance. Res. Policy, 33, 1477–1492.

    Article  Google Scholar 

  • Benfratello, L., & Sembenelli, A. (2002). Research joint ventures and firm level performance. Res. Policy, 31, 493–507.

    Article  Google Scholar 

  • Broekel, T. (2015). Do cooperative research and development (R&D) subsidies stimulate regional innovation efficiency? Evidence from Germany. Reg. Stud., 49(7), 1087–1110.

    Article  Google Scholar 

  • Broekel, T., & Graf, H. (2012). Public research intensity and the structure of German R&D networks: A comparison of 10 technologies. Econ. Innov. New Technol., 21(4), 345–372.

    Article  Google Scholar 

  • Broekel, T., Schimke, A., & Brenner, T. (2011). The effects of cooperative R&D subsidies and subsidized cooperation on employment growth. Working Paper Series in Economics, No. 34.

  • Busom, I. (2000). An empirical evaluation of the effects of R&D subsidies. Econ. Innov. New Technol., 9(2), 111–148.

    Article  Google Scholar 

  • Busom, I., & Fernández-Ribas, A. (2004). Firm strategies in R&D: Cooperation and participation in R&D programs. Barcelona: Departamento de Economía Aplicada, Universidad Autónoma de Barcelona.

    Google Scholar 

  • Cassiman, B., & Veugelers, R. (2002). R&D co-operation and spillovers: some empirical evidence from Belgium. Am. Econ. Rev., 92, 1169–1184.

    Article  Google Scholar 

  • Cassiman, B., & Veugelers, R. (2006). In search of complementarity in innovation strategy: Internal R&D and external knowledge acquisition. Manage. Sci., 52(1), 68–82.

    Article  Google Scholar 

  • Círculo de Empresarios Documents. (2013). The Spanish medium sized enterprise. Madrid.

  • Cohen, W. M., & Levinthal, D. A. (1989). Innovation and learning: The two faces of R&D. Econ. J., 99, 569–596.

    Article  Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Adm. Sci. Q., 35(1), 128–152.

    Article  Google Scholar 

  • Czarnitzki, D., Ebersberger, B., & Fier, A. (2007). The relationship between R&D collaboration, subsidies and patenting activity: Empirical evidence from Finland and Germany. Journal of Applied Econometrics, 22(7), 1347–1366.

    Article  Google Scholar 

  • D’Aspremont, C., & Jacquemin, A. (1988). Cooperative and noncooperative R&D in duopoly with spillovers. Am. Econ. Rev., 78(5), 1133–1137.

    Google Scholar 

  • Ebersberger, B., & Herstad, S. (2013). The relationship between international innovation collaboration, intramural R&D and SMEs innovation performance: a quantile regression approach. Applied Economic Letters, 20(7), 626–630.

    Article  Google Scholar 

  • Edler, J. (2008). Creative internationalization: widening the perspectives on analysis and policy regarding international R&D activities. J. Technol. Transfer, 33, 337–352.

    Article  Google Scholar 

  • Edler, J. (2010). International policy coordination for collaboration in S&T. Manchester Business School Working Paper, Paper n. 590.

  • Ennen, E., & Richter, A. (2010). The whole is more than the sum of its parts—Or is it? A review of the empirical literature on complementarities in organizations. J. Manag., 36(1), 207–233.

    Google Scholar 

  • Escribano, A., Fosfuri, A., & Tribó, J. A. (2009). Managing external knowledge flows: The moderating role of absorptive capacity. Res. Policy, 39, 96–105.

    Article  Google Scholar 

  • European Commission. (2011a). From challenges to opportunities: Towards a common strategic framework for EU research and innovation funding—Green Paper. Luxembourg: Publications Office of the European Union.

    Google Scholar 

  • European Commission. (2011b). Innovation union competitiveness report. Luxembourg: Publications Office of the European Union.

    Google Scholar 

  • Faems, D., de Visser, M., Andries, P., & Van Looy, B. (2010). Technology alliance portfolios and financial performance: value-enhancing and cost-increasing effects of open innovation. J. Prod. Innov. Manag., 27(6), 785–796.

    Article  Google Scholar 

  • Fornahl, D., Brökel, T., & Boschma, R. A. (2011). What drives patent performance of German biotech firms? The impact of R&D subsidies, knowledge networks and their location. Papers in Regional Science, 90(2), 395–418.

    Article  Google Scholar 

  • Franco, Ch., & Gussoni, M. (2014). The role of firm and national level factors in fostering R&D cooperation: A cross country comparison. J. Technol. Transfer, 39, 945–976.

    Article  Google Scholar 

  • Franco, Ch., Marzucchi, A., & Montresor, S. (2012). Absorptive capacity, innovation cooperation and human-capital. Evidence from 3 European countries. JRC-IPTS Working Papers on Corporate R&D and Innovation 2012-05.

  • Giuliani, E., & Bell, M. (2005). The micro-determinants of meso-level learning and innovation: Evidence from a Chilean wine cluster. Res. Policy, 34(1), 47–68.

    Article  Google Scholar 

  • Graevenittz, G. (2004). Spillovers reconsidered: How optimal R&D subsidies depend on the spillover process. Mimeo: Department of Economics, University College London.

    Google Scholar 

  • Grossman, G. M., & Helpman, E. (1991). Innovation and growth in the global economy. Cambridge, MA: MIT Press.

    Google Scholar 

  • Hall, B. H., Mairesse, J., & Mohnen, P. (2010). Measuring the returns to R&D. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation. Amsterdam: Elsevier.

    Google Scholar 

  • Hinloopen, J. (2001). Subsidizing R&D cooperatives. De Economist, 149(3), 313–345.

    Article  Google Scholar 

  • Hottenrott, H., & Lopes-Bento, C. (2014). (International) R&D collaboration and SMEs: The effectiveness of targeted public R&D support schemes. Res. Policy, 43, 1055–1066.

    Article  Google Scholar 

  • Katz, M. L., & Ordover, J. A. (1990). R&D cooperation and competition. In M. N. Baily & C. Winston (Eds.), Brookings papers on economic activity: Microeconomics (pp. 137–203). Washington, DC: Brookings Institution.

    Google Scholar 

  • Kuhlman, S., & Edler, J. (2003). Scenarios of technology and innovation policies in Europe: Investigating future governance. Technol. Forecast. Soc. Chang., 70, 619–637.

    Article  Google Scholar 

  • Laursen, K., & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Manage Journal, 27(2), 131–150.

    Article  Google Scholar 

  • Lee, J. J. Y. (2008). Complementary effects of information technology investment on firm profitability: The functional form of the complementarities. Information Systems Management, 25(4), 364–371.

    Article  Google Scholar 

  • Lee, C. Y., & Sung, T. (2005). Schumpeter’s legacy: A new perspective on the relationship between firm size and R&D. Res. Policy, 34(6), 914–931.

    Article  Google Scholar 

  • López, A. (2008). Determinants of R&D cooperation: Evidence from Spanish manufacturing firms. Int. J. Ind. Organ., 26, 113–136.

    Article  Google Scholar 

  • Marín, P. L., & Siotis, G. (2008). Public policies towards research joint venture: Institutional design and participants’ characteristics. Res. Policy, 37, 1057–1065.

    Article  Google Scholar 

  • Martin, S. (2002). Spillovers, appropriability, and R&D. J. Econ., 75(1), 1–32.

    Article  Google Scholar 

  • Milgrom, P., & Roberts, J. (1990). The economics of modern manufacturing: Technology, strategy, and organization. Am. Econ. Rev., 80, 511–528.

    Google Scholar 

  • Mohnen, P., & Röller, L. (2005). Complementarities in innovation policy. European Economic Review, 49(6), 1431–1450.

    Article  Google Scholar 

  • Muldur, U., Corvers, F., Delanghe, H., Dratwa, J., Heimberger, D., Sloan, B., et al. (2006). A new deal for an effective European research policy: The design and impacts of the 7th Framework Programme. Netherlands: Springer.

    Google Scholar 

  • Rammer, C., Czarnitzki, D., & Spielkamp, A. (2009). Innovation success of non-R&D-performers: Substituting technology by management in SMEs. Small Bus. Econ., 33, 35–58.

    Article  Google Scholar 

  • Romer, P. M. (1990). Endogenous technological change. J. Polit. Econ., 98(5), 71–102.

    Article  Google Scholar 

  • Sakakibara, M. (2001). The diversity of R&D consortia and firm behavior: Evidence from Japanese data. Journal of Industrial Economics, 49(2), 181–196.

    Article  Google Scholar 

  • Scherngell, T., & Barber, M. J. (2011). Distinct spatial characteristics of industrial and public research collaborations: Evidence from the fifth EU Framework Programme. Annals of Regional Science, 46, 247–266.

    Article  Google Scholar 

  • Schwartz, M., Peglow, F., Fritsch, M., & Günther, J. (2012). What drives innovation output from subsidized R&D cooperation? Project level evidence from Germany. Technovation, 32, 358–369.

    Article  Google Scholar 

  • Segarra-Blasco, A. (2011). R&D cooperation between Spanish firms and scientific partners: What is the role of tertiary education? Universidad Rovira i Virgili, WP XREAP2011-17.

  • Topkis, D. M. (1978). Minimizing a submodular function on a lattice. Oper. Res., 26(2), 305–321.

    Article  Google Scholar 

  • Tsai, W. (2001). Knowledge transfer in intraorganizational networks: Effects of network position and absorptive capacity on business unit innovation and performance. Acad. Manag. Rev., 44, 996–1004.

    Google Scholar 

  • Van Beers, C., & Zand, F. (2014). R&D cooperation, partner diversity, and innovation performance: An empirical analysis. J. Prod. Innov. Manag., 31(2), 292–312.

    Article  Google Scholar 

  • Veugelers, R. (1997). Internal R&D expenditures and external technology sourcing. Res. Policy, 26, 303–315.

    Article  Google Scholar 

  • Wolfe, R. A. (1994). Organizational innovation: Review, critique and suggested research directions. J. Manage. Stud., 31(3), 405–431.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Financial Economics and Accounting, University of Extremadura, Av. De la Universidad, s/n, 10071, Cáceres, Spain

    Manuel Guisado-González & José Luís Coca-Pérez

  2. University of Extremadura, Av. De la Universidad, s/n, 10071, Cáceres, Spain

    Jennifer González-Blanco

  3. Departament of Business Administration, University of Vigo, Campus Vigo, 36310, Vigo, Spain

    Manuel Guisado-Tato

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  1. Manuel Guisado-González
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Guisado-González, M., González-Blanco, J., Coca-Pérez, J.L. et al. Assessing the relationship between R&D subsidy, R&D cooperation and absorptive capacity: an investigation on the manufacturing Spanish case. J Technol Transf 43, 1647–1666 (2018). https://doi.org/10.1007/s10961-017-9579-7

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