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Intramural and external R&D: evidence for complementarity or substitutability

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Abstract

The aim of this study is to ascertain the impact of two firm innovation strategies—namely, intramural R&D and external R&D, including either contracted R&D and import of technology, upon total factor productivity (TFP). In order to evaluate these effects we consider robust estimates of TFP through a GMM approach where we account for the diverse innovation strategies carried out by firms (intramural only, external only or both). Using data for Spanish manufacturing firms drawn from the Encuesta de Estrategias Empresariales (ESEE), over the period 1991–2014, our results suggest that inhouse R&D and external R&D are complementary strategies only for large firms in high tech sectors. For the rest of firms, both strategies turn out to be substitutive. Further, R&D strategies only offer a TFP premium to exporters. We find no positive synergies between in-house and external R&D for large exporters, while for small exporters both strategies are substitutes.

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Notes

  1. According to the Technological Innovation Panel (PITEC), a yearly survey of Spanish firms conducted since 2004 by the National Statistical Institute (INE), about 12% of total expenditure in external R&D comes from foreign providers for the average firm in the sample. The acquisition of international licenses just represents 0.05% of the total R&D expenditure (according to the Spanish Survey of Firm Strategies, ESEE, a yearly survey of Spanish firms on manufacturing conducted since 1990 by the SEPI Foundation).

  2. This approach has been shown to suffer from measurement problems and inference difficulties (Arora 1996; Piga and Vivarelli 2004).

  3. The law of motion for capital follows a deterministic dynamic process according to which kit = (1 − δ)kit−1 + Iit−1. Thus, it is assumed that the capital that the firm uses in period t was actually decided in period t − 1.

  4. Our period of analysis starts in 1991 as information for some variables is only available from this year onwards.

  5. For example, innovation or export strategies pursued by firms.

  6. In contrast to PITEC, the ESEE does not distinguish between R&D purchased at home and abroad.

  7. Further information about this survey can be found in the following web page, provided by FUNEP: http://www.funep.es/esee/en/einfo_que_es.asp.

  8. In Table 12 in the "Appendix", we report the descriptive statistics of the main variables used to estimate firm TFP.

  9. We define innovative firms those declaring positive R&D expenditures (either in internal or externally contracted R&D activities plus importers of technology through licensing) during at least one year of the observed period.

  10. We exclude size in the control category when size appears as dependent variable.

  11. We have also estimated the production function by OLS and using an exogenous Markov process. These results are available from the authors upon request.

References

  • Ackerberg, D. A., Caves, K., & Frazer, G. (2015). Identification properties of recent production function estimators. Econometrica, 83(6), 2411–2451.

    Article  Google Scholar 

  • Alarcón, S., & Sánchez, M. (2013). External and internal R&D, capital investment and business performance in the spanish agri-food industry. Journal of Agricultural Economics, 64(3), 654–675.

    Article  Google Scholar 

  • Añón Higón, D. (2016). In-house versus external basic research and first-to-market innovations. Research Policy, 45(4), 816–829.

    Article  Google Scholar 

  • Arora, A. (1996). Testing for complementarities in reduced form regressions. Economics Letters, 50, 51–55.

    Article  Google Scholar 

  • Beneito, P. (2006). The innovative performance of in-house and contracted R&D in terms of patents and utility models. Research Policy, 35(4), 502–517.

    Article  Google Scholar 

  • Bönte, W. (2003). R&D and productivity: Internal vs. external R&D—evidence from West German manufacturing industries. Economics of Innovation and New Technology, 12, 343–360.

    Article  Google Scholar 

  • Carree, M., Lokshin, B., & Belderbos, R. (2011). A note on testing for complementarity and substitutability in the case of multiple practices. Journal of Productivity Analysis, 35(3), 263–269.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Chesbrough, H. (2003). The era of open innovation. Sloan Management Review., 44, 35–41.

    Google Scholar 

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

    Article  Google Scholar 

  • Cruz-Cázares, C., Bayona-Sáez, C., & García-Marco, T. (2010). R&D strategies and firm innovative performance: A panel data analysis. International Journal of Innovation Management., 14(06), 1013–1045.

    Article  Google Scholar 

  • De Loecker, J. (2010). A note on detecting learning by exporting. National Bureau of Economic Research. N. w16548.

  • De Loecker, J. (2013). Detecting learning by exporting. American Economic Journal: Microeconomics, 5(3), 1–21.

    Google Scholar 

  • Doraszelski, U., & Jaumandreu, J. (2013). R&D and productivity: Estimating endogenous productivity. Review of Economic Studies, 80(4), 1338–1383.

    Article  Google Scholar 

  • Freel, M. (2003). Sectoral patterns of small firm innovation, networking and proximity. Research Policy, 32, 751–770.

    Article  Google Scholar 

  • García-Vega, M., & Huergo, E. (2011). The role of international and domestic R&D outsourcing for firms’ innovativeness. Working Paper of University of Nottingham. 2011b (3).

  • Griliches, Z. (1980). R&D and the productivity slowdown. American Economic Review, 70, 343–348.

    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 (pp. 1033–1082). Amsterdam: Elsevier B.V.

    Google Scholar 

  • Jirjahn, U., & Kraft, K. (2011). Do spillovers stimulate incremental or drastic product innovations? Evidence from German establishment data. Oxford Bulletin of Economics and Statistics, 73(4), 509–538.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Levinsohn, J., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies, 70(2), 317–341.

    Article  Google Scholar 

  • Lokshin, B., Belderbos, R., & Carree, M. (2008). The productivity effects of internal and external R&D: Evidence from a dynamic panel data model. Oxford Bulletin of Economics and Statistics, 70(3), 399–416.

    Article  Google Scholar 

  • Love, J. H., Roper, S., & Vahter, P. (2014). Dynamic complementarities in innovation strategies. Research Policy, 43(10), 1774–1784.

    Article  Google Scholar 

  • Martinez-Noya, A., Garcia-Canal, E., & Guillen, M. F. (2012). International R&D service outsourcing by technology-intensive firms: Whether and where? Journal of International Management, 18(1), 18–37.

    Article  Google Scholar 

  • Milgrom, P., & Roberts, J. (1990). The economics of modern manufacturing: Technology, strategy, and organization. The American Economic Review, 80(3), 511–528.

    Google Scholar 

  • Narula, R. (2001). Choosing between internal and non-internal R&D activities: Some technological and economic factors. Technology Analysis & Strategic Management., 13, 365–388.

    Article  Google Scholar 

  • Olley, G. S., & Pakes, A. (1996). The Dynamics of Productivity in the Telecommunications Equipment Industry. Econometrica., 64(6), 1263–1297.

    Article  Google Scholar 

  • Piga, C., & Vivarelli, M. (2004). Internal and external R&D: A sample selection approach. Oxford Bulletin of Economics and Statistics, 66, 457–482.

    Article  Google Scholar 

  • Roberts, V. (2001). Managing strategic outsourcing in the healthcare industry. Journal of Healthcare Management, 46(4), 239–249.

    Article  Google Scholar 

  • Segarra, A., & Teruel, M. (2011). Productivity and R&D sources: Evidence for Catalan firms. Economics of Innovation and New Technology., 20(8), 727–748.

    Article  Google Scholar 

  • Schmiedeberg, C. (2008). Complementarities of innovation activities: An empirical analysis of the German manufacturing sector. Research Policy, 37(9), 1492–1503.

    Article  Google Scholar 

  • Vega-Jurado, J., Gutiérrez-Gracia, A., & Fernández-de-Lucio, I. (2009). Does external knowledge sourcing matter for innovation? Evidence from the Spanish manufacturing industry. Industrial and Corporate Change., 18(4), 637–670.

    Article  Google Scholar 

  • Williamson, O. E. (1985). The Economic Institutions of Capitalism. New York: Free Press.

    Google Scholar 

  • Wooldridge, J. M. (2009). On estimating firm-level production functions using proxy variables to control for unobservables. Economics Letters, 104, 112–114.

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge financial support from the Ministerio de Economía y Competitividad (Grants ECO2017-86793-R and ECO2014-55745-R) and from Generalitat Valenciana (Grant PROMETEOII/2014/054). Usual caveats apply.

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Authors and Affiliations

  1. Department of Applied Economics II and ERICES, Universitat de València, Valencia, Spain

    Dolores Añón Higón, Juan A. Máñez & Juan A. Sanchis-Llopis

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  1. Dolores Añón Higón
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  2. Juan A. Máñez
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  3. Juan A. Sanchis-Llopis
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Correspondence to Juan A. Máñez.

Appendix: variable definitions

Appendix: variable definitions

Value Added (va) Real value added. Nominal values are deflated using firm-level price deflators.

Labour (l) This is measured as the number of effective hours worked.

Capital (k) Real value of the stock of capital measured using the perpetual inventory method and adjusted for capacity utilization.

Materials (m) Real value of intermediate materials.

Size: Dummy variable that takes the value of 1 if the firm has more than 200 employees (large) and 0 otherwise (small).

Innovative firms Dummy variable that takes the value of 1 if the firm declares a positive expenditure on R&D, and 0 otherwise.

Only internal R&D Dummy variable that takes the value of 1 if the firm declares that performs only internal R&D, and 0 otherwise.

Only external R&D Dummy variable that takes the value of 1 if the firm declares that performs only external R&D or/and imports technology through licenses, and 0 otherwise.

Both internal and external R&D Dummy variable that takes the value of 1 if the firm declares that performs both internal and external R&D, and 0 otherwise.

Exporter in t Dummy variable that takes the value of 1 if the firm exports in the current period t, and 0 otherwise.

Exporter Dummy variable that takes the value of 1 if the firm exports at least half of the years she is in the sample, and 0 otherwise.

Foreign-owned firms Dummy variable that takes the value of 1 if the firm has foreign capital participation, and 0 otherwise.

Low tech sectors Meat industry, Beverages, Textiles and clothing, Leather and shoes, Wood, Paper industry, Printing and printing products, Non-metallic mineral products, Metallic products, Furniture and Other manufacturing goods.

Med tech sectors Food and tobacco, Rubber and plastic, Ferrous and non-ferrous metals, Vehicles, cars and motors.

High tech sectors Office machines, Electric and electronic machinery and material and Other transport equipment.

See Table 12.

Table 12 Descriptive statistics of the TFP variables
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Añón Higón, D., Máñez, J.A. & Sanchis-Llopis, J.A. Intramural and external R&D: evidence for complementarity or substitutability. Econ Polit 35, 555–577 (2018). https://doi.org/10.1007/s40888-018-0100-z

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  • DOI: https://doi.org/10.1007/s40888-018-0100-z

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