Firma Dinamiklerinin İnovasyon ve Büyüme İlişkisindeki Rolü: En Yüksek Ar-Ge Yatırımcısı Firmalar Üzerine Ampirik Kanıtlar

Bu çalışmanın temel amacı, firmaların sahip olduğu teknoloji yoğunluğu ve büyüme hızı gibi dinamiklerin inovasyon ve büyüme ilişkisinde oynadığı rolün tespit edilmesidir. Ayrıca, firma büyüklüğü ve firma yaşı gibi değişkenlerin büyüme üzerinde yaratacağı etkiler de dikkate alınarak, sürdürülebilir büyüme açısından en uygun firma yapısının hangisi olacağının belirlenmesi amaçlanmaktadır. Bu amaç doğrultusunda inovasyon ve büyüme arasındaki ilişki, AB Endüstriyel ArGe Yatırım Skorbordu veri tabanında yer alan, dünya genelindeki en yüksek 2500 Ar-Ge yatırımcısı firma arasından seçilen 302 firmanın, 2005-2016 dönemini kapsayan verileri üzerine panel kantil regresyon ve sistem-genelleştirilmiş momentler metodu (GMM) tahmincisi kullanılarak ampirik olarak test edilmiştir. Analizde inovasyon göstergesi olarak veri zarflama analiziyle her bir örneklem ve yıl için hesaplanan inovasyon etkinliği skorları kullanılmıştır. Analiz sonuçlarına göre, nispeten daha küçük ölçekli, genç, hızlı büyüyen ve yenilikçi “süperstar” firmalar tarafından gerçekleştirilecek inovasyonun firma büyümesi üzerindeki etkisinin diğerlerine kıyasla çok daha büyük olacağı sonucuna varılmaktadır.

The Role of Firm Dynamics in İnnovation and Growth Relationship: Empirical Evidence from The Top R&D İnvestor Firms

The main purpose of this study is to determine the role of firm dynamics such as technological intensity and growth rate of firms in the relationship between innovation and growth. Moreover, in this study it is aimed to determine the most appropriate firm structure in terms of sustainable growth considering the effects of variables such as firm size and firm age on growth. In line with this purpose, the relationship between innovation and growth was empirically tested by applying panel quantile regression and system-generalized method of moments (GMM) estimators covering the period of 2005-2016 for the sample of 302 firms. These 302 firms were selected from the database of the EU Industrial R&D Investment Scoreboard among World’s 2500 top R&D investors. Innovation efficiency scores calculated from data envelopment analysis for each sample and year were used as an innovation indicator in the analysis. According to the results of the analysis, it has been concluded that the impact of innovation to be realized by the relatively smaller sized, young, fast-growing and innovative “superstar” firms on firm growth will be much larger than others.

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  • Abrevaya, J., & Dahl, C. M. (2008). The effects of birth inputs on birthweight: Evidence from quantile estimation on panel data. Journal of Business and Economic Statistics, 26(4), 379–397.
  • Aghion, P., & Howitt, P. (1992). A model of growth through creative destruction. Econometrica, 60(2), 323–351.
  • Akcigit, U., & Kerr, W. R. (2018). Growth through heterogeneous innovations. Journal of Political Economy, 126(4), 1374–1443.
  • Alvarez, R., & Crespi, G. (2003). Determinants of technical efficiency in small firms. Small Business Economics, 20(3), 233–244.
  • Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51.
  • Arundel, A., & Kabla, I. (1998). What percentage of innovations are patented? Empirical estimates for European firms. Research Policy, 27(2), 127–141.
  • Bache, S. H. M., Dahl, C. M., & Kristensen, J. T. (2013). Headlights on tobacco road to low birthweight outcomes: Evidence from a battery of quantile regression estimators and a heterogeneous panel. Empirical Economics, 44(3), 1593–1633.
  • Baltagi, B. H. (2013). Econometric Analysis of Panel Data (Fifth Edit). West Sussex: Wiley.
  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.
  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.
  • Bottazzi, G., Dosi, G., Lippi, M., Pammolli, F., & Riccaboni, M. (2001). Innovation and corporate growth in the evolution of the drug industry. International Journal of Industrial Organization, 19(7), 1161–1187.
  • Brouwer, E., Kleinknecht, A., & Reijnen, J. O. N. (1993). Employment growth and innovation at the firm level: An empirical study. Journal of Evolutionary Economics, 3(2), 153–159.
  • Cass, D. (1965). Optimum growth in an aggregative model of capital accumulation. Review of Economic Studies, 32(3), 233–240.
  • Cefis, E., & Marsili, O. (2005). A matter of life and death: Innovation and firm survival. Industrial and Corporate Change, 14(6), 1167–1192.
  • Chamberlain, G. (1982). Multivariate regression models for panel data. Journal of Econometrics, 18(1), 5–46.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1981). Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through. Management Science, 27(6), 668–697.
  • Coad, A. (2009). The growth of firms - A survey of theories and empirical evidence. Içinde Edward Elgar. Cheltenham, UK: Edward Elgar.
  • Coad, A., & Rao, R. (2008). Innovation and firm growth in high-tech sectors: A quantile regression approach. Research Policy, 37, 633–648.
  • Coad, A., Segarra, A., & Teruel, M. (2016). Innovation and firm growth: Does firm age play a role? Research Policy, 45(2), 387–400.
  • Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European Economic Review, 39(5), 859–887.
  • Colombelli, A., Haned, N., & Le Bas, C. (2013). On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004). Structural Change and Economic Dynamics, 26, 14–26.
  • Corsino, M., & Gabriele, R. (2010). Product innovation and firm growth: Evidence from the integrated circuit industry. Industrial and Corporate Change, 20(1), 29–56.
  • Cruz-Cázares, C., Bayona-Sáez, C., & García-Marco, T. (2013). You can’t manage right what you can’t measure well: Technological innovation efficiency. Research Policy, 42(6–7), 1239–1250.
  • Czarnitzki, D., & Delanote, J. (2013). Young innovative companies: The new high-growth firms? Industrial and Corporate Change, 22(5), 1315–1340.
  • Del Monte, A., & Papagni, E. (2003). R&D and the growth of firms: Empirical analysis of a panel of Italian firms. Research Policy, 32(6), 1003–1014.
  • Demirel, P., & Mazzucato, M. (2012). Innovation and firm growth: Is R&D worth it? Industry and Innovation, 19(1), 45–62.
  • Diamond, P. A. (1965). National debt in a neoclassical growth model. American Economic Review, 55(1), 1126–1150.
  • Dosi, G. (1988). Sources, procedures, and microeconomic effects of innovation. Journal of Economic Literature, 26(3), 1120–1171.
  • Erdem, E., & Köseoğlu, A. (2014). Teknoloji̇k deği̇şi̇m ve rekabet gücü ili̇şki̇si̇: Türki̇ye üzeri̇ne bi̇r uygulama. Bilgi Ekonomisi ve Yönetimi Dergisi, 9(1), 51-68.
  • Ernst, H. (2001). Patent applications and subsequent changes of performance: Evidence from time-series cross-section analyses on the firm level. Research Policy, 30(1), 143–157.
  • Evans, D. S. (1987). Tests of alternative theories of firm growth. Journal of Political Economy, 95(4), 657–674.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series A, 120(3), 253–290.
  • Freel, M. S., & Robson, P. J. A. (2004). Small firm innovation, growth and performance: Evidence from Scotland and Northern England. International Small Business Journal, 22(6), 561–575.
  • García-Manjón, J. V., & Romero-Merino, M. E. (2012). Research, development, and firm growth. Empirical evidence from European top R&D spending firms. Research Policy, 41(6), 1084–1092.
  • Geroski, P. A., & Machin, S. (1992). Do innovating firms outperform non-innovators? Business Strategy Review, Summer, 79–90.
  • Geroski, P. A., Machin, S., & Van Reenen, J. (1993). The profitability of innovating firms. RAND Journal of Economics, 24(2), 198–211.
  • Griliches, Z. (1979). Issues in assessing the contribution of research and development to productivity. The Bell Journal of Economics, 10(1), 92–116.
  • Griliches, Z. (1990). Patent statistics as economic indicators : A survey. Journal of Economic Literature, 28, 1661–1707.
  • Grossman, G. M., & Helpman, E. (1991a). Innovation and growth in the global economy. Cambridge, MA: MIT Press.
  • Grossman, G. M., & Helpman, E. (1991b). Quality ladders in the theory of growth. Review of Economic Studies, 58(1), 43–61.
  • Guan, J., & Chen, K. (2010). Measuring the innovation production process: A cross-region empirical study of China’s high-tech innovations. Technovation, 30(5–6), 348–358.
  • Hall, B. H., & Mairesse, J. (1995). Exploring the relationship between R&D and productivity in French manufacturing firms. Journal of Econometrics, 65(1), 263–293.
  • Hall, B. H., & Oriani, R. (2006). Does the market value R&D investment by European firms? Evidence from a panel of manufacturing firms in France, Germany, and Italy. International Journal of Industrial Organization, 24(5), 971–993.
  • Hatzichronoglou, T. (1997). Revision of the high-technology sector and product classification. OECD Science, Technology and Industry Working Papers, (1997/02).
  • Hölzl, W. (2009). Is the R&D behaviour of fast-growing SMEs different? Evidence from CIS III data for 16 countries. Small Business Economics, 33(1), 59–75.
  • IRI-JRC-European Commission. (2017). The 2017 EU Industrial R&D Investment Scoreboard. Publications Office of the European Union, Luxembourg.
  • Jones, C. I. (1995). R&D-based models of economic growth. Journal of Political Economy, 103(4), 759–784.
  • Koellinger, P. (2008). The relationship between technology, innovation, and firm performance-Empirical evidence from e-business in Europe. Research Policy, 37(8), 1317–1328.
  • Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74–89.
  • Koenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33–50.
  • Koenker, R., & Hallock, K. F. (2001). Quantile Regression. Journal of Economic Perspectives, 15(4), 143–156.
  • Koopmans, T. C. (1965). On the concept of optimal economic growth. Içinde Econometric Approach to Development Planning (ss. 225–287). Amsterdam: North-Holland Publishing Company.
  • Kortum, S. (1997). Research, patenting, and technological change. Econometrica, 65(6), 1389–1419.
  • Lanjouw, J. O., & Schankerman, M. (2004). Patent quality and research productivity: Measuring innovation with multiple indicators. The Economic Journal, 114(495), 441–465.
  • Lee, C. Y. (2010). A theory of firm growth: Learning capability, knowledge threshold, and patterns of growth. Research Policy, 39(2), 278–289.
  • Lotti, F. (2007). Firm dynamics in manufacturing and services: A broken mirror? Industrial and Corporate Change, 16(3), 347–369.
  • Mansfield, E. (1962). Entry, Gibrat’s law, innovation, and the growth of firms. American Economic Review, 52(5), 1023–1051.
  • Minniti, A., & Venturini, F. (2017). The long-run growth effects of R&D policy. Research Policy, 46(1), 316–326.
  • Montresor, S., & Vezzani, A. (2015). The production function of top R&D investors: Accounting for size and sector heterogeneity with quantile estimations. Research Policy, 44(2), 381–393.
  • Mowery, D. C. (1983). Industrial research and firm size, survival, and growth in American manufacturing, 1921-1946: An assessment. Journal of Economic History, 43(4), 953–980.
  • Nunes, P. M., Serrasqueiro, Z., & Leitão, J. (2012). Is there a linear relationship between R&D intensity and growth? Empirical evidence of non-high-tech vs. high-tech SMEs. Research Policy, 41(1), 36–53.
  • Parente, P. M. D. C., & Santos Silva, J. M. C. (2016). Quantile regression with clustered data. Journal of Econometric Methods, 5(1), 1–15.
  • Ramsey, F. P. (1928). A mathematical theory of saving. The Economic Journal, 38(152), 543–559.
  • Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94(5), 1002–1037.
  • Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98(5), 71–102.
  • Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal, 9(1), 86–136.
  • Roper, S. (1997). Product innovation and small business growth: A comparison of the strategies of German, U.K. and Irish companies. Small Business Economics, 9(6), 523–537.
  • Scherer, F. M. (1965). Corporate inventive output, profits, and growth. Journal of Political Economy, 73(3), 290–297.
  • Schmookler, J. (1966). Invention and economic growth. Cambridge, MA: Harvard University Press.
  • Segerstrom, P. S. (1998). Endogenous growth without scale effects. American Economic Review, 88(5), 1290–1310.
  • Singh, A., & Whittington, G. (1975). The size and growth of firms. Review of Economic Studies, 42(1), 15–26.
  • Solow, R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1), 65–94.
  • Stam, E., & Wennberg, K. (2009). The roles of R&D in new firm growth. Small Business Economics, 33(1), 77–89.
  • Sutton, J. (1997). Gibrat’s legacy. Journal of Economic Literature, 35(1), 40–59.
  • Törnqvist, L., Vartia, P., & Vartia, Y. O. (1985). How should relative changes be measured? American Statistician, 39(1), 43–46.
  • Wallace, T. D., & Hussain, A. (1969). The use of error components models in combining cross section with time series data. Econometrica, 37(1), 55–72.
  • Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126(1), 25–51.