Economic Growth and International R&D Cooperation: A Panel Granger Causality Analysis

Tarek Sadraoui^1, , Tarek Ben Ali² and Bechir Deguachi²

¹Quantitative Method, Higher Institute of business Administration, Gafsa, Tunisia

²Economic Sciences, Higher Institute of business Administration, Gafsa, Tunisia

Cite this paper:
Tarek Sadraoui, Tarek Ben Ali and Bechir Deguachi. Economic Growth and International R&D Cooperation: A Panel Granger Causality Analysis. International Journal of Econometrics and Financial Management. 2014; 2(1):7-21. doi: 10.12691/ijefm-2-1-2

Abstract

This paper will investigate the Granger causality between R&D cooperation and economic growth in 32 industrial and developing countries from 1970 to 2012. We use an innovative econometric method which is based on a panel test of the Granger non causality hypothesis. Using a new method to evaluate causality in a heterogeneous panel, we find that the causal relationship from R&D cooperation to economic growth is homogeneous among the panel. However, we find strong evidence of a heterogeneity of the causal relationship from economic growth to R&D cooperation in our sample. Results provide support for a robust causality relationship from economic growth to R&D cooperation. On the contrary, the non causality hypothesis from R&D cooperation to economic growth can’t be rejected in most of the cases. However, these results only imply that, if such a relationship exists, it can’t be easily identified in a simply bi-variate Granger causality test.

Keywords:
Granger Causality Tests dynamic panel data R&D cooperation economic growth spillovers

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	Antonelli, M. (1994) ‘Ttechnological districts localized spillovers and productivity growth. The Italian evidence on technological externalities in the core regions’, International Review of Applied Economics, pp. 18-30.
[2]	2 Arellano, M. and Bond, S. (1991) ‘Some test of specification for panel data: Monte Carlo evidence and application to employment equations’, Review of Economic Studies, Vol. 58, pp. 277-297.
[3]	Arellano, M. and Bond, S. (1998) ‘Dynamic panel data Estimating using DPD98-A Guide for users’, institute for Fiscal Studies, mimeo.
[4]	Baumol, W. J. (1992) ‘Horizontal collusion and innovation’, Economic Journal, Vol.102, pp, 129-137.
[5]	Baumol, W. J. (1997) ‘Pareto optimal sizes of innovation spillovers’, Research Report, pp. 97-42, The C.V. Starr Centre for Applied Economics, Department of Economics, New York University.
[6]	Baumol. W. J. (1993) ‘the Mechanisms of Technology Transfer, II: Technology Consortia in Complementary Innovations’ In Entrepreneurship, Management, and the Structure of Payoffs. MIT Press: Cambridge MA, pp, 193-222.
[7]	Broekel, T. and Boschma R. (2011): Knowledge networks in Dutch aviation industry: the proximity paradox, Journal of Economic Geography, forthcoming.
[8]	Broekel, T., Buerger, M., Brenner, T. (2010) an investigation of the relation between cooperation and the innovative success of German regions. Papers in Evolutionary Economic Geography. 10.11, Utrecht University, Utrecht.
[9]	Broekel, T. and Graf, H. (2012): Public research intensity and the structure of German R&D networks: A comparison of ten technologies. Economics of Innovation and New Technology, Economics of Innovation and New Technology 21/4, 345-372.
[10]	Cassiman, B. and Veugelers, R. (2002) ‘R&D cooperation and spillovers: some empirical evidence from Belgium’, American Economic Review, Vol. 92, N. 4, pp. 1169-1184.
[11]	Combe, E. (1998) ‘Pour quoi les firmes s’allient-elles ? Un Etat de l’art’, Revue d’économie Politique, Vol. 4 N. 108, pp. 433-475.
[12]	Cozzi, G. (1999) ‘R&D cooperation and growth’, Journal of Economic Theory, Vol. 86, pp. 17-49.
[13]	Crampes, C. and Encaoua, D. (2001) ‘Microéconomie de l’innovation’, Série verte, Bargaining over monetary policy and the desirability of central bank independence, V01067.
[14]	D’aspremont, C. and Jacquemin, A. (1988) ‘Cooperative and non cooperative R&D in duopoly with spillovers’, American Economic Review, Vol. 5, N. 78. pp. 1133-1137.
[15]	D’aspremont, C. and Jacquemin, A. (1990) ‘Cooperative and Non-cooperative R&D in Duopoly with Spillovers: Erratum’, American Economic Review, Vol. 78, pp. 1133-1137.
[16]	Davidson, R. and MacKinnon, J. G. (1992) ‘Regression-Based Methods for Using Control and Antithetic Variates in Monte Carlo Experiments’, Journal of Econometrics, Vol. 54, pp. 203-222.
[17]	Dickey, D. and Fuller, W. (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”, Journal of the American Statistical Association, 74, 427-431.
[18]	Gallie, E.P. (2003) ‘La coopération, vecteur d’externalités de connaissances’, Colloque “Economie de la firme: quelles nouveautés? Annecy, 17-18.
[19]	Geroski, P.A. (1992) ‘Vertical relations between firms and industrial policy’, Economic Journal, Vol. 102, N. 410, pp. 138-147.
[20]	Hurlin, C. et Venet, B. (2001), ''Granger Causality Tests in Panel Data Models with Fixed Coefficients'', Cahier de Recherche EURISCO n° 2001-09, Université Paris IX Dauphine.
[21]	Im, K., Pesaran, H. and Shin, Y. (2003) ‘Testing for unit roots in heterogeneous panels’, Journal of Econometrics, Vol. 115, pp. 53-74.
[22]	Irwin, D. and Klenow, P. (1996) ‘High-Tech R&D Subsidies: Estimating the effects of SEMATECH’, Journal of International Economics’, Vol. 40, pp. 323-344.
[23]	Judson, R. and Owen, A. 1999. Estimating dynamic panel data models: a guide for macroeconomic. Economics Letters 65, 9-15.
[24]	Kao, C. (1999), “Spurious regression and residual based tests for co integration in panel data”, Journal of Econometrics pp, 1-44.
[25]	Katz, M. L. (1986) ‘An analysis of cooperative research and development’, RAND Journal of Economics’, Vol. 17, N. 4, pp. 527-543.
[26]	Kiviet Jan. F (1995) Neglected Dynamics in Dynamic Panel Data Models; Consequences and Detection in Finite Samples, (with I. T. van den Doel), Statistica Neerlandica, 49, 343-361.
[27]	Levin, A., Lin, C. and Chu, C. J. (2002) ‘Unit root tests in panel data: Asymptotic and nite-sample properties’, Journal of Econometrics, Vol. 108, pp. 1-24.
[28]	Levin, R., Cohen, W. and Mowery, D. (1985) ‘R&D appropriability, opportunity and market structure: New evidence on some Schumpeterian hypotheses’, American Economic Review’, Vol. 75, pp. 20-24.
[29]	Levin, R., Klevorick, N.R. and Winter S. (1987) ‘Appropriating returns from industrial research and development in Baily, M. and Winston, C. redactors ‘Brooking papers on Economic activity’, Wachington, the brooking institution.
[30]	March, 1991, Exploration and Exploitation in Organizational learning, Organization Science, V 2, p 71. 3.
[31]	McKelvie, A. and Wiklund, J. (2010): Advancing Firm Growth Research: A Focus on Growth Mode Instead of Growth Rate, Entrepreneurship: Theory & Practice, 34(2):261-288.
[32]	Mowery, D. and Rosenberg, N. (1989) ‘Technology and the pursuit of economic growth’, Cambridge University Press.
[33]	Mowery, D., Oxley, C. and Silverman, B. (1996) ‘Strategic Alliances and Inter-firm Knowledge Transfer’, Strategic Management Journal, Vo1. 7, pp. 77-91.
[34]	Nair-Reichert, U.; Weinhold, D.; (2001) Causality tests for cross-country panels: a new look at FDI and economic growth in developing countries. Oxford Bulletin of Economics and Statistics, 63 (2) pp. 153-171.
[35]	Nooteboom, B. (1999) ‘Inter-firm alliances-analysis and design’, London, Routledge.
[36]	Robert F. Engle; C. W. J. Granger (1987), Co-Integration and Error Correction: Representation, Estimation, and Testing Econometrica, Vol. 55, No. 2. pp. 251-276.