Interregional R and D spillovers and regional convergence: a spatial econometric evidence from the EU regions
DOI:
https://doi.org/10.24136/eq.v12i1.1Keywords:
beta convergence modelling, spatial econometrics, R&D indicators, R&D spillovers effectsAbstract
Research background: Many contemporary empirical studies and also most of economic growth theories recognize the importance of innovation and knowledge for achieving an economic growth. A large part of empirical literature has treated the issue of beta convergence without the spatial aspect, i.e. the possible spatial dependence among regions or states in growth process was neglected.
Purpose of the article: In this paper, we investigate the link between selected R and D (Research and Development) indicators as proxies for the regional innovation and knowledge and economic performance of the region. We also assume a significant role of regional R and D spillovers in the regional growth process determination.
Methods: The main methodological basis for our analysis is beta convergence approach and the dataset under the consideration consists of 245 NUTS 2 (Nomenclature of Units for Territorial Statistics) EU (European Union) regions during the 2003?2014 period. Our analysis is made with respect to spatial interactions across the EU regions.
Findings and Value added: The influence of R and D indicators on the economic growth has been confirmed, and spatial interconnection across the EU regions have been proven. Potential existence of geographical R and D spillovers across the EU regions was examined by formulation of additional beta convergence model with spatial lag variables. We have identified that the influence of R and D spillovers is not strictly restricted to the neighbouring regions, but they spread across a larger area. For the construction of spatial lags of R and D indicators different spatial weight matrices were considered.
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References
Arbia, G. (2006). Spatial econometrics. Statistical foundations and applications to regional convergence. Berlin: Springer-Verlag.
Bal-Domańska, B. (2016). The impact of economic crisis on convergence processes in European Union regions. Prague Economic Papers, 25(5). doi: 10.18267/j.pep.574.
Barro, R. J. (1990). Government spending in a simple model of endogeneous growth. Journal of Political Economy, 98(5, Part 2). doi: 10.1086/261726.
Barro, R. J. & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2). doi: 10.1086/261816.
Battisti, M., & Di Vaio, G. (2009). A spatially filtered mixture of ?-convergence regressions for EU regions, 1980?2002. In G. Arbia & B. H. Baltagi. Spatial econometrics. methods and applications. Heidelberg: Physica ? Verlag.
Bivand, R. S. (2010). Exploratory spatial data analysis. In M. M. Fischer & A. Getis. Handbook of applied spatial analysis. Software tools, methods and applications. Heidelberg: Springer-Verlag.
Chocholatá, M., & Furková, A. (2016). Does the location and institutional background matter in convergence modelling of the EU regions? Central European Journal of Operations Research. doi: 10.1007/s10100-016-0447-6.
Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European Economic Review, 39(5). doi: 10.1016/0014-2921(94)00100-e.
European Commission (2010). Europe 2020: a European strategy for smart, sustainable and inclusive growth. Retrieved from http://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri=COM:2010:2020:FIN:EN:PDF (05.02.2015).
Fernández, N., Martinez, V., & Sanchez-Robles, B. (2012). R&D and growth in the Spanish regions: an empirical approximation. SSRN Electronic Journal, 3(10). doi:10.2139/ssrn.2060924.
Forni, M., & Paba, S. (2003). Spillovers and the growth of local industries. Journal of Industrial Economics, 50(2). doi:10.1111/1467-6451.00172.
Furková, A. (2016). Spatial pattern of innovative activity in the EU regions: exploratory spatial data analysis and spatial econometric approach. In Advances in applied business research: the L.A.B.S. initiative. New York: Nova Science Publishers.
Furková, A., & Chocholatá, M. (2016). Income convergence and R&D spillovers of the EU regions: spatial econometric approach. In Proceedings of 8th international conference economic challenges in enlarged Europe 2016, Tallinn.
Getis, A. (2010). Spatial autocorrelation. In M. M. Fischer & A. Getis. Handbook of applied spatial analysis. Software tools, methods and applications. Heidelberg: Springer-Verlag.
Griliches, Z. (1990). Patent statistics as economic indicators: a survey. Journal of Economic Literature, 28(4). doi: 10.3386/w3301.
Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1). doi: 10.1016/0304-3932(88)90168-7.
Martin, P., & Ottaviano, G. I. (2001). Growth and agglomeration. International Economic Review, 42(4). doi:10.1111/1468-2354.00141.
Moreno, R., Paci, R., & Usai, S. (2005). Spatial spillovers and innovation activity in European regions. Environment and Planning, 37(10). doi: 10.1068/a37341.
Paas, T., Kuusk, A., Schlitte, F., & V?rk, A. (2007). Econometric analysis of income convergence in selected EU countries and their Nuts 3 level regions. SSRN Electronic Journal. doi:10.2139/ssrn.1078863.
Pakes, A., & Griliches, Z. (1980). Patents and R&D at the firm level: a first report. Economics Letters, 5(4). doi: 10.1016/0165-1765(80)90136-6.
Pohulak-Żołędowska, E. (2016). Innovation in contemporary economies. Oeconomia Copernicana, 7(3). doi: http:10.12775/OeC.2016.026.
Rebelo, S. (1991). Long-run policy analysis and long-run growth. Journal of Political Economy, 99(3).
Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98(5, Part 2). doi: 10.1086/261725.
Sokolov-Mladenović, S., Cvetanović, S., & Mladenović, I. (2016). R&D expenditure and economic growth: EU28 evidence for the period 2002?2012. Economic Research-Ekonomska Istraživanja, 29(1). doi: 10.1080/1331677X.2016. 1211948.
Smith, E. T. (2014). Spatial weight matrices. Retrevied from http://www.seas.upenn.edu/~ese502/lab-content/extra_materials/SPATIAL%20 WEIGHT%20MATRICES.pdf (12.04.2014).
Solow, R. A. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1).
Stel, A. J., & Nieuwenhuijsen, H. R. (2004). Knowledge spillovers and economic growth: an analysis using data of Dutch regions in the period 1987?1995. Regional Studies, 38(4). doi: 10.1080/03434002000213914.
Viton, P. A. (2010). Notes on spatial econometric models. Retrevied from http://facweb.knowlton.ohio-state.edu/pviton/courses2/crp8703/spatial.pdf (15.02.2015).
http://ec.europa.eu/eurostat/ (10.02.2016).
https://geodacenter.asu.edu/software/downloads (15.02.2015).
http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units (15.02.2015).