Open AccessInterregional R and D spillovers and regional convergence: a spatial econometric evidence from the EU regions
Author(s) -
Andrea Furková,
Michaela Chocholatá
Publication year - 2017
Publication title -
equilibrium
Language(s) - English
Resource type - Journals
eISSN - 2353-3293
pISSN - 1689-765X
DOI - 10.24136/eq.v12i1.1
Subject(s) - european union , convergence (economics) , spatial econometrics , economic geography , spatial analysis , spatial dependence , econometrics , regional science , geography , economics , lag , international trade , mathematics , economic growth , statistics , computer network , remote sensing , computer science
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.