Interregional R and D spillovers and regional convergence: a spatial econometric evidence from the EU regions

Abstract

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.

Tourism and regional growth in the Carpathian Euroregion – a panel data approach

“…We analysed the impact of tourism on economic growth for 2005-2015 by employing a conditional βconvergence model, following Barro and Sala-i-Martin (1992). The topic of economic convergence and economic growth has been extensively researched (e.g., De la Fuente,1997; Eckey andTürk, M., 2007, Goecke andHüther, 2016;Výrostová, 2016;Furková a Chocholatá, 2017, Butkus et al, 2018. The βconvergence model is based on Solow's neoclassical growth model ( 1956), a growth regression framework with the level of initial income as the key explanatory variable.…”

Modifiable Areal Unit Problem: the issue of determining the relationship between microparameters and a macroparameter

“…Therefore, there are more scientific works, where the dimension of space is taken into account for the studied economic phenomena. The subject literature presents analyses of the spatial diversity of the phenomena studied (see Balcerzak, 2016a;2016b;2017;Nowak, 2018;Semenko et al, 2019), the results of the use of taxonomic methods for region analysis (see Smékalová et al, 2015;Simionescu, 2016;Reiff et al, 2016;Kuc, 2017a;Tvaronavičienė & Razminienė, 2017;Hlaváček & Siviček, 2017;Rollnik-Sadowska & Dąbrowska, 2018;Kljucnikov et al, 2018;Rogalska, 2018;Horská et al, 2019), the results of the use of spatial statistics methods allowing the identification of spatial dependencies and measurement of spatial autocorrelation (see Furková & Chocholatá, 2017) and the results of the use of spatial econometrics models (see Pietrzak, 2012;Bal-Domańska, 2016;Kuc, 2017b).…”

Intensywność nakładów na badania i rozwój w regionach Unii Europejskiej w ujęciu przestrzennym

“…Coraz mocniej akcentuje siê przy tym podejoecie przestrzenne [Martín, Mulas-Granados, Sanz, 2005, s. 41-61;Maggioni, Uberti, 2007, s. 230-255;Narula, Santangelo, 2009, s. 393-403], które uwzglêdnia specyfikê ka¿dego regionu, wymagaj¹c¹ stosowania indywidualnie dopasowanych narzêdzi wsparcia [Benos, Karagiannis, Karkalakos, 2015;McCann, Ortega-Argilés, 2015, s. 1291-1302Rodríguez-Pose, 2015]. Zgodnie z aktualnym podejoeciem potencja³ badawczy i technologiczny regionu zale¿y od szeregu specyficznych czynników, takich jak kultura biznesu, kapita³ ludzki, edukacja i instytucje badawcze, us³ugi wspieraj¹ce innowacje, mechanizmy transferu technologii, infrastruktura regionalna, mobilnooeae badaczy, Ÿród³a finansowania czy pomys³owooeae podmiotów w regionie [Peiro-Palomino, 2016;European Union, 2017, s. 152], ale tak¿e od czynników geograficznych, co prowadzi do przestrzennej koncentracji potencja³u innowacyjnego oraz wzrostu dysproporcji miêdzyregionalnych w UE [Alexiadis, Korres, 2010;de Dominicis, Florax, de Groot, 2011;Furková, Chocholatá, 2017].…”