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Tracing the Spatial Patterns of Innovation Determinants in Regional Economic Performance

dc.contributor.authorOlejnik, Alicja
dc.contributor.authorŻółtaszek, Agata
dc.date.accessioned2021-04-01T13:32:45Z
dc.date.available2021-04-01T13:32:45Z
dc.date.issued2020-12-30
dc.identifier.issn1508-2008
dc.identifier.urihttp://hdl.handle.net/11089/34913
dc.description.abstractIn this paper, we investigate innovation factors and their role in regional economic performance for a sample of 261 EU NUTS 2 regions over the period 2009–2012. In our study, we identify regions with spillover as well as drain effects of innovation factors on economic performance. The spatial analysis indicates that both regional innovativeness and regional development are strongly determined by the region’s location and “neighbourhood”, with severe consequences for Central and Eastern Europe. We assessed the impact of innovation factors and their spatial counterparts on economic performance using a spatial Durbin panel model. The model is designed to test the existence and strength of the country‑effect of innovativeness on the level of regional economic status. This allows for controlling the country‑specific socio‑economic factors, without reducing the number of degrees of freedom. Our model shows that regions benefit economically from their locational spillovers in terms of social capital. However, the decomposition of R&D expenditures revealed competition effect between internal R&D and external technology acquisition, favouring in‑house over outsourced research.en
dc.description.abstractNiniejszy artykuł analizuje rolę czynników innowacyjności w rozwoju regionalnym 261 regionów UE w latach 2009–2012. Analiza przestrzenna wskazała, że regionalna innowacyjność, a dalej rozwój regionalny, zależą nie tylko od położenia geograficznego regionu, ale i jego sąsiadów. Pociąga to za sobą szczególnie poważne konsekwencje dla Europy Środkowo‑Wschodniej. Za pomocą przestrzennego modelu panelowego Durbina ze stałymi efektami grupowymi (dla krajów), oceniliśmy wpływ czynników innowacji i ich przestrzennych odpowiedników na regionalne wyniki ekonomiczne. Pokazał on, że regiony czerpią korzyści ekonomiczne ze swoich efektów lokalizacyjnych pod względem kapitału społecznego, jednak w przypadku wydatków na badania i rozwój ujawniono efekt konkurencji między regionami.pl
dc.language.isoen
dc.publisherWydawnictwo Uniwersytetu Łódzkiegopl
dc.relation.ispartofseriesComparative Economic Research. Central and Eastern Europe;4pl
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectregional innovationen
dc.subjectpatterns of innovationen
dc.subjectspatial spilloveren
dc.subjectcommon factorsen
dc.subjectspatial panel econometric modelen
dc.subjectinnowacjność regionówpl
dc.subjectwzorce innowacjipl
dc.subjectprzestrzenne rozprzestrzenianiepl
dc.subjectczynniki wspólnepl
dc.subjectprzestrzenny ekonometryczny model panelowypl
dc.titleTracing the Spatial Patterns of Innovation Determinants in Regional Economic Performanceen
dc.title.alternativeOkreślenie przestrzennych wzorców determinant innowacji w regionalnych wynikach gospodarczychpl
dc.typeArticle
dc.page.number87-108
dc.contributor.authorAffiliationOlejnik, Alicja - Department of Spatial Econometrics, Institute of Spatial Economy, Faculty of Economics and Sociology, University of Lodz, Polanden
dc.contributor.authorAffiliationŻółtaszek, Agata - Department of Spatial Econometrics, Institute of Spatial Economy, Faculty of Economics and Sociology, University of Lodz, Polanden
dc.identifier.eissn2082-6737
dc.referencesAnselin, L. (1998), Spatial Econometrics: Methods and Models, Kluwer, Dordrecht.en
dc.referencesAnselin, L., Le Gallo, J., Jayet, H. (2008), Spatial panel econometrics, [in:] L. Mátyás, P. Sevestre (eds.) The econometrics of panel data, fundamentals and recent developments in theory and practice, 3rd ed., Kluwer, Dordrecht. https://doi.org/10.1007/978-3-540-75892-1_19en
dc.referencesAnselin, L., Varga, A., Acs, Z. (1997), Local Geographic Spillovers between University Research and High Technology Innovations, “Journal of Urban Economics”, 42 (3), pp. 422–448. https://doi.org/10.1006/juec.1997.2032en
dc.referencesBilbao-Osorio, B., Rodríguez-Pose, A. (2004), From R&D to Innovation and Economic Growth in the EU, “Growth and Change”, 35 (4), pp. 434–455. https://doi.org/10.1111/j.1468-2257.2004.00256.xen
dc.referencesBoschma, R. (2005), Proximity and innovation – a critical assessment, “Regional Studies”, 39 (1), pp. 61–74. https://doi.org/10.1080/0034340052000320887en
dc.referencesBrouwer, E., Kleinknecht, A. (1999), Innovative output, and a firm’s propensity to patent. An exploration of CIS micro data, “Research Policy”, 28 (6), pp. 615–624. https://doi.org/10.1016/S0048-7333(99)00003-7en
dc.referencesCabrer-Borrás, B., Serran-Domingo, G. (2007), Innovation and R&D spillover effects in Spanish regions: A spatial approach, “Research Policy”, 36, pp. 1357–1371. https://doi.org/10.1016/j.respol.2007.04.012en
dc.referencesCaragliu, A., Nijkamp, P. (2012), The impact of regional absorptive capacity on spatial knowledge spillovers: the Cohen and Levinthal model revisited, “Applied Economics”, 44, pp. 1363–1374. https://doi.org/10.1080/00036846.2010.539549en
dc.referencesCliff, A.D., Ord, J.K. (1981), Spatial processes: models and applications, Taylor & Francis, London.en
dc.referencesCorrado, C., Haskel J., Jona-Lasinio, C. (2017), Knowledge Spillovers, ICT and Productivity Growth, “Oxford Bulletin of Economics and Statistics”, 79 (4), pp. 592–618. https://doi.org/10.1111/obes.12171en
dc.referencesCorrado, C., Hulten, Ch., Sichel, D. (2009), Intangible capital and U.S. economic growth, “The Review of Income and Wealth”, 55 (3), pp. 661–685. https://doi.org/10.1111/j.1475-4991.2009.00343.xen
dc.referencesCrescenzi, R., Rodrígue-Pose, A., Storper, M. (2007), The territorial dynamics of innovation: a Europe – United States comparative analysis, “Journal of Economic Geography”, 7 (6), pp. 673–709. https://doi.org/10.1093/jeg/lbm030en
dc.referencesDominicis, L. de, Florax, R.J.G.M., Groot, H.L.F. de (2013), Regional clusters of innovative activity in Europe: are social capital and geographical proximity key determinants?, “Applied Economics”, 45 (17), pp. 2325–2335. https://doi.org/10.1080/00036846.2012.663474en
dc.referencesEducational attainment statistics. http://ec.europa.eu/eurostat/statistics-explained/index.php/Educational_attainment_statistics (accessed: 23.02.2020).en
dc.referencesElhorst, J.P. (2014), Spatial Panel Models, [in:] M. Fischer, P. Nijkamp (eds.) Handbook of Regional Science, Berlin, Springer. https://doi.org/10.1007/978-3-642-23430-9_86en
dc.referencesElhorst, J.P., Gross M., Tereanu E. (2018), Spillovers in space and time: where spatial econometrics and Global VAR models meet, European, Central Bank, Frankfurt, Working Paper Series, No. 2134.en
dc.referencesEuropean Innovation Scoreboard 2016. https://op.europa.eu/en/publication-detail/-/publication/693eaaba-de16-11e6-ad7c-01aa75ed71a1/language-en/format-PDF/source-31233711 (accessed: 23.02.2020).en
dc.referencesEurostat Regional Database. https://ec.europa.eu/eurostat/web/regions/data/database (accessed: 23.02.2020).en
dc.referencesFrascati Manual (2002). https://www.oecd-ilibrary.org/science-and-technology/frascati-manual-2002_9789264199040-en (accessed: 23.02.2020).en
dc.referencesGlobal Innovation Index 2016 report. http://www.wipo.int/edocs/pubdocs/en/wipo_pub_gii_2016.pdf (accessed: 23.02.2020).en
dc.referencesGlobal Innovation Index 2017 report. https://www.globalinnovationindex.org/userfiles/file/reportpdf/gii-full-report-2017.pdf (accessed: 23.02.2020).en
dc.referencesGlobal Innovation Index 2018 report. https://www.globalinnovationindex.org/userfiles/file/reportpdf/gii_2018-report-new.pdf (accessed: 23.02.2020).en
dc.referencesGlobal Innovation Index 2019 report. https://www.globalinnovationindex.org/userfiles/file/reportpdf/GII2019-keyfinding-E-Web3.pdf (accessed: 23.02.2020).en
dc.referencesGonçalves, E., Almaida, E.S. (2009), Innovation and Spatial Knowledge Spillovers: Evidence from Brazilian Patent Data, “Regional Studies”, 43 (4), pp. 513–528. https://doi.org/10.1080/00343400701874131en
dc.referencesGranovetter, M. (2005), The impact of social structure on economic outcomes, “Journal of Economic Perspectives”, 19 (1), pp. 33–50. https://doi.org/10.1257/0895330053147958en
dc.referencesGriliches, Z. (1979), Issues in assessing the contribution of research and development to productivity growth, “Bell Journal of Economics”, 10 (1), pp. 92–116. https://doi.org/10.2307/3003321en
dc.referencesHalleck, V.S., Elhorst J.P. (2016), A regional unemployment model simultaneously accounting for serial dynamics, spatial dependence and common factors, “Regional Science and Urban Economics”, 60, pp. 85–95. https://doi.org/10.1016/j.regsciurbeco.2016.07.002en
dc.referencesJaffe, A.B. (1989), Real effects of academic research, “American Economic Review”, 79 (5), pp. 957–970.en
dc.referencesKelejian, H.H., Prucha, I.R. (1998), A Generalised Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances, “The Journal of Real Estate Finance and Economics”, 17 (1), pp. 99–121.en
dc.referencesKelejian, H.H., Prucha, I.R. (2010), Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances, “Journal of Econometrics”, 157 (1), pp. 53–67. https://doi.org/10.1016/j.jeconom.2009.10.025en
dc.referencesLeSage, J., Pace, R.K. (2009), Introduction to Spatial Econometrics, Taylor & Francis Group, New York. https://doi.org/10.1201/9781420064254en
dc.referencesMoran, P.A.P. (1948), The Interpretation of Statistical Maps, “Journal of the Royal Statistical Society”, Series B (Methodological), 10 (2), pp. 243–251. https://doi.org/10.1111/j.2517-6161.1948.tb00012.xen
dc.referencesOlejnik, J., Olejnik, A. (2020), QML estimation with non summable weight matrices, “Journal of Geographical Systems”, 22, pp. 469–495. https://doi.org/10.1007/s10109-020-00326-2en
dc.referencesOrd, K. (1975), Estimation Methods for Models of Spatial Interaction, “Journal of the American Statistical Association”, 70, pp. 120–126. https://doi.org/10.1080/01621459.1975.10480272en
dc.referencesRegional Innovation Scoreboard 2016 report. https://op.europa.eu/en/publication-detail/-/publication/693eaaba-de16-11e6-ad7c-01aa75ed71a1/language-en/format-PDF/source-31233711 (accessed: 23.02.2020).en
dc.referencesRegional Innovation Scoreboard 2017 report. https://op.europa.eu/en/publication-detail/-/publication/ce38bc9d-5562-11e7-a5ca-01aa75ed71a1/language-en/format-PDF/source-99532255 (accessed: 23.02.2020).en
dc.referencesRegional Innovation Scoreboard 2019 report. https://ec.europa.eu/growth/sites/growth/files/ris2019.pdf (accessed: 23.02.2020)en
dc.referencesShi, W., Lee, L.F. (2017), Spatial dynamic panel data model with interactive fixed effects, “Journal of Econometrics”, 197, pp. 323–347. https://doi.org/10.1016/j.jeconom.2016.12.001en
dc.contributor.authorEmailOlejnik, Alicja - alicja.olejnik@uni.lodz.pl
dc.contributor.authorEmailŻółtaszek, Agata - agata.zoltaszek@uni.lodz.pl
dc.identifier.doi10.18778/1508-2008.23.29
dc.relation.volume23


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