The analysis of employment rates in the context of spatial connectivity of the EU regions

Authors

  • Michaela Chocholatá University of Economics in Bratislava
  • Andrea Furková University of Economics in Bratislava

DOI:

https://doi.org/10.24136/eq.2018.010

Keywords:

employment rate, exploratory spatial data analysis, EU NUTS 2 regions

Abstract

Research background: The main objective of this paper is to analyse the employment rates in the context of spatial connectivity of the EU regions. Employment rate is declared as one of the important indicators of the strategic document Europe 2020. The achievement of high levels of employment in individual regions plays therefore an important role.

Purpose of the article: The aim of the paper is to verify the possible spill-over effects within the EU regions and their territorial interconnection in the context of employment rates.

Methods: Analysis is based on tools of the Exploratory Spatial Data Analysis (ESDA) to consider spatial connectivity of the EU regions.

Findings & Value added: The results show that the statistically significant clusters of regions with high employment rates are situated mainly in the central, northern and north-western part of the EU while the clusters with low values are located mainly in Greece, Spain, Italy, Portugal, Bulgaria, Romania and some French regions.

Downloads

Download data is not yet available.

References

Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2). doi: 10.1111/j.1538-4632.1995.tb00338.x.

DOI: https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
View in Google Scholar

Balcerzak, A. P. (2015). Europe 2020 strategy and structural diversity between old and new member states. Application of zero-unitarization method for dynamic analysis in the years 2004–2013. Economics & Sociology, 8(2). doi: 10.14254/2071-789X.2015/8-2/14.

DOI: https://doi.org/10.14254/2071-789X.2015/8-2/14
View in Google Scholar

Barca, F., McCann, P. & Rodríguez–Pose, A. (2012). The case for regional development intervention: place-based versus place-neutral approaches. Journal of Regional Science, 52(1). doi.org/10.1111/j.1467-9787.2011.00756.x.

DOI: https://doi.org/10.1111/j.1467-9787.2011.00756.x
View in Google Scholar

Bivand, S. (2010). Exploratory spatial data analysis. In M. M. Fischer & A. Getis (Eds.). Handbook of applied spatial analysis. Software tools, methods and applications. Berlin Heidelberg: Springer–Verlag.

DOI: https://doi.org/10.1007/978-3-642-03647-7_13
View in Google Scholar

Chocholatá, M., & Furková, A. (2017). Does the location and institutional background matter in convergence modelling of the EU regions? Central European Journal of Operations Research, 25(3). doi: 10.1007/s10100-016-0447-6.

DOI: https://doi.org/10.1007/s10100-016-0447-6
View in Google Scholar

Chocholatá, M. (2018). Spatial analysis of the tertiary educational attainment in European Union. In Proceedings of the 15th International Conference Efficiency and Responsibility in Education 2018. Prague.
View in Google Scholar

Cracolici, M. F., Cuffaro, M., & Nijkamp, P. (2009). A spatial analysis on Italian unemployment differences. Statistical Methods and Applications, 18(2). doi: 10.1007/s10260-007-0087-z.

DOI: https://doi.org/10.1007/s10260-007-0087-z
View in Google Scholar

European Commission (2010). Communication from the Commission Europe 2020: a strategy for smart, sustainable and inclusive growth. Retrieved from http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2010:2020:FIN :EN:PDF (10.02.2016).
View in Google Scholar

Eurostat (2015). Administrative units, statistical units, Eurostat. Retrieved from http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-unitsstatistical-units (15.02.2015).
View in Google Scholar

Eurostat (2016). Statistics by theme. Retrieved from http://ec.europa.eu/eurostat/data/browse-statistics-by-theme (10.02.2016).
View in Google Scholar

Feldkircher, M. (2006). Regional convergence within the EU-25: a spatial econometric analysis. Retrieved from https://www.oenb.at/Publikationen/Volks wirtschaft/Workshopbaende/2006/Workshop-No.-09.html (05.01.2018)
View in Google Scholar

Fischer, M. M., & Wang, J. (2011). Spatial data analysis. Models, methods and techniques. Heidelberg Dordrecht London New York: Springer.

DOI: https://doi.org/10.1007/978-3-642-21720-3
View in Google Scholar

Franzese, R. J. & Hays, J. C. (2005). Spatial econometric modeling, with application to employment spillovers and active-labor-market policies in the European Union. Retrieved from http://www-personal.umich.edu/~franzese/ FranzeseHays.SpatialEcon.EmploymentSpillovers.ALP.pdf (10.08.2017).
View in Google Scholar

Furková, A. (2016). Spatial pattern of innovative activity in the EU regions: exploratory spatial data analysis and spatial econometric approach. In Gomes, O. & H. Martins (Eds.). Advances in applied business research: the L.A.B.S. initiative. New York: Nova Science Publishers.
View in Google Scholar

GeoDa (2015). Home page. Retrieved from https://geodacenter.asu.edu/software /downloads (15.02.2015).
View in Google Scholar

Getis, A. (2010). Spatial autocorrelation. In M. M. Fischer & A. Getis (Eds.). Handbook of applied spatial analysis. Software tools, methods and applications. Berlin Heidelberg: Springer–Verlag.

DOI: https://doi.org/10.1007/978-3-642-03647-7_14
View in Google Scholar

Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3).

DOI: https://doi.org/10.1111/j.1538-4632.1992.tb00261.x
View in Google Scholar

Haining, R. (2003). Spatial data analysis: theory and practice. Cambridge: Cambridge University Press.

DOI: https://doi.org/10.1017/CBO9780511754944
View in Google Scholar

Lottmann, F. (2012). Explaining regional unemployment differences in Germany: a spatial panel data analysis. Retrieved from http://sfb649.wiwi.hu-berlin.de (10.02.2016).
View in Google Scholar

Monastiriotis, V. (2007). Patterns of spatial association and their persistence across socio-economic indicators: the case of the Greek regions. Retrieved from http://www.lse.ac.uk/europeanInstitute/research/LSEE/PDFs/Latest%20Research/2007item4monastiriotis.pdf (25.01.2018).
View in Google Scholar

Niebuhr, A. (2003). Spatial interaction and regional unemployment in Europe. European Journal of Spatial Development, 5.
View in Google Scholar

Ord, J. K., & Getis, A. (1995). Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27(4). doi: 10.1111/j.1538-4632.1995.tb00912.x.

DOI: https://doi.org/10.1111/j.1538-4632.1995.tb00912.x
View in Google Scholar

Pagliacci, F. (2014). Europe 2020 challenges and regional imbalances. A spatial analysis. Retrieved from https://www.aisre.it/images/old_papers/Pagliacci.pdf (05.01.2017).
View in Google Scholar

Pavlyuk, D. (2011). Spatial analysis of regional employment rates in Latvia. Scientific Journal of Riga Technical University, 2.
View in Google Scholar

Perugini, C., & Signorelli, J. (2004). Employment performance and convergence in the European countries and regions. European Journal of Comparative Economics, 1(2).
View in Google Scholar

Pietrzak, M. B. & Balcerzak, A. P. (2016). A spatial SAR model in evaluating influence of entrepreneurship and investments on unemployment in Poland. In M. Reiff & P. Gezik (Eds.). Proceedings of the international scientific conference quantitative methods in economics multiple criteria decision making XVIII. Vratna: Letra Interactive.
View in Google Scholar

Smith, E. T. (2014). Spatial weight matrices. Retrieved from http://www.seas.upenn.edu/~ese502/lab-content/extra_materials/SPATIAL%2 0WEIGHT%20MATRICES.pdf (04.12.2014).
View in Google Scholar

Viton, P. A. (2010). Notes on spatial econometric models. Retrieved from http://facweb.knowlton.ohio-state.edu/pviton/courses2/crp8703/spatial.pdf (04.12.2014).
View in Google Scholar

Downloads

Published

2018-06-30

How to Cite

Chocholatá, M., & Furková, A. (2018). The analysis of employment rates in the context of spatial connectivity of the EU regions. Equilibrium. Quarterly Journal of Economics and Economic Policy, 13(2), 181–213. https://doi.org/10.24136/eq.2018.010

Issue

Section

Articles

Similar Articles

<< < 4 5 6 7 8 9 10 11 12 13 > >> 

You may also start an advanced similarity search for this article.