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Regional Heterogeneity, Conditional Convergence and Regional Inequality

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  • Michael Beenstock
  • Daniel Felsenstein

Abstract

Beenstock M. and Felsenstein D. Regional heterogeneity, conditional convergence and regional inequality, Regional Studies. The paper stresses the importance of accounting for regional heterogeneity in the dynamic analysis of regional economic disparities. Studies of regional growth mainly presume that regions are homogeneous in their socio-demographic composition. It is argued that the analysis of regional convergence needs to be tested conditionally, i.e. conditional upon the socio-demographic structure of the workers in the various regions. To this end, various measures of conditional regional earnings inequality are estimated using Israeli regional data for the period 1991-2002. The results show that about half of regional earnings inequality may be accounted for by the conditioning variables. Conditioning also makes a large difference to estimates of Gini and beta-convergence. Conditional beta and Gini mobility are about half their unconditional counterparts. [image omitted] Beenstock M. et Felsenstein D. L'heterogeneite regionale, la convergence sous condition et les ecarts regionaux, Regional Studies. Cet article met l'accent sur l'importance de tenir compte de l'heterogeneite regionale dans l'analyse dynamique des ecarts regionaux economiques. En regle generale, les etudes sur la croissance regionale laissent supposer que la structure socio-demographique des regions est homogene. On cherche ici a affirmer que l'analyse de la convergence regionale doit etre tester sous condition, telle la structure socio-demographique des travailleurs dans les diverses regions. Dans ce but, on estime plusieurs mesures de l'ecart des salaires regionaux sous condition a partir des donnees israeliennes pour la periode de 1991 a 2002. Les resultats laissent voir que la moitie de l'ecart des salaires regionaux environ s'explique par les conditions posees. Poser des conditions influe sensiblement sur les estimations de convergence Gini et beta. Les mobilites beta et Gini sous condition se chiffrent a environ la moitie de leurs equivalents sans condition. Heterogeneite regionale Ecart Convergence sous condition Mobilite Beenstock M. und Felsenstein D. Regionale Heterogenitat, konditionale Konvergenz und regionale Unterschiede, Regional Studies. In diesem Beitrag wird die Bedeutung einer Berucksichtigung der regionalen Heterogenitat bei einer dynamischen Analyse der regionalen wirtschaftlichen Disparitaten betont. In den meisten Studien zum Regionalwachstum wird davon ausgegangen, dass Regionen hinsichtlich ihrer soziodemografischen Zusammensetzung homogen sind. Wir argumentieren, dass die Analyse der regionalen Konvergenz konditional uberpruft werden muss, d.h. in Abhangigkeit von der soziodemografischen Struktur der Arbeitnehmer in den verschiedenen Regionen. Zu diesem Zweck schatzen wir die verschiedenen Massstabe fur die konditionalen regionalen Einkommensunterschiede mit Hilfe von Regionaldaten aus Israel fur den Zeitraum von 1991 bis 2002. Aus unseren Ergebnissen geht hervor, dass sich etwa die Halfte der regionalen Einkommensunterschiede auf die konditionierenden Variablen zuruckfuhren lasst. Die Konditionierung macht auch bei den Schatzungen des Gini-Koeffizienten und der Beta-Konvergenz einen erheblichen Unterschied. Die konditionale Beta- und Gini-Mobilitat betragt etwa die Halfte ihrer nicht konditionalen Vergleichswerte. Regionale Homogenitat Ungleichheit Konditionale Konvergenz Mobilitat Beenstock M. y Felsenstein D. Heterogeneidad regional, convergencia condicional y desigualdades regionales, Regional Studies. En este ensayo recalcamos la importancia de tener en cuenta la heterogeneidad regional en el analisis dinamico de las desigualdades economicas a nivel regional. En los estudios de crecimiento regional se supone principalmente que las regiones son homogeneas en su composicion sociodemografica. Sostenemos que debe comprobarse condicionalmente el analisis de la convergencia regional, es decir, condicional en la estructura sociodemografica de los trabajadores en las diferentes regiones. Con este fin calculamos las diferentes medidas de las desigualdades salariales condicionales en las regiones usando datos regionales de Israel durante el periodo de 1991 a 2002. Nuestros resultados indican que aproximadamente la mitad de las desigualdades salariales regionales se deben a variables condicionales. Este acondicionamiento tambien muestra grandes diferencias en los calculos del indice Gini y la convergencia beta. La movilidad condicional de beta y Gini representan casi la mitad de su equivalentes incondicionales. Homogeneidad regional Desigualdad Convergencia condicional Movilidad

Suggested Citation

  • Michael Beenstock & Daniel Felsenstein, 2008. "Regional Heterogeneity, Conditional Convergence and Regional Inequality," Regional Studies, Taylor & Francis Journals, vol. 42(4), pages 475-488.
    • Handle: RePEc:taf:regstd:v:42:y:2008:i:4:p:475-488
    DOI: 10.1080/00343400701291500
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    3. Sidorov, Alexander, 2011. "The Impact of Exogenous Asymmetry on Trade and Agglomeration in Core-Periphery Model," MPRA Paper 29627, University Library of Munich, Germany.
    4. Mapa, Dennis S & Sandoval, Monica Flerida B & Yap, David Joseph Emmanuel B, 2009. "Investigating the Presence of Regional Economic Growth Convergence in the Philippines using Kalman Filter," MPRA Paper 20681, University Library of Munich, Germany.
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    6. Daniel Felsenstein, 2011. "Capital Deepening and Regional Inequality: An Empirical Analysis (refereed paper)," ERSA conference papers ersa10p759, European Regional Science Association.
    7. Dimitris Kallioras & Vassilis Monastiriotis & George Petrakos, 2018. "Spatial dynamics and agglomeration forces in the external EU periphery," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(3), pages 591-612, May.
    8. Michael Beenstock & Daniel Felsenstein, 2010. "Marshallian theory of regional agglomeration," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 155-172, March.
    9. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    10. Vito Imbrenda & Rosa Coluzzi & Valerio Di Stefano & Gianluca Egidi & Luca Salvati & Caterina Samela & Tiziana Simoniello & Maria Lanfredi, 2022. "Modeling Spatio-Temporal Divergence in Land Vulnerability to Desertification with Local Regressions," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
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    12. Daniel Shefer & Malka Antonio, 2013. "Spatial Inequality Between and Within Urban Areas: The Case of Israeli Cities," European Planning Studies, Taylor & Francis Journals, vol. 21(3), pages 373-387, March.
    13. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    14. Vera A. Adamchik & Thomas J. Hyclak, 2013. "The Evolution Of Regional Wage Differentials In A Transition Economy: Evidence From Poland," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 7(5), pages 1-13.
    15. Michael Beenstock & Daniel Felsenstein & Nadav Ben Zeev, 2011. "Capital deepening and regional inequality: an empirical analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(3), pages 599-617, December.

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