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Multilevel Models: An Application To The Beta-Convergence Model

Author

Listed:
  • Coro CHASCO

    (Department of Applied Economics, Universidad Autónoma de Madrid (Spain))

  • Ana Mª LÓPEZ

    (Department of Applied Economics, Universidad Autónoma de Madrid (Spain))

Abstract

Many kinds of data in the social sciences have a hierarchical, multilevel or clustered structure. For example, municipalities are grouped into regions; regions are formed within countries; and quite often, countries belong to supra-national organizations. Once groupings are established, they will tend to become differentiated, and this differentiation implies that the group and its members both influence and are influenced by group membership. To ignore this relationship is to risk overlooking the importance of group effects and it may also render invalid many of the traditional statistical analysis techniques used for studying data relationships. In this paper, we specify a basic two-level model for a conditional beta-convergence model of a sample of European NUTS-2 regions. Specifically, we test for the role of regional decentralization (country-level variable) on regional income growth, since it has been suggested that countries with a governmental form of regional decentralization foster innovation and economic growth.

Suggested Citation

  • Coro CHASCO & Ana Mª LÓPEZ, 2009. "Multilevel Models: An Application To The Beta-Convergence Model," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 30, pages 35-58.
    • Handle: RePEc:tou:journl:v:30:y:2009:p:35-58
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    References listed on IDEAS

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    1. Bernard Fingleton, 2003. "Models and Simulations of GDP per Inhabitant Across Europe’s Regions: A Preliminary View," Advances in Spatial Science, in: Bernard Fingleton (ed.), European Regional Growth, chapter 1, pages 11-53, Springer.
    2. Michael Bräuninger & Annekatrin Niebuhr, 2005. "Convergence, Spatial Interaction and Agglomeration Effects in the EU," ERSA conference papers ersa05p528, European Regional Science Association.
    3. Michael Bräuninger & Annekatrin Niebuhr, 2008. "Agglomeration, Spatial Interaction and Convergence in the EU," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(3), pages 329-349.
    4. BAUMONT, Catherine & ERTUR, Cem & LE GALLO, Julie, 2001. "A Spatial Econometric Analysis of Geographic Spillovers and Growth for European Regions, 1980-1995," LATEC - Document de travail - Economie (1991-2003) 2001-04, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    5. Bernard Fingleton (ed.), 2003. "European Regional Growth," Advances in Spatial Science, Springer, number 978-3-662-07136-6.
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    Citations

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    Cited by:

    1. Felipe Santos‐Marquez & Carlos Mendez, 2021. "Regional convergence, spatial scale, and spatial dependence: Evidence from homicides and personal injuries in Colombia 2010–2018," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1162-1184, August.
    2. Venera M. Timiryanova & Konstantin E. Grishin & Natalya Z. Solodilova & Rustam I. Malikov, 2022. "Economic Growth of Municipalities in Russia: Assessment of Unevenness in Time and Space," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 21(3), pages 514-544.
    3. Fazio, Giorgio & Piacentino, Davide, 2018. "Convergence analysis for hierarchical longitudinal data," Economic Modelling, Elsevier, vol. 73(C), pages 89-99.
    4. Eduardo Almeida & Pablo Guimarães, 2014. "Economic Growth and Infrastructure in Brazil: A Spatial Multilevel Approach," ERSA conference papers ersa14p219, European Regional Science Association.

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    More about this item

    Keywords

    MULTILEVEL MODELS; HIERARCHICAL MODELS; CONVERGENCE; EUROPEAN REGIONS; DECENTRALIZATION; SPATIAL EFFECTS;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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