IDEAS home Printed from https://ideas.repec.org/p/hig/wpaper/50-ec-2014.html
   My bibliography  Save this paper

The asymmetric spatial effects for eastern and western regions of Russia

Author

Listed:
  • Olga A. Demidova

    (National Research University Higher School of Economics)

Abstract

The purpose of this study is to identify the spatial effects of the main macroeconomic indicators of the eastern and western regions of Russia. These regions differ significantly in population density and the distances between cities. The main research question we are interested in is the following: how are events occurring in one of the western regions, such as economic growth or a decrease in the unemployment rate, effecting similar indicators in other western and eastern regions. The spatial effects of the western and eastern regions, when considered separately, may differ both qualitatively and with of the ‘flow on effect’. The determinants of the same macro-economic indicators in the eastern and western regions may also differ. In order to test the hypothesis of a possible difference in the spatial effects and determinants for these regions, we have developed a special class of model with four spatial matrices (west-west, east-east, west-east, and east-west) and a double set of control variables (one for each type of region). As the macroeconomic indicators monitor the rate of unemployment in the region, the real regional wage and GRP growth for the year were chosen for our models. We controlled the variables describing the socio-demographic situation in the region, migration processes, economic development, and export-import activity in the region. The models were estimated by the Arellano-Bond method on panel data for Russian regions over 2000-2010. Our analysis revealed, 1) a positive spatial correlation of the main macroeconomic indicators for the western regions, 2) both positive and negative externalities for the eastern regions and 3) the asymmetric influence of eastern and western regions on each other. Usually “impulses” from the western regions have a positive effect on the eastern regions, but the “impulses” from the eastern regions usually do not affect the western regions.

Suggested Citation

  • Olga A. Demidova, 2014. "The asymmetric spatial effects for eastern and western regions of Russia," HSE Working papers WP BRP 50/EC/2014, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:50/ec/2014
    as

    Download full text from publisher

    File URL: http://www.hse.ru/data/2014/02/07/1327986458/50EC2014.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Konstantin A. Kholodilin & Aleksey Oshchepkov & Boriss Siliverstovs, 2012. "The Russian Regional Convergence Process," Eastern European Economics, Taylor & Francis Journals, vol. 50(3), pages 5-26, May.
    2. James Lesage & Manfred Fischer, 2008. "Spatial Growth Regressions: Model Specification, Estimation and Interpretation," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(3), pages 275-304.
    3. Fuchs-Schündeln, Nicola & Izem, Rima, 2012. "Explaining the low labor productivity in East Germany – A spatial analysis," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 1-21.
    4. Ye.A. Kolomak (ekolomak@academ.org ), 2010. "Spatial externalities as a source of economic growth," Journal "Region: Economics and Sociology", Institute of Economics and Industrial Engineering of Siberian Branch of RAS, vol. 4.
    5. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
    6. Roberto Basile, 2010. "Labour Productivity Polarization Across Western European Regions: Threshold Effects Versus Neighbourhood Effects," AIEL Series in Labour Economics, in: Floro Ernesto Caroleo & Francesco Pastore (ed.), The Labour Market Impact of the EU Enlargement. A New Regional Geography of Europe?, edition 1, chapter 4, pages 75-97, AIEL - Associazione Italiana Economisti del Lavoro.
    7. Basile, Roberto & Padoa Schioppa, Fiorella Kostoris, 2002. "Unemployment Dynamics of the 'Mezzogiornos of Europe': Lessons for the Mezzogiorno of Italy," CEPR Discussion Papers 3594, C.E.P.R. Discussion Papers.
    8. Olga Demidova & Marcello Signorelli, 2012. "Determinants of youth unemployment in Russian regions," Post-Communist Economies, Taylor & Francis Journals, vol. 24(2), pages 191-217, January.
    9. Manfred M. Fischer & James P. LeSage, 2015. "A Bayesian space-time approach to identifying and interpreting regional convergence clubs in Europe," Papers in Regional Science, Wiley Blackwell, vol. 94(4), pages 677-702, November.
    10. Oleg Lugovoy & Vladimir V. Dashkeyev & Ilya Mazaev & Denis Fomchenko & Albert Hecht, 2007. "Analysis of Economic Growth in Regions: Geographical and Institutional Aspect," Published Papers 5, Gaidar Institute for Economic Policy, revised 2007.
    11. Mark D. Partridge & Marlon Boarnet & Steven Brakman & Gianmarco Ottaviano, 2012. "Introduction: Whither Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 167-171, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Demidova, Olga, 2014. "Spatial-autoregressive model for the two groups of related regions (eastern and western parts of Russia)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 19-35.
    2. Vera Ivanova, 2018. "Spatial convergence of real wages in Russian cities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(1), pages 1-30, July.
    3. Демидова Ольга Анатольевна & Иванов Денис Сергеевич, 2016. "Модели Экономического Роста С Неоднородными Пространственными Эффектами (На Примере Российских Регионов)," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(1), pages 52-75.
    4. Vera Ivanova, 2015. "How Space Channels Wage Convergence: The Case of Russian Cities," HSE Working papers WP BRP 120/EC/2015, National Research University Higher School of Economics.
    5. Geerte Cotteleer & Tracy Stobbe & G. Cornelis van Kooten, 2011. "Bayesian Model Averaging In The Context Of Spatial Hedonic Pricing: An Application To Farmland Values," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 540-557, August.
    6. Brada, Josef C. & Gajewski, Paweł & Kutan, Ali M., 2021. "Economic resiliency and recovery, lessons from the financial crisis for the COVID-19 pandemic: A regional perspective from Central and Eastern Europe," International Review of Financial Analysis, Elsevier, vol. 74(C).
    7. Philipp Piribauer & Jesús Crespo Cuaresma, 2016. "Bayesian Variable Selection in Spatial Autoregressive Models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(4), pages 457-479, October.
    8. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    9. Jesús Crespo Cuaresma & Martin Feldkircher, 2013. "Spatial Filtering, Model Uncertainty And The Speed Of Income Convergence In Europe," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 720-741, June.
    10. Sergei Guriev & Elena Vakulenko, 2012. "Convergence between Russian regions," Working Papers w0180, New Economic School (NES).
    11. Seya, Hajime & Tsutsumi, Morito & Yamagata, Yoshiki, 2012. "Income convergence in Japan: A Bayesian spatial Durbin model approach," Economic Modelling, Elsevier, vol. 29(1), pages 60-71.
    12. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
    13. Guilherme Resende & Alexandre Carvalho & Patrícia Sakowski & Túlio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    14. Monique DANTAS & Frédéric GASCHET & Guillaume POUYANNE, 2010. "Regulatory zoning and coastal housing prices: a bayesian hedonic approach (In French)," Cahiers du GREThA (2007-2019) 2010-12, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    15. Jesus regstdpo-Cuaresma & Neil Foster & Robert Stehrer, 2011. "Determinants of Regional Economic Growth by Quantile," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 809-826.
    16. Elena Vakulenko, 2016. "Does migration lead to regional convergence in Russia?," International Journal of Economic Policy in Emerging Economies, Inderscience Enterprises Ltd, vol. 9(1), pages 1-25.
    17. Craig Wesley Carpenter & F. Carson Mencken & Charles M. Tolbert & Michael Lotspeich, 2018. "Locally Owned Bank Commuting Zone Concentration and Employer Start-Ups in Metropolitan, Micropolitan and Non-Core Rural Commuting Zones from 1970-2010," Working Papers 18-34, Center for Economic Studies, U.S. Census Bureau.
    18. Solmaria Halleck Vega & J. Paul Elhorst, 2014. "Modelling regional labour market dynamics in space and time," Papers in Regional Science, Wiley Blackwell, vol. 93(4), pages 819-841, November.
    19. Aleh Mazol, 2016. "Spatial wage inequality in Belarus," BEROC Working Paper Series 35, Belarusian Economic Research and Outreach Center (BEROC).
    20. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher, 2009. "Economic Growth Determinants for European Regions: Is Central and Eastern Europe Different?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 22-37.

    More about this item

    Keywords

    Russian regions; spatial effects; spatial econometric models;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hig:wpaper:50/ec/2014. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shamil Abdulaev or Shamil Abdulaev (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.