IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/205.html
   My bibliography  Save this paper

Network Dependency in Migration Flows – A Space-time Analysis for Germany since Re-unification

Author

Listed:
  • Mitze, Timo

Abstract

The contribution of this paper is to analyse the role of network interdependencies in a dynamic panel data model for German internal migration flows since re-unification. So far, a capacious account of spatial patterns in German migration data is still missing in the empirical literature. In the context of this paper, network dependencies are associated with correlations of migration flows strictly attributable to proximate flows in geographic space. Using the neoclassical migration model, we start from its aspatial specification and show by means of residual testing that network dependency effects are highly present. We then construct spatial weighting matrices for our system of interregional flow data and apply spatial regression techniques to properly handle the underlying space-time interrelations. Besides spatial extensions to the Blundell-Bond (1998) system GMM estimator in form of the commonly known spatial lag and unconstrained spatial Durbin model, we also apply system GMM to spatially filtered variables. Finally, combining both approaches to a mixed spatial filteringregression specification shows a remarkably good performance in terms of capturing spatial dependence in our migration equation and at the same time qualify the model to pass essential IV diagnostic tests. The basic message for future research is that space-time dynamics is highly relevant for modelling German internal migration flows.

Suggested Citation

  • Mitze, Timo, 2010. "Network Dependency in Migration Flows – A Space-time Analysis for Germany since Re-unification," Ruhr Economic Papers 205, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:205
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/45310/1/635643774.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation," MPRA Paper 11569, University Library of Munich, Germany, revised Nov 2008.
    3. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(2), pages 167-196.
    4. Brian Cushing & Jacques Poot, 2004. "Crossing boundaries and borders: Regional science advances in migration modelling," Advances in Spatial Science, in: Raymond J. G. M. Florax & David A. Plane (ed.), Fifty Years of Regional Science, pages 317-338, Springer.
    5. Michele Battisti & Gianfranco Vaio, 2009. "A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 105-121, Springer.
    6. Matías Mayor & Ana Jesús López, 2009. "Spatial shift-share analysis versus spatial filtering: an application to Spanish employment data," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 123-142, Springer.
    7. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    8. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    9. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    10. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    11. Iara, Anna & Traistaru, Iulia, 2004. "How flexible are wages in EU accession countries?," Labour Economics, Elsevier, vol. 11(4), pages 431-450, August.
    12. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    13. Björn Alecke & Timo Mitze & Gerhard Untiedt, 2010. "Internal migration, regional labour market dynamics and implications for German East-West disparities: results from a Panel VAR," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 30(2), pages 159-189, September.
    14. Salima Bouayad-Agha & Lionel Védrine, 2010. "Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 205-227.
    15. repec:zbw:rwirep:0083 is not listed on IDEAS
    16. Mitze, Timo, 2009. "Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or not IV?," Ruhr Economic Papers 83, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Jesús Mur & Ana Angulo, 2006. "The Spatial Durbin Model and the Common Factor Tests," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 207-226.
    18. Raymond J. G. M. Florax & Arno J. Van der Vlist, 2003. "Spatial Econometric Data Analysis: Moving Beyond Traditional Models," International Regional Science Review, , vol. 26(3), pages 223-243, July.
    19. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    20. repec:zbw:rwirep:0096 is not listed on IDEAS
    21. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ilse Ruyssen & Glenn Rayp, 2014. "Determinants of Intraregional Migration in Sub-Saharan Africa 1980-2000," Journal of Development Studies, Taylor & Francis Journals, vol. 50(3), pages 426-443, March.
    2. Rayp, Glenn & Ruyssen, Ilse & Standaert, Samuel, 2017. "Measuring and Explaining Cross-Country Immigration Policies," World Development, Elsevier, vol. 95(C), pages 141-163.

    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. repec:zbw:rwirep:0205 is not listed on IDEAS
    2. Timo Mitze, 2010. "Network Dependency in Migration Flows – A Space-time Analysis for Germany since Re-unification," Ruhr Economic Papers 0205, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    3. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    4. Seo-Young Cho & Axel Dreher & Eric Neumayer, 2014. "Determinants of Anti-Trafficking Policies: Evidence from a New Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 116(2), pages 429-454, April.
    5. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    6. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    7. Carmelo Algeri & Antonio F. Forgione & Carlo Migliardo, 2022. "Do spatial dependence and market power matter in the diversification of cooperative banks?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    8. Björn Alecke & Timo Mitze & Gerhard Untiedt, 2010. "Internal migration, regional labour market dynamics and implications for German East-West disparities: results from a Panel VAR," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 30(2), pages 159-189, September.
    9. Salima Bouayad Agha & Nadine Turpin & Lionel Vedrine, 2010. "Fostering the potential endogenous development of European regions: a spatial dynamic panel data analysis of the Cohesion Policy on regional convergence over the period 1980-2005," Working Papers halshs-00812077, HAL.
    10. Timo Mitze, 2012. "Within and Between Panel Cointegration in the German Regional Output–Trade–FDI Nexus," Lecture Notes in Economics and Mathematical Systems, in: Empirical Modelling in Regional Science, edition 127, chapter 0, pages 191-215, Springer.
    11. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2014. "Spatial agglomeration and firm exit: a spatial dynamic analysis for Italian provinces," Small Business Economics, Springer, vol. 43(1), pages 213-228, June.
    12. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    13. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    14. Yongfu Huang & M. G. Quibria, 2013. "Green Growth: Theory and Evidence," WIDER Working Paper Series wp-2013-056, World Institute for Development Economic Research (UNU-WIDER).
    15. Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    16. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.
    17. Marbuah, George & Gren, Ing-Marie & Tirkaso, Wondmagegn Tafesse, 2021. "Social capital, economic development and carbon emissions: Empirical evidence from counties in Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    18. Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2009. "Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors," Other publications TiSEM d473cc67-03f6-4389-9a9f-3, Tilburg University, School of Economics and Management.
    19. Breidenbach, Philipp & Mitze, Timo & Schmidt, Christoph M., 2016. "EU structural funds and regional income convergence: A sobering experience," Ruhr Economic Papers 608, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    20. Fidrmuc, Jarko & Degler, Moritz, 2021. "Temporal And Spatial Dependence Of Interregional Risk Sharing: Evidence From Russia," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 178-200, January.
    21. Schmidt, Christoph & Mitze, Timo & Breidenbach, Philipp, 2016. "EU Structural Funds and Regional Income Convergence – A Sobering Experience," CEPR Discussion Papers 11210, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    internal migration; dynamic panel data; Spatial Durbin Model; GMM;
    All these keywords.

    JEL classification:

    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    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:zbw:rwirep:205. See general information about how to correct material in RePEc.

    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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.