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Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors

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  • Solmaria Halleck Vega
  • J. Paul Elhorst

Abstract

Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors. Spatial Economic Analysis. Although there is an abundant regional labour market literature taking a spatial perspective, only a few studies have explored extending the analysis of labour force participation with spatial effects. This paper revisits this important issue, proposing a time–space recursive modelling approach that builds on and appraises Fogli and Veldkamp’s methodology from 2011 and finding for the United States that participation rates vary with past values in nearby regions. Major shortcomings in their study are corrected for, including stationarity and the control for endogenous regressors other than the time and space–time-lagged dependent variable using system generalized method of moments (GMM). The paper also highlights interaction effects among explanatory variables for the first time in this context. Using a panel of 108 regions across the European Union over 1986–2010, the results for total, male and female participation rates throw a new light on the socio-economic relevance of different determinants. Importantly, characteristics in neighbouring regions play a significant role, and neglecting endogeneity is found to have serious consequences, underlining increased attention on the specification and estimation of spatial econometric models with endogenous regressors.

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  • Solmaria Halleck Vega & J. Paul Elhorst, 2017. "Regional labour force participation across the European Union: a time–space recursive modelling approach with endogenous regressors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 138-160, July.
  • Handle: RePEc:taf:specan:v:12:y:2017:i:2-3:p:138-160
    DOI: 10.1080/17421772.2016.1224374
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    1. Richard Blundell & Howard Reed & Thomas M. Stoker, 2003. "Interpreting Aggregate Wage Growth: The Role of Labor Market Participation," American Economic Review, American Economic Association, vol. 93(4), pages 1114-1131, September.
    2. Blanchard, Olivier & Wolfers, Justin, 2000. "The Role of Shocks and Institutions in the Rise of European Unemployment: The Aggregate Evidence," Economic Journal, Royal Economic Society, vol. 110(462), pages 1-33, March.
    3. 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.
    4. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    5. 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.
    6. Franzese, Robert J. & Hays, Jude C., 2007. "Spatial Econometric Models of Cross-Sectional Interdependence in Political Science Panel and Time-Series-Cross-Section Data," Political Analysis, Cambridge University Press, vol. 15(2), pages 140-164, April.
    7. Martin Falk & Thomas Leoni, 2010. "Regional Female Labour Force Participation: An Empirical Application with Spatial 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 12, pages 309-326, AIEL - Associazione Italiana Economisti del Lavoro.
    8. Luc Anselin, 2003. "Spatial Externalities, Spatial Multipliers, And Spatial Econometrics," International Regional Science Review, , vol. 26(2), pages 153-166, April.
    9. Ian Gordon & Ian Molho, 1985. "Women in the Labour Markets of the London Region: A Model of Dependence and Constraint," Urban Studies, Urban Studies Journal Limited, vol. 22(5), pages 367-386, October.
    10. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    11. J. Paul Elhorst & Annette S. Zeilstra, 2007. "Labour force participation rates at the regional and national levels of the European Union: An integrated analysis," Papers in Regional Science, Wiley Blackwell, vol. 86(4), pages 525-549, November.
    12. Alessandra Fogli & Laura Veldkamp, 2011. "Nature or Nurture? Learning and the Geography of Female Labor Force Participation," Econometrica, Econometric Society, vol. 79(4), pages 1103-1138, July.
    13. Decressin, Jorg & Fatas, Antonio, 1995. "Regional labor market dynamics in Europe," European Economic Review, Elsevier, vol. 39(9), pages 1627-1655, December.
    14. J. Elhorst, 2008. "A spatiotemporal analysis of aggregate labour force behaviour by sex and age across the European Union," Journal of Geographical Systems, Springer, vol. 10(2), pages 167-190, June.
    15. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    16. Danielle Venn, 2009. "Legislation, Collective Bargaining and Enforcement: Updating the OECD Employment Protection Indicators," OECD Social, Employment and Migration Working Papers 89, OECD Publishing.
    17. LeSage, James P. & Pace, Robert Kelley, 2011. "Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology," The Review of Regional Studies, Southern Regional Science Association, vol. 41(1), pages 13-26, Summer.
    18. Daron Acemoglu & David H. Autor & David Lyle, 2004. "Women, War, and Wages: The Effect of Female Labor Supply on the Wage Structure at Midcentury," Journal of Political Economy, University of Chicago Press, vol. 112(3), pages 497-551, June.
    19. Daniel P. McMillen, 2012. "Perspectives On Spatial Econometrics: Linear Smoothing With Structured Models," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 192-209, May.
    20. Korniotis, George M., 2010. "Estimating Panel Models With Internal and External Habit Formation," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 145-158.
    21. 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.
    22. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, August.
    23. 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.
    24. Julie Le Gallo & Bernard Fingleton, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances : finite sample properties," Post-Print hal-00485035, HAL.
    25. Bernard Fingleton & Enrique López‐Bazo, 2006. "Empirical growth models with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 85(2), pages 177-198, June.
    26. Vera Gács & Peter Huber, 2005. "Quantity adjustments in the regional labour markets of EU candidate countries," Papers in Regional Science, Wiley Blackwell, vol. 84(4), pages 553-574, November.
    27. Partridge, Mark D. & Rickman, Dan S., 2003. "The waxing and waning of regional economies: the chicken-egg question of jobs versus people," Journal of Urban Economics, Elsevier, vol. 53(1), pages 76-97, January.
    28. Peter Huber, 2003. "Quantity Adjustments in Candidate Countries Regional Labour Markets," ERSA conference papers ersa03p239, European Regional Science Association.
    29. Bernard Fingleton, 2011. "The empirical performance of the NEG with reference to small areas," Journal of Economic Geography, Oxford University Press, vol. 11(2), pages 267-279, March.
    30. Joachim Möller & Alisher Aldashev, 2006. "Interregional differences in labor market participation," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 26(1), pages 25-50, March.
    31. J. Paul Elhorst, 2003. "The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 709-748, December.
    32. Giuseppe Arbia & Bernard Fingleton, 2008. "New spatial econometric techniques and applications in regional science," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 311-317, August.
    33. Fleisher, Belton M & Rhodes, George, 1976. "Unemployment and the Labor Force Participation of Married Men and Women: A Simultaneous Model," The Review of Economics and Statistics, MIT Press, vol. 58(4), pages 398-406, November.
    34. Tito Boeri & Jan van Ours, 2013. "The Economics of Imperfect Labor Markets: Second Edition," Economics Books, Princeton University Press, edition 1, number 10142.
    35. Baltagi, Badi H. & Blien, Uwe & Wolf, Katja, 2012. "A dynamic spatial panel data approach to the German wage curve," Economic Modelling, Elsevier, vol. 29(1), pages 12-21.
    36. Eleonora Patacchini & Yves Zenou, 2007. "Spatial dependence in local unemployment rates," Journal of Economic Geography, Oxford University Press, vol. 7(2), pages 169-191, March.
    37. Mark D. Partridge, 2001. "Exploring the Canadian‐U.S. Unemployment and Nonemployment Rate Gaps: Are There Lessons for Both Countries?," Journal of Regional Science, Wiley Blackwell, vol. 41(4), pages 701-734, November.
    38. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    39. J. Paul Elhorst & Uwe Blien & Katja Wolf, 2007. "New Evidence on the Wage Curve," International Regional Science Review, , vol. 30(2), pages 173-191, April.
    40. Kenneth A. Small & Seiji S.C. Steimetz, 2012. "Spatial Hedonics And The Willingness To Pay For Residential Amenities," Journal of Regional Science, Wiley Blackwell, vol. 52(4), pages 635-647, October.
    41. 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.
    42. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
    43. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    44. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
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