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Local and Spatial Cointegration in the Wage Curve: A Spatial Panel Analysis for German Regions

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  • Reinhold Kosfeld
  • Christian Dreger

Abstract

The wage curve introduced by Blanchflower and Oswald (1990, 1994) postulates a negative correlation between wages and unemployment. Empirical results focus on particular theoretical channels establishing the relationship. Panel models mostly draw on unionized bargaining or the efficiency wage hypothesis. Spatial econometric approaches can be rationalized by monopsonistic competition. However, the approaches either ignore the issue of nonstationarity or treat the data as if it were nonspatial. In this paper, we adopt a global cointegration approach recently proposed by Bienstock and Felsenstein (2010) to account for nonstationarity of regional data. By specifying a spatial error correction model (SpECM), equilibrium adjustments are considered in both space and time. Applying the methodology for West German labour markets, we find strong evidence for the existence of a long-run wage curve with spatial effects.

Suggested Citation

  • Reinhold Kosfeld & Christian Dreger, 2015. "Local and Spatial Cointegration in the Wage Curve: A Spatial Panel Analysis for German Regions," Discussion Papers of DIW Berlin 1538, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1538
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    Cited by:

    1. David Blanchflower & Alex Bryson & Jackson Spurling, 2024. "The wage curve after the Great Recession," Economica, London School of Economics and Political Science, vol. 91(362), pages 653-668, April.
    2. Persyn, Damiaan, 2021. "Aggregation bias in wage rigidity estimation," MPRA Paper 106464, University Library of Munich, Germany.
    3. Kosfeld, Reinhold & Dreger, Christian, 2019. "Towards an East German wage curve - NUTS boundaries, labour market regions and unemployment spillovers," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 115-124.
    4. Triki, Mohamed Bilel, 2019. "The Italian wage curve revisited: A local and spatial cointegration," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 73-90.
    5. Damiaan Persyn, 2020. "Spatial aggregation bias in wage curve and NAWRU estimation," JRC Working Papers on Territorial Modelling and Analysis 2020-02, Joint Research Centre.
    6. Demidova, O. & Timofeeva, E., 2021. "Spatial aspects of wage curve estimation in Russia," Journal of the New Economic Association, New Economic Association, vol. 51(3), pages 69-101.

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    More about this item

    Keywords

    Wage curve; regional labour markets; spatial panel models; global cointegration analysis;
    All these keywords.

    JEL classification:

    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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