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Sources of German unemployment: a structural vector error correction analysis

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  • Ralf Brüggemann

Abstract

In this paper we analyze the sources of German unemployment within a structural vector error correction model (SVECM) framework. For this purpose, we propose a method to estimate an exactly identified Subset SVECM, which is a SVECM with short run parameter restrictions. A cointegration analysis for the unified Germany reveals a long rum relationship between real wages, productivity and unemployment which is interpreted as a wage setting relation. From a Subset VECM we identify meaningful structural shocks and assess their importance for unemployment by impulse response analysis and forecast error variance decompositions. We compare these results to results from a standard SVECM and find that, using the Subset VECM reduces estimation uncertainty. In contrast to previous studies for West Germany, we find that, unemployment is equally determined by technology, labor supply and labor demand shocks in the long run. - Unemployment ; Subset VECM ; Structural VECM ; Bootstrap ; Cointegration
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  • Ralf Brüggemann, 2006. "Sources of German unemployment: a structural vector error correction analysis," Empirical Economics, Springer, vol. 31(2), pages 409-431, June.
  • Handle: RePEc:spr:empeco:v:31:y:2006:i:2:p:409-431
    DOI: 10.1007/s00181-005-0021-x
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    4. Antoine Kamiantako Miyamueni & Henry Ngongo Muganza, 2018. "Chocs technologiques, chocs des prix et fluctuations du ch\^omage en R\'epublique D\'emocratique du Congo," Papers 1804.09532, arXiv.org.
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    8. Andreas Röthig, 2011. "On speculators and hedgers in currency futures markets: who leads whom?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(1), pages 63-69, January.
    9. Juan José Echavarría Soto & Enrique López Enciso & Martha Misas Arango, 2008. "El tipo de cambio real de equilibrio en Colombia y su desalineamiento: estimación a través de un modelo SVEC," Investigación Conjunta-Joint Research, in: Centro de Estudios Monetarios Latinoamericanos (CEMLA) (ed.), Estimación y Uso de Variables no Observables en la Región, edition 1, volume 1, chapter 12, pages 365-395, Centro de Estudios Monetarios Latinoamericanos, CEMLA.
    10. Tafirenyika Sunde & Olusegun A. Akanbi, 2016. "Sources of unemployment in Namibia: an application of the structural VAR approach," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 8(2), pages 125-143.
    11. Juan José Echavarría Soto & Enrique López Enciso & Martha Misas Arango, 2008. "La tasa de cambio real de equilibrio en Colombia y su desalineamiento: estimación a través de un modelo SVEC," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 26(57), pages 282-319, December.
    12. Mosso-Martínez, Margarita M. & López-Herrera, Francisco, 2020. "Variables económicas y deterioro de la calidad de la cartera de hipotecas bursatilizadas en México," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(52), pages 47-68, Primer se.
    13. Maciej Bukowski & Grzegorz Koloch & Piotr Lewandowski, 2013. "Shocks and rigidities as determinants of CEE labour markets’ performance," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 21(3), pages 553-581, July.
    14. Firew B Woldeyes, 2013. "Long-Run Effects of Resource Rents in Developing Countries: The role of public investment management," OxCarre Working Papers 105, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    15. Haffar, Adlane & Le Fur, Eric, 2021. "Structural vector error correction modelling of Bitcoin price," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 170-178.
    16. Martha Misas Arango & Enrique López Enciso & Juana Téllez Corredor & José Fernando Escobar, 2005. "La Inflación Subyacente en Colombia: Un Enfoque de Tendencias Estocásticas Comunes Asociadas a un VEC Estructural," Borradores de Economia 324, Banco de la Republica de Colombia.
    17. Ilhan Dogus, 2019. "Rising wage differential between white-collar and blue-collar workers and market concentration: The case of the USA, 1964-2007," PSL Quarterly Review, Economia civile, vol. 72(290), pages 223-251.
    18. Silvia Fedeli & Francesco Forte, 2009. "The Laffer effects of a program of deregulation cum detaxation: the Italian reform of labour contracts in the period 1997–2001," European Journal of Law and Economics, Springer, vol. 27(3), pages 211-232, June.
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    20. Klemens Hauzenberger & Robert Stehrer, 2010. "An Empirical Characterization of Redistribution Shocks and Output Dynamics," wiiw Working Papers 68, The Vienna Institute for International Economic Studies, wiiw.
    21. Anita Staneva, 2008. "Analysis of the Labour Market in Bulgaria through a Error Correction Model," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 90-106.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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