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Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S.: A VAR-GARCH-M Approach

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  • Gianluigi Pelloni

    (Department of Economics, Faculty of Political Science, University of Pisa, Via Serafini, 3, Pisa, I-56126, Italy)

  • Wolfgang Polasek

    (Department of Statistics and Economics, University of Basel, CH-4051, Basel, Switzerland)

Abstract

A VAR-GARCH-M model for aggregate employment and employment shares is developed to explore the macroeconomic effects of sectoral shocks. Using U.S., U.K. and German data, three main issues are investigated: the relevance of shocks volatility; the amount of aggregate employment growth variation accounted for by re-allocation shocks and the amount of aggregate innovation volatility explained by sectoral components. Bayesian methods are used for estimation model selection and innovation accounting -- Bayes factors for model selection and MCMC for estimation. The results favor the VAR-GARCH-M model. A significant GARCH-M component indicates the presence of volatility clustering and the feedback of volatilities on aggregate employment and sectoral shares growth rates. The innovation analysis supports sectoral shocks as a triggering force for aggregate employment fluctuations. In all three countries, 45% to 55% of aggregate employment variation is accounted for by sectoral innovations.

Suggested Citation

  • Gianluigi Pelloni & Wolfgang Polasek, 2003. "Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S.: A VAR-GARCH-M Approach," Computational Economics, Springer;Society for Computational Economics, vol. 21(1_2), pages 65-85, February.
    • Handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:65-85
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    Cited by:

    1. James D. Hamilton, 2008. "Macroeconomics and ARCH," NBER Working Papers 14151, National Bureau of Economic Research, Inc.
    2. Reicher, Christopher Phillip, 2011. "A tale of two countries: A comparison of the aggregate effects of sectoral reallocation in the United States and Germany," Kiel Working Papers 1721, Kiel Institute for the World Economy (IfW Kiel).
    3. Panagiotidis, Theodore & Pelloni, Gianluigi, 2007. "Nonlinearity In The Canadian And U.S. Labor Markets: Univariate And Multivariate Evidence From A Battery Of Tests," Macroeconomic Dynamics, Cambridge University Press, vol. 11(5), pages 613-637, November.
    4. Theodore Panagiotidis & Gianluigi Pelloni, 2014. "Asymmetry and Lilien’s Sectoral Shifts Hypothesis: A Quantile Regression Approach," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 6(1), pages 68-86, June.
    5. Dimitrios Bakas & Theodore Panagiotidis & Gianluigi Pelloni, 2017. "Regional And Sectoral Evidence Of The Macroeconomic Effects Of Labor Reallocation: A Panel Data Analysis," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 501-526, January.
    6. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 369-385, January.
    7. Pelloni, Gianluigi & Panagiotidis, Theodore, 2003. "Macroeconomic Effects of Reallocation Shock: A Generalished Impulse Response Function Analysis for Three European Countries," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 18, pages 794-816.
    8. Cathy W. S. Chen & Hong Than-Thi & Manabu Asai, 2021. "On a Bivariate Hysteretic AR-GARCH Model with Conditional Asymmetry in Correlations," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 413-433, August.
    9. Theodore Panagiotidis & Gianluigi Pelloni, 2013. "Employment Reallocation and Unemployment Revisited: A Quantile Regression Approach," Working Paper series 01_13, Rimini Centre for Economic Analysis, revised Feb 2014.
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    11. Acconcia, Antonio & Simonelli, Saverio, 2008. "Interpreting aggregate fluctuations looking at sectors," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 3009-3031, September.
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