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Unemployment Persistence And The Nairu: A Bayesian Approach

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  • Tino Berger
  • Gerdie Everaert

Abstract

This paper estimates the United States and euro area NAIRU in a Bayesian framework. We set out a simple structural model explaining unemployment by demand and supply factors, which are treated as unobserved variables that have observable effects on measured unemployment, output and inflation. The model allows for unemployment persistence and a time‐varying core inflation rate. The results show that although cyclical shocks are very persistent, most of the increase in European unemployment is driven by structural factors. The degree of persistence is lower in the United States but demand shocks seem to be more important in explaining variation in unemployment.

Suggested Citation

  • Tino Berger & Gerdie Everaert, 2008. "Unemployment Persistence And The Nairu: A Bayesian Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(3), pages 281-299, July.
    • Handle: RePEc:bla:scotjp:v:55:y:2008:i:3:p:281-299
    DOI: 10.1111/j.1467-9485.2008.00454.x
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    References listed on IDEAS

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    1. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    2. Fabrice Orlandi & Karl Pichelmann, 2000. "Disentangling trend and cycle in the EUR-11 unemployment series," European Economy - Economic Papers 2008 - 2015 140, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
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    Citations

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    Cited by:

    1. Pedro Clavijo-Cortes, 2023. "Is unemployment hysteretic or structural? A Bayesian model selection approach," Empirical Economics, Springer, vol. 65(6), pages 2837-2866, December.
    2. Bozani, Vasiliki & Drydakis, Nick, 2011. "Studying the NAIRU and its Implications," IZA Discussion Papers 6079, Institute of Labor Economics (IZA).
    3. Kajuth Florian, 2016. "NAIRU Estimates for Germany: New Evidence on the Inflation–Unemployment Tradeoff," German Economic Review, De Gruyter, vol. 17(1), pages 104-125, February.
    4. Giorgio Canarella & Rangan Gupta & Stephen M. Miller & Stephen K. Pollard, 2019. "Unemployment rate hysteresis and the great recession: exploring the metropolitan evidence," Empirical Economics, Springer, vol. 56(1), pages 61-79, January.
    5. Tino Berger, 2011. "Estimating Europe’s natural rates," Empirical Economics, Springer, vol. 40(2), pages 521-536, April.
    6. Kajuth, Florian, 2012. "Identifying the Phillips curve through shifts in volatility," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 975-991.
    7. Gehrke, Britta & Weber, Enzo, 2018. "Identifying asymmetric effects of labor market reforms," European Economic Review, Elsevier, vol. 110(C), pages 18-40.
    8. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).
    9. Vosseler, Alexander, 2016. "Bayesian model selection for unit root testing with multiple structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 616-630.
    10. Nuhu, Peter & Bukari, Dramani & Sulemana, Yusif, 2023. "A decomposition analysis of the nexus between employment and credit in West Africa’s biggest economies," MPRA Paper 118345, University Library of Munich, Germany.
    11. Berger, Tino & Kempa, Bernd, 2011. "Bayesian estimation of the output gap for a small open economy: The case of Canada," Economics Letters, Elsevier, vol. 112(1), pages 107-112, July.

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