IDEAS home Printed from https://ideas.repec.org/a/bla/scotjp/v55y2008i3p281-299.html
   My bibliography  Save this article

Unemployment Persistence And The Nairu: A Bayesian Approach

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9485.2008.00454.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9485.2008.00454.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Gehrke, Britta & Weber, Enzo, 2018. "Identifying asymmetric effects of labor market reforms," European Economic Review, Elsevier, vol. 110(C), pages 18-40.
    3. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).
    4. Kajuth, Florian, 2012. "Identifying the Phillips curve through shifts in volatility," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 975-991.
    5. 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.
    6. Bozani, Vasiliki & Drydakis, Nick, 2011. "Studying the NAIRU and its Implications," IZA Discussion Papers 6079, Institute of Labor Economics (IZA).
    7. 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.
    8. 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.
    9. 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.
    10. Tino Berger, 2011. "Estimating Europe’s natural rates," Empirical Economics, Springer, vol. 40(2), pages 521-536, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gian Luigi Mazzi & Frédéric Reynès & Matthieu Lemoine & Paola Veroni, 2008. "Real Time Estimation of Potential Output and Output Gap for the Euro-Area : Comparing Production Function with Unobserved Components and SVAR Approaches," SciencePo Working papers Main hal-01027422, HAL.
    2. repec:spo:wpecon:info:hdl:2441/7349 is not listed on IDEAS
    3. Tino Berger, 2011. "Estimating Europe’s natural rates," Empirical Economics, Springer, vol. 40(2), pages 521-536, April.
    4. repec:hal:spmain:info:hdl:2441/7349 is not listed on IDEAS
    5. Berger, Tino & Everaert, Gerdie, 2010. "Labour taxes and unemployment evidence from a panel unobserved component model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 354-364, March.
    6. T. Berger & G. Everaert, 2006. "Re-examining the Structural and the Persistence Approach to Unemployment," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/383, Ghent University, Faculty of Economics and Business Administration.
    7. repec:hal:wpspec:info:hdl:2441/7349 is not listed on IDEAS
    8. Maximilian Grimm & Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2023. "Loose Monetary Policy and Financial Instability," Working Paper Series 2023-06, Federal Reserve Bank of San Francisco.
    9. Victor Bystrov, 2018. "Measuring the Natural Rates of Interest in Germany and Italy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(4), pages 333-353, December.
    10. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering," Econometrics, MDPI, vol. 6(4), pages 1-22, December.
    11. Fernández-Macho, Javier, 2008. "Spectral estimation of a structural thin-plate smoothing model," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 189-195, September.
    12. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    13. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
    14. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    15. François R. Velde, 2009. "Chronicle of a Deflation Unforetold," Journal of Political Economy, University of Chicago Press, vol. 117(4), pages 591-634, August.
    16. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    17. Chen, Peimin & Wu, Chunchi, 2014. "Default prediction with dynamic sectoral and macroeconomic frailties," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 211-226.
    18. Sudhanshu Kumar & Naveen Srinivasan & Muthiah Ramachandran, 2012. "A time‐varying parameter model of inflation in India," Indian Growth and Development Review, Emerald Group Publishing Limited, vol. 5(1), pages 25-50, April.
    19. repec:zbw:bofitp:2019_008 is not listed on IDEAS
    20. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    21. Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
    22. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    23. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    24. Eric Heyer & Frédéric Reynès & Henri Sterdyniak, 2004. "Observable and unobservable variables in the theory of the equilibrium rate of unemployment, a comparison between France and the United States," Working Papers hal-01027420, HAL.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:scotjp:v:55:y:2008:i:3:p:281-299. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/sesssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.