IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v79y2017i1p101-123.html
   My bibliography  Save this article

Mismatch and the Forecasting Performance of Matching Functions

Author

Listed:
  • Christian Hutter
  • Enzo Weber

Abstract

No abstract is available for this item.

Suggested Citation

  • Christian Hutter & Enzo Weber, 2017. "Mismatch and the Forecasting Performance of Matching Functions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 101-123, February.
  • Handle: RePEc:bla:obuest:v:79:y:2017:i:1:p:101-123
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/obes.12142
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ebrahimy, Ehsan & Shimer, Robert, 2010. "Stock-flow matching," Journal of Economic Theory, Elsevier, vol. 145(4), pages 1325-1353, July.
    2. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    3. Mortensen, Dale & Pissarides, Christopher, 2011. "Job Creation and Job Destruction in the Theory of Unemployment," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 1-19.
    4. Regis Barnichon & Andrew Figura, 2015. "Labor Market Heterogeneity and the Aggregate Matching Function," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(4), pages 222-249, October.
    5. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    6. Lilien, David M, 1982. "Sectoral Shifts and Cyclical Unemployment," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 777-793, August.
    7. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    8. Bauer, Anja, 2013. "Mismatch unemployment : evidence from Germany 2000-2010," IAB-Discussion Paper 201310, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    9. Regis Barnichon & Christopher J. Nekarda, 2012. "The Ins and Outs of Forecasting Unemployment: Using Labor Force Flows to Forecast the Labor Market," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(2 (Fall)), pages 83-131.
    10. Jackman, R & Roper, S, 1987. "Structural Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(1), pages 9-36, February.
    11. Matthes, Britta & Burkert, Carola & Biersack, Wolfgang, 2008. "Berufssegmente: Eine empirisch fundierte Neuabgrenzung vergleichbarer beruflicher Einheiten," IAB-Discussion Paper 200835, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    12. Maria E. Canon & Mingyu Chen & Elise Marifian, 2013. "Labor mismatch in the Great Recession: a review of indexes using recent U.S. data," Review, Federal Reserve Bank of St. Louis, vol. 95(May), pages 237-272.
    13. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    14. Yashiv, Eran, 2007. "Labor search and matching in macroeconomics," European Economic Review, Elsevier, vol. 51(8), pages 1859-1895, November.
    15. Ay?egül ?ahin & Joseph Song & Giorgio Topa & Giovanni L. Violante, 2014. "Mismatch Unemployment," American Economic Review, American Economic Association, vol. 104(11), pages 3529-3564, November.
    16. Todd Clark & Michael McCracken, 2012. "Reality Checks and Comparisons of Nested Predictive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 53-66.
    17. Per Kropp & Barbara Schwengler, 2016. "Three-Step Method for Delineating Functional Labour Market Regions," Regional Studies, Taylor & Francis Journals, vol. 50(3), pages 429-445, March.
    18. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    19. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    20. Sabine Klinger & Enzo Weber, 2016. "Decomposing Beveridge Curve Dynamics By Correlated Unobserved Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 877-894, December.
    21. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    22. Kang, In-Bong, 2003. "Multi-period forecasting using different models for different horizons: an application to U.S. economic time series data," International Journal of Forecasting, Elsevier, vol. 19(3), pages 387-400.
    23. Klinger, Sabine & Weber, Enzo, 2020. "GDP-employment decoupling in Germany," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 82-98.
    24. Sedláček, Petr, 2014. "Match efficiency and firms' hiring standards," Journal of Monetary Economics, Elsevier, vol. 62(C), pages 123-133.
    25. Coles, Melvyn G & Smith, Eric, 1998. "Marketplaces and Matching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(1), pages 239-254, February.
    26. Haroon Mumtaz & Francesco Zanetti, 2015. "Labor Market Dynamics: A Time-Varying Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 319-338, June.
    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. Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
    2. Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
    3. Christian Hutter & Francesco Carbonero & Sabine Klinger & Carsten Trenkler & Enzo Weber, 2022. "Which factors were behind Germany's labour market upswing? A data‐driven approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1052-1076, October.
    4. Jung, Philip & Korfmann, Philipp & Preugschat, Edgar, 2023. "Optimal regional labor market policies," European Economic Review, Elsevier, vol. 152(C).
    5. repec:iab:iabjlr:v:55:i::p:art.1 is not listed on IDEAS
    6. Hartl, Tobias & Hutter, Christian & Weber, Enzo, 2021. "Matching for three: big data evidence on search activity of workers, firms, and employment service," IAB-Discussion Paper 202101, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. Hutter, Christian & Weber, Enzo, 2017. "Labour market effects of wage inequality and skill-biased technical change in Germany," IAB-Discussion Paper 201705, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

    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. Hutter, Christian & Weber, Enzo, 2014. "Forecasting with a mismatch-enhanced labor market matching function," IAB-Discussion Paper 201416, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    3. Crawley, Andrew & Welch, Sarah & Yung, Julieta, 2021. "Improving estimates of job matching efficiency with different measures of unemployment," Journal of Macroeconomics, Elsevier, vol. 67(C).
    4. Carlos Carrillo‐Tudela & Ludo Visschers, 2023. "Unemployment and Endogenous Reallocation Over the Business Cycle," Econometrica, Econometric Society, vol. 91(3), pages 1119-1153, May.
    5. Firmin Doko Tchatoka & Qazi Haque, 2023. "On bootstrapping tests of equal forecast accuracy for nested models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1844-1864, November.
    6. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    7. Turrell, Arthur & Speigner, Bradley & Copple, David & Djumalieva, Jyldyz & Thurgood, James, 2021. "Is the UK’s productivity puzzle mostly driven by occupational mismatch? An analysis using big data on job vacancies," Labour Economics, Elsevier, vol. 71(C).
    8. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    9. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    10. Álvarez de Toledo, Pablo & Núñez, Fernando & Usabiaga, Carlos, 2014. "An empirical approach on labour segmentation. Applications with individual duration data," Economic Modelling, Elsevier, vol. 36(C), pages 252-267.
    11. Matheson, Troy D., 2008. "Phillips curve forecasting in a small open economy," Economics Letters, Elsevier, vol. 98(2), pages 161-166, February.
    12. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    13. Carlos Usabiaga & Pablo Álvarez de Toledo & Fernando Núñez, 2013. "Labour Market Segmentation, Clusters, Mobility And Unemployment Duration With Individual Microdata," EcoMod2013 5688, EcoMod.
    14. Gehrke, Britta & Weber, Enzo, 2018. "Identifying asymmetric effects of labor market reforms," European Economic Review, Elsevier, vol. 110(C), pages 18-40.
    15. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    16. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    17. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    18. Sabine Klinger & Enzo Weber, 2016. "Decomposing Beveridge Curve Dynamics By Correlated Unobserved Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 877-894, December.
    19. Hugo Erken & Eric van Loon & Wouter Verbeek, 2015. "Mismatch on the Dutch labour market in the Great Recession," CPB Discussion Paper 303.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    20. Yuelin Liu, 2022. "How structural is unemployment in the United States?," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1258-1276, July.

    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:obuest:v:79:y:2017:i:1:p:101-123. 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/sfeixuk.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.