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The ins and outs of forecasting unemployment: Using labor force flows to forecast the labor market

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Abstract

This paper presents a forecasting model of unemployment based on labor force ows data that, in real time, dramatically outperforms the Survey of Professional Forecasters, historical forecasts from the Federal Reserve Board's Greenbook, and basic time-series models. Our model's forecast has a root-mean-squared error about 30 percent below that of the next-best forecast in the near term and performs especially well surrounding large recessions and cyclical turning points. Further, because our model uses information on labor force ows that is likely not incorporated by other forecasts, a combined forecast including our model's forecast and the SPF forecast yields an improvement over the latter alone of about 35 percent for current-quarter forecasts, and 15 percent for next-quarter forecasts, as well as improvements at longer horizons.

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  • Régis Barnichon & Christopher J. Nekarda, 2013. "The ins and outs of forecasting unemployment: Using labor force flows to forecast the labor market," Finance and Economics Discussion Series 2013-19, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2013-19
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    1. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
    2. Rothman, Philip, 1991. "Further evidence on the asymmetric behavior of unemployment rates over the business cycle," Journal of Macroeconomics, Elsevier, vol. 13(2), pages 291-298.
    3. Barnichon, Regis, 2012. "Vacancy posting, job separation and unemployment fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 315-330.
    4. Barbara Petrongolo & Christopher A. Pissarides, 2008. "The Ins and Outs of European Unemployment," American Economic Review, American Economic Association, vol. 98(2), pages 256-262, May.
    5. Amos Golan & Jeffrey M. Perloff, 2004. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 433-438, February.
    6. Shigeru Fujita, 2011. "Dynamics of worker flows and vacancies: evidence from the sign restriction approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 89-121, January/F.
    7. Laura Brown & Saeed Moshiri, 2004. "Unemployment variation over the business cycles: a comparison of forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 497-511.
    8. Baghestani, Hamid, 2008. "Federal Reserve versus private information: Who is the best unemployment rate predictor," Journal of Policy Modeling, Elsevier, vol. 30(1), pages 101-110.
    9. Stephanie Aaronson & Bruce Fallick & Andrew Figura & Jonathan Pingle & William Wascher, 2006. "The Recent Decline in the Labor Force Participation Rate and Its Implications for Potential Labor Supply," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 37(1), pages 69-154.
    10. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    11. Peter Tulip, 2009. "Has the Economy Become More Predictable? Changes in Greenbook Forecast Accuracy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1217-1231, September.
    12. Shigeru Fujita & Garey Ramey, 2012. "Exogenous vs. endogenous separation," Working Papers 12-2, Federal Reserve Bank of Philadelphia.
    13. Rothman Philip A, 2008. "Reconsideration of the Markov Chain Evidence on Unemployment Rate Asymmetry," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-18, September.
    14. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
    15. Wesley Clair Mitchell, 1927. "Business Cycles: The Problem and Its Setting," NBER Books, National Bureau of Economic Research, Inc, number mitc27-1, August.
    16. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    17. Charles A. Fleischman & John M. Roberts, 2011. "From many series, one cycle: improved estimates of the business cycle from a multivariate unobserved components model," Finance and Economics Discussion Series 2011-46, Board of Governors of the Federal Reserve System (U.S.).
    18. Bruce Fallick & Jonathan F. Pingle, 2006. "A cohort-based model of labor force participation," Finance and Economics Discussion Series 2007-09, Board of Governors of the Federal Reserve System (U.S.).
    19. Barnichon, Regis, 2010. "Building a composite Help-Wanted Index," Economics Letters, Elsevier, vol. 109(3), pages 175-178, December.
    20. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    21. repec:rim:rimwps:49-07 is not listed on IDEAS
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