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The Current Depth-of-Recession and Unemployment-Rate Forecasts

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  • Parker Randall E.

    (East Carolina University East Carolina University)

  • Rothman Philip

    (East Carolina University East Carolina University)

Abstract

Building upon Beaudry and Koop's (1993) analysis, we consider a "current depth of the recession" (CDR) variable in modeling the time-series behavior of the postwar quarterly U.S. unemployment rate. The CDR approach is consistent with the state-dependent behavior in the unemployment rate documented in the business-cycle asymmetry literature. We show that while the CDR effect is significant in-sample, no statistically significant out-of-sample forecast improvement is obtained relative to the linear alternative. Augmenting an AR(2) model by inclusion of the CDR term, however, does not significantly worsen the out-of-sample forecast performance.

Suggested Citation

  • Parker Randall E. & Rothman Philip, 1998. "The Current Depth-of-Recession and Unemployment-Rate Forecasts," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-10, January.
    • Handle: RePEc:bpj:sndecm:v:2:y:1998:i:4:n:5
    DOI: 10.2202/1558-3708.1036
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    Cited by:

    1. Julien Chevallier & Florian Ielpo, 2013. "Cross-market linkages between commodities, stocks and bonds," Applied Economics Letters, Taylor & Francis Journals, vol. 20(10), pages 1008-1018, July.
    2. Anupam Das & Leanora Brown & Adian Mcfarlane, 2023. "Economic Misery and Remittances in Jamaica," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 48(2), pages 33-52.
    3. Matthews, Kent & Minford, Patrick & Naraidoo, Ruthira, 2008. "Vicious and virtuous circles -- The political economy of unemployment in interwar UK and USA," European Journal of Political Economy, Elsevier, vol. 24(3), pages 605-614, September.
    4. Philip Rothman, 1999. "Time Irreversible Unemployment Rates," Working Papers 9903, East Carolina University, Department of Economics.
    5. Floros, Ch., 2005. "Forecasting the UK Unemployment Rate: Model Comparisons," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 57-72.
    6. Bårdsen Gunnar & Hurn Stanley & McHugh Zöe, 2012. "Asymmetric Unemployment Rate Dynamics in Australia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-22, January.
    7. Chen, Wei-Shing, 2011. "Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1332-1342.
    8. Proietti, Tommaso, 2003. "Forecasting the US unemployment rate," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 451-476, March.
    9. Gunnar Bårdsen & Stan Hurn & Zoë McHugh, 2002. "A smooth-transition model of the Australian unemployment rate," Working Paper Series 1002, Department of Economics, Norwegian University of Science and Technology, revised 01 Jul 2003.
    10. Mihai Mutascu & Scott W. Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 400-416, June.
    11. Skalin, Joakim & Teräsvirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(2), pages 202-241, April.

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