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Stochastic levels and duration dependence in US unemployment

Author

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  • de Bruijn, L.P.
  • Franses, Ph.H.B.F.

Abstract

We introduce a new time series model that can capture the properties of data as is typically exemplified by monthly US unemployment data. These data show the familiar nonlinear features, with steeper increases in unem- ployment during economic downswings than the decreases during economic prosperity. At the same time, the levels of unemployment in each of the two states do not seem fixed, nor are the transition periods abrupt. Finally, our model should generate out-of-sample forecasts that mimic the in-sample properties. We demonstrate that our new and flexible model covers all those features, and our illustration to monthly US unemployment data shows its merits, both in and out of sample.

Suggested Citation

  • de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:78710
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    References listed on IDEAS

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    1. Castro, Vítor, 2010. "The duration of economic expansions and recessions: More than duration dependence," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 347-365, March.
    2. Rose Cunningham & Ilan Kolet, 2011. "Housing market cycles and duration dependence in the United States and Canada," Applied Economics, Taylor & Francis Journals, vol. 43(5), pages 569-586.
    3. Luc Bauwens & Arie Preminger & Jeroen V. K. Rombouts, 2010. "Theory and inference for a Markov switching GARCH model," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 218-244, July.
    4. Kim, Chang-Jin, 2009. "Markov-switching models with endogenous explanatory variables II: A two-step MLE procedure," Journal of Econometrics, Elsevier, vol. 148(1), pages 46-55, January.
    5. Pok-sang Lam, 2004. "A Markov-Switching Model Of Gnp Growth With Duration Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 175-204, February.
    6. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    7. Sichel, Daniel E, 1991. "Business Cycle Duration Dependence: A Parametric Approach," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 254-260, May.
    8. Francis X. Diebold & Glenn Rudebusch & Daniel Sichel, 1993. "Further Evidence on Business-Cycle Duration Dependence," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 255-284, National Bureau of Economic Research, Inc.
    9. Diebold, Francis X & Rudebusch, Glenn D, 1990. "A Nonparametric Investigation of Duration Dependence in the American Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 98(3), pages 596-616, June.
    10. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    11. Layton, Allan P. & Smith, Daniel R., 2007. "Business cycle dynamics with duration dependence and leading indicators," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 855-875, December.
    12. de Groot, Bert & Franses, Philip Hans, 2012. "Common socio-economic cycle periods," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 59-68.
    13. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307.
    14. Nalewaik, Jeremy J., 2011. "Incorporating vintage differences and forecasts into Markov switching models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 281-307, April.
    15. Pierre Guérin & Massimiliano Marcellino, 2013. "Markov-Switching MIDAS Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 45-56, January.
    16. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
    17. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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    More about this item

    Keywords

    Markov switching; duration dependence; Gibbs sampling; unemployment; stochastic levels;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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