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Nonstationarity and Nonlinearity in the US Unemployment Rate: A Re-examination

  • Dipak Ghosh
  • Swarna (Bashu) Dutt
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    Conventional econometric tests cannot distinguish nonstationarity from nonlinearity because of the joint modeling of unit roots with threshold effects. Caner–Hansen (CH, 2001) provides a new test which for the first time can simultaneously test for both (without any prior assumption of stationarity). Their threshold unit root tests are more powerful than conventional Augmented Dickey-Fuller tests, especially when the true process is nonlinear. They look at unemployment among adult males, and find contrary to many previous studies, that it is a “stationary nonlinear threshold process”. This paper attempts to re-examine and reconfirm the CH methodology by using unemployment in the civilian labor force. We extend the data up to December 2004, to see if the results hold up to the recent turbulent times, when unemployment changed dramatically from 3.9 % (1999) to 6.2 % (2003). Our results support the premise that US unemployment is a stationary threshold autoregressive process.

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    File URL: http://frank.mtsu.edu/~jee/fall2008/4-MS608-2ndrevision.pdf
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    Article provided by Middle Tennessee State University, Business and Economic Research Center in its journal Journal for Economic Educators.

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    Handle: RePEc:mts:jrnlee:200809
    Contact details of provider: Web page: http://www.mtsu.edu/~jee
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    1. Bruce E. Hansen & Mehmet Caner, 1997. "Threshold Autoregressions with a Unit Root," Boston College Working Papers in Economics 381, Boston College Department of Economics.
    2. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Philip Arestis & Andrea Cipollini & Bassam Fattouh, 2002. "Threshold Effects in the U.S. Budget Deficit," Economics Working Paper Archive wp_358, Levy Economics Institute.
    5. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    6. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March.
    7. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    8. Pippenger, Michael K & Goering, Gregory E, 1993. "A Note on the Empirical Power of Unit Root Tests under Threshold Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 55(4), pages 473-81, November.
    9. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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