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A Threshold Model of Real U.S. GDP and the Problem of Constructing Confidence Intervals in TAR Models

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Author Info
Walter Enders (University of Alabama)
Barry Falk (Iowa State University)
Pierre Siklos (Wilfrid Laurier University)

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Abstract

We estimate real US GDP growth as a threshold autoregressive process, and construct confidence intervals for the parameter estimates. However, there are various approaches that can be used in constructing the confidence intervals. We construct confidence intervals for the slope coefficients and the threshold using asymptotic results and bootstrap methods, finding that the results for the different methods have very different economic implications. We perform a Monte Carlo experiment to evaluate the various methods. Surprisingly, the confidence intervals are wide enough to cast doubt on the assertion that the time-series responses of GDP to negative growth rates are different than the responses to positive growth rates.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 11 (2007)
Issue (Month): 3 ()
Pages: 1322-1322
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Handle: RePEc:bep:sndecm:11:2007:3:1322-1322

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Related research
Keywords: bootstrap threshold autoregressive confidence intervals

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  2. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
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  3. Peel, D A & Speight, A E H, 1998. "Threshold Nonlinearities in Output: Some International Evidence," Applied Economics, Taylor and Francis Journals, vol. 30(3), pages 323-33, March. [Downloadable!] (restricted)
  4. 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. [Downloadable!] (restricted)
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  5. Bruce E. Hansen, 1999. "The Grid Bootstrap And The Autoregressive Model," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 594-607, November. [Downloadable!] (restricted)
  6. Burgess, S M, 1992. "Nonlinear Dynamics in a Structural Model of Employment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S101-18, Suppl. De. [Downloadable!] (restricted)
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  7. Krager, Horst & Kugler, Peter, 1993. "Non-linearities in foreign exchange markets: a different perspective," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 195-208, April. [Downloadable!] (restricted)
  8. Galbraith, John W, 1996. "Credit Rationing and Threshold Effects in the Relation between Money and Output," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 419-29, July-Aug.. [Downloadable!] (restricted)
  9. Gonzalo, Jesus & Wolf, Michael, 2005. "Subsampling inference in threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 127(2), pages 201-224, August. [Downloadable!] (restricted)
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  10. 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. [Downloadable!] (restricted)
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  11. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-25, April-Jun. [Downloadable!] (restricted)
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  12. George Kapetanios, 2003. "Threshold models for trended time series," Empirical Economics, Springer, vol. 28(4), pages 687-707, November. [Downloadable!] (restricted)
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