IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v11y2007i3n4.html
   My bibliography  Save this article

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

Author

Listed:
  • Enders Walter

    (University of Alabama)

  • Falk Barry L

    (Iowa State University)

  • Siklos Pierre

    (Wilfrid Laurier University)

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.

Suggested Citation

  • Enders Walter & Falk Barry L & Siklos Pierre, 2007. "A Threshold Model of Real U.S. GDP and the Problem of Constructing Confidence Intervals in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(3), pages 1-28, September.
    • Handle: RePEc:bpj:sndecm:v:11:y:2007:i:3:n:4
    DOI: 10.2202/1558-3708.1322
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1558-3708.1322
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1558-3708.1322?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Catherine Araujo Bonjean & Jean-François Brun, 2014. "Chocolate price fluctuations may cause depression: an analysis of price pass-through in the cocoa chain," Working Papers halshs-01074157, HAL.
    2. Catherine ARAUJO BONJEAN & Jean-François BRUN, 2010. "Price Transmission in the Cocoa-Chocolate Chain," Working Papers 201003, CERDI.
    3. Catherine Araujo Bonjean & Jean-François Brun, 2011. "Price Transmission in the Cocoa-Chocolate Chain," CERDI Working papers halshs-00552997, HAL.
    4. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.
    5. Donayre Luiggi & Eo Yunjong & Morley James, 2018. "Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-11, February.
    6. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    7. Subervie, Julie, 2011. "Producer price adjustment to commodity price shocks: An application of threshold cointegration," Economic Modelling, Elsevier, vol. 28(5), pages 2239-2246, September.
    8. Enders, Walter & Im, Kyung So & Lee, Junsoo & Strazicich, Mark C., 2010. "IV threshold cointegration tests and the Taylor rule," Economic Modelling, Elsevier, vol. 27(6), pages 1463-1472, November.
    9. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
    10. Catherine Araujo Bonjean & Jean-François Brun, 2014. "Chocolate price fluctuations may cause depression: an analysis of price pass-through in the cocoa chain," CERDI Working papers halshs-01074157, HAL.
    11. Shahbaba Babak, 2009. "Discovering Hidden Structures Using Mixture Models: Application to Nonlinear Time Series Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-21, May.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:11:y:2007:i:3:n:4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.