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A Threshold Model of Real US GDP and the Problem of Constructing Confidence Intervals in TAR Models

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Abstract

We estimate real U.S. 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. Specifically, standard- t , bootstrap- t , and bootstrap-percentile confidence intervals are simulated for the slope coefficients and the estimated threshold. However, the results for the different methods have very different economic implications. We perform a Monte Carlo experiment to evaluate the various methods.

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File URL: http://www.wlu.ca/documents/22943/E_F_S_12_2006.pdf
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Bibliographic Info

Paper provided by Wilfrid Laurier University, Department of Economics in its series Working Papers with number eg0052.

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Length: 36
Date of creation: 2006
Date of revision: 2006
Handle: RePEc:wlu:wpaper:eg0052

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Keywords: Bootstrap GDP; Threshold Autoregression; Bootstrap Confidence Intervals;

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Cited by:
  1. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
  2. 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.

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