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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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Author Info
P. Siklos, W. Enders & B. Falk () (Wilfrid Laurier University)

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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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Publisher 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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Related research
Keywords: Bootstrap GDP; Threshold Autoregression; Bootstrap Confidence Intervals;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation

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