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Effects of filtering data on testing asymmetry in threshold autoregressive models

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  • Li Jing

    (Miami University, Economics, 800 H High Street, Oxford, OH 45056, USA)

Abstract

Empirical macroeconomic research on business cycle typically filters economic time series in order to obtain cyclical components. This paper examines the effects of filtering data on the test for a linear autoregression against a threshold autoregression. Monte Carlo simulation shows that (1) filtering data in general reduces the power of the test, (2) the power is sensitive to the choice of filters and the specification of the trend and cyclical components, (3) regime-varying variance of the error term can affect the rejection frequency. Empirical evidences for cyclical asymmetry are provided for the quarterly US real GNP.

Suggested Citation

  • Li Jing, 2016. "Effects of filtering data on testing asymmetry in threshold autoregressive models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 549-565, December.
    • Handle: RePEc:bpj:sndecm:v:20:y:2016:i:5:p:549-565:n:2
    DOI: 10.1515/snde-2015-0016
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    References listed on IDEAS

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    1. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    2. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    3. Cao, C Q & Tsay, R S, 1992. "Nonlinear Time-Series Analysis of Stock Volatilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 165-185, Suppl. De.
    4. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-236, April.
    5. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    6. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    7. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    8. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    9. Zacharias Psaradakis & Martin Sola, 2003. "On detrending and cyclical asymmetry," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 271-289.
    10. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    11. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-311, July.
    12. 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 419-429, July-Aug..
    13. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
    14. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    15. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
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