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Testing for nonlinearity in mean in the presence of heteroskedasticity. Working paper #8

  • Stan Hurn
  • Ralf Becker

    (National Centre for Econometric Research)

This paper considers an important practical problem in testing time-series data for nonlinearity in mean. Most popular tests reject the null hypothesis of linearity too frequently if the the data are heteroskedastic. Two approaches to redressing this size distortion are considered, both of which have been proposed previously in the literature although not in relation to this particular problem. These are the heteroskedasticity-robust-auxiliary-regression approach and the wild bootstrap. Simulation results indicate that both approaches are effective in reducing the size distortion and that the wild bootstrap others better performance in smaller samples. Two practical examples are then used to illustrate the procedures and demonstrate the potential pitfalls encountered when using non-robust tests.

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File URL: http://www.ncer.edu.au/papers/documents/WpNo8Jan07.pdf
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Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 8.

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Date of creation: 15 Jan 2007
Date of revision:
Handle: RePEc:qut:auncer:2007-2
Contact details of provider: Phone: 07 3138 5066
Fax: 07 3138 1500
Web page: http://www.ncer.edu.au

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  1. Pesaran,H.M. & Shin,Y., 1995. "Long-Run Structural Modelling," Cambridge Working Papers in Economics 9419, Faculty of Economics, University of Cambridge.
  2. Alejandro Justiniano & Bruce Preston, 2006. "Can Structural Small Open Economy Models Account For The Influence Of Foreign Disturbances?," CAMA Working Papers 2006-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, March.
  4. Peter N. Ireland, 1999. "A method for taking models to the data," Working Paper 9903, Federal Reserve Bank of Cleveland.
  5. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2012. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199650460, March.
  6. Gonzalo, Jesus & Ng, Serena, 2001. "A systematic framework for analyzing the dynamic effects of permanent and transitory shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1527-1546, October.
  7. A. R. Pagan & J. C. Robertson, 1998. "Structural Models Of The Liquidity Effect," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 202-217, May.
  8. Michael R. Wickens & Roberto Motto, 2001. "Estimating shocks and impulse response functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 371-387.
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