Properties of Recursive Trend-Adjusted Unit Root Tests
In this paper, we analyse the properties of recursive trend adjusted unit root tests. We show that OLS based recursive trend adjustment can produce unit root tests which are not invariant when the data is generated from a random walk with drift and investigate whether the power performance previously observed in the literature is maintained under invariant versions of the tests. A finite sample evaluation of the size and power of the invariant procedures is presented.
|Date of creation:||2004|
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- Shin, Dong Wan & So, Beong Soo, 2002. "Recursive mean adjustment and tests for nonstationarities," Economics Letters, Elsevier, vol. 75(2), pages 203-208, April.
- Taylor, A M Robert, 2002. "Regression-Based Unit Root Tests with Recursive Mean Adjustment for Seasonal and Nonseasonal Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 269-81, April.
- So, Beong Soo & Shin, Dong Wan, 2001. "An invariant sign test for random walks based on recursive median adjustment," Journal of Econometrics, Elsevier, vol. 102(2), pages 197-229, June.
- Phillips, Peter C. B. & Park, Joon Y. & Chang, Yoosoon, 2004.
"Nonlinear instrumental variable estimation of an autoregression,"
Journal of Econometrics,
Elsevier, vol. 118(1-2), pages 219-246.
- Peter C.B. Phillips & Joon Y. Park & Yoosoon Chang, 2001. "Nonlinear Instrumental Variable Estimation of an Autoregression," Cowles Foundation Discussion Papers 1331, Cowles Foundation for Research in Economics, Yale University.
- Sul, Donggyu & Phillips, Peter & Choi, Chi-Young, 2003.
"Prewhitening Bias in HAC Estimation,"
141, Department of Economics, The University of Auckland.
- Peter C.B. Phillips & Chi-Young Choi & Donggyu Sul, 2004. "Prewhitening Bias in HAC Estimation," Yale School of Management Working Papers ysm426, Yale School of Management.
- Donggyu Sul & Peter C.B. Phillips & Choi, Chi-Young, 2003. "Prewhitening Bias in HAC Estimation," Cowles Foundation Discussion Papers 1436, Cowles Foundation for Research in Economics, Yale University.
- Yoosoon Chang, 2000.
"Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency,"
CIRJE-F-85, CIRJE, Faculty of Economics, University of Tokyo.
- Chang, Yoosoon, 2002. "Nonlinear IV unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 110(2), pages 261-292, October.
- Chang, Yoosoon, 2002. "Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency," Working Papers 2000-08, Rice University, Department of Economics.
- Leybourne, Stephen J. & C. Mills, Terence & Newbold, Paul, 1998. "Spurious rejections by Dickey-Fuller tests in the presence of a break under the null," Journal of Econometrics, Elsevier, vol. 87(1), pages 191-203, August.
- Paulo M. M. Rodrigues, 2004.
"Properties of Recursive Trend-Adjusted Unit Root Tests,"
Economics Working Papers
ECO2004/31, European University Institute.
- Rodrigues, Paulo M.M., 2006. "Properties of recursive trend-adjusted unit root tests," Economics Letters, Elsevier, vol. 91(3), pages 413-419, June.
- So, Beong Soo & Shin, Dong Wan, 1999. "Recursive mean adjustment in time-series inferences," Statistics & Probability Letters, Elsevier, vol. 43(1), pages 65-73, May.
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