Nonlinear regression for unit root models with autoregressive errors
AbstractThis paper shows that the nonlinear least squares estimator for unit root models has the limiting distribution free of nuisance parameters and is more efficient than the augmented Dickey-Fuller estimator when the sum of coefficients for lagged variables is negative.
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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 100 (2008)
Issue (Month): 3 (September)
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Web page: http://www.elsevier.com/locate/ecolet
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- Park, Joon Y & Phillips, Peter C B, 2001.
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- Joon Y. Park & Peter C. B. Phillips, 1999. "Nonlinear Regressions with Integrated Time Series," Working Paper Series no6, Institute of Economic Research, Seoul National University.
- Park, Joon Y. & Phillips, Peter C.B., 1999.
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- Peter C.B. Phillips & Joon Y. Park, 1998. "Asymptotics for Nonlinear Transformations of Integrated Time Series," Cowles Foundation Discussion Papers 1182, Cowles Foundation for Research in Economics, Yale University.
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- 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.
- 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.
- DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
- Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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