An I(d) Model with Trend and Cycles
This paper deals with models allowing for trending processes and cyclical component with error processes that are possibly nonstationary, nonlinear, and non-Gaussian. Asymptotic confidence intervals for the trend, cyclical component, and memory parameters are obtained. The confidence intervals are applicable for a wide class of processes, exhibit good coverage accuracy, and are easy to implement.
|Date of creation:||Jan 2010|
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- Abadir, Karim M. & Distaso, Walter & Giraitis, Liudas, 2007. "Nonstationarity-extended local Whittle estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 1353-1384, December.
- Violetta Dalla & Liudas Giraitis & Javier Hidalgo, 2006.
"Consistent estimation of the memory parameter for nonlinear time series,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 27(2), pages 211-251, 03.
- V Dalla & L Giraitis & J Hidalgo, "undated". "Consistent estimation of the memory parameter for nonlinear time series," Discussion Papers 05/17, Department of Economics, University of York.
- Violetta Dalla & Liudas Giraitis & Javier Hidalgo, 2006. "Consistent estimation of the memory parameterfor nonlinear time series," STICERD - Econometrics Paper Series /06/497, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Donald W. K. Andrews & Yixiao Sun, 2004. "Adaptive Local Polynomial Whittle Estimation of Long-range Dependence," Econometrica, Econometric Society, vol. 72(2), pages 569-614, 03.
- Donald W.K. Andrews & Yixiao Sun, 2002. "Adaptive Local Polynomial Whittle Estimation of Long-range Dependence," Cowles Foundation Discussion Papers 1384, Cowles Foundation for Research in Economics, Yale University.
- ANDREWS, DONALD W & Sun, Yixiao X, 2002. "Adaptive Local Polynomial Whittle Estimation of Long-Range Dependence," University of California at San Diego, Economics Working Paper Series qt9wt048tt, Department of Economics, UC San Diego.
- Violetta Dalla & Liudas Giraitis & Javier Hidalgo, 2006. "Consistent estimation of the memory parameter for nonlinear time series," LSE Research Online Documents on Economics 6813, London School of Economics and Political Science, LSE Library. Full references (including those not matched with items on IDEAS)
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