Fixed-B Asymptotics For The Studentized Mean From Time Series With Short, Long, Or Negative Memory
This paper considers the problem of variance estimation for the sample mean in the context of long memory and negative memory time series dynamics, adopting the fixed-bandwidth approach now popular in the econometrics literature. The distribution theory generalizes the short memory results of Kiefer and Vogelsang (2005, Econometric Theory 21, 1130–1164). In particular, our results highlight the dependence on the kernel (we include flat-top kernels), whether or not the kernel is nonzero at the boundary, and, most important, whether or not the process is short memory. Simulation studies support the importance of accounting for memory in the construction of confidence intervals for the mean.
Volume (Year): 28 (2012)
Issue (Month): 02 (April)
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References listed on IDEAS
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- Hurvich, Clifford M., 2002. "Multistep forecasting of long memory series using fractional exponential models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 167-179.
- Nicholas M. Kiefer & Timothy J. Vogelsang & Helle Bunzel, 2000.
"Simple Robust Testing of Regression Hypotheses,"
Econometric Society, vol. 68(3), pages 695-714, May.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005.
"A New Asymptotic Theory for Heteroskedasticity-Autocorrelation Robust Tests,"
05-08, Cornell University, Center for Analytic Economics.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory For Heteroskedasticity-Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1130-1164, December.
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