Fixed-b asymptotics for the studentized mean from time series with short, long or negative memory
AbstractThis paper considers the problem of distribution estimation for the studentized 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 complements the Short Memory results of Kiefer and Vogelsang (2005). In particular, our results highlight the dependence on the employed kernel, whether or not the taper is nonzero at the boundary, and most importantly whether or not the process has short memory. We also demonstrate that small-bandwidth approaches fail when long memory or negative memory is present since the limiting distribution is either a point mass at zero or degenerate. Extensive numerical work provides approximations to the quantiles of the asymptotic distribution for a range of tapers and memory parameters; these quantiles can be used in practice for the construction of confidence intervals and hypothesis tests for the mean of the time series.
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Bibliographic InfoPaper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number qt70c4x0sq.
Date of creation: 01 Dec 2009
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confidence intervals; critical values; dependence; gaussian; kernel spectral density; tapers; testing; Social and Behavioral Sciences;
Other versions of this item:
- McElroy, Tucker & Politis, Dimitris N., 2012. "Fixed-B Asymptotics For The Studentized Mean From Time Series With Short, Long, Or Negative Memory," Econometric Theory, Cambridge University Press, vol. 28(02), pages 471-481, April.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kiefer, Nicholas M. & Bunzel, Helle & Vogelsang, Timothy & Vogelsang, Timothy & Bunzel, Helle, 2000.
"Simple Robust Testing of Regression Hypotheses,"
Staff General Research Papers
1832, Iowa State University, Department of Economics.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005.
"A New Asymptotic Theory For Heteroskedasticity-Autocorrelation Robust Tests,"
Cambridge University Press, vol. 21(06), pages 1130-1164, December.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory for Heteroskedasticity-Autocorrelation Robust Tests," Working Papers 05-08, Cornell University, Center for Analytic Economics.
- 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.
- McElroy, Tucker S. & Politis, Dimitris N., 2012.
"Distribution Theory for the Studentized Mean for Long, Short, and Negative Memory Time Series,"
University of California at San Diego, Economics Working Paper Series
qt35c7r55c, Department of Economics, UC San Diego.
- McElroy, Tucker & Politis, Dimitris N., 2013. "Distribution theory for the studentized mean for long, short, and negative memory time series," Journal of Econometrics, Elsevier, vol. 177(1), pages 60-74.
- McElroy, Tucker S & Politis, D N, 2011. "Distribution Theory for the Studentized Mean for Long, Short, and Negative Memory Time Series," University of California at San Diego, Economics Working Paper Series qt0dr145dt, Department of Economics, UC San Diego.
- Politis, Dimitris, 2012. "On The Behavior Of Nonparametric Density And Spectral Density Estimators At Zero Points Of Their Support," University of California at San Diego, Economics Working Paper Series qt40g0z0tz, Department of Economics, UC San Diego.
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