Bootstrapping the Small Sample Critical Values of the Rescaled Range Statistic
Abstract
Finite sample critical values of the rescaled range or R/S statistic may be obtained by bootstrapping. The empirical size and power performance of these critical values is good. Using the post blackened, moving block bootstrap helps to replicate the time dependencies in the original data. The Monte Carlo results show that the asymptotic critical values in Lo (1991) should not be used.Download Info
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Article provided by Economic and Social Studies in its journal Economic and Social Review.
Volume (Year): 31 (2000)
Issue (Month): 4 ()
Pages: 351-359
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References listed on IDEASPlease 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.:
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009.
"Long Memory in US Real Output per Capita,"
Discussion Papers of DIW Berlin
891, DIW Berlin, German Institute for Economic Research.
- Guglielmo Caporale & Luis Gil-Alana, 2013. "Long memory in US real output per capita," Empirical Economics, Springer, vol. 44(2), pages 591-611, April.
- Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," CESifo Working Paper Series 2671, CESifo Group Munich.
- Murphy, A. & Izzeldin, M., 2009.
"Bootstrapping long memory tests: Some Monte Carlo results,"
Computational Statistics & Data Analysis,
Elsevier, vol. 53(6), pages 2325-2334, April.
- Anthony Murphy & Marwan Izzeldin, 2006. "Bootstrapping long memory tests: some Monte Carlo results," Working Papers 574547, Lancaster University Management School, Economics Department.
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