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LOMODRS: Stata module to perform Lo R/S test for long range dependence in timeseries

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Author Info

  • Christopher F Baum

    ()
    (Boston College)

  • Tairi Room

Abstract

lomodrs performs Lo's (1991) modified rescaled range (R/S, "range over standard deviation") test for long range dependence of a time series. The classical R/S test, devised by Hurst (1951) and Mandelbrot (1972), is shown to be excessively sensitive to "short-range dependence" (e.g. ARMA components). Lo's modified version of the statistic takes account of short-range dependence by performing a Newey-West correction (using a Bartlett window) to derive a consistent estimate of the long-range variance of the timeseries. Inference from the modified R/S test for long range dependence is complementary to that derived from that of other tests for long memory, or fractional integration in a timeseries, such as kpss, gphudak, modlpr and roblpr. This is version 1.0.3 of the software, updated from that published in STB-60 and compatible with Stata version 8 syntax. It may be applied to a single timeseries in a panel with the if qualifier or to all timeseries with the by prefix.

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File URL: http://fmwww.bc.edu/repec/bocode/l/lomodrs.ado
File Function: program code
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File URL: http://fmwww.bc.edu/repec/bocode/l/lomodrs.hlp
File Function: help file
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Bibliographic Info

Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S412601.

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Programming language: Stata
Requires: Stata version 8.2
Date of creation: 28 Jun 2000
Date of revision: 26 Jun 2006
Handle: RePEc:boc:bocode:s412601

Note: This module may be installed from within Stata by typing "ssc install lomodrs". Windows users should not attempt to download these files with a web browser.
Contact details of provider:
Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Phone: 617-552-3670
Fax: +1-617-552-2308
Email:
Web page: http://fmwww.bc.edu/EC/
More information through EDIRC

Order Information:
Web: http://repec.org/docs/ssc.php

Related research

Keywords: time-series data; long range dependence; r/s test; rescaled range test;

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