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IVACTEST: Stata module to perform Cumby-Huizinga test for autocorrelation after IV/OLS estimation

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Author Info

  • Christopher F Baum

    ()
    (Boston College)

  • Mark E Schaffer

    ()
    (Heriot-Watt University)

Abstract

ivactest performs the general specification test of serial correlation proposed by Cumby and Huizinga (1992) after OLS or instrumental variables (IV) estimation. In their words, the null hypothesis of the test is that the regression error is a moving average of known order q>=0 against the general alternative that autocorrelations of the regression error are nonzero at lags greater than q. The test is general enough to test the hypothesis that the regression error has no serial correlation (q=0) or the null hypothesis that serial correlation in the regression error exists, but dies out at a known finite lag (q>0). The test is especially attractive because it can be used in frequently encountered cases where alternative such as the Box-Pierce test (wntestq), Durbin's h test (estat durbinalt) and the Breusch-Godfrey test (estat bgodfrey) are not applicable. NB: This routine has been superseded by the authors' actest, which offers a wider range of capabilities.

Download Info

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File URL: http://fmwww.bc.edu/repec/bocode/i/ivactest.ado
File Function: program code
Download Restriction: no

File URL: http://fmwww.bc.edu/repec/bocode/i/ivactest.hlp
File Function: help file
Download Restriction: no

Bibliographic Info

Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S456841.

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Programming language: Stata
Requires: Stata version 9.2
Date of creation: 29 Apr 2007
Date of revision: 23 Jul 2013
Handle: RePEc:boc:bocode:s456841

Note: This module should be installed from within Stata by typing "ssc install ivactest". 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: instrumental variables; autocorrelation; serial correlation; moving average errors;

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