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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 and DIW Berlin)
Mark E Schaffer () (Heriot-Watt University)

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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.

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File URL: http://fmwww.bc.edu/repec/bocode/i/ivactest.ado
File Format: text/plain
File Function: program code
Download Restriction: no
File URL: http://fmwww.bc.edu/repec/bocode/i/ivactest.hlp
File Format: text/plain
File Function: help file
Download Restriction: no

Publisher 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: 14 Jul 2007
Handle: RePEc:boc:bocode:s456841

Note: This module may 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

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

For technical questions regarding this item, or to correct its listing, contact: (Christopher F Baum).

Related research
Keywords: instrumental variables autocorrelation serial correlation moving average errors

Statistics
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This page was last updated on 2008-5-9.


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