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

Christopher Baum and Mark Schaffer ()

Statistical Software Components from Boston College Department of Economics

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 NB: This routine has been superseded by the authors' actest, which offers a wider range of capabilities.

Language: Stata
Requires: Stata version 9.2
Keywords: instrumental variables; autocorrelation; serial correlation; moving average errors (search for similar items in EconPapers)
Date: 2007-04-29, Revised 2013-07-23
Note: This module should be installed from within Stata by typing "ssc install ivactest". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/i/ivactest.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/i/ivactest.hlp help file (text/plain)

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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s456841

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