ACTEST: Stata module to perform Cumby-Huizinga general test for autocorrelation in time series
Christopher Baum () and
Mark Schaffer ()
Statistical Software Components from Boston College Department of Economics
actest performs the general specification test of serial correlation in a time series proposed by Cumby and Huizinga (1990, 1992). It can be applied to a univariate time series or as a postestimation command after OLS or instrumental variables (IV) estimation. The null hypothesis of the test is that the time series is a moving average of known order q, which could be zero or a positive value. The test considers the general alternative that autocorrelations of the time series are nonzero at lags greater than q. The test is general enough to test the hypothesis that the time series has no serial correlation (q=0) or the null hypothesis that serial correlation in the time series exists, but dies out at a known finite lag (q>0).
Requires: Stata version 11.2 (version 9.2 for actest9)
Keywords: autocorrelation; serial correlation; moving average errors; Box-Pierce test; Ljung-Box test; Breusch-Godfrey test; Arellano-Bond test; panel; panel autocorrelation (search for similar items in EconPapers)
Date: 2013-07-23, Revised 2015-01-24
Note: This module should be installed from within Stata by typing "ssc install actest". Windows users should not attempt to download these files with a web browser.
References: Add references at CitEc
Citations Track citations by RSS feed
Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/a/actest.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/a/actest9.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/a/actest.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/l/livreg2.mlib Mata object library (application/x-stata)
http://fmwww.bc.edu/repec/bocode/c/cs_actest_1.0.13.do certification script (text/plain)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s457668
Ordering information: This software item can be ordered from
Access Statistics for this software item
More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Series data maintained by Christopher F Baum ().