Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions

Robert Cumby () and John Huizinga

No 92, NBER Technical Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper derives the asymptotic distribution for a vector of sample autocorrelations of regression residuals from a quite general linear model. The asymptotic distribution forms the basis for a test of the null hypothesis that the regression error follows a moving average of order q [greaterthan or equal] 0 against the general alternative that autocorrelations of the regression error are non-zero at lags greater than q. By allowing for endogenous, predetermined and/or exogenous regressors, for estimation by either ordinary least squares or a number of instrumental variables techniques, for the case q>0, and for a conditionally heteroscedastic error term, the test described here is applicable in a variety of situations where such popular tests as the Box-Pierce (1970) test, Durbin's (1970) h test, and Godfrey's (1978b) Lagrange multiplier test are net applicable. The finite sample properties of the test are examined in Monte Carlo simulations where, with a sample sizes of 50 and 100 observations, the test appears to be quite reliable.

Date: 1990-10
Note: ITI IFM
References: Add references at CitEc
Citations: View citations in EconPapers (11)

Published as Econometrica, Volume 60, No. 1, January 1992, pp. 185-195

Downloads: (external link)
http://www.nber.org/papers/t0092.pdf (application/pdf)

Related works:
Journal Article: Testing the Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions (1992)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberte:0092

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/t0092

Access Statistics for this paper

More papers in NBER Technical Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().