help for qll

Perform Elliott-Müller efficient test for general persistent time variation in > regression coefficients


qll depvar varlist [ (zvarlist) ] [if exp] [in range] [, rlag(#) ]

qll is for use with time-series data. You must tsset your data before using qll; see tsset. You may apply qll to a single time series of a panel dataset. varlist may contain time-series operators; see help varlist.


qll performs the qLL efficient test for general persistence in time variation in regression coefficients proposed by Elliott and Müller (2006). The test contrasts a stable regression model y = X beta + Z gamma + epsilon from the unstable alternative y = X beta(t) + Z gamma + epsilon. This very general specification nests many of the 'structural break' and 'time varying parameter' models in the literature, allowing for almost any pattern of variation in the coefficients of the X variables, with good power and size even in a heteroskedastic context.

zvarlist specifies the set of Z regressors, whose coefficients are assumed to be fixed over time.


rlag(#) specifies the number of lags to be used in computing the long-run variance matrix. If a positive value is given, that number of lags is used, just as in newey. If a negative value is given, the optimal lag order is chosen by the BIC criterion.

Saved results

qll saves the value of the test statistic, the number of observations in the estimation sample, and a three-element matrix (r(cvmat)) containing the 10%, 5% and 1% critical values of the test for up to 10 regressors in X. If the number of lags is chosen by the BIC criterion, it is also saved as r(biclags). See return list.


. use http://www.stata-press.com/data/r9/lutkepohl.dta

(Quarterly SA West German macro data, Bil DM, from Lutkepohl 1993 Table E.1)

. qll linvestment lincome (lconsumption)

. qll linvestment lincome (lconsumption), rlag(4)

. qll linvestment L(1/4).lincome (L(1/4).lconsumption)

. qll linvestment lincome (lconsumption) if tin(30,85)


I am grateful to Graham Elliott for his clear presentation of the underlying th > eory when visiting Boston College in Spring 2007, and for his MATLAB code from which this > routine was constructed. Remaining errors are my own.


Elliott, G. and Müller, U.K., 2006. Efficient Tests for General Persistent Time Variation in Regression Coefficients. Review of Economic Studies, Vol. 73, pp. 907-940.


qll is not an official Stata command. It is a free contribution to the research community, like a paper. Please cite it as such:

Baum, C.F., 2007. qll: Stata module to perform Elliott-Müller efficient test for general persistent time variation in regression coefficients. http://ideas.repec.org/c/boc/bocode/s456862.html


Christopher F Baum, Boston College, USA baum@bc.edu

Also see

On-line: help for newey