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Parameter instability in quantile regression

Marilena Furno is Department of Economics, Universitá di Cassino, Italy furnoma{at}tin.it

The paper analyzes the behavior of a test for structural break based on quantile regression estimates. It considers the case of an estimated break in conjunction with independent and identically distributed (i.i.d.) and non-i.i.d. errors. It compares the null and the alternative models, where the null imposes stability, while the alternative allows the regression coefficients to change in response to the break. The test relies on the increase of the objective function and the worsening of the fit when unnecessary constraints are imposed. An example with serially correlated real data and a Monte Carlo study taking into account non-normal and non-i.i.d. errors analyze the behavior of the test.

Key Words: likelihood ratio test • quantile regression • robustness • structural break

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Statistical Modelling, Vol. 7, No. 4, 345-362 (2007)
DOI: 10.1177/1471082X0700700405


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This Article Abstract Free Full Text (Free PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Add to Saved Citations Download to citation manager Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Furno, M. Search for Related Content Social Bookmarking                         What's this?