Testing for Autocorrelation in Quantile Regression Models

Lijuan Huo, Tae-Hwan Kim (), Yunmi Kim and Dong Jin Lee
Additional contact information
Lijuan Huo: Beijing Institute of Technology
Yunmi Kim: University of Seoul
Dong Jin Lee: University of Connecticut

No 2014rwp-76, Working papers from Yonsei University, Yonsei Economics Research Institute

Abstract: Quantile regression (QR) models have been increasingly employed in many applied areas in economics. At the early stage, applications in the quantile regression literature have usually used cross-sectional data, but the recent development has seen an increase in the use of quantile regression in both time-series and panel datasets. However, testing for possible autocorrelation, especially in the context of time-series models, has received little attention. As a rule of thumb, one might attempt to apply the usual Breusch-Godfrey LM test to the residuals of a baseline quantile regression. In this paper, we demonstrate analytically and by Monte Carlo simulations that such an application of the LM test can result in potentially large size distortions, especially in either low or high quantiles. We then propose a correct test (named the QF test) for autocorrelation in quantile regression models, which does not suffer from size distortion. Monte Carlo simulations demonstrate that the proposed test performs fairly well in finite samples, across either different quantiles or different underlying error distributions.

Keywords: Quantile regression; autocorrelation; LM test. (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Pages: 22pages
Date: 2014-12
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://121.254.254.220/repec/yon/wpaper/2014rwp-76.pdf (application/pdf)

Related works:
Working Paper: Testing for Autocorrelation in Quantile Regression Models (2013)
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:yon:wpaper:2014rwp-76

Access Statistics for this paper

More papers in Working papers from Yonsei University, Yonsei Economics Research Institute Contact information at EDIRC.
Bibliographic data for series maintained by YERI ().