A simple solution of the spurious regression problem

Wang Cindy Shin-Huei and Christian Hafner
Additional contact information
Wang Cindy Shin-Huei: National Tsing Hua University, Department of Quantitative Finance, Hsinchu City, Taiwan

Studies in Nonlinear Dynamics & Econometrics, 2018, vol. 22, issue 3, 14

Abstract: This paper develops a new estimator for cointegrating and spurious regressions by applying a two-stage generalized Cochrane-Orcutt transformation based on an autoregressive approximation framework, even though the exact form of the error term is unknown in practice. We prove that our estimator is consistent for a wide class of regressions. We further show that a convergent usual t-statistic based on our new estimator can be constructed for the spurious regression cases analyzed by (Granger, C. W. J., and P. Newbold. 1974. “Spurious Regressions in Econometrics.” Journal of Econometrics 74: 111–120) and (Granger, C. W. J., N. Hyung, and H. Jeon. 2001. “Spurious Regressions with Stationary Series.” Applied Economics 33: 899–904). The implementation of our estimator is easy since it does not necessitate estimation of the long-run variance. Simulation results indicate the good statistical properties of the new estimator in small and medium samples, and also consider a more general framework including multiple regressors and endogeneity.

Keywords: autoregressive approximation; cointegration; generalized Cochrane-Orcutt estimation; spurious regression (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/snde-2015-0040 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
Working Paper: A simple solution of the spurious regression problem (2018)
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:bpj:sndecm:v:22:y:2018:i:3:p:14:n:1

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.1515/snde-2015-0040

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().