Skip to main content
SpringerLink
Log in

Resolving spurious regressions and serially correlated errors

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

This study investigates the spurious regression phenomenon for two independent stationary and non-stationary processes and illustrates, using a Monte Carlo analysis, that estimation of the spurious regression in first differences or with a lagged dependent variable eliminates the spurious regression problem. Moreover, the results also apply in eliminating the problem of serially correlated errors as well as the problem of ARCH(1) errors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Agiakloglou C (2009) Evidence of ARCH(1) errors in the context of spurious regressions. Commun Stat 38: 1803–1810

    Google Scholar 

  • Box GEP, Jenkins GM (1976) Time series analysis, forecasting and control. Holden Day, San Francisco

    Google Scholar 

  • Ferson EW, Sarkissian S, Simin T (2003) Spurious regressions in financial economics?. J Finance 58: 1393–1413

    Article  Google Scholar 

  • Granger CWJ, Newbold P (1974) Spurious regressions in econometrics. J Econom 2: 111–120

    Article  Google Scholar 

  • Granger CWJ, Hyung N, Jeon Y (2001) Spurious regressions with stationary series. Appl Econ 33: 899–904

    Google Scholar 

  • Hendry DF (1980) Econometrics—alchemy or science?. Economica 47: 387–406

    Article  Google Scholar 

  • Marmol F (1995) Spurious regressions between I(d) processes. J Time Ser Anal 16: 313–321

    Article  Google Scholar 

  • Newbold P, Davies N (1978) Error mis-specification and spurious regressions. Int Econ Rev 19: 513–519

    Article  Google Scholar 

  • Phillips PCB (1986) Understanding spurious regressions in econometrics. J Econom 33: 311–340

    Article  Google Scholar 

  • Yule GU (1926) Why do we sometimes get nonsense-correlations between time-series? A study in sampling and the nature of time-series. J R Stat Soc 89: 1–64

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, University of Piraeus, Piraeus, Greece

    Christos Agiakloglou

Authors
  1. Christos Agiakloglou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christos Agiakloglou.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Agiakloglou, C. Resolving spurious regressions and serially correlated errors. Empir Econ 45, 1361–1366 (2013). https://doi.org/10.1007/s00181-012-0647-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00181-012-0647-4

Keywords

JEL Classification

Search

Navigation