A simple recursive estimation method for linear regression models with AR(p) disturbances

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

An exact transformation that reduces the AR(p) process into white noise is well known in statistics, see Fuller (1976). However, practitioners still use and econometric textbooks still recommend the Cochrane-Orcutt procedure for p>2, see Greene (1990). This paper derives an alternative exact transformation for the AR(p) process which is computationally simple. Based on this transformation, a GLS estimator is proposed, requiring only least squares regressions and recursive computations. This is illustrated for the AR(3) case.

Original languageEnglish (US)
Pages (from-to)93-100
Number of pages8
JournalStatistical Papers
Volume35
Issue number1
DOIs
StatePublished - Dec 1 1994
Externally publishedYes

Keywords

  • Autocorrelation Transformation
  • Autoregressive Process
  • Serial Correlation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'A simple recursive estimation method for linear regression models with AR(p) disturbances'. Together they form a unique fingerprint.

Cite this