Second-order properties of estimators of serial correlation from regression residuals

Dennis P. Sheehan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Second-order properties of estimators and tests offer a way of choosinf among aymptotically equivalent procedures. This paper studies the second-order terms of two estimators of serial correlation in the linear model. Using these second-order approximations, the maximum likelihood estimator is judge to be superior in terms of bias and variance. A small Monte Carlo experiment is done to assess the accuracy of the results.

Original languageEnglish (US)
Pages (from-to)299-311
Number of pages13
JournalJournal of Econometrics
Volume27
Issue number3
DOIs
StatePublished - Jan 1 1985

Fingerprint

Serial Correlation
Regression
Estimator
Second-order Approximation
Monte Carlo Experiment
Maximum Likelihood Estimator
Linear Model
Term
Serial correlation
Monte Carlo experiment
Maximum likelihood estimator
Second-order approximation

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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Second-order properties of estimators of serial correlation from regression residuals. / Sheehan, Dennis P.

In: Journal of Econometrics, Vol. 27, No. 3, 01.01.1985, p. 299-311.

Research output: Contribution to journalArticle

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