ON THE FIRST-ORDER EFFICIENCY AND ASYMPOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS

Risto Heijmans and Jan Magnus ()

No 293068, University of Amsterdam, Actuarial Science and Econometrics Archive from University of Amsterdam, Faculty of Economics and Business

Abstract: In this paper we study the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations. Our conditions are somewhat weaker than usual, in that we do not require convergences in probability to be uniform or thirdorder derivatives to exist; moreover, the conditions will appear to be readily verifiable. This paper builds on Witting and Nalle's result concerning the asymptotic normality of the maximum likelihood estimator obtained from independent and identically distributed observations, and on a martingale theorem by McLeish.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 24
Date: 1983-06
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Related works:
Journal Article: ON THE FIRST–ORDER EFFICIENCY AND ASYMPTOTIC NORMALITY OF MAXIMUM LIKELIHOOD ESTIMATORS OBTAINED FROM DEPENDENT OBSERVATIONS (1986)
Working Paper: On the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations (1984)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:amstas:293068

DOI: 10.22004/ag.econ.293068

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