On the Consistency of Approximate Maximizing Estimator Sequences in the Case of Quasiconcave Functions

Gordon Kemp ()

Economics Discussion Papers from University of Essex, Department of Economics

Abstract: This paper demonstrates consistency for estimators obtained by approximately maximizing a sequence of stochastic quasiconcave functions on RP that converges in probability pointwise to a non-stochastic function. In the scalar parameter case all that is necessary for consistency is that the parameter value of interest is a unique maximizer of the limiting function. However, in the vector parameter case certain further conditions on the limiting function are necessary to establish consistency. The paper also discusses the relation of these results to existing results on the consistency of estimators obtained by approximately maximizing concave functions and to the concepts of hypoconvergence and epiconvergence.

New Economics Papers: this item is included in nep-ecm and nep-eff
Date: 2007-09-28

Downloads: (external link)
http://www.essex.ac.uk/economics/discussion-papers/papers-text/dp641.pdf

Related works:
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: http://EconPapers.repec.org/RePEc:esx:essedp:641

Ordering information: This working paper can be ordered from
Discussion Papers Administrator, Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, U.K.
http://www.essex.ac. ... /papers-request.shtm

Access Statistics for this paper

More papers in Economics Discussion Papers from University of Essex, Department of Economics
Contact information at EDIRC.
Series data maintained by Essex Economics Web Manager ().