A note on the asymptotic efficiency of the restricted estimation

José Hernández (joseantonio.hernandez@ulpgc.es)

Documentos de trabajo conjunto ULL-ULPGC from Facultad de Ciencias Económicas de la ULPGC

Abstract: This paper provides a unified framework for the analysis of the stochastic and deterministic constrained estimation. In a general framework it is show that stochastic restrictions method estimates can be asymptotically more e.cient than estimates ignoring prior information, and can achieve efficiency of the restricted estimate if prior information grows faster than the sample information in the asymptotics. As an example of the applicability of the previous result, the maximum likelihood stochastically restricted criterion is provided.

Keywords: Prior information; stochastic restrictions; efficiency; maximum likelihood. (search for similar items in EconPapers)
Pages: 19 pages
Date: 2005-01
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.bibliotecas.ulpgc.es/fcee/hemeroteca/do ... /doc41/DT2005-01.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to www.bibliotecas.ulpgc.es:80 (No such host is known. )

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: https://EconPapers.repec.org/RePEc:can:series:2005-01

Access Statistics for this paper

More papers in Documentos de trabajo conjunto ULL-ULPGC from Facultad de Ciencias Económicas de la ULPGC
Bibliographic data for series maintained by Patricia Santana (patricia.santana106@estudiantes.ulpgc.es).