A comparison of normal and discrete bootstraps for standard errors in equation systems

Henri Theil, Mercedes C. Rosalsky and Renate Finke

Statistics & Probability Letters, 1984, vol. 2, issue 3, 175-180

Abstract: Root-mean-squared errors and asymptotic standard errors of ML coefficient estimates are compared for equation systems of different size, using normal and discrete bootstrap. It appears that exploiting normality does not yield any gain. Suggestions are made for correcting the downward bias of bootstrap RMSEs.

Keywords: asymptotic; standard; error; bootstrap; equation; system; maximum; likelihood (search for similar items in EconPapers)
Date: 1984
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(84)90010-5
Full text for ScienceDirect subscribers only

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:eee:stapro:v:2:y:1984:i:3:p:175-180

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().