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

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.

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Year of publication:	1984
Authors:	Theil, Henri ; Rosalsky, Mercedes C. ; Finke, Renate
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 2.1984, 3, p. 175-180
Publisher:	Elsevier
Keywords:	asymptotic standard error bootstrap equation system maximum likelihood

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005259201