Theory and Methods: Influence Diagnostics for Simultaneous Equations Models

This paper presents influence diagnostics for simultaneous equations models. It proposes residuals, leverage and other influence measures. A missing data method is adopted to minimize the masking effect due to case deletions. The assessment of local influence is also considered. The paper shows how...

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Bibliographic Details
Published inAustralian & New Zealand journal of statistics Vol. 40; no. 3; pp. 345 - 358
Main Authors Zhao, Yuejen, Lee, Andy H.
Format Journal Article
LanguageEnglish
Published Oxford, UK and Boston, USA Blackwell Publishers Ltd 01.09.1998
Subjects
diagnostics
influential observations
local influence
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Summary:This paper presents influence diagnostics for simultaneous equations models. It proposes residuals, leverage and other influence measures. A missing data method is adopted to minimize the masking effect due to case deletions. The assessment of local influence is also considered. The paper shows how to evaluate the effects that perturbations to the endogenous variables, predetermined variables and case weights may have on the parameter estimates. The diagnostics are illustrated with two examples.
Bibliography:istex:2F16A16D28F0B89FBA57F3B087B40D8AC5F5B260
ArticleID:ANZS038
ark:/67375/WNG-Q2CBC321-J
ISSN:1369-1473
1467-842X
DOI:10.1111/1467-842X.00038