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Windows of Opportunity

Window Subseries Empirical Variance Estimators in International Relations

Bibliographic Data

ID7971001
AuthorsPatrick Heagerty, Patrick J Heagerty (0000-0002-3403-6007, University of Washington), Michael D Ward (0000-0002-6561-6186, Université Pierre Mendes France), Kristian Skrede Gleditsch (0000-0003-4149-3211, University of California San Diego)
Year2002
Volume10
Issue3
Pages304-317
Publication date2002-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePolitical Analysis (JOURNAL)
Journal identifiersISSN: 1047-1987 • E-ISSN: 1476-4989
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1093/pan/10.3.304
OpenAlexW2147726445
LanguageEN
Citations received11
References cited35

We show that temporal, spatial, and dyadic dependencies among observations complicate the estimation of covariance structures in panel databases. Ignoring these dependencies results in covariance estimates that are often too small and inferences that may be more confident about empirical patterns than is justified by the data. In this article, we detail the development of a nonparametric approach, window subseries empirical variance estimators (WSEV), that can more fully capture the impact of these dependencies on the covariance structure. We illustrate this approach in a simulation as well as with a statistical model of international conflict similar to many applications in the international relations literature

Analysis of covariance · Covariance · Econometrics · Economics · Empirical research · Estimator · Nonparametric statistics · Statistics · Variance (accounting · Computer Science · Global trade and economics · Mathematics · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis

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Unique citing works11
Citations per year0,48
Citation span2003 - 2022 (20)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 11

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