SUR Approach for IV Estimation of Canonical Contagion Models

Dong Wan Shin; Hyo Jin Kim; Jinwook Seo

doi:10.1080/03610918.2013.864764

SUR Approach for IV Estimation of Canonical Contagion Models

Dong Wan Shin, Hyo Jin Kim, Jinwook Seo

Department of Statistics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Seemingly unrelated regression (SUR) method is applied to the instrumental variable (IV) estimation of the canonical contagion models. A finite sample Monte Carlo experiment shows that the resulting estimator, IV-SUR estimator, is substantially better than the existing IV estimator in terms of both bias and mean squares error under diverse circumstance of instrument, conditional heteroscedasticity, and cross-section correlation.

Original language	English
Pages (from-to)	378-387
Number of pages	10
Journal	Communications in Statistics: Simulation and Computation
Volume	45
Issue number	1
DOIs	https://doi.org/10.1080/03610918.2013.864764
State	Published - 2 Jan 2016

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Publisher Copyright:
© 2016 Taylor & Francis Group, LLC.

Keywords

Contagion
Instrumental variable estimator
Seemingly unrelated regression

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10.1080/03610918.2013.864764

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SUR Approach for IV Estimation of Canonical Contagion Models

Abstract

Bibliographical note

Keywords

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