Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 신동완 | * |
dc.date.accessioned | 2016-08-27T04:08:32Z | - |
dc.date.available | 2016-08-27T04:08:32Z | - |
dc.date.issued | 2016 | * |
dc.identifier.issn | 0361-0918 | * |
dc.identifier.issn | 1532-4141 | * |
dc.identifier.other | OAK-16005 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/217822 | - |
dc.description.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. | * |
dc.language | English | * |
dc.publisher | TAYLOR & | * |
dc.publisher | FRANCIS INC | * |
dc.subject | Contagion | * |
dc.subject | Instrumental variable estimator | * |
dc.subject | Seemingly unrelated regression | * |
dc.title | SUR Approach for IV Estimation of Canonical Contagion Models | * |
dc.type | Article | * |
dc.relation.issue | 1 | * |
dc.relation.volume | 45 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 378 | * |
dc.relation.lastpage | 387 | * |
dc.relation.journaltitle | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | * |
dc.identifier.doi | 10.1080/03610918.2013.864764 | * |
dc.identifier.wosid | WOS:000365094700022 | * |
dc.identifier.scopusid | 2-s2.0-84947741330 | * |
dc.author.google | Shin, Dong Wan | * |
dc.author.google | Kim, Hyo Jin | * |
dc.author.google | Seo, Jinwook | * |
dc.contributor.scopusid | 신동완(7403352539) | * |
dc.date.modifydate | 20240116115756 | * |