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- Publisher Website: 10.1016/j.jeconom.2018.07.010
- Scopus: eid_2-s2.0-85062921008
- WOS: WOS:000468259700010
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Article: Identification and estimation of linear social interaction models
Title | Identification and estimation of linear social interaction models |
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Authors | |
Keywords | Diagonalization Diameter Network Social interaction Spatial model |
Issue Date | 2019 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom |
Citation | Journal of Econometrics, 2019, v. 210 n. 2, p. 434-458 How to Cite? |
Abstract | This paper has two parts. The first part derives the identification conditions for higher-order social interaction models. In the case where social effects depend on the distance between individuals, the upper bounds on the network diameters for non-identified models are derived. Many network properties of non-identified models in the literature can be derived from these upper bounds. This part analyzes which fixed effect elimination methods require less restrictive identification conditions. The second part considers estimation with panel data. This part develops an estimator which is computationally simple and asymptotically as efficient as the maximum likelihood estimator under normality. |
Persistent Identifier | http://hdl.handle.net/10722/258911 |
ISSN | 2023 Impact Factor: 9.9 2023 SCImago Journal Rankings: 9.161 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Kwok, HH | - |
dc.date.accessioned | 2018-09-03T03:57:56Z | - |
dc.date.available | 2018-09-03T03:57:56Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Journal of Econometrics, 2019, v. 210 n. 2, p. 434-458 | - |
dc.identifier.issn | 0304-4076 | - |
dc.identifier.uri | http://hdl.handle.net/10722/258911 | - |
dc.description.abstract | This paper has two parts. The first part derives the identification conditions for higher-order social interaction models. In the case where social effects depend on the distance between individuals, the upper bounds on the network diameters for non-identified models are derived. Many network properties of non-identified models in the literature can be derived from these upper bounds. This part analyzes which fixed effect elimination methods require less restrictive identification conditions. The second part considers estimation with panel data. This part develops an estimator which is computationally simple and asymptotically as efficient as the maximum likelihood estimator under normality. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom | - |
dc.relation.ispartof | Journal of Econometrics | - |
dc.subject | Diagonalization | - |
dc.subject | Diameter | - |
dc.subject | Network | - |
dc.subject | Social interaction | - |
dc.subject | Spatial model | - |
dc.title | Identification and estimation of linear social interaction models | - |
dc.type | Article | - |
dc.identifier.email | Kwok, HH: kwokhh@hku.hk | - |
dc.identifier.authority | Kwok, HH=rp01632 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.jeconom.2018.07.010 | - |
dc.identifier.scopus | eid_2-s2.0-85062921008 | - |
dc.identifier.hkuros | 289106 | - |
dc.identifier.volume | 210 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 434 | - |
dc.identifier.epage | 458 | - |
dc.identifier.isi | WOS:000468259700010 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 0304-4076 | - |