Network effects error components models

This paper develops a random effects error components structure for network data regression models. In particular, it allows for edge and triangle specific components, which serve as a basal model for modeling network effects. It then evaluates the potential effects of ignoring network effects in th...

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Autor principal: Montes Rojas, Gabriel
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2018
Materias:
Ciencias Económicas
Networks
Clusters
Moulton factor
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/169449
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SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-169449
record_format dspace
spelling I19-R120-10915-1694492024-09-02T20:01:50Z http://sedici.unlp.edu.ar/handle/10915/169449 Network effects error components models Montes Rojas, Gabriel 2018-11 2018 2024-09-02T17:58:51Z en Ciencias Económicas Networks Clusters Moulton factor This paper develops a random effects error components structure for network data regression models. In particular, it allows for edge and triangle specific components, which serve as a basal model for modeling network effects. It then evaluates the potential effects of ignoring network effects in the estimation of the variance-covariance matrix. Network effects will typically imply heteroskedasticity, and as with the Moulton factor, the key role is given by the joint consideration of the intra-network correlation of the error term(s) and the covariates. Then it proposes consistent estimator of the variance components and Lagrange Multiplier tests for evaluating the appropriate model of random components in networks. Monte Carlo simulations show the tests have very good performance in finite samples. Facultad de Ciencias Económicas Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Económicas
Networks
Clusters
Moulton factor
spellingShingle Ciencias Económicas
Networks
Clusters
Moulton factor
Montes Rojas, Gabriel
Network effects error components models
topic_facet Ciencias Económicas
Networks
Clusters
Moulton factor
description This paper develops a random effects error components structure for network data regression models. In particular, it allows for edge and triangle specific components, which serve as a basal model for modeling network effects. It then evaluates the potential effects of ignoring network effects in the estimation of the variance-covariance matrix. Network effects will typically imply heteroskedasticity, and as with the Moulton factor, the key role is given by the joint consideration of the intra-network correlation of the error term(s) and the covariates. Then it proposes consistent estimator of the variance components and Lagrange Multiplier tests for evaluating the appropriate model of random components in networks. Monte Carlo simulations show the tests have very good performance in finite samples.
format Objeto de conferencia
Objeto de conferencia
author Montes Rojas, Gabriel
author_facet Montes Rojas, Gabriel
author_sort Montes Rojas, Gabriel
title Network effects error components models
title_short Network effects error components models
title_full Network effects error components models
title_fullStr Network effects error components models
title_full_unstemmed Network effects error components models
title_sort network effects error components models
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/169449
work_keys_str_mv AT montesrojasgabriel networkeffectserrorcomponentsmodels
_version_ 1809234775886528512

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