Error component model for networks: Specification and testing

This paper develops a subgraph network random effects error components 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 ignor...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Montes Rojas, Gabriel
Formato: Artículo publishedVersion
Lenguaje:Inglés
Publicado: Instituto Interdisciplinario de Economía Política (IIEP UBA-CONICET) 2019
Materias:
Redes
Factor Moulton
Clusters
Networks
Moulton factor
Acceso en línea:https://ojs.economicas.uba.ar/DT-IIEP/article/view/2460
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=dociiep&d=2460_oai
Aporte de:
Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-2460_oai
record_format dspace
spelling I28-R145-2460_oai2026-02-09 Montes Rojas, Gabriel 2019-11-28 This paper develops a subgraph network random effects error components 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. It also 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 that the tests have good performance in finite samples. It applies the proposed tests to the Call interbank market in Argentina. Este trabajo desarrolla modelos de componentes de errores para regresiones con datos en redes. En particular, el modelo permite efectos específicos de links y triángulos, que sirven como una primera aproximación para modelar efectos de redes más complejos. Se evalúan las consecuencias de ignorar los efectos de redes sobre la estimación de la matriz de varianzas y covarianzas en modelos de regresión. Se proponen estimadores consistentes de los componentes de la varianza y contrastes de multiplicadores de Lagrange para evaluar el modelo correcto a ser usado. Simulaciones de Monte Carlo muestran una buena performance en muestras finitas. Se aplican los contrastes al mercado interbancario Call en Argentina. application/pdf https://ojs.economicas.uba.ar/DT-IIEP/article/view/2460 eng Instituto Interdisciplinario de Economía Política (IIEP UBA-CONICET) https://ojs.economicas.uba.ar/DT-IIEP/article/view/2460/3198 Documentos de trabajo del Instituto Interdisciplinario de Economía Política; Núm. 44 (2019): Documento de trabajo del Instituto Interdisciplinario de Economía Política UBA CONICET; 1-38 Working Papers series at Instituto Interdisciplinario de Economía Política; No. 44 (2019): Working Paper Instituto Interdisciplinario de Economía Política UBA CONICET; 1-38 2451-5728 Redes Factor Moulton Clusters Clusters Networks Moulton factor Error component model for networks: Specification and testing Modelo de componentes de errores para redes: Especificación y contrastes info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=dociiep&d=2460_oai
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-145
collection Repositorio Digital de la Universidad de Buenos Aires (UBA)
language Inglés
orig_language_str_mv eng
topic Redes
Factor Moulton
Clusters
Clusters
Networks
Moulton factor
spellingShingle Redes
Factor Moulton
Clusters
Clusters
Networks
Moulton factor
Montes Rojas, Gabriel
Error component model for networks: Specification and testing
topic_facet Redes
Factor Moulton
Clusters
Clusters
Networks
Moulton factor
description This paper develops a subgraph network random effects error components 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. It also 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 that the tests have good performance in finite samples. It applies the proposed tests to the Call interbank market in Argentina.
format Artículo
publishedVersion
author Montes Rojas, Gabriel
author_facet Montes Rojas, Gabriel
author_sort Montes Rojas, Gabriel
title Error component model for networks: Specification and testing
title_short Error component model for networks: Specification and testing
title_full Error component model for networks: Specification and testing
title_fullStr Error component model for networks: Specification and testing
title_full_unstemmed Error component model for networks: Specification and testing
title_sort error component model for networks: specification and testing
publisher Instituto Interdisciplinario de Economía Política (IIEP UBA-CONICET)
publishDate 2019
url https://ojs.economicas.uba.ar/DT-IIEP/article/view/2460
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=dociiep&d=2460_oai
work_keys_str_mv AT montesrojasgabriel errorcomponentmodelfornetworksspecificationandtesting
AT montesrojasgabriel modelodecomponentesdeerrorespararedesespecificacionycontrastes
_version_ 1857043022506622976

Ejemplares similares