Robust Test for Heteroskedasticity in the Error Components Model

Detalles Bibliográficos
Autor Principal: Montes Rojas, Gabriel
Otros autores o Colaboradores: Sosa Escudero, Walter
Formato: Recurso web
Lengua:inglés
Datos de publicación: [S.l.] : s.n. , 2010
Temas:
Acceso en línea:Consultar en el Cátalogo
Resumen:This paper constructs tests for homoskedasticity in one-way panel data error components models in line with Baltagi, Bresson and Pirotte (Journal of Econometrics 134, 2006). Our proposed tests have two robustness properties. First, we present evidence showing that the Gaussian based statistics of Baltagi et al. reject too often in the presence of asymmetric (e.g. log-normal) and heavy-tailed (e.g. t-Student) distributions. By using simple moment conditions, we derive distribution free tests statistics that are robust to these non-normalities. Second, a small sample correction makes our marginal tests insensitive to heteroskedasticity in the component not being checked, and hence help identify the source of heteroskedasticity. Additionally, they are computationally convenient since they are based on simple artificial regressions using pooled OLS residuals
Notas:Publicado en: Journal of Econometrics, 160, 300–310

MARC

LEADER 00000nai a2200000 a 4500
001 166503
003 AR-LpUFCE
005 20250714121630.0
007 cr |||||||||||
008 230201s2010 en || woo 0 ||eng d
024 8 |a DEO-M15221  |z DEO013692 
040 |a AR-LpUFCE  |b spa  |c AR-LpUFCE 
100 1 |a Montes Rojas, Gabriel 
245 1 0 |a Robust Test for Heteroskedasticity in the Error Components Model 
260 |a [S.l.] :  |b  s.n. ,  |c 2010 
500 |a Publicado en: Journal of Econometrics, 160, 300–310 
520 |a This paper constructs tests for homoskedasticity in one-way panel data error components models in line with Baltagi, Bresson and Pirotte (Journal of Econometrics 134, 2006). Our proposed tests have two robustness properties. First, we present evidence showing that the Gaussian based statistics of Baltagi et al. reject too often in the presence of asymmetric (e.g. log-normal) and heavy-tailed (e.g. t-Student) distributions. By using simple moment conditions, we derive distribution free tests statistics that are robust to these non-normalities. Second, a small sample correction makes our marginal tests insensitive to heteroskedasticity in the component not being checked, and hence help identify the source of heteroskedasticity. Additionally, they are computationally convenient since they are based on simple artificial regressions using pooled OLS residuals 
650 4 |a ECONOMÍA 
700 1 |a Sosa Escudero, Walter 
942 |c BK 
863 |i 2010 
866 0 |a 2010 
952 |0 0  |1 0  |4 0  |7 3  |8 BD  |9 257114  |a DEO  |b DEO  |d 2025-07-14  |l 0  |r 2025-07-14 12:16:30  |u http://catalogo.econo.unlp.edu.ar/meran/getDocument.pl?id=1502  |w 2025-07-14  |y BK 
999 |c 166503  |d 166503