Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects.
PLoS One
; 16(12): e0261144, 2021.
Article
en En
| MEDLINE
| ID: mdl-34905573
ABSTRACT
This paper considers the quantile regression model with individual fixed effects for spatial panel data. Efficient minimum distance quantile regression estimators based on instrumental variable (IV) method are proposed for parameter estimation. The proposed estimator is computational fast compared with the IV-FEQR estimator proposed by Dai et al. (2020). Asymptotic properties of the proposed estimators are also established. Simulations are conducted to study the performance of the proposed method. Finally, we illustrate our methodologies using a cigarettes demand data set.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Simulación por Computador
/
Análisis de Regresión
/
Interpretación Estadística de Datos
/
Modelos Estadísticos
/
Productos de Tabaco
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2021
Tipo del documento:
Article
País de afiliación:
China