Heteroscedastic stratified two-way EC models of single equations and SUR systems

Abstract

A relevant issue in panel data estimation is heteroscedasticity, which often occurs when the sample is large and individual units are of varying size. Furthermore, many of the available panel data sets are unbalanced in nature, because of attrition or accretion, and micro-econometric models applied to panel data are frequently multi-equation models. This paper considers the general least squares estimation of the heteroscedastic stratified two-way error component (EC) models of both single equations and seemingly unrelated regressions (SUR) systems (with cross-equations restrictions) on unbalanced panel data. The derived heteroscedastic estimators of both single equations and SUR systems improve the estimation efficiency.

Determinan Pertumbuhan Ekonomi Negara ASEAN: Model Data Panel

“…Sebagai solusi atas masalah tersebut, model fixed effect yang terpilih di estimasi dengan metode GLS menggunakan timbangan cross section SUR (Platoni et al, 2020). Hasil uji Breausch-Pagan LM model fixed effect tertimbang cross section SUR memperoleh nilai uji statistik 0,6509 dengan nilai p-value sebesar 1,00.…”

“…Hasil uji Breausch-Pagan LM model fixed effect tertimbang cross section SUR memperoleh nilai uji statistik 0,6509 dengan nilai p-value sebesar 1,00. Hasil uji ini menunjukkan bahwa residual model fixed effect tertimbang cross section SUR bersifat homogen atau memenuhi asumsi (Platoni et al, 2020). Demikian juga, nilai statistik Durbin-Watson pada model fixed effect tertimbang cross section SUR, menunjukkan nilai yang lebih tinggi dari nilai statistik Durbin-Watson model fixed effect tanpa tertimbang.…”