Maximum likelihood estimation of spatial lag models in the presence of the error-prone variables
Yükleniyor...
Dosyalar
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The literature has recently devoted close attention to error-prone variables. Nevertheless, only a small number of research have considered measurement error in spatial econometric models. The presence of measurement error in the spatial econometric models needs to be considered as a result of the rise in spatial data analysis, as the relationship between the spatial correlation and measurement error influences parameter estimation. Therefore, in this study, the impacts of classical measurement error on the parameter estimation of the spatial lag model are theoretically examined for both response and explanatory variables. Then, using simulation studies, finite sample properties are investigated for various situations. The major findings indicate that although error-prone response variable has an opposing bias effect on parameter estimations, error-prone explanatory variables have a significant influence effect on the bias of parameter estimations. As a result, it is occasionally possible to obtain unbiased estimates only in certain circumstances.
Açıklama
Sahika Gokmen has been supported by TUBITAK 2219 Pot-doc scholarship.
Anahtar Kelimeler
Spatial Econometrics Models, Spatial Lag Model, Spatial Autoregressive Model, Error-Prone Variables, Simulation Study
Kaynak
Communications in Statistics-Theory and Methods
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
52
Sayı
10
Künye
Eralp, A., Gokmen, S., & Dagalp, R. (2023). Maximum likelihood estimation of spatial lag models in the presence of the error-prone variables. Communications in Statistics-Theory and Methods, 52(10), 3229-3240.
