Title :
ML Estimation of Spatial Panel Data Geographically Weighted Regression Model
Author_Institution :
Sch. of Econ. & Commerce, South China Univ. of Technol., Guangzhou, China
Abstract :
In this article, the data base of Geographically Weighted Regression (shorted for GWR) model was expanded to panel data. Based on local bandwidth theory, spatial panel data GWR model Maximum Likelihood (ML) estimation, which is under the specification of pooled effect, fixed effects, and random effects, was also deduced in this article, as solved the problem that GWR model can only be used with the cross-sectional data and covered the flaw of global bandwidth insufficiency, so that the estimation could go better with economic actuality.
Keywords :
econometrics; maximum likelihood estimation; regression analysis; GWR model; ML estimation; fixed effect; geographically weighted regression model; local bandwidth theory; maximum likelihood estimation; pooled effect; random effect; spatial panel data; Bandwidth; Data models; Economics; Maximum likelihood estimation; Planning; Spatial databases;
Conference_Titel :
Management and Service Science (MASS), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6579-8
DOI :
10.1109/ICMSS.2011.5999234