scholarly journals Least squares estimation of spatial autoregressive models for large-scale social networks

2019 ◽  
Vol 13 (1) ◽  
pp. 1135-1165
Author(s):  
Danyang Huang ◽  
Wei Lan ◽  
Hao Helen Zhang ◽  
Hansheng Wang
Keyword(s):  
Social Networks ◽  
Least Squares ◽  
Large Scale ◽  
Least Squares Estimation ◽  
Autoregressive Models ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models

CONSISTENCY AND EFFICIENCY OF LEAST SQUARES ESTIMATION FOR MIXED REGRESSIVE, SPATIAL AUTOREGRESSIVE MODELS

2002 ◽  
Vol 18 (2) ◽  
pp. 252-277 ◽  
Author(s):  
Lung-Fei Lee
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Instrumental Variables ◽  
Estimation Method ◽  
Least Squares Estimation ◽  
Autoregressive Models ◽  
Least Squares Estimators ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models ◽  
Asymptotically Efficient

Least squares estimation has casually been dismissed as an inconsistent estimation method for mixed regressive, spatial autoregressive models with or without spatial correlated disturbances. Although this statement is correct for a wide class of models, we show that, in economic spatial environments where each unit can be influenced aggregately by a significant portion of units in the population, least squares estimators can be consistent. Indeed, they can even be asymptotically efficient relative to some other estimators. Their computations are easier than alternative instrumental variables and maximum likelihood approaches.

Sign in / Sign up

Export Citation Format

Share Document