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Asymptotic Distributions of Quasi‐Maximum Likelihood Estimators for Spatial Autoregressive Models
Author(s) -
Lee LungFei
Publication year - 2004
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.1111/j.1468-0262.2004.00558.x
Subject(s) - estimator , autoregressive model , mathematics , convergence (economics) , rate of convergence , statistics , maximum likelihood , matrix (chemical analysis) , econometrics , computer science , economics , computer network , channel (broadcasting) , materials science , composite material , economic growth
This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi‐maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of those estimators may depend on some general features of the spatial weights matrix of the model. It is important to make the distinction with different spatial scenarios. Under the scenario that each unit will be influenced by only a few neighboring units, the estimators may have ‐rate of convergence and be asymptotically normal. When each unit can be influenced by many neighbors, irregularity of the information matrix may occur and various components of the estimators may have different rates of convergence.