Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension

DOI10.1016/j.jeconom.2017.05.019zbMath1378.62070OpenAlexW3023379985MaRDI QIDQ1680193

Peter M. Robinson, Abhimanyu Gupta

Publication date: 23 November 2017

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://eprints.lse.ac.uk/84085/

zbMATH Keywords

consistencyasymptotic normalitynonlinear regressionspatial autoregressionfinite sample performanceincreasingly many parameterspseudo Gaussian maximum likelihood

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

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GMM estimation of a spatial autoregressive model with autoregressive disturbances and endogenous regressors, Polynomial network autoregressive models with divergent orders, Sequential monitoring of high‐dimensional time series, Spatial autoregressions with an extended parameter space and similarity-based weights, Inference in a similarity-based spatial autoregressive model, Bipartite network influence analysis of a two-mode network, Shrinkage estimation of network spillovers with factor structured errors, Covariance Model with General Linear Structure and Divergent Parameters, Nonparametric specification testing via the trinity of tests, ESTIMATION OF SPATIAL AUTOREGRESSIONS WITH STOCHASTIC WEIGHT MATRICES, Adjusted QMLE for the spatial autoregressive parameter, Approximate least squares estimation for spatial autoregressive models with covariates, LARGE SAMPLE PROPERTIES OF BAYESIAN ESTIMATION OF SPATIAL ECONOMETRIC MODELS, SPATIAL DEPENDENCE IN OPTION OBSERVATION ERRORS, Efficient closed-form estimation of large spatial autoregressions

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