Gupta, Abhimanyu and Robinson, Peter M (2018) Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension. Journal of Econometrics, 202 (1). pp. 92-107. DOI https://doi.org/10.1016/j.jeconom.2017.05.019
Gupta, Abhimanyu and Robinson, Peter M (2018) Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension. Journal of Econometrics, 202 (1). pp. 92-107. DOI https://doi.org/10.1016/j.jeconom.2017.05.019
Gupta, Abhimanyu and Robinson, Peter M (2018) Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension. Journal of Econometrics, 202 (1). pp. 92-107. DOI https://doi.org/10.1016/j.jeconom.2017.05.019
Abstract
Pseudo maximum likelihood estimates are developed for higher-order spatial autoregressive models with increasingly many parameters, including models with spatial lags in the dependent variables both with and without a linear or nonlinear regression component, and regression models with spatial autoregressive disturbances. Consistency and asymptotic normality of the estimates are established. Monte Carlo experiments examine finite-sample behaviour.
Item Type: | Article |
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Uncontrolled Keywords: | Spatial autoregression; Increasingly many parameters; Consistency; Asymptotic normality; Pseudo Gaussian maximum likelihood; Finite sample performance |
Subjects: | H Social Sciences > HB Economic Theory |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Economics, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 20 Jul 2018 11:45 |
Last Modified: | 30 Oct 2024 15:53 |
URI: | http://repository.essex.ac.uk/id/eprint/21578 |
Available files
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Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0