A spatial autoregressive model with a nonlinear transformation of the dependent variable

Xingbai Xu; Lung Fei Lee

doi:10.1016/j.jeconom.2014.12.005

A spatial autoregressive model with a nonlinear transformation of the dependent variable

Xingbai Xu, Lung Fei Lee^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

39 Citations (Scopus)

Abstract

This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a statistical test to compare the nonlinear transformation against alternatives. Monte Carlo experiments are designed to investigate finite sample performance of the proposed estimates and the sizes and powers of the test.

Original language	English
Pages (from-to)	1-18
Number of pages	18
Journal	Journal of Econometrics
Volume	186
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2014.12.005
Publication status	Published - 1 May 2015
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier B.V.

Keywords

Asymptotic distribution of estimators
Instrumental variables
Maximum likelihood
Near-epoch dependence
Nonlinear spatial autoregressive model

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10.1016/j.jeconom.2014.12.005

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abstract = "This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a statistical test to compare the nonlinear transformation against alternatives. Monte Carlo experiments are designed to investigate finite sample performance of the proposed estimates and the sizes and powers of the test.",

keywords = "Asymptotic distribution of estimators, Instrumental variables, Maximum likelihood, Near-epoch dependence, Nonlinear spatial autoregressive model",

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AB - This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a statistical test to compare the nonlinear transformation against alternatives. Monte Carlo experiments are designed to investigate finite sample performance of the proposed estimates and the sizes and powers of the test.

KW - Asymptotic distribution of estimators

KW - Instrumental variables

KW - Maximum likelihood

KW - Near-epoch dependence

KW - Nonlinear spatial autoregressive model

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JO - Journal of Econometrics

JF - Journal of Econometrics

IS - 1

ER -

A spatial autoregressive model with a nonlinear transformation of the dependent variable

Abstract

Bibliographical note

Keywords

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