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- W2566026835 abstract "ABSTRACTHeteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-varying coefficients. Spatial Economic Analysis. The spatial model with space-varying coefficients proposed by Sun et al. in 2014 has proved to be useful in detecting the location effects of the impacts of covariates as well as spatial interaction in empirical analysis. However, Sun et al.’s estimator is inconsistent when heteroskedasticity is present – a circumstance that is more realistic in certain applications. In this study, we propose a kind of semi-parametric generalized method of moments (GMM) estimator that is not only heteroskedasticity robust but also takes a closed form written explicitly in terms of observed data. We derive the asymptotic distributions of our estimators. Moreover, the results of Monte Carlo experiments show that the proposed estimators perform well in finite samples." @default.
- W2566026835 created "2017-01-06" @default.
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- W2566026835 date "2016-12-09" @default.
- W2566026835 modified "2023-09-26" @default.
- W2566026835 title "Heteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-varying coefficients" @default.
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- W2566026835 doi "https://doi.org/10.1080/17421772.2017.1250940" @default.
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