Malikov, Emir and Sun, Yiguo (2017): Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models. Forthcoming in: Journal of Econometrics
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Abstract
This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in which unknown coefficients are permitted to be nonparametric functions of some contextual variables to allow for potential nonlinearities and parameter heterogeneity in the spatial relationship. Unlike other semiparametric spatial dependence models, ours permits the spatial autoregressive parameter to meaningfully vary across units and thus allows the identification of a neighborhood-specific spatial dependence measure conditional on the vector of contextual variables. We propose several (locally) nonparametric GMM estimators for our model. The developed two-stage estimators incorporate both the linear and quadratic orthogonality conditions and are capable of accommodating a variety of data generating processes, including the instance of a pure spatially autoregressive semiparametric model with no relevant regressors as well as multiple partially linear specifications. All proposed estimators are shown to be consistent and asymptotically normal. We also contribute to the literature by putting forward two test statistics to test for parameter constancy in our model. Both tests are consistent.
Item Type: | MPRA Paper |
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Original Title: | Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models |
Language: | English |
Keywords: | Consistent Test, Constrained Estimation, Local Linear Fitting, Nonparametric GMM, Partially Linear, Quadratic Moments, SAR, Spatial Lag |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions |
Item ID: | 77253 |
Depositing User: | Dr. Emir Malikov |
Date Deposited: | 03 Mar 2017 16:14 |
Last Modified: | 26 Sep 2019 08:25 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/77253 |