SPATIAL SEMIPARAMETRIC MODEL WITH ENDOGENOUS REGRESSORS
This paper proposes a semiparametric generalized method of moments estimator (GMM) estimator for a partially parametric spatial model with endogenous spatially dependent regressors. The finite-dimensional estimator is shown to be consistent and root-n asymptotically normal under some reasonable cond...
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| Veröffentlicht in: | Econometric theory 2016-06, Vol.32 (3), p.714-739 |
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| container_title | Econometric theory |
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| creator | Jenish, Nazgul |
| description | This paper proposes a semiparametric generalized method of moments estimator (GMM) estimator for a partially parametric spatial model with endogenous spatially dependent regressors. The finite-dimensional estimator is shown to be consistent and root-n asymptotically normal under some reasonable conditions. A spatial heteroscedasticity and autocorrelation consistent covariance estimator is constructed for the GMM estimator. The leading application is nonlinear spatial autoregressions, which arise in a wide range of strategic interaction models. To derive the asymptotic properties of the estimator, the paper also establishes a stochastic equicontinuity criterion and functional central limit theorem for near-epoch dependent random fields. |
| doi_str_mv | 10.1017/S0266466614000905 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0266-4666 |
| ispartof | Econometric theory, 2016-06, Vol.32 (3), p.714-739 |
| issn | 0266-4666 1469-4360 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1878788371 |
| source | Cambridge Journals; JSTOR Archive Collection A-Z Listing |
| subjects | Central limit theorem Econometrics Economic models Economic statistics Economic theory Generalized method of moments Random variables Regression analysis Studies Theorems |
| title | SPATIAL SEMIPARAMETRIC MODEL WITH ENDOGENOUS REGRESSORS |
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