Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances |
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Authors: | Lung-fei Lee |
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Institution: |
a Department of Economics, Ohio State University, Columbus, Ohio, USA |
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Abstract: | Estimation of a cross-sectional spatial model containing both a spatial lag of the dependent variable and spatially autoregressive disturbances are considered. Kelejian and Prucha (1998)]described a generalized two-stage least squares procedure for estimating such a spatial model. Their estimator is, however, not asymptotically optimal. We propose best spatial 2SLS estimators that are asymptotically optimal instrumental variable (IV) estimators. An associated goodness-of-fit (or over identification) test is available. We suggest computationally simple and tractable numerical procedures for constructing the optimal instruments. |
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Keywords: | Spatial autoregressive model Two-stage least squares Asymptotic efficiency Best two-stage least squares Cholesky decomposition Contracting mapping |
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