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主讲人 |
Lung-Fei Lee |
简介 |
<p>We provide a novel analytic procedure to construct best linear and quadratic moments of the generalized method of moments (GMM) estimation for a large class of, network and spatial econometric models, which generate a GMM estimator that is, asymptotically more efficient than the quasi maximum likelihood estimator when the, disturbances are non-normal. We apply this procedure to a high order spatial autoregressive model with spatial errors, where the disturbances are heteroskedastic with an, unknown distribution. We apply the model and the estimator to employment data, in US counties, which demonstrates spatial interdependence patterns and channels of, regional economic growth.</p> |
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主讲人简介 |
<p>Prof. Lung-Fei Lee is a professor of economics at the Ohio State University. He is also a fellow of Journal of Econometrics, the Econometric Society, the Spatial Econometrics Association, and the Society for Economic Measurement. He has served as co-editor or associate editor of Journal of Econometrics, Journal of Applied Econometrics, and Regional Science and Urban Economics. His research and publications are in the areas of microeconometrics and theoretical econometrics. His current research is on the development of econometric models of spatial or social interactions. His work has been published in journals including Econometrica, Journal of Econometrics, International Economic Review, Journal of Applied Econometrics.</p>
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期数 |
高级计量经济学与统计学系列讲座2023年春季学期第二讲（总154讲） |
