请教： 空间面板logit 模型

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在STATA中，空间计量模型。如何做空间面板的 logit模型？即spatial error/Dubin/ autoregressive logit model
命令是什么?

万分感谢。

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关键词：logit 空间面板 Log logit模型 Spatial error 空间 模型 如何

xgmlt

wfldragon 发表于 2014-1-15 01:41
xgmlt

找来一看，处理截面的而且这个命令，无法安装

那就不太清楚了，建议使用R

wfldragon 发表于 2014-1-15 10:15
那就不太清楚了，建议使用R

谢谢您。
向您确认一下：R可以处理 面板 的spatial Durbin logit model ？对吗？

区域经济爱好者 发表于 2014-1-15 21:36
谢谢您。
向您确认一下：R可以处理 面板 的spatial Durbin logit model ？对吗？

Spatial regression : The choice of function for spatial regression will depend on the support available. If the data are characterised by point support and the spatial process is continuous, geostatistical methods may be used, or functions in the nlme package. If the support is areal, and the spatial process is not being treated as continuous, functions provided in the spdep package may be used. This package can also be seen as providing spatial econometrics functions, and, as noted above, provides basic functions for building neighbour lists and spatial weights, tests for spatial autocorrelation for areal data like Moran's I, and functions for fitting spatial regression models. It provides the full range of local indicators of spatial association, such as local Moran's I and diagnostic tools for fitted linear models, including Lagrange Multiplier tests. Spatial regression models that can be fitted using maximum likelihood include spatial lag models, spatial error models, and spatial Durbin models. For larger data sets, sparse matrix techniques can be used for maximum likelihood fits, while spatial two stage least squares and generalised method of moments estimators are an alternative. When using GMM, sphet can be used to accommodate both autocorrelation and heteroskedasticity. Spatial count regression is provided using custom MCMC by spatcounts. The McSpatial provides functions for locally weighted regression, semiparametric and conditionally parametric regression, fourier and cubic spline functions, GMM and linearized spatial logit and probit, k-density functions and counterfactuals, nonparametric quantile regression and conditional density functions, Machado-Mata decomposition for quantile regressions, spatial AR model, repeat sales models, and conditionally parametric logit and probit. The splm package provides methods for fitting spatial panel data by maximum likelihood and GM. spatialprobit make possible Bayesian estimation of the spatial autoregressive probit model (SAR probit model).
不知道这里有没有你想要的