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首页> 外文期刊>Journal of Econometrics >Efficient GMM estimation of spatial dynamic panel data models with fixed effects
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Efficient GMM estimation of spatial dynamic panel data models with fixed effects

机译：具有固定效应的空间动态面板数据模型的有效GMM估计

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摘要

In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with fixed effects when n is large, and T can be large, but small relative to n. The GMM estimation methods are designed with the fixed individual and time effects eliminated from the model, and are computationally tractable even under circumstances where the ML approach would be either infeasible or computationally complicated. The ML approach would be infeasible if the spatial weights matrix is not row-normalized while the time effects are eliminated, and would be computationally intractable if there are multiple spatial weights matrices in the model; also, consistency of the MLE would require T to be large and not small relative to n if the fixed effects are jointly estimated with other parameters of interest. The GMM approach can overcome all these difficulties. We use exogenous and predetermined variables as instruments for linear moments, along with several levels of their neighboring variables and additional quadratic moments. We stack up the data and construct the best linear and quadratic moment conditions. An alternative approach is to use separate moment conditions for each period, which gives rise to many moments estimation. We show that these GMM estimators are root nT consistent, asymptotically normal, and can be relatively efficient. We compare these approaches on their finite sample performance by Monte Carlo.
机译：在本文中，我们推导了当n较大且T可以较大但相对于n较小时具有固定影响的空间动态面板数据模型的GMM估计的渐近性质。 GMM估计方法的设计是从模型中消除了固定的个体和时间影响，并且即使在ML方法不可行或计算复杂的情况下，也可以在计算上易于处理。如果在消除时间影响的同时未对行权重矩阵进行行归一化，则ML方法将是不可行的;如果模型中存在多个行权重矩阵，则ML方法将难以计算;同样，如果将固定效应与其他感兴趣的参数联合估算，则MLE的一致性要求T相对于n较大且不小。 GMM方法可以克服所有这些困难。我们使用外生的和预定的变量作为线性矩的工具，以及它们相邻变量的数个级别以及其他二次矩。我们堆叠数据并构造最佳线性和二次矩条件。一种替代方法是为每个周期使用单独的力矩条件，这会导致许多力矩估算。我们证明了这些GMM估计量是根nT一致的，渐近正态的，并且可以相对有效。我们将这些方法的蒙特卡罗（Monte Carlo）的有限样本性能进行了比较。

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