The Spatial Efficiency Multiplier and Random Effects in Spatial Stochastic Frontier Models

Anthony J. Glass, Karligash Glass, R. Sickles, T. Weyman-Jones
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引用次数: 6

Abstract

We extend the emerging literature on spatial frontier models in three respects. Firstly, we account for latent heterogeneity by developing a maximum likelihood random effects spatial autoregressive (SAR) stochastic frontier model. Secondly, to analyze the finite sample properties of a spatial stochastic frontier model we develop a Monte Carlo experimental methodology which we then apply. Thirdly, we introduce the concept of the spatial efficiency multiplier and show that the efficiency benchmark for a productive unit from the structural form of a spatial stochastic frontier model differs from the efficiency benchmark from the reduced form of the model.
空间随机前沿模型的空间效率乘数和随机效应
我们从三个方面扩展了空间前沿模型的新兴文献。首先,我们建立了一个极大似然随机效应空间自回归随机前沿模型来解释潜在异质性。其次,为了分析空间随机前沿模型的有限样本性质,我们开发了一种蒙特卡罗实验方法,然后应用于该方法。第三,引入空间效率乘数的概念,证明了空间随机前沿模型结构形式下的生产单位效率基准与模型简化形式下的效率基准是不同的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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