Stochastic Semi-Nonparametric Efficiency Analysis of Electricity Distribution Networks: Application of the StoNED Method in the Finnish Regulatory Model

Timo Kuosmanen
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引用次数: 2

Abstract

Electricity distribution network is a prime example of a natural local monopoly. In many countries, electricity distribution is regulated by the government. In Finland, the regulator estimates the efficient cost frontier using the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) methods. This paper reports the main results of the research project commissioned by the Finnish regulator for further development of the efficiency estimation in their regulatory model. The key objectives of the project were to integrate a stochastic SFA-style noise term to the nonparametric, axiomatic DEA-style cost frontier, and take into account the heterogeneity of firms and their operating environments. To estimate the resulting stochastic semi-parametric cost frontier model, a new method called stochastic nonparametric envelopment of data (StoNED) is proposed. Based on the insights obtained in the empirical analysis using real data of the regulated networks, the Finnish regulator is replacing the currently used DEA and SFA methods by the StoNED method.
配电网的随机半非参数效率分析:StoNED方法在芬兰监管模型中的应用
配电网络是地方自然垄断的典型例子。在许多国家,电力分配是由政府管理的。在芬兰,监管机构使用数据包络分析(DEA)和随机前沿分析(SFA)方法估计有效成本前沿。本文报告了芬兰监管机构委托的研究项目的主要结果,以进一步发展其监管模型中的效率估计。该项目的主要目标是将随机sfa风格的噪声项整合到非参数、公理化dea风格的成本前沿,并考虑到企业及其经营环境的异质性。为了估计得到的随机半参数成本前沿模型,提出了一种新的方法——随机非参数数据包络(StoNED)。基于使用受监管网络的真实数据进行实证分析所获得的见解,芬兰监管机构正在用StoNED方法取代目前使用的DEA和SFA方法。
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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