衡量意大利电力市场的需求弹性:双重定价方案下的贝叶斯实验

Maria Chiara D’Errico
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引用次数: 0

摘要

本研究旨在提供一个􏰅exible和分析优雅的框架,以可靠地估计电力需求的价格弹性。推断适用于意大利批发电力市场的每小时需求水平,并使用个人需求出价数据。个人的出价代表了事前支付意愿,因此可以利用二元性方法构建基于消费者行为理论的市场需求。采用贝叶斯计量估计,放宽了传统线性回归模型的同方差假设。它允许识别稳健的结果,显示弹性变化显著􏰄cantly之间的小时一天,区域分割以及均衡价格的水平。贝叶斯推理还提供了一个机会,包括来自先前研究的先验信息和控制代理人行为的制度结构。这种先验信息包含一定程度的不确定性,因此贝叶斯方法将其分配为概率分布。然后利用贝叶斯规则,根据观测数据更新先验信息。结果验证了旨在促进竞争和增加福利的市场改革,即使是通过触发消费者价格反应的时变定价方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring Demand Elasticity in the Italian Power Market: a Bayesian Experiment under dual pricing scheme
This study run experiment aiming to provide a 􏰅exible and analytically elegant framework to reliably estimate the price elasticity of electricity demand. Inference pertains to the demand at hourly level in the Italian wholesale electricity market and uses individual demand bid data. Individuals' bids represent the ex-ante willingness to pay and thus allows for constructing a market demand grounded in the consumer behavior theory, by exploiting the duality approach. Bayesian econometric estimation is applied, relaxing homoskedasticity assumptions of the traditional linear regression model. It allows to identify robust results, showing that elasticity varies signi􏰄cantly among hours of the day, zone segmentation as well as the level of equilibrium price. Bayesian inference provides also the opportunity to include prior information sourced from previous studies and the institutional struc- ture governing the agents' behavior. This prior information involves some degree of uncertainty, for this reason Bayesian approach assigns it a probability distribution. Using Bayes rule, prior information are then updated according to the observed data. Results validate the market reform designed to foster competition and increase wel- fare even through the time-varying pricing schemes that trigger the consumers' price reaction.
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