Bayesian Estimation of Demand Functions under Block-Rate Pricing

Koji Miyawaki, Yasuhiro Omori () and Akira Hibiki

No CIRJE-F-712, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: This article proposes a Bayesian estimation of demand functions under block-rate pricing by focusing on increasing block-rate pricing. This is the first study that explicitly considers the separability condition which has been ignored in previous literature. Under this pricing structure, the price changes when consumption exceeds a certain threshold and the consumer faces a utility maximization problem subject to a piecewise-linear budget constraint. Solving this maximization problem leads to a statistical model in which model parameters are strongly restricted by the separability condition. In this article, by taking a hierarchical Bayesian approach, we implement a Markov chain Monte Carlo simulation to properly estimate the demand function. We find, however, that the convergence of the distribution of simulated samples to the posterior distribution is slow, requiring an additional scale transformation step for parameters to the Gibbs sampler. These proposed methods are then applied to estimate the Japanese residential water demand function.

Pages: 35pages
Date: 2010-01
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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http://www.cirje.e.u-tokyo.ac.jp/research/dp/2010/2010cf712.pdf (application/pdf)

Related works:
Working Paper: Bayesian Estimation of Demand Functions under Block Rate Pricing (2009)
Working Paper: Bayesian Estimation of Demand Functions under Block Rate Pricing (2008)
Working Paper: Bayesian Estimation of Demand Functions under Block Rate Pricing (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2010cf712

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