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Panel Data Analysis of Japanese Residential Water Demand Using a Discrete/Continuous Choice Approach

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  • Koji Miyawaki
  • Yasuhiro Omori
  • Akira Hibiki

Abstract

Block rate pricing is often applied to income taxation, telecommunication services, and brand marketing in addition to its best-known application in public utility services. Under block rate pricing, consumers face piecewise-linear budget constraints. A discrete/continuous choice approach is usually used to account for piecewise-linear budget constraints for demand and price endogeneity. A recent study proposed a methodology to incorporate a separability condition that previous studies ignore, by implementing a Markov chain Monte Carlo simulation based on a hierarchical Bayesian approach. To extend this approach to panel data, our study proposes a Bayesian hierarchical model incorporating the individual effect. The random coefficients model result shows that the price and income elasticities are estimated to be negative and positive, respectively, and the coefficients of the number of members and the number of rooms per household are estimated to be positive. Furthermore, the AR(1) error component model suggests that the Japanese residential water demand does not have serial correlation.

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Paper provided by Institute of Economic Research, Hitotsubashi University in its series Global COE Hi-Stat Discussion Paper Series with number gd09-123.

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Date of creation: Mar 2010
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Handle: RePEc:hst:ghsdps:gd09-123

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Keywords: Block rate pricing; Bayesian analysis; Panel data; residential water demand;

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  1. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
  2. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  3. Motta, Ronaldo Ser A Da & Huber, Richard M. & Ruitenbeek, H. Jack, 1999. "Market based instruments for environmental policymaking in Latin America and the Caribbean: lessons from eleven countries," Environment and Development Economics, Cambridge University Press, vol. 4(02), pages 177-201, May.
  4. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
  5. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2006. "Bayesian Estimation of Demand Functions under Block Rate Pricing," CIRJE F-Series CIRJE-F-424, CIRJE, Faculty of Economics, University of Tokyo.
  6. Julie A. Hewitt & W. Michael Hanemann, 1995. "A Discrete/Continuous Choice Approach to Residential Water Demand under Block Rate Pricing," Land Economics, University of Wisconsin Press, vol. 71(2), pages 173-192.
  7. Ellen M. Pint, 1999. "Household Responses to Increased Water Rates during the California Drought," Land Economics, University of Wisconsin Press, vol. 75(2), pages 246-266.
  8. Jasper M. Dalhuisen & Raymond J. G. M. Florax & JHenri L. F. de Groot & Peter Nijkamp, 2003. "Price and Income Elasticities of Residential Water Demand: A Meta-Analysis," Land Economics, University of Wisconsin Press, vol. 79(2), pages 292-308.
  9. Hausman, Jerry A, 1985. "The Econometrics of Nonlinear Budget Sets," Econometrica, Econometric Society, vol. 53(6), pages 1255-82, November.
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