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

Author

Listed:
  • Koji Miyawaki

    (National Institute for Environmental Studies)

  • Yasuhiro Omori

    (Faculty of Economics, University of Tokyo)

  • Akira Hibiki

    (National Institute for Environmental Studies)

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 random and fixed individual effects. In both models, the price and income elasticities are estimated to be negative and positive, respectively. Further, the number of members and the number of rooms per household have positive relationship to the residential water demand when we apply the model with random individual effects, while they do not in the model with fixed individual effects.

Suggested Citation

  • Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2010. "Panel Data Analysis of Japanese Residential Water Demand Using a Discrete/Continuous Choice Approach," CIRJE F-Series CIRJE-F-764, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2010cf764
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. Piet Rietveld & Jan Rouwendal & Bert Zwart, 2000. "Block Rate Pricing of Water in Indonesia: An Analysis of Welfare Effects," Bulletin of Indonesian Economic Studies, Taylor & Francis Journals, vol. 36(3), pages 73-92.
    6. Hausman, Jerry A, 1985. "The Econometrics of Nonlinear Budget Sets," Econometrica, Econometric Society, vol. 53(6), pages 1255-1282, November.
    7. 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.
    8. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    9. 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.
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    Citations

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    Cited by:

    1. Havranek, Tomas & Irsova, Zuzana & Vlach, Tomas, 2016. "Publication Bias in Measuring the Income Elasticity of Water Demand," MPRA Paper 75247, University Library of Munich, Germany.
    2. María Pérez-Urdiales & María A. García-Valiñas & Roberto Martínez-Espiñeira, 2016. "Responses to Changes in Domestic Water Tariff Structures: A Latent Class Analysis on Household-Level Data from Granada, Spain," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(1), pages 167-191, January.
    3. repec:uwp:landec:v:94:y:2018:i:2:p:259-283 is not listed on IDEAS
    4. Martins, Rita & Quintal, Carlota & Cruz, Luís & Barata, Eduardo, 2016. "Water affordability issues in developed countries – The relevance of micro approaches," Utilities Policy, Elsevier, vol. 43(PA), pages 117-123.
    5. Tomas Havranek & Zuzana Irsova & Tomas Vlach, 2017. "Measuring the Income Elasticity of Water Demand: The Importance of Publication and Endogeneity Biases," Working Papers IES 2017/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2017.
    6. Kenneth A. Baerenklau & Kurt A. Schwabe & Ariel Dinar, 2014. "The Residential Water Demand Effect of Increasing Block Rate Water Budgets," Land Economics, University of Wisconsin Press, vol. 90(4), pages 683-699.
    7. Darío F. Jiménez & Sergio A. Orrego & Felipe A. Vásquez & Roberto D. Ponce, 2017. "Estimating water demand for urban residential use using a discrete-continuous model and disaggregated data at the household level: the case of the city of Manizales, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 153-178, Enero - J.
    8. Baerenklau, Kenneth A. & Schwabe, Kurt & Dinar, Ariel, 2014. "Do Increasing Block Rate Water Budgets Reduce Residential Water Demand? A Case Study in Southern California," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170019, Agricultural and Applied Economics Association.
    9. Zhang, Zibin & Cai, Wenxin & Feng, Xiangzhao, 2017. "How do urban households in China respond to increasing block pricing in electricity? Evidence from a fuzzy regression discontinuity approach," Energy Policy, Elsevier, vol. 105(C), pages 161-172.
    10. Ming-Feng Hung & Bin-Tzong Chie, 2013. "Residential Water Use: Efficiency, Affordability, and Price Elasticity," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 275-291, January.
    11. Maamar Sebri, 2014. "A meta-analysis of residential water demand studies," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 16(3), pages 499-520, June.
    12. Ming-Feng Hung & Bin-Tzong Chie & Tai-Hsin Huang, 2017. "Residential water demand and water waste in Taiwan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(2), pages 249-268, April.
    13. Jiménez, Darío F. & Orrego, Sergio A. & Vásquez, Felipe A. & Ponce, Roberto D., 2016. "Estimación de la demanda de agua para uso residencial urbano usando un modelo discreto-continuo y datos desagregados a nivel de hogar: el caso de la ciudad de Manizales, Colombia," REVISTA LECTURAS DE ECONOMÍA, UNIVERSIDAD DE ANTIOQUIA - CIE, issue 86, pages 153-178, December.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

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