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Modelling seasonality in residential water demand: the case of Tunisia

Author

Listed:
  • Younes Ben Zaied

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

  • Marie-Estelle Binet

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

Abstract

This article proposes to model seasonal patterns of residential water demand using the techniques of seasonal integration and cointegration. The methodology is applied to quarterly aggregate time series data for Tunisia (1980-2007), applying the same increasing, multi-step pricing scheme in the whole country. First, a seasonal cointegration analysis demonstrates the relevance of a pricing policy that increases the size of the lower consumption block in summer. Second, the non-seasonal cointegration analysis reveals a relatively high price elasticity for the highest consumption block. Therefore, we also propose to increase the tariff progressivity to promote water savings. This modified pricing scheme will help to achieve goals of environmental protection and social equity.

Suggested Citation

  • Younes Ben Zaied & Marie-Estelle Binet, 2015. "Modelling seasonality in residential water demand: the case of Tunisia," Post-Print halshs-01102007, HAL.
  • Handle: RePEc:hal:journl:halshs-01102007
    DOI: 10.1080/00036846.2014.1002896
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    References listed on IDEAS

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    1. S. Gaudin, 2006. "Effect of price information on residential water demand," Applied Economics, Taylor & Francis Journals, vol. 38(4), pages 383-393.
    2. Simon Porcher, 2014. "Efficiency and equity in two-part tariffs: the case of residential water rates," Applied Economics, Taylor & Francis Journals, vol. 46(5), pages 539-555, February.
    3. Boswijk, H Peter & Franses, Philip Hans, 1995. "Periodic Cointegration: Representation and Inference," The Review of Economics and Statistics, MIT Press, vol. 77(3), pages 436-454, August.
    4. Graeme Dandy & Tin Nguyen & Carolyn Davies, 1997. "Estimating Residential Water Demand in the Presence of Free Allowances," Land Economics, University of Wisconsin Press, vol. 73(1), pages 125-139.
    5. Engle, R. F. & Granger, C. W. J. & Hylleberg, S. & Lee, H. S., 1993. "The Japanese consumption function," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 275-298.
    6. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    7. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    8. Marie-Estelle Binet & Fabrizio Carlevaro & Michel Paul, 2014. "Estimation of Residential Water Demand with Imperfect Price Perception," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(4), pages 561-581, December.
    9. Franses, Philip Hans, 1993. "A method to select between periodic cointegration and seasonal cointegration," Economics Letters, Elsevier, vol. 41(1), pages 7-10.
    10. Lee, Hahn Shik, 1992. "Maximum likelihood inference on cointegration and seasonal cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 1-47.
    11. Moosa, Imad A., 1996. "Modeling Japanese oil imports: A seasonal cointegration approach," Japan and the World Economy, Elsevier, vol. 8(3), pages 279-290, September.
    12. Philip Hans Franses & Michael McAleer, 1998. "Cointegration Analysis of Seasonal Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 651-678, December.
    13. Renwick, Mary E. & Green, Richard D., 2000. "Do Residential Water Demand Side Management Policies Measure Up? An Analysis of Eight California Water Agencies," Journal of Environmental Economics and Management, Elsevier, vol. 40(1), pages 37-55, July.
    14. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    15. James Yoo & Silvio Simonit & Ann P. Kinzig & Charles Perrings, 2014. "Estimating the Price Elasticity of Residential Water Demand: The Case of Phoenix, Arizona," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(2), pages 333-350.
    16. Whittington, Dale, 1992. "Possible Adverse Effects of Increasing Block Water Tariffs in Developing Countries," Economic Development and Cultural Change, University of Chicago Press, vol. 41(1), pages 75-87, October.
    17. John A. Nordin, 1976. "A Proposed Modification of Taylor's Demand Analysis: Comment," Bell Journal of Economics, The RAND Corporation, vol. 7(2), pages 719-721, Autumn.
    18. Philip Hans Franses & Michael McAleer, 1998. "Cointegration Analysis of Seasonal Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 651-678, December.
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    Cited by:

    1. Younes Ben Zaied & Nidhaleddine Ben Cheikh & Pascal Nguyen, 2017. "Modeling nonlinear water demand : The case of Tunisia," Economics Bulletin, AccessEcon, vol. 37(2), pages 637-644.
    2. Favre, Marine & Montginoul, Marielle, 2018. "Water pricing in Tunisia: Can an original rate structure achieve multiple objectives?," Utilities Policy, Elsevier, vol. 55(C), pages 209-223.
    3. Michael O'Donnell & Robert P. Berrens, 2018. "Understanding Falling Municipal Water Demand in a Small City Dependent on the Declining Ogallala Aquifer: Case Study of Clovis, New Mexico," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 1-40, October.

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