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Estimating Water Demand in Urban Indonesia: A Maximum Likelihood Approach to block Rate Pricing Data

Author

Listed:
  • Piet Rietveld

    (Vrije Universiteit Amsterdam)

  • Jan Rouwendal

    (Landbouwuniversiteit Wageningen)

  • Bert Zwart

    (Vrije Universiteit Amsterdam)

Abstract

In this paper the Burtless and Hausman model is used to estimate water demand in Salatiga, Indonesia. Other statistical models, as OLS and IV, are found to be inappropiate. A topic, which does not seem to appear in previous studies, is the fact that the density function of the loglikelihood can be made arbitrary high if observations are located exactly on a kink of the budget constraint. To avoid this problem, a discretization technique is used to work with genuine probabilities. The unconditional distribution of water demand is explored with parametric and semiparametric techniques. An important conclusion is that the distribution of water demand is not unimodal and that data are clustered aroundkinks. Main estimation results are a price elasticity of approximately -1.2 and an income elasticity of 0.05. Price and income elasticities are mutually dependent. The estimated model is finally used to investigate consequences for social welfare when a uniform price level is chosen. It is argued that without loss of total welfare, the complex rate structure can be replaced by a uniform marginal price.

Suggested Citation

  • Piet Rietveld & Jan Rouwendal & Bert Zwart, 1997. "Estimating Water Demand in Urban Indonesia: A Maximum Likelihood Approach to block Rate Pricing Data," Tinbergen Institute Discussion Papers 97-072/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19970072
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    File URL: https://papers.tinbergen.nl/97072.pdf
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    References listed on IDEAS

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    1. Soest, Arthur van & Kapteyn, Arie & Kooreman, Peter, 1993. "Coherency and regularity of demand systems with equality and inequality constraints," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 161-188.
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    3. Thomas MaCurdy & David Green & Harry Paarsch, 1990. "Assessing Empirical Approaches for Analyzing Taxes and Labor Supply," Journal of Human Resources, University of Wisconsin Press, vol. 25(3), pages 415-490.
    4. Blomquist, Soren, 1996. "Estimation methods for male labor supply functions How to take account of nonlinear taxes," Journal of Econometrics, Elsevier, vol. 70(2), pages 383-405, February.
    5. Michael L. Nieswiadomy & David J. Molina, 1989. "Comparing Residential Water Demand Estimates under Decreasing and Increasing Block Rates Using Household Data," Land Economics, University of Wisconsin Press, vol. 65(3), pages 280-289.
    6. repec:hoo:wpaper:e-90-11 is not listed on IDEAS
    7. Moffitt, Robert, 1990. "The Econometrics of Kinked Budget Constraints," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 119-139, Spring.
    8. Hausman, Jerry A, 1981. "Exact Consumer's Surplus and Deadweight Loss," American Economic Review, American Economic Association, vol. 71(4), pages 662-676, September.
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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. Arbues, Fernando & Garcia-Valinas, Maria Angeles & Martinez-Espineira, Roberto, 2003. "Estimation of residential water demand: a state-of-the-art review," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(1), pages 81-102, March.
    3. Tomas Havranek & Zuzana Irsova & Tomas Vlach, 2018. "Measuring the Income Elasticity of Water Demand: The Importance of Publication and Endogeneity Biases," Land Economics, University of Wisconsin Press, vol. 94(2), pages 259-283.
    4. Ada Jansen & Carl‐erik Schulz, 2006. "Water Demand And The Urban Poor: A Study Of The Factors Influencing Water Consumption Among Households In Cape Town, South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 74(3), pages 593-609, September.

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