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Quantity Uncertainty and Demand: The Case of Water Smart Reader Ownership

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  • Strong Aaron

    (Public Policy Center, University of Iowa, 200 S. Quad, Iowa City, IA 52242, USA)

  • Goemans Chris

    (Department of Agricultural and Resource Economics, Colorado State University, Ft. Collins, CO, USA)

Abstract

There are a number of instances when consumers have imperfect information regarding the quantity they consume. This paper has two objectives: (1) to formally describe how quantity uncertainty is likely to affect consumer behavior and (2) to describe how these changes in behavior are likely to differ depending on how the quantity uncertain good is priced. We develop a theoretical model of consumer behavior under quantity uncertainty which we use to illustrate how different price structures and different locations within price structures matter for how information impacts behavior. We test these hypotheses using a unique panel data set containing information on water consumption habits of more than 88,000 households in the City of Aurora, Colorado. In 2005, Aurora subsidized the purchase of electronic devices for households to monitor water use. These devices provide households with real-time information on their water use. We find that, consistent with the aims of the program, households with the device decreased their water use during periods when they faced a constant marginal price; however, contrary to the aims of the program, their consumption increased during periods when they faced an increasing block rate pricing structure. These results are consistent with the predictions of the theoretical model developed herein.

Suggested Citation

  • Strong Aaron & Goemans Chris, 2014. "Quantity Uncertainty and Demand: The Case of Water Smart Reader Ownership," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 14(3), pages 1-26, July.
  • Handle: RePEc:bpj:bejeap:v:14:y:2014:i:3:p:26:n:8
    DOI: 10.1515/bejeap-2013-0050
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    References listed on IDEAS

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    1. 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.
    2. Olmstead, Sheila M., 2009. "Reduced-Form Versus Structural Models of Water Demand Under Nonlinear Prices," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 84-94.
    3. Isamu Matsukawa, 2004. "The Effects of Information on Residential Demand for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-18.
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    Cited by:

    1. Joseph,George & Ayling,Sophie Charlotte Emi & Miquel-Florensa,Pepita & Bejarano,Hernán D. & Cardona,Alejandra Quevedo, 2021. "Behavioral Insights in Infrastructure Sectors : A Survey," Policy Research Working Paper Series 9704, The World Bank.
    2. María Ángeles García-Valiñas & Sara Suárez-Fernández, 2022. "Are Economic Tools Useful to Manage Residential Water Demand? A Review of Old Issues and Emerging Topics," Post-Print hal-04067487, HAL.
    3. Wichman, Casey J., 2017. "Information provision and consumer behavior: A natural experiment in billing frequency," Journal of Public Economics, Elsevier, vol. 152(C), pages 13-33.

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