The impact of real-time quantity information on residential water demand

Brandt, Peiffer, 2006. 2006 Water and wastewater survey preliminary results and industry trends. Raftelis Financial Consultants, Inc. 〈http://www.environmental-expert.com/Files%5C5306%5Carticles%5C13827%5C462.pdf〉 (accessed 18.05.12). Carter, 2005, Price knowledge in household demand for utility services, Land Econ., 81, 265, 10.3368/le.81.2.265 Darby, Sarah, 2006. The Effectiveness of Feedback on Energy Consumption. Environmental Change Institute, University of Oxford. The Economist, Nov. 6, 2010. Making Every Drop Count. 〈http://www.economist.com/node/17388318〉 (accessed 15.07.13). Faruqui, 2010, The impact of informational feedback on energy consumption – a survey of the experimental evidence, Energy, 35, 1598, 10.1016/j.energy.2009.07.042 Gaudin, 2006, Effect of price information on residential water demand, Appl. Econ., 38, 383, 10.1080/00036840500397499 Hausman, 1978, Specification tests in econometrics, Econometrica, 46, 1251, 10.2307/1913827 Hausman, 1985, Taxes and labor supply, 213, 10.1016/S1573-4420(85)80007-0 Hewitt, 2000, A discrete/continuous choice model of demand under block rate pricing: reply, Land Econ., 76, 324, 10.2307/3147233 Hewitt, 1995, A discrete/continuous choice model of demand under block rate pricing, Land Econ., 71, 173, 10.2307/3146499 Kenney, 2008, Residential water demand management: lessons from Aurora, Colorado, J. Am. Water Resour. Assoc., 44, 192, 10.1111/j.1752-1688.2007.00147.x Kluger, 1996, The effects of feedback interventions on performance: a historical review, a meta-analysis, and a preliminary feedback intervention theory, Psychol. Bull., 119.2, 254, 10.1037/0033-2909.119.2.254 Jessoe, Katrina, Rapson, David, 2012. Knowledge is (Less) power: experimental evidence from residential energy use. NBER Working Paper: 18344. Matsukawa, 2004, The effects of information of residential demand for electricity, Energy J., 25, 1, 10.5547/ISSN0195-6574-EJ-Vol25-No1-1 Moffitt, 1986, The econometrics of piecewise-linear budget constraints: a survey and exposition of the maximum likelihood method, J. Bus. Econ. Stat., 4, 317 Nataraj, 2011, Does marginal price matter? A regression discontinuity approach to estimating water demand, J. Environ. Econ. Manag., 61, 198, 10.1016/j.jeem.2010.06.003 Organization for Economic Cooperation and Development, 1999. Household Water Pricing in OECD Countries. OECD, Paris. Olmstead, 2009, Reduced-form vs. structural models of water demand under non-linear prices, J. Bus. Econ. Stat., 87, 84, 10.1198/jbes.2009.0007 Pint, 1999, Household responses to increased water rates during the California drought, Land Econ., 75, 246, 10.2307/3147009 Sexton, 1989, The conservation and welfare effects of information in a time-of-day pricing experiment, Land Econ., 65, 272, 10.2307/3146671 Stratus Consulting Inc., 1998. Water price elasticities for single-family homes in Texas. Final Report Prepared For: Texas Water Development Board, Boulder, Colorado Strong, 2014, Quantity uncertainty and demand: the case of water smart reader ownership, B.E. J. Econ. Anal. Policy, 14, 669, 10.1515/bejeap-2013-0050 United States Census Bureau, 2000. Census.U.S. Census Bureau. 2000 〈http://www2.census.gov/census_2000/datasets/〉. Waldman, 2000, A discrete/continuous choice model of demand under block rate pricing: comment, Land Econ., 76, 322, 10.2307/3147232 Willis, 2010, Alarming visual display monitors affecting shower end use water and energy conservation in Australian residential households, Resour. Conserv. Recycl., 54, 1117, 10.1016/j.resconrec.2010.03.004 Palma, 1994, Rational choice under an imperfect ability to choose, Am. Econ. Rev., 84, 419 W. Michael Hanemann <http://are.berkeley.edu/courses/EEP162/spring2007/documents/hanemannDeterminantsUrbanWater.pdf.>