Abstract. Meta-analysis is used to determine if there are factors that systematically affect price elasticity estimates in studies of residential water demand in the United States. An econometric model is estimated, using price elasticity estimates from previous studies as the dependent variable. Explanatory variables include functional form, cross-sectional versus time series, water price specification, rate structure, location, season, and estimation technique. Inclusion of income, rainfall, and evapotranspiration are all found to influence the estimate of the price elasticity. Population density, household size, and temperature do not significantly influence the estimate of the price elasticity. Pricing structure and season are, also found to significantly influence the estimate of the price elasticity.
Meta-analysis is used to quantitatively summarize previous studies of residential electricity demand to determine if there are factors that systematically affect estimated elasticities. In this study, price and income elasticities of residential demand for electricity from previous studies are used as the dependent variables, with data characteristics, model structure, and estimation technique as independent variables, using both least square estimation of a semilog model and maximum likelihood estimation of a gamma model. The findings of this research can help better inform public policy makers, regulators, and utilities about the responsiveness of residential electricity consumers to price and income changes.
In this paper we examine the possible reasons why individuals who live in homes facing a flat monthly rate for water accept or reject an offer to have water metering devices installed at no cost to them. A logit model is used to model the discrete choice of acceptance. Since the demand for metering is directly tied to water demand, we estimate demand models for unmetered households in the Reno/Sparks metropolitan area using contingent data obtained by presenting households with hypothetical prices they might encounter under a metering system. Conditional logit and demand models are then used to examine the potential for metering to promote water conservation in the arid Reno/Sparks, Nevada metropolitan area.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.