Abstract
Although widely studied, the residential water demand remains a controversial issue. The purpose of the current study is to investigate systematic variations across related studies using meta-analysis approach. Particularly, a meta-analytical regression is performed to assess the sensitivity of the price, income and household size elasticities to a number of characteristics including demand specification, data characteristics, price specification, tariff structure, functional form, estimation technique and location of demand. The empirical results of the study reveal that these characteristics have differing influence on the reported elasticities. Obviously, these findings lie in their importance for regulators and policy makers and for academics alike. Among others, two important conclusions emerge. First, water use in summer and winter seasons and water use for indoor and outdoor purposes are found to be important factors affecting the price elasticity. This suggests that peak-load water pricing may be an effective tool for managing water demand. Second, the three elasticities tend to be differently estimated across various regions of the world as well as between developed and developing countries. Therefore, decision makers in a given country would not rely on the findings of studies conducted on other countries in formulating their policies.



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Notes
Due to limited space, the complete list of studies used in this meta-analysis is not provided here but is available upon request from the author.
Evidently, the income and household size are not controlled for in the two meta-regressions of the income and household size elasticities, respectively.
The Shin price specification is used to address the price perception issue. Shin (1985) introduced a price-perception parameter to test whether consumers respond to average price, marginal price, or a combination of the two. Different values of this parameter, combined with different rate structures, yield different theoretical results about the ordering of perceived, marginal, and average price values (Arbués et al. 2003).
The REML is estimated using the Stata’s metareg routine.
Note here that the common approach consists in using the precision (inverse of standard errors) or standard errors on the vertical axis. However, as explained previously, these latter are not available and, therefore, the square root of sample size are used instead. Such a practice is recently adopted by many meta-analysts in constructing the funnel plots, including Delmas et al. (2013) and Dimitropoulos et al. (2011).
Due to the limited number of observations, the meta-regression of the household size elasticity is not estimated by the bootstrap OLS.
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The author is very grateful to the Editor D. Pimentel and two anonymous reviewers for their valuable comments and suggestions, which have helped improve the paper considerably.
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Sebri, M. A meta-analysis of residential water demand studies. Environ Dev Sustain 16, 499–520 (2014). https://doi.org/10.1007/s10668-013-9490-9
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DOI: https://doi.org/10.1007/s10668-013-9490-9