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A meta-analysis of residential water demand studies

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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

  1. 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.

  2. Evidently, the income and household size are not controlled for in the two meta-regressions of the income and household size elasticities, respectively.

  3. 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).

  4. The REML is estimated using the Stata’s metareg routine.

  5. 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).

  6. It is worth noting in what follows that the comparisons of the current results with those of Dalhuisen et al. (2003) and Espey et al. (1997) should partly be taken with caution due mainly to differences in the data used and in some considered variables.

  7. Sebri (2013), Miyawaki et al. (2011), Olmstead (2009) and Martínez-Espiñeira (2003) are still among the few authors who have applied this approach to the context of water demand.

  8. Due to the limited number of observations, the meta-regression of the household size elasticity is not estimated by the bootstrap OLS.

References

  • Arbués, F., Barberán, R., & Villanúa, I. (2004). Price impact on urban residential water demand: A dynamic panel data approach. Water Resources Research, 40(11), W11402(1)–W11402(9).

  • Arbués, F., García-Valiñas, M. A., & Martínez-Espiñeira, R. (2003). Estimation of residential water demand: A state of the art review. Journal of Socio-Economics, 32(1), 81–102.

    Article  Google Scholar 

  • Arbués, F., Villanúa, I., & Barberán, R. (2010). Household size and residential water demand: An empirical approach. The Australian Journal of Agricultural and Resource Economics, 54, 61–80.

    Article  Google Scholar 

  • Asenso-Boadi, F., Peters, T. J., & Coast, J. (2008). Exploring differences in empirical time preference rates for health: An application of meta-regression. Health Economics, 17, 235–248.

    Article  Google Scholar 

  • Ashenfelter, O., Harmon, C., & Oosterbeek, H. (1999). A review of estimates of the schooling/earnings relationship, with tests for publication bias. Labour Economics, 6, 453–470.

    Google Scholar 

  • Barberán, R., & Arbués, F. (2009). Equity in domestic water rates design. Water Resources Management, 23, 2101–2118.

    Article  Google Scholar 

  • Benos, N., & Zotou, S. (2013). Education and economic growth: A meta-regression analysis. MPRA working paper No 46143.

  • Brander, L. M., Van Beukering, P., & Cesar, H. S. J. (2007). The recreational value of coral reefs: A meta-analysis. Ecological Economics, 63, 209–218.

    Article  Google Scholar 

  • Brons, M., Pels, E., Nijkamp, P., & Rietveld, P. (2002). Price elasticities of demand for passenger air travel: A meta-analysis. Journal of Air Transport Management, 8, 165–175.

    Article  Google Scholar 

  • Dalhuisen, J. M., Florax, R. J. G. M., de Groot, H. L. F., & Nijkamp, P. (2003). Price and income elasticities of residential water demand: A meta-analysis. Land Economics, 79, 292–308.

    Article  Google Scholar 

  • Day, B. (1999). A meta-analysis of wage-risk estimates of the value of statistical life. Centre for social and economic research on the global environment, University College London, mimeo.

  • de Blaeij, A., Florax, R. J. G. M., Rietveld, P., & Verhoef, E. T. (2003). The value of statistical life in road safety: A meta-analysis. Accident Analysis and Prevention, 35, 973–986.

    Article  Google Scholar 

  • Delmas, M. A., Fischlein, M., & Asensio, O. I. (2013). Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012. Energy Policy, 61, 729–739.

    Article  Google Scholar 

  • Dimitropoulos, A., Rietveld, P., & van Ommeren, J. N. (2011). Consumer valuation of driving range: A meta-analysis. Tinbergen Institute Discussion Paper 133/3.

  • Espey, J. A., & Espey, M. (2004). Turning on the lights: A meta-analysis of residential electricity demand elasticities. Journal of Agricultural and Applied Economics, 36(1), 65–81.

    Google Scholar 

  • Espey, M., Espey, J., & Shaw, W. D. (1997). Price elasticity of residential demand for water: A meta-analysis. Water Resources Research, 33(6), 1369–1374.

    Article  Google Scholar 

  • Florax, R. (2001). Methodological pitfalls in meta-analysis: Publication bias. Serie Research Memoranda 0028, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

  • Gallet, C. A. (2010). The income elasticity of meat: A meta-analysis. The Australian Journal of Agricultural and Resource Economics, 54, 477–490.

    Article  Google Scholar 

  • Harbord, R. M., Harris, R. J., & Sterne, J. A. C. (2009). Updated tests for small-study effects in meta-analyses. The Stata Journal, 9(2), 197–210.

    Google Scholar 

  • Lindhjem, H. (2007). 20 years of stated preference valuation of non-timber benefits from Fennoscandian forests: A meta-analysis. Journal of Forest Economics, 12, 251–277.

    Article  Google Scholar 

  • Loomis, J. B., & White, D. S. (1996). Economic benefits of rare and endangered species: Summary and meta-Analysis. Ecological Economics, 18, 197–206.

    Article  Google Scholar 

  • Martínez-Espiñeira, R. (2003). Estimating water demand under increasing block tariffs using aggregate data and proportions of users per block. Environmental & Resource Economics, 26(1), 5–23.

    Article  Google Scholar 

  • Miyawaki, K., Omori, Y., & Hibiki, A. (2011). Panel data analysis of Japanese residential water demand using a discrete/continuous choice approach. The Journal of Japanese Economic Association, 62, 417–421.

    Google Scholar 

  • Mu, X., Whittington, D., & Briscoe, J. (1990). Modeling village water demand behavior: A discrete choice approach. Water Resources Research, 26(4), 521–529.

    Article  Google Scholar 

  • Mulatu, A., Florax, R., & Whithagen, C. A. (2003). Environmental regulation and competitiveness: An exploratory meta-analysis. In A. Läschel (Ed.), Empirical modeling of the economy and the environment (pp. 23–54). Berlin: Springer.

    Chapter  Google Scholar 

  • Nauges, C., & Whittington, D. (2010). Estimation of water demand in developing countries: An overview. World Bank Research Observer, 25(2), 263–294.

    Article  Google Scholar 

  • Nelson, J. P. (2004). Meta-analysis of airport noise and hedonic property values: Problems and prospects. Journal of Transport Economics and Policy, 38, 1–28.

    Google Scholar 

  • Nelson, J. P. (2011). Alcohol marketing, adolescent drinking and publication bias in longitudinal studies: A critical survey using meta-analysis. Journal of Economic Surveys, 25(2), 191–232.

    Article  Google Scholar 

  • Nelson, J. P., & Kennedy, P. E. (2009). The use (and abuse) of meta-analysis in environmental and natural resource economics: An assessment. Environmental & Resource Economics, 42, 345–377.

    Article  Google Scholar 

  • Olmstead, S. M. (2009). Reduced-form versus structural models of water demand under non-linear prices. Journal of Business and Economic Statistics, 87(1), 84–94.

    Google Scholar 

  • Rosenberger, R., & Loomis, J. B. (2000). Using meta-analysis for benefit transfer: In sample convergent validity tests for outdoor recreation database. Water Resources Research, 36, 1097–1107.

    Article  Google Scholar 

  • Rosenthal, R. (1979). The “File drawer problem” and tolerance for null results. Psychological Bulletin, 86(3), 638–641.

    Article  Google Scholar 

  • Scheierling, S. M. (2006). Irrigation water demand: A meta-analysis of price elasticities. Water Resources Research, 42, W01411.

    Google Scholar 

  • Sebri, M. (2013). Intergovernorate disparities in residential water demand in Tunisia: A discrete/continuous choice approach. Journal of Environmental Planning and Management, 56(8), 1192–1211.

    Article  Google Scholar 

  • Shin, J. S. (1985). Perception of price when information is costly: Evidence from residential electricity demand. Review of Economics and Statistics, 67(4), 591–598.

    Article  Google Scholar 

  • Stanley, T. D., & Doucouliagos, H. (2012). Meta-regression analysis in economics and business. London: Routledge.

    Google Scholar 

  • Stanley, T. D., & Doucouliagos, H. (2013). Neither fixed nor random: Weighted least squares meta-analysis. School working paper, Economic Series 2013/1, Deakin University, Australia.

  • van den Bergh, J. C., & Button, K. J. (1997). Meta-analysis of environmental issues in regional, urban and transport economics. Urban Studies, 34, 927–944.

    Article  Google Scholar 

  • van Houtven, G., Powers, J., & Pattanayak, S. K. (2007). Valuing water quality improvements in the United States using meta-analysis: Is the glass half-full or half-empty for national policy analysis. Resource and Energy Economics, 29, 206–228.

    Article  Google Scholar 

  • Warren, D., & Chen, L. T. (2013). The relationship between public service motivation and performance. In E. Ringquist (Ed.), Meta-analysis for public management and policy (pp. 442–473). London: Wiley.

    Google Scholar 

  • Worthington, A. C., & Hoffman, M. (2008). An empirical survey of residential water demand modeling. Journal of Economic Surveys, 22(5), 842–871.

    Article  Google Scholar 

  • Zamparini, L., & Reggiani, A. (2007). Meta-analysis and the value of travel time savings: A transatlantic perspective in passenger transport. Networks and Spatial Economics, 7(4), 377–396.

    Article  Google Scholar 

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Acknowledgments

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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  1. Faculty of Economics and Management of Sousse, University of Sousse, Erriadh City, 4023, Sousse, Tunisia

    Maamar Sebri

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  1. Maamar Sebri
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Correspondence to Maamar Sebri.

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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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