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Long-run Study of Residential Water Consumption

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  • Céline Nauges
  • Alban Thomas

Abstract

The estimation of dynamic models and themeasure of long-run effects arerare in residential water demand studies. Weshow in this paper that a dynamicmodel of water consumption can be derived froma structural optimisation programsolved by local communities. Thisnonlinear model is estimated on asample of French municipalities and is foundasymptotically equivalent to a dynamic panel data model that is linear in theparameters. The latter includes anoriginal error-component structure that allowsfor a flexible heterogeneity pattern, including both the usual idiosyncraticeffect, and an additional individualeffect affected by a multiplicative time-varyingparameter. As usual GMM estimators for panel data are not consistent inthis case, we propose a new GMMprocedure that yields consistent and efficientestimates of short- and long-runprice elasticities (respectively −0.26 and−0.40). Copyright Kluwer Academic Publishers 2003

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Bibliographic Info

Article provided by European Association of Environmental and Resource Economists in its journal Environmental and Resource Economics.

Volume (Year): 26 (2003)
Issue (Month): 1 (September)
Pages: 25-43

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Handle: RePEc:kap:enreec:v:26:y:2003:i:1:p:25-43

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  1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  2. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  3. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
  4. Lars Gårn Hansen, 1996. "Water and Energy Price Impacts on Residential Water Demand in Copenhagen," Land Economics, University of Wisconsin Press, vol. 72(1), pages 66-79.
  5. Alain Carpentier & Robert D. Weaver, 1997. "Damage Control Productivity: Why Econometrics Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 47-61.
  6. Ahn, Seung C. & Schmidt, Peter, 1997. "Efficient estimation of dynamic panel data models: Alternative assumptions and simplified estimation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 309-321.
  7. Patrick Point, 1993. "Partage de la ressource en eau et demande d'alimentation en eau potable," Revue économique, Presses de Sciences-Po, vol. 0(4), pages 849-862.
  8. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  9. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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Cited by:
  1. Maria de los Angeles Garcia Valinas, 2006. "Analysing rationing policies: drought and its effects on urban users' welfare (Analysing rationing policies during drought)," Applied Economics, Taylor & Francis Journals, vol. 38(8), pages 955-965.
  2. Worthington, Andrew C., 2010. "Commercial and Industrial Water Demand Estimation: Theoretical and Methodological Guidelines for Applied Economics Research/Estimación de la demanda de agua comercial e industrial: pautas teóricas y," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 28, pages 237-258, Agosto.
  3. David R. Bell & Ronald C. Griffin, 2011. "Urban Water Demand with Periodic Error Correction," Land Economics, University of Wisconsin Press, vol. 87(3), pages 528-544.
  4. María Angeles García Valiñas, 2005. "Promotion and remuneration of university professors: from the LRU to the COU," Hacienda Pública Española, IEF, vol. 172(1), pages 119-143, June.
  5. Schleich, Joachim & Hillenbrand, Thomas, 2009. "Determinants of residential water demand in Germany," Ecological Economics, Elsevier, vol. 68(6), pages 1756-1769, April.
  6. R. Quentin Grafton & Michael B. Ward & Hang To & Tom Kompas, 2011. "Determinants of Residential Water Consumption: Evidence and Analysis from a Ten-country Household Survey," Crawford School Research Papers 1114, Crawford School of Public Policy, The Australian National University.
  7. Martinez-Espineira, Roberto, 2005. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," MPRA Paper 615, University Library of Munich, Germany, revised Jan 2006.
  8. Henrique Monteiro, 2010. "Residential Water Demand in Portugal: checking for efficiency-based justifications for increasing block tariffs," Working Papers Series 1 ercwp0110, ISCTE-IUL, Business Research Unit (BRU-IUL).
  9. Marie-Estelle Binet & Younes Ben Zaïd, 2011. "A Seasonal Integration and Cointegration Analysis of Residential Water Demand in Tunisia," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 201122, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
  10. Ben Zaied Younes, 2013. "A long-run analysis of residential water consumption," Economics Bulletin, AccessEcon, vol. 33(1), pages 536-544.

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