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The costs of adaptation to climate change for water infrastructure in OECD countries

  • Hughes, Gordon
  • Chinowsky, Paul
  • Strzepek, Ken
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    There is concern that climate change may greatly increase the costs of providing water infrastructure in rich countries, but the estimates available cannot be compared across countries. This paper develops and applies a top-down approach to estimate the costs of adapting to climate change on a consistent basis for different climate scenarios. The analysis separates (a) the costs of maintaining service standards for a baseline projection of demand, and (b) the costs of changes in water use and infrastructure as a consequence of changes in climate patterns. The engineering estimates focus on the direct capital and operating costs of adaptation without relying upon economic incentives to affect patterns of water use. On this assumption, the costs of adaptation are 1-2% of baseline costs for all OECD countries with the main element being the extra cost of water resources to meet higher level of municipal water demand. There are large differences in the cost of adaptation across countries and regions. Adopting an economic approach under which water levies are used to cap total water abstractions leads to a large reduction in the burden of adaptation and generates savings of $6-12 billion per year under different climate scenarios.

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    File URL: http://www.sciencedirect.com/science/article/B6VFT-50156S4-2/2/ef14b060a622adcb5672e7b7702ab4d3
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    Article provided by Elsevier in its journal Utilities Policy.

    Volume (Year): 18 (2010)
    Issue (Month): 3 (September)
    Pages: 142-153

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    Handle: RePEc:eee:juipol:v:18:y:2010:i:3:p:142-153
    Contact details of provider: Web page: http://www.elsevier.com/locate/inca/30478

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    1. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2012. "Forecasting with spatial panel data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3381-3397.
    2. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    3. John Horowitz, 2009. "The Income–Temperature Relationship in a Cross-Section of Countries and its Implications for Predicting the Effects of Global Warming," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 44(4), pages 475-493, December.
    4. Kristin Komives & Vivien Foster & Jonathan Halpern & Quentin Wodon, 2005. "Water, Electricity, and the Poor : Who Benefits from Utility Subsidies?," World Bank Publications, The World Bank, number 6361, August.
    5. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    6. Fay, Marianne & Yepes, Tito, 2003. "Investing in infrastructure : what is needed from 2000 to 2010?," Policy Research Working Paper Series 3102, The World Bank.
    7. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
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