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Simulating the Macroeconomic Impact of Future Water Scarcity


  • Roberto Roson
  • Richard Damania, the World Bank, Washington D.C.


In this paper, the macroeconomic implications of possible future water scarcity are assessed. In order to do so, the sustainability of a number of economic growth scenarios in terms of water resources are considered. The analysis is based on a comparison between potential demand for water and estimated water availability. Water supply is calculated using the Global Change Assessment Model (GCAM). Three different climatic Global Circulation Models (GCMs) were used as inputs—CCSM, FIO, and GISS—to feed the complex hydrologic model. The main output of this model is an estimate of runoffs and water inflows for many regions in the world. Sustainable (renewable) water supply is defined as the total yearly runoff (where necessary integrated by water inflow) within a given region, and scenarios are considered in which this is the only available source of water. Therefore, the possible exploitation of non-renewable water resources (e.g., the so-called “fossil water”) is implicitly ruled out, whereas the adoption of unconventional water supply means (desalination, recycling, harvesting) is indirectly accounted for as improvements in water efficiency (fresh water needed per unit of economic activity). Since demand for water is mostly an indirect demand, depending on the level of economic activity and income, a global general equilibrium model is used to conduct simulation experiments aimed at assessing changes in economic structure and trade flows, from which the demand for water is obtained. The economic model considers 14 macro-regions and 20 industries. The exercise is conducted for two future reference years, 2050 and 2100, but policy analysis focuses on 2050 only. Two “Shared Socio-economic Pathways” (SSP) were chosen to represent two plausible, but distinct, future economic reference pathways: SSP1, termed “Sustainability”, and SSP3, termed “Regional Rivalry”. SSP1 is characterized by the following narrative: “Sustainable development proceeds at a reasonably high pace, inequalities are lessened, technological change is rapid and directed toward environmentally friendly processes, including lower carbon energy sources and high productivity of land”. By contrast, SSP3 is characterized by the following narrative: “Unmitigated emissions are high due to moderate economic growth, a rapidly growing population, and slow technological change in the energy sector, making mitigation difficult. Investments in human capital are low, inequality is high, a regionalized world leads to reduced trade flows, and institutional development is unfavorable, leaving large numbers of people vulnerable to climate change and many parts of the world with low adaptive capacity”. Water demand projections are based on water intensity coefficients, that is, water per unit of output. These are obtained as ratios between sectoral water usage and output in the base calibration year. In turn, sectoral consumption has been estimated by elaborating information from various sources: the WIOD project (Dietzenbacher et el., 2013), Mekonnen and Hoekstra (2011), the European research project WASSERMed (Roson and Sartori, 2015), Mielke, Diaz Anadon and Narayanamurti (2010), the U.S. Energy Information Administration (2015). To estimate the regional “sustainable water supply”, results from the GCAM hydrologic model have been used. Water supply in each macro-region is expressed as the sum of yearly runoffs of all countries belonging to the region, averaged for three GCMs climate scenarios. We found that water consumption in the Middle East (and, to a lesser extent, in South Asia [India and neighboring countries]) already exceeds “sustainable” water consumption. This suggests that in these regions non-renewable water resources are being exploited, including unsustainable abstraction of groundwater. However, in 2050 and 2100 water resources become insufficient in several other regions, all located in Africa and Asia. This implies that for those regions, the strong economic development scenarios are incompatible with the estimated availability of water resources. Equivalently, the analysis highlights that water (or water scarcity) has been neglected in the definition of the Shared Socio-Economic Pathways, suggesting a potential inconsistency. How can the emerging water demand gap be accommodated in the water-constrained regions? Three complementary ways are envisaged: If water is a non-substitutable production factor, production should fall in all water-consuming industries by the same percentage of the excess demand gap. This gap is generally large, which would imply dramatic and unrealistic drops in production levels. In any case, at least some part of the demand gap (in this exercise 1/4 is assumed) translates into production cuts or, in economics jargon, into reductions of multi-factor productivity. As water becomes a scarcer resource, its explicit market price or its shadow cost would rise, reducing the relative competitiveness of water intensive activities. Within each industry in the large macro-regions, activities would then be reallocated in time and space (by specific policies or by market forces), and more efficient water techniques would be adopted. These mechanisms end up reducing the industrial water intensity coefficients, by increasing the overall water efficiency. It is assumed here that this effect can cover 3/4 of the demand gap (other parameter values have also been used to test robustness, but for brevity are not discussed here). In addition to efficiency-improving reallocations within industries, water would be reallocated between industries. This either requires establishing water markets or specific policies at the national or regional level. The inverse of the water intensity coefficient is the value of production per unit of water, that is, the water industrial productivity. Recognizing that perfect reallocations are improbable and unrealistic, policy scenarios are explored, where the cut in water consumption levels is not applied uniformly across all industries, but smaller reductions are applied where water is relatively more valuable (and vice versa). Three cases are discussed here: (1) no inter-industrial water reallocation [NO-WR], (2) mild [MILD] and (3) strong [STRONG] water reallocation. Without reallocation of water resources among sectors, water scarcity imposes a reduction to the world real GDP of -0.37% in the SSP1 and -0.49% in the SSP3. However there are large disparities across regions, with a large drop in income for some regions, but small gains in some other regions (e.g., Central America) due to improved terms of trade and relative competitiveness. A complete different picture emerges when some redistribution of water resources across sectors is allowed. Industrial water reallocations are guided by an equation where an elasticity parameter (with values set at 0, 0.1, 0.25 for the three policy scenarios) determines the sensitivity to the relative water productivity. With a limited reallocation of water (MILD) the reduction of global GDP is reduced by 42% in both scenarios, whereas regional reductions range from -22% to -67%. The results demonstrate that water remains a significant obstacle to growth and development in the context of a changing climate. It also forcefully illustrates that prudent management of water resources is likely sufficient to neutralize some of the undesirable impacts, and three main messages emerge from the analysis. First, scenarios of economic development that have been recently proposed to support the scientific analyses of climate change have ignored water availability. The underlying assumptions of sustained economic growth, especially for developing countries, would imply an excessive consumption of water, even when substantial improvements in water efficiency are envisaged. Second, and related to the previous point, the emerging water scarcity will mainly affect developing countries in Africa and Asia, hampering their prospects of economic growth. This means that water scarcity will increase economic inequality around the world.

Suggested Citation

  • Roberto Roson & Richard Damania, the World Bank, Washington D.C., 2016. "Simulating the Macroeconomic Impact of Future Water Scarcity," EcoMod2016 9167, EcoMod.
  • Handle: RePEc:ekd:009007:9167

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    References listed on IDEAS

    1. Tol, Richard S.J., 2005. "Emission abatement versus development as strategies to reduce vulnerability to climate change: an application of FUND," Environment and Development Economics, Cambridge University Press, vol. 10(05), pages 615-629, October.
    2. Francesco Bosello & Fabio Eboli & Roberta Pierfederici, 2012. "Assessing the Economic Impacts of Climate Change. An Updated CGE Point of View," Working Papers 2012.02, Fondazione Eni Enrico Mattei.
    3. Eboli, Fabio & Parrado, Ramiro & Roson, Roberto, 2010. "Climate-change feedback on economic growth: explorations with a dynamic general equilibrium model," Environment and Development Economics, Cambridge University Press, vol. 15(05), pages 515-533, October.
    4. repec:wsi:wepxxx:v:01:y:2015:i:01:n:s2382624x14500015 is not listed on IDEAS
    5. Bigano, Andrea & Bosello, Francesco & Roson, Roberto & Tol, Richard S.J., 2006. "Economy-Wide Estimates of the Implications of Climate Change: A Joint Analysis for Sea Level Rise and Tourism," Climate Change Modelling and Policy Working Papers 12022, Fondazione Eni Enrico Mattei (FEEM).
    6. Roberto Roson & Dominique Van der Mensbrugghe, 2012. "Climate change and economic growth: impacts and interactions," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 4(3), pages 270-285.
    7. Bosello, Francesco & Roson, Roberto & Tol, Richard S.J., 2006. "Economy-wide estimates of the implications of climate change: Human health," Ecological Economics, Elsevier, vol. 58(3), pages 579-591, June.
    8. Roberto Roson & Martina Sartori, 2016. "Estimation of Climate Change Damage Functions for 140 Regions in the GTAP 9 Database," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 1(2), pages 78-115, December.
    9. Detlef Vuuren & Jae Edmonds & Mikiko Kainuma & Keywan Riahi & Allison Thomson & Kathy Hibbard & George Hurtt & Tom Kram & Volker Krey & Jean-Francois Lamarque & Toshihiko Masui & Malte Meinshausen & N, 2011. "The representative concentration pathways: an overview," Climatic Change, Springer, vol. 109(1), pages 5-31, November.
    10. Elmar Kriegler & Jae Edmonds & Stéphane Hallegatte & Kristie Ebi & Tom Kram & Keywan Riahi & Harald Winkler & Detlef Vuuren, 2014. "A new scenario framework for climate change research: the concept of shared climate policy assumptions," Climatic Change, Springer, vol. 122(3), pages 401-414, February.
    11. Roberto Roson & Martina Sartori, 2012. "Climate Change, Tourism and Water Resources in the Mediterranean: A General Equilibrium Analysis," IEFE Working Papers 51, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    12. Erik Dietzenbacher & Bart Los & Robert Stehrer & Marcel Timmer & Gaaitzen de Vries, 2013. "The Construction Of World Input-Output Tables In The Wiod Project," Economic Systems Research, Taylor & Francis Journals, vol. 25(1), pages 71-98, March.
    13. Brian O’Neill & Elmar Kriegler & Keywan Riahi & Kristie Ebi & Stephane Hallegatte & Timothy Carter & Ritu Mathur & Detlef Vuuren, 2014. "A new scenario framework for climate change research: the concept of shared socioeconomic pathways," Climatic Change, Springer, vol. 122(3), pages 387-400, February.
    14. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2012. "Temperature Shocks and Economic Growth: Evidence from the Last Half Century," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(3), pages 66-95, July.
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