Simulations under the DRES and DRUS scenarios are based on the assumptions that regions, in which potential demand for water exceeds sustainable supply, differ in their capability of absorbing the excess demand (water deficit). The absorption percentages applied in the various cases are based on a mixed qualitative-quantitative analysis of the relevant characteristics, where we keep distinct the potential of technological innovation from the degree of flexibility in the economic structure and trade flows.
Looking first at the innovation side, notice that a number of technologies and management options can be put in place to improve the water efficiency (lowering demand) and/or expanding the water supply. Theoretically, the different options could be ranked in terms of economic efficiency, from the lowest to the highest unit cost, and those whose unit cost (possibly including externalities) falls below the shadow value of water (increasing as the water gets scarcer) should be selected (WRG 2009). In practice, however, the technological response to the water stress is much more complicated, as a variety of factors (technical, political, institutional, safety, etc.) ultimately affects the choice among the different technology options (Becker et al. 2010).
We therefore rely on a qualitative index of technology potential for each of the potentially water stressed macro-regions, based on a subjective evaluation of several options and characteristics. Because of the subjective and qualitative nature of this index, the latter should be interpreted as expressing an informed scenario, rather than as a solid scientific appraisal of (future) technical capability in the regions.
We consider three important classes of technology or management options:
Enhanced irrigation techniques and reduced evaporation
For each of them, we identify five “facilitating factors”, possibly making the implementation of each option more likely:
Physical conditions (e.g., desalination projects will be more effective if most of the urban centres are found along the coast).
Factor availability (e.g., access to energy sources for desalination).
Institutional capacity (efficient level of government, quality of public institutions).
Human and physical capital (relevant for large and complex projects).
Demand potential (e.g., enhanced irrigation is primarily targeted to agriculture, therefore its effectiveness depends on the share of agricultural water on total water consumption).
We assign to each factor in each region and for all the three alternatives above a simple scoring system: 1 (poor), 2 (average), 3 (good). A “Technology Potential Index” (Table 4.10
) is quite naturally obtained by simply adding up all the given points. The higher this index, the easier is the expected capability of a region to adjust to water deficits through the introduction of new technologies and more efficient management techniques.
Regional technology potential index
A second adjustment mechanism is related to the endogenous changes in the regional economic structure. Indeed, when actual water availability turns out to be lower than what would be required for production and consumption purposes, the consumers’ utility diminishes and the productivity in water-using industries declines. Even in the absence of a formal market for water resources, scarcity is transmitted as a price signal, and a structural adjustment takes place in the economic system, alleviating the overall impact of the negative shock for the economy. What is maybe less known is that the same process leads to an improvement in the aggregate water efficiency or productivity (water per unit of output), whose magnitude—however—depends on a series of specific characteristics of the economic system under consideration.
Many factors contribute in determining the structural flexibility, and it is not easy to ascertain what economies could respond better and why. To shed some light on this issue, we performed a simple numerical experiment with the global general equilibrium model. In each of the potentially water stressed macro-regions, we simulated a −10% reduction in multi-factor productivity in agriculture, which is the sector where most of the water is utilized. The consequent drop in total agricultural output volume is shown in Table 4.11
Agricultural output change
A CGE model cannot capture all the factors and characteristics affecting the actual degree of flexibility in a certain economy. Nonetheless, a simple experiment like the one above can offer an order of magnitude, or at least can suggest a ranking of the regional economies from the most rigid one (Central Asia) to the most flexible one (East Asia), in terms of absorption of productivity shocks in agriculture, possibly induced by water scarcity.
We combine the ranking provided by Tables 4.10
to split the absorption of the excess water demand in the three components: internal structural adjustment, technical and management solutions, and reduction in water delivery. The latter component, which is obtained as a residual, determines the amount of decrease in water delivery (with effects on productivity) in the scenarios DRUS and DRES (Table 4.12
Decomposition of excess water demand absorption