143
Choice of the discount rate is crucial when making comparisons between decisions
or impacts at different times. The use of too high a discount rate will result in too
little value placed on avoiding damaging future events and too little investment in
technologies that enhance sustainability. Conversely, applying too low a discount
rate will result in too much investment in items that benefit the future at the expense
of the current.
Investment in climate change mitigation is a clear instance where the discount
rate causes different conclusions to be reached. Debate in the literature on discounting has often focused on how to select the correct discount rate (Stern 2007;
W. D. Nordhaus 2007; Weitzman 2007; Zhuang et al. 2007). Regardless of the rate
chosen, it is important to remember that the discount rate is a critical determinant in
the outcome of an analysis, and for each project, a single rate must be applied to all
future benefits and costs. For example, Stern (2007) advocates more ambitious
greenhouse gas mitigation than Nordhaus does, and this is in part influenced by
Stern’s use of a much lower discount rate.
5.3.4 Uncertainty and Risk Aversion
Uncertainty adds complexity to Nexus systems. Uncertainty may be represented by
year-to-year variations in water supplies and commodity prices caused by drought
or floods plus an uncertain future for the rate of population growth, climate change
incidence, technological progress or aquifer/fossil fuel reservoir depletion.
Collectively, such uncertainties raise needs for stochastic modeling and scenario
analysis. Stochastic modeling involves considering multiple possible say water
availability situation and their probabilities. For example, in the South-Central
Texas EDSIMR model (see Sect. 5.4), shorter run uncertainty was addressed by
having nine levels water availability and their historical probabilities. For long run
uncertainly, the model was run under alternative scenarios involving population
growth and future climate change.
Broadly following Moschini and Hennessy (2001), the main sources of uncertainty in the Nexus system as being from:
1. Production uncertainty which refers to the variation in levels of production like
crop yields where the amount and quality of output that will result from a given
bundle of inputs are typically not known with certainty.
2. Price uncertainty, where production decisions are made in advance of the time
when the final product becomes available, so that market price for the output is
typically unknown when these decisions have to be made.
3. Technology improvement uncertainty which acknowledges that increases in
production output and input usage efficiency are uncertain across all sectors.
4. Policy uncertainty where one is unsure of the persistence and enactment of economic policies that significantly impact sectors like renewable energy subsidies
or requirements.
5 Economics
Choice of the discount rate is crucial when making comparisons between decisions
or impacts at different times. The use of too high a discount rate will result in too
little value placed on avoiding damaging future events and too little investment in
technologies that enhance sustainability. Conversely, applying too low a discount
rate will result in too much investment in items that benefit the future at the expense
of the current.
Investment in climate change mitigation is a clear instance where the discount
rate causes different conclusions to be reached. Debate in the literature on discounting has often focused on how to select the correct discount rate (Stern 2007;
W. D. Nordhaus 2007; Weitzman 2007; Zhuang et al. 2007). Regardless of the rate
chosen, it is important to remember that the discount rate is a critical determinant in
the outcome of an analysis, and for each project, a single rate must be applied to all
future benefits and costs. For example, Stern (2007) advocates more ambitious
greenhouse gas mitigation than Nordhaus does, and this is in part influenced by
Stern’s use of a much lower discount rate.
5.3.4 Uncertainty and Risk Aversion
Uncertainty adds complexity to Nexus systems. Uncertainty may be represented by
year-to-year variations in water supplies and commodity prices caused by drought
or floods plus an uncertain future for the rate of population growth, climate change
incidence, technological progress or aquifer/fossil fuel reservoir depletion.
Collectively, such uncertainties raise needs for stochastic modeling and scenario
analysis. Stochastic modeling involves considering multiple possible say water
availability situation and their probabilities. For example, in the South-Central
Texas EDSIMR model (see Sect. 5.4), shorter run uncertainty was addressed by
having nine levels water availability and their historical probabilities. For long run
uncertainly, the model was run under alternative scenarios involving population
growth and future climate change.
Broadly following Moschini and Hennessy (2001), the main sources of uncertainty in the Nexus system as being from:
1. Production uncertainty which refers to the variation in levels of production like
crop yields where the amount and quality of output that will result from a given
bundle of inputs are typically not known with certainty.
2. Price uncertainty, where production decisions are made in advance of the time
when the final product becomes available, so that market price for the output is
typically unknown when these decisions have to be made.
3. Technology improvement uncertainty which acknowledges that increases in
production output and input usage efficiency are uncertain across all sectors.
4. Policy uncertainty where one is unsure of the persistence and enactment of economic policies that significantly impact sectors like renewable energy subsidies
or requirements.
5 Economics