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Although stochastic analysis has become the accepted standard for decision analytic cost effectiveness models, deterministic one-way sensitivity analysis continues to be used to meet the needs of decision makers to understand the impact that changing the value taken by one specific parameter has on the results of the analysis. However, there are a number of problems with this approach.
We review the reasons why deterministic one-way sensitivity analysis will provide decision makers with biased and incomplete information. We then describe a new method - stochastic one-way sensitivity analysis (SOWSA), and apply this to a previously published cost effectiveness analysis, to produce a stochastic tornado diagram and conditional incremental net benefit curve. We then discuss how these outputs should be interpreted and the potential barriers to the implementation of SOWSA.
The results illustrate the shortcomings of the current approaches to deterministic one-way sensitivity analysis. For SOWSA, the expected costs and outcomes are captured, along with the sampled value of the parameter and these are linked to the probability that the parameter takes that value – which can be read off the probability distribution for the parameter used in the stochastic analysis. From these results it is possible to gain insights into probability that a parameter will take a value that will change a decision.
Although a well-used technique, one-way deterministic sensitivity analysis has a number of shortcomings that may contribute to incorrect conclusions being drawn about the importance of certain parameter values on model results. By providing fuller information on uncertainty in model results, it is hoped that the methods here will lead to more informed decision making. Although, as with all developments in the presentation of analytic results to decision makers, care will be required to ensure that the decision makers understand the information provided to them.
Several scholars have argued that abundant natural resources can be harmful to economic performance under bad institutions and helpful when institutions are good. These arguments have either been theoretical or based on naturally occurring variation in natural resource wealth. We test this theory by using a laboratory experiment to reap the benefits of randomized control. We conduct this experiment in a virtual world (Second Life™) to make institutions more visceral. We find support for the theory.
Analysis in Chapter 12 shows that a radical transformation of the fossil energy landscape is feasible for simultaneously meeting the multiple sustainability goals of wider access to modern energy carriers, reduced air pollution health risks, enhanced energy security, and major greenhouse gas (GHG) emissions reductions.
Fossil fuels will dominate energy use for decades to come. Two findings apply to developing and industrialized countries alike. First, fossil fuels must be used judiciously – by designing energy systems for which the quality of energy supply is well matched to the quality of energy service required, and by exploiting other opportunities for realizing high efficiencies. Second, continued use of coal and other fossil fuels in a carbon-constrained world requires that carbon capture and storage (CCS) becomes a major carbon mitigation activity.
Since developing and industrialized countries have different energy priorities, strategies for fossil energy development will be different between these regions in the short term, but must converge in the long term. The focus in developing countries should be on increasing access to modern and clean energy carriers, building new manufacturing and energy infrastructures that anticipate the evolution to low carbon energy systems, and exploiting the rapid growth in these infrastructures to facilitate introduction of the advanced energy technologies needed to meet sustainability goals. Rapidly growing economies are good theaters for innovation. In industrialized countries, where energy infrastructures are largely already in place, a high priority should be overhauling existing coal power plant sites to add additional capabilities (such as coproduction of power and fuels) and CCS.
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