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Tuesday, April 21, 2009

Policy and Uncertainty

Robert Stavins:

What Baseball Can Teach Policymakers, by Robert Stavins: ...Uncertainty is an absolutely fundamental aspect of environmental problems and the policies that are employed to address those problems. Any analysis that fails to recognize this runs the risk not only of being incomplete, but misleading as well. ...

To estimate proposed regulations’ benefits and costs, analysts frequently rely on inputs that are uncertain – sometimes substantially so. Such uncertainties in underlying inputs are propagated through analyses, leading to uncertainty in ultimate benefit and cost estimates...

Despite this uncertainty, the most prominently displayed results ... are typically single, apparently precise point estimates of benefits, costs, and net benefits (benefits minus costs), masking uncertainties inherent in their calculation and possibly obscuring tradeoffs among competing policy options. Historically, efforts to address uncertainty ... have been very limited...

Over the years, formal quantitative uncertainty assessments — known as Monte Carlo analyses — have become common in a variety of fields, including engineering, finance, and a number of scientific disciplines...

The first step in a Monte Carlo analysis involves the development of probability distributions of uncertain inputs to an analysis. These probability distributions reflect the implications of uncertainty regarding an input for the range of its possible values and the likelihood that each value is the true value. Once probability distributions of inputs to a benefit‑cost analysis are established, a Monte Carlo analysis is used to simulate the probability distribution of the regulation’s net benefits by carrying out the calculation of benefits and costs thousands, or even millions, of times. With each iteration of the calculations, new values are randomly drawn from each input’s probability distribution and used in the benefit and/or cost calculations. ... Importantly, any correlations among individual items in the benefit and cost calculations are taken into account. The resulting set of net benefit estimates characterizes the complete probability distribution of net benefits.

Uncertainty is inevitable in estimates of environmental regulations’ economic impacts, and assessments of the extent and nature of such uncertainty provides important information for policymakers evaluating proposed regulations. Such information offers a context for interpreting benefit and cost estimates, and can lead to point estimates of regulations= benefits and costs that differ from what would be produced by purely deterministic analyses (that ignore uncertainty). In addition, these assessments can help establish priorities for research.

Due to the complexity of interactions among uncertainties in inputs..., an accurate assessment of uncertainty can be gained only through the use of formal quantitative methods, such as Monte Carlo analysis. Although these methods can offer significant insights, they require only limited additional effort... Much of the data required for these analyses are already obtained...; and widely available software allows the execution of Monte Carlo analysis in common spreadsheet programs on a desktop computer. ...

Formal quantitative assessments of uncertainty can mark a truly significant step forward in enhancing regulatory analysis... They have the potential to improve substantially our understanding of the impact of environmental regulations, and thereby to lead to more informed policymaking.

Macroeconomic policy uses the same type of framework for looking at uncertainty, but with additional twists, the addition of model uncertainty, and the addition of parameter uncertainty within a given model. The steps above are carried out over a variety of different policies, models, and a distribution of parameter values, and the goal is to find the most likely outcomes as well as the distribution of outcomes for each policy. The monetary and fiscal authorities then choose policies that, for example, avoid the chance that the policies will backfire and cause severe problems. But if the true model (or a close approximation to it) is not well represented by the models used in the uncertainty analysis, big policy errors are still possible. That's something we tend to forget when we do these types of analyses characterizing the degree of uncertainty that we face.

    Posted by on Tuesday, April 21, 2009 at 12:24 AM in Economics, Environment, Policy | Permalink  TrackBack (0)  Comments (3)

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