Friday, December 16, 2011

Measuring optimists and pessimists

According to Wikipedia, the Oxford English Dictionary defines optimism as "hopefulness and confidence about the future or successful outcome of something; a tendency to take a favourable or hopeful view." This is a poor definition, I think, because it mixes two concepts: a) that one has subjective probabilities on good outcomes higher than what objective ones would warrant, 2) that one is less sensitive to uncertainty. Put it that way, it becomes quite obvious that economists have the tools to separate the two and can thus document what I would call true optimism (or pessimism), a tendency for favor good outcomes in expected utility.

David Dillenberger, Andrew Postlewaite, and Kareen Rozen do exactly this by appealing to Savage's subjective expected utility. If we look at choices of an individual across lotteries, then we should be able to back out both the subjective probability distribution and the aversion to risk. This can actually be a big deal, for example when one wants to give advice in a risky environment. The advisor will try to understand the preferences of the subject, but ignoring optimism/pessimism may lead to a very erroneous assessment of risk aversion. This can be crucial in assessing, say, investment strategies, health care options, or career choices.

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