Accounting for optimism and pessimism in expected utility

We provide a preference foundation for decision under risk resulting in a model where probability weighting is linear as long as the corresponding probabilities are not extreme (i.e., 0 or 1). This way, most of the elegance and mathematical tractability of expected utility is maintained and also much of its normative foundation. Yet, the new model can accommodate the extreme sensitivity towards changes from 0 to almost impossible and from almost certain to 1 that has widely been documented in the experimental literature. The model can be viewed as “expected utility with the best and worst in mind” as suggested by Chateauneuf, Eichberger and Grant (Chateauneuf, Alain, Eichberger, Jürgen, Grant, Simon, 2007. Choice under uncertainty with the best and worst in mind: NEO-Additive capacities. Journal of Economic Theory 137, 538–567) or, following our preference foundation, interpreted as “expected utility with consistent optimism and pessimism”.     

Maxmin expected utility with additivity on unambiguous events

This paper provides a model of beliefs representation in which ambiguity and unambiguity are endogenously distinguished in the maxmin expected utility model of Gilboa and Schmeidler (1989). Specifically, I first extend it by getting a representation of beliefs such that the probabilistic beliefs over each ambiguous event are represented by a nondegenerate interval, while the ones over each unambiguous event are represented by a number. I then suggest a behavioral definition of ambiguity. It provides a choice theoretical foundation for the Knightian distinction between ambiguity and unambiguity.     

Firm and regional economic outcomes associated with a new,broad measure of business innovation

ABSTRACT

Most innovation-oriented studies use measures such as patent activity or research expenditures, likely ignoring the role of more home-grown upgrades or opportunity-recognizing activity common in businesses across the U.S. This study develops a broader ‘innovation index’ using a new survey of businesses that provides a wide lens for capturing innovative practices. The index is used in a series of regressions testing the relationship between innovation and both firm and regional-level economic outcomes. Results from the firm-level regressions show that the innovation index has a positive and significant relationship with wages paid to employees and product market growth. The regional analysis demonstrates that innovation is correlated with several regional economic variables, including median household income, and that spatial spillovers from innovation exist in some instances.