Skewed Noise

48 Pages Posted: 20 Mar 2015

See all articles by David Dillenberger

David Dillenberger

University of Pennsylvania - Department of Economics

Uzi Segal

Boston College - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: March 18, 2015

Abstract

We study the attitude of decision makers to skewed noise. For a binary lottery that yields the better outcome with probability p, we identify noise around p, with a compound lottery that induces a distribution over the exact value of the probability and has an average value p. We propose and characterize a new notion of skewed distributions, and use a recursive non-expected utility model to provide conditions under which rejection of symmetric noise implies rejection of skewed to the left noise as well. We demonstrate that rejection of these types of noises does not preclude acceptance of some skewed to the right noise, in agreement with recent experimental evidence. We apply the model to study random allocation problems (one-sided matching) and show that it can predict systematic preference for one allocation mechanism over the other, even if the two agree on the overall probability distribution over assignments. The model can also be used to address the phenomenon of ambiguity seeking in the context of decision making under uncertainty.

Keywords: Skewed distributions, recursive non-expected utility, ambiguity seeking, one-sided matching

JEL Classification: D81, C78

Suggested Citation

Dillenberger, David and Segal, Uzi, Skewed Noise (March 18, 2015). PIER Working Paper No. 15-015. Available at SSRN: https://ssrn.com/abstract=2580407 or http://dx.doi.org/10.2139/ssrn.2580407

David Dillenberger (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
133 South 36th Street
Philadelphia, PA 19104-6297
United States
215-898-1503 (Phone)

Uzi Segal

Boston College - Department of Economics ( email )

140 Commonwealth Avenue
Chestnut Hill, MA 02467
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
36
Abstract Views
496
PlumX Metrics