Marciano Siniscalchi Associate Professor of Economics 3213 Andersen Hall, Department of Economics Phone: (847) 491-5398 email: marciano AT northwestern DOT edu My Curriculum Vitae updated November 1, 2007.

News (December 15, 2007)

In related news, I will update a "user's guide to VEU preferences" shortly. The idea is to document a few cool tricks that simplify the use of the VEU model. I'm pretty excited about this... stay tuned!

Research

Published / Forthcoming / Accepted Papers

A Behavioral Characterization of Plausible Priors, Journal of Economic Theory vol. 128, 2006. See also the Online Appendix for additional results and omitted proofs.

Efficient Sorting in a Dynamic Adverse-Selection Model, with Igal Hendel and Alessandro Lizzeri. Review of Economic Studies vol. 72 n. 2, April 2005. See also the Web Appendix for additional results and omitted proofs.

A Subjective Spin on Roulette Wheels, with Paolo Ghirardato, Fabio Maccheroni and Massimo Marinacci; Econometrica , vol. 71 n. 6, November 2003.

Rationalization and Incomplete Information, with Pierpaolo Battigalli. Advances in Theoretical Economics, Vol. 3 No. 1, Article 3. BEPRess link: http://www.bepress.com/bejte/advances/vol3/iss1/art3.

Rationalizable Bidding in First-Price Auctions, with Pierpaolo Battigalli. Games and Economic Behavior, 45, October 2003, pp. 38-72.

Strong Belief and Forward-Induction Reasoning, with Pierpaolo Battigalli; Journal of Economic Theory (2002), 106 no. 2, pp. 356-391.

Hierarchies of Conditional Beliefs and Interactive Epistemology in Dynamic games, with Pierpaolo Battigalli. Journal of Economic Theory (1999), 88, 188-230. Additional material not in the published version.

Interactive Beliefs, Epistemic Independence and Strong Rationalizability, with Pierpaolo Battigalli. Research in Economics (1999) 53, 247-273.

Manuscripts

Vector Expected Utility and Attitudes towards Variation; November 2007.
Abstract. This paper analyzes a model of decision under ambiguity, deemed vector expected utility or VEU. According to the proposed model, an act f : Ω → X is evaluated via the functional V(f) = ∫ u • f dp + A(∫ u • f dm), where u : X → R is a von Neumann-Morgenstern utility function, p is a baseline probability measure, ∫ u • f dm is an adjustment vector of finite or countably infinite dimension, whose i-th component is the Lebesgue integral ∫ u • f dm_i of the real function u • f with respect to a signed measure m_i on Ω, and the function A is symmetric about zero: A(φ) = A(-φ). The signed measures (m_i)_{0 ≤ i < n} encode the possibility that ambiguity about certain events may (partially) "cancel out." The adjustment term A(∫ u • f dm) may be interpreted as reflecting the variability of the act f around its baseline expected utility ∫ u • f dp; in particular, like classical statistical measures of variability, it is invariant to location and sign changes. A behavioral characterization of the VEU model is provided. Furthermore, an updating rule for VEU preferences is proposed and characterized. The suggested updating rule facilitates the analysis of sophisticated dynamic choice with VEU preferences.

Dynamic Choice under Ambiguity; mimeo, December 2006.
Abstract. This paper analyzes sophisticated dynamic choice for ambiguity-sensitive decision makers. It characterizes Consistent Planning via axioms on preferences over decision trees. Furthermore, it shows how to elicit conditional preferences from prior preferences. The key axiom is a weakening of Dynamic Consistency, deemed Sophistication. The analysis accommodates arbitrary decision models and updating rules. Hence, the results indicate that (i) ambiguity attitudes, (ii) updating rules, and (iii) sophisticated dynamic choice are mutually orthogonal aspects of preferences. Updated on Dec 8: some nasty typos fixed.

As an example, a characterization of prior-by-prior Bayesian updating and Consistent Planning for arbitrary maxmin-expected utility preferences is presented. The resulting sophisticated MEU preferences are then used to analyze the value of information under ambiguity; a basic trade-off between information acquisition and commitment is highlighted.

Bayesian Updating for General Maxmin-Expected Utility Preferences, September 2001. The main result of this paper has been incorporated in Section 4 of ``Dynamic Choice under Ambiguity'', available above. So this paper is basically obsolete...

Contributed Papers