PhD Candidate, MEDS

Contact Information

Department of Managerial Economics and Decision Sciences
Northwestern University
2211 Campus Drive
Evanston, IL 60208

Phone: (847) 491-7011

lorenzo DOT stanca AT kellogg DOT northwestern DOT edu

 

 

 

Education

Ph.D., Managerial Economics & Strategy (expected), Kellogg School of Management, 2022.
MS, Managerial Economics & Strategy, Kellogg School of Management, 2017.
M.Sc., Economics, Bocconi University, 2016.

Primary Fields of Specialization

Microeconomic Theory, Decision Theory.

Curriculum Vitae

Download Vita (PDF)

Job Market Paper

“Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty.”

Updated version

Abstract: Models of recursive utility are commonly associated with a preference for early resolution of uncertainty. Such a behavioral feature is considered an important economic channel that determines asset prices. A less studied feature is sensitivity to correlation and in particular correlation aversion. We provide and investigate such a property. We show that an increase in correlation makes a decision maker that prefers early resolution worse off even when increasing correlation provides non-instrumental information about future consumption. Relatedly, we show that one can separate risk aversion from intertemporal substitution by considering a domain of choice in which pure preferences for early resolution of uncertainty play no role. Finally, we apply the insights of this paper to better understand the features possessed by existing models of recursive utility. We argue that it is the attitude toward correlation that is the key behavioral feature driving the conclusions of consumption-based asset pricing models.

Published Papers

Smooth Aggregation of Bayesian Experts, Journal of Economic Theory, Volume 196, September 2021.

Foundations of ambiguity models under symmetry: α-MEU and smooth ambiguity, with Peter Klibanoff, Sujoy Mukerji and Kyoungwon Seo. Forthcoming at Journal of Economic Theory. 

A Simplified Approach to Subjective Expected Utility, Journal of Mathematical Economics, 2020.

 

Working papers

Robust Bayesian Choice

Abstract: A major concern with the Bayesian approach is the use of a unique probability measure to quantify all relevant uncertainty. Specifying a unique probability with extreme precision when only vague or fragmentary information is available may not be feasible. This would be less of a concern under a form of prior robustness, i.e. when a minor variation in the prior would lead to decisions with similar value. This paper studies prior robustness as a form of continuity of the value of a decision problem under uncertainty. I show that this notion of robustness can be characterized by a form of stable choice over a sequence of perturbed decision problems, i.e. decision problems in which the available acts are perturbed in a precise fashion. I then study a measure of prior robustness that captures the sensitivity of the value under perturbations of the prior. Finally, I consider applications to portfolio choice and a consumption-savings problem.

Ongoing research projects

A model of “smooth” discounting.

Abstract: Discounted expected utility is the standard model of decision making under uncertainty. However, it has several shortcomings, both at the experimental and theoretical level.  For example, it conflates attitudes toward risk with intertemporal substitution; it takes the rate of time preference as “given” or exogenous; it implies risk-seeking attitudes over prospects that contain uncertainty only over the date of payment. We propose, in an axiomatic framework, a new model of multiple discount factors that addresses such shortcomings while maintaining dynamic consistency. We illustrate important implications of this model for the theory of asset pricing.

Deliberate randomization and preference for correlation (with Xiaoyu Cheng).

Extended Abstract: We revisit the literature on stochastic choice based on an observation from the existing experimental evidence: A decision-maker (DM) often chooses differently from the same set of alternatives when asked to choose multiple times. The existing literature offers an interpretation that the DM has a convex preference over lotteries, i.e., strictly prefers a non-degenerate probability distribution over the alternatives to any degenerate ones. Because the experiments are often conducted in a dynamic setting, we observe that the subjects’ choices also exhibit a form of negative correlation: if an alternative was chosen in the past, it is less likely that it will be chosen today. In other words, it shows a form of intertemporal preference for variety. In order to capture such a preference, we translate the convex preference over lotteries to a convex preference in an intertemporal setting. Specifically, we introduce a dynamic extension of the Cautious Expected Utility model and show that it can generate this pattern of choice. In addition, we aim to show that the converse is true, i.e., any stochastic choice function that exhibits negative correlation over time is the product of the optimization of some dynamic convex preference.

Structured Ambiguity and Model Misspecification: an axiomatization.

Refereeing activity

Journal of Economic Theory, Economic Theory.

Teaching

TA for MECS 560-2, Dynamic Optimization in Economics, 2018, 2019, 2020 and 2021.

TA for DECS 430-0, Business Analytics, 2017.

TA for DECS 452-0, Game Theory and Strategic Decision Making, 2018 and 2019.

References

Prof. Peter Klibanoff (Committee Co-Chair)

Prof. Marciano Siniscalchi (Committee Co-Chair)

Prof. Nabil Al-Najjar.

 

 

 

 

 

Comments are closed, but trackbacks and pingbacks are open.