Farzad Pourbabaee

I received my PhD in economics and MA in statistics from UC Berkeley.
Currently, I am a postdoc at Caltech HSS division. Here is my CV.

Contact: farzad.pourbabaee@gmail.com and
far@caltech.edu or farzad@berkeley.edu

Research

    Working Papers:

  1. Individual and Collective Welfare in Risk Sharing with Many States (with Federico Echenique)
    PDF | arXiv |

    Abstract. We provide a quantitative assessment of welfare in the classical model of risk-sharing and exchange under uncertainty. We prove three kinds of results. First, that in an equilibrium allocation, the scope for improving individual welfare by a given margin (an \(\varepsilon\)-improvement) vanishes as the number of states increases. Second, that the scope for a change in aggregate resources that may be distributed to enhance individual welfare by a given margin also vanishes. Equivalently: in an inefficient allocation, for a given level of resource sub-optimality (as measured by the coefficient of resource under-utilization), the possibilities for enhancing welfare by perturbing aggregate resources decrease exponentially to zero with the number of states. Finally, we consider efficient risk-sharing in standard models of uncertainty aversion with multiple priors, and show that, in an inefficient allocation, certain sets of priors shrink with the size of the state space.

  2. Binary Mechanisms under Privacy-Preserving Noise (with Federico Echenique)
    Revise and Resubmit, Journal of Economic Theory.    PDF | arXiv |

    Abstract. We study mechanism design for public-good provision under a noisy privacy-preserving transformation of individual agents' reported preferences. The setting is a standard binary model with transfers and quasi-linear utility. Agents report their preferences for the public good, which are randomly flipped, so that any individual report may be explained away as the outcome of noise. We study the tradeoffs between preserving the public decisions made in the presence of noise (noise sensitivity), pursuing efficiency, and mitigating the effect of noise on revenue.

    WINE '23: The 19th Conference On Web and Internet Economics, 2023
  3. The Impact of Connectivity on the Production and Diffusion of Knowledge (with Gustavo Manso)
    PDF | arXiv | Presentation slides |

    Abstract. We study a social bandit problem featuring production and diffusion of knowledge. While higher connectivity enhances knowledge diffusion, it may reduce knowledge production as agents shy away from experimentation with new ideas and free ride on the observation of other agents. As a result, under some conditions, greater connectivity can lead to homogeneity and lower social welfare.

    Presentations: NETSCIECON; Midwest Economic Theory; North American Summer Meetings of the Econometric Society 2022; Informs ADA 2022
  4. Delegated Learning and Non-Credible Communication (with Peter B. McCrory)
    PDF | SSRN |

    Abstract. We consider a setting in which an impatient agent acquires payoff-relevant information about the true state of the world. The agent endogenously chooses when to stop learning, at which point an uninformed principal takes an action to maximize her own expected payoff. The agent's preferences are biased relative to the principal's, generating misalignment of expected payoffs. When communication is non-credible, the principal can only rely upon the agent's endogenous stopping rule when strategically specifying her course of action. In the no-communication equilibrium, the agent adopts a one-sided stopping rule as a function of her posterior belief that is consistent with the principal's pre-specified course of action at the time of stopping. When the principal has commitment power, relative to the full-communication equilibrium, the agent is always worse off; for intermediate values of prior beliefs, the principal is better off. The one-sided equilibrium stopping rule (and associated action) can switch discretely as a function of prior beliefs, generating dramatic regime changes for arbitrarily small changes in beliefs. When learning is initiated in the no-communication equilibrium there is a non-zero probability of indefinite delay, in which the agent never ceases learning and the principal never takes an action.

  5. Tail Probability Estimation of Factor Models with Regularly-Varying Tails: Asymptotics and Efficient Estimation (with Omid Sham Solari)
    PDF | SSRN |

    Abstract. We study the tail probability of linear factor models generated from non-identically distributed components with regularly-varying tails, a large subclass of heavy-tailed distributions. An efficient sampling method for tail probability estimation for this class is introduced and theoretically shown to exponentially outperform the crude Monte-Carlo estimator, in terms of the coverage probability and the confidence interval's length. The theoretical results are empirically validated through stochastic simulations on independent non-identically Pareto distributed factors. The proposed estimator is available as part of a more comprehensive TPE package.


  6. Publications:

  7. Reputation, Learning and Project Choice in Frictional Economies
    Forthcoming at Economic Theory, 2024.    PDF | Published Paper | arXiv |

    Abstract. I introduce a dynamic model of learning and random meetings between a long-lived agent with unknown ability and heterogeneous projects with observable qualities. The outcomes of the agent's matches with the projects determine her posterior belief about her ability (i.e., her reputation). In a self-type learning framework with endogenous outside option, I find the optimal project selection strategy of the agent, that determines what types of projects the agent with a certain level of reputation will accept. Sections of the optimal matching set become increasing intervals, with different cutoffs across different types of the projects. Increasing the meeting rate has asymmetric effects on the sections of the matching sets: it unambiguously expands the section for the high type projects, while on some regions, it initially expands and then shrinks the section of the low type projects.

  8. The Hazards and Benefits of Condescension in Social Learning
    (with Itai Arieli, Yakov Babichenko, Stephan Müller and Omer Tamuz)
    Forthcoming at Theoretical Economics, 2024.     PDF | arXiv |

    Abstract. In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In contrast, too much condescension leads to worse outcomes, as does anti-condescension.

    EC '23: Proceedings of the 24th ACM Conference on Economics and Computation, 2023
  9. Robust Experimentation in the Continuous Time Bandit Problem
    Economic Theory, 2022.     PDF | Published Paper | arXiv |

    Abstract. We study the experimentation dynamics of a decision maker (DM) in a two-armed bandit setup (Bolton and Harris [1999]), where the agent holds ambiguous beliefs regarding the distribution of the return process of one arm and is certain about the other one. The DM entertains Multiplier preferences á la Hansen and Sargent [2001], thus we frame the decision making environment as a two-player differential game against nature in continuous time. We characterize the DM's value function and her optimal experimentation strategy that turns out to follow a cut-off rule with respect to her belief process. The belief threshold for exploring the ambiguous arm is found in closed form and is shown to be increasing with respect to the ambiguity aversion index. We then study the effect of provision of an unambiguous information source about the ambiguous arm. Interestingly, we show that the exploration threshold rises unambiguously as a result of this new information source, thereby leading to more conservatism. This analysis also sheds light on the efficient time to reach for an expert opinion.

  10. High Dimensional Decision Making, Upper and Lower Bounds
    Economics Letters, 2021.     PDF | Published Paper | arXiv |

    A decision maker's utility depends on her action \(a \in A \subset \mathbb{R}^d\) and the payoff relevant state of the world \(\theta \in \Theta\). One can define the value of acquiring new information as the difference between the maximum expected utility pre- and post information acquisition. In this paper, I find asymptotic results on the expected value of information as \(d \to \infty\), by using tools from the theory of (sub)-Guassian processes and generic chaining.

  11. Risk Minimization and Portfolio Diversification (with Minsuk Kwak and Traian A. Pirvu)
    Quantitative Finance, 2016.     PDF | Published Paper | arXiv
  12. Lattice Coding for Multiple Access Channels with Common Message and Additive Interference
    Information Theory Workshop (IEEE), 2012.     Published Paper

Teaching

Caltech HSS:

First year PhD courses (UC Berkeley):

Undergraduate courses (UC Berkeley):