Juan Pablo Xandri
Department of Economics
Fisher Hall, Office 212
Princeton, NJ 08544
NBER Working Papers and Publications
|March 2018||Financial Centrality and Liquidity Provision|
with Arun G. Chandrasekhar, Robert Townsend: w24406
We study an endowment economy in which agents face income risk, as if uncertain returns on a portfolio, and agents can only make transfers in states when they are actively participating in the market. Besides income risk, agents also have limited and stochastic market access, with a probability distribution governed by an underlying social network. While network connections may serve to dissipate shocks, they may also provide obstacles to the sharing of risk, as when participation frictions are generated through the network.
We identify and quantify the value of key players in terms of whether they are likely to be able to smooth the resulting market participation risk and how valuable that smoothing would be when they are there. We define financial centrality in economic terms, given the...
|August 2015||Testing Models of Social Learning on Networks: Evidence from a Lab Experiment in the Field|
with Arun G. Chandrasekhar, Horacio Larreguy: w21468
Agents often use noisy signals from their neighbors to update their beliefs about a state of the world. The effectiveness of social learning relies on the details of how agents aggregate information from others. There are two prominent models of information aggregation in networks: (1) Bayesian learning, where agents use Bayes' rule to assess the state of the world and (2) DeGroot learning, where agents instead consider a weighted average of their neighbors' previous period opinions or actions. Agents who engage in DeGroot learning often double-count information and may not converge in the long run. We conduct a lab experiment in the field with 665 subjects across 19 villages in Karnataka, India, designed to structurally test which model best describes social learning. Seven subjects were ...