25 citations · 93 across the 13 of their papers we have counts for
8 papers · 1 filter
Attention and Social Learning
Krishna Dasaratha, Kevin He
In an incentivized laboratory experiment, we study how people account for and respond to others' incentives for paying attention. Participants learn a binary state from an attentio…
Optimal Bailouts in Diversified Financial Networks
Krishna Dasaratha, Santosh Venkatesh, Rakesh Vohra
Widespread default involves substantial deadweight costs which could be countered by injecting capital into failing firms. Injections have positive spillovers that can trigger a re…
Equity Pay In Networked Teams
Krishna Dasaratha, Benjamin Golub, Anant Shah
A group of agents each exert effort to produce a joint output, with the complementarities between their efforts represented by a (weighted) network. Under equity compensation, a pr…
Learning from Viral Information
Krishna Dasaratha, Kevin He
Motivated by social media, we study an equilibrium model of agents interacting with and learning from each other's signals. Rational agents arrive sequentially, observe a signal (c…
Aggregative Efficiency of Bayesian Learning in Networks
Krishna Dasaratha, Kevin He
When individuals in a social network learn about an unknown state from private signals and neighbors' actions, the network structure often causes information loss. We consider rati…
Innovation and Strategic Network Formation
Krishna Dasaratha
We study a model of innovation with a large number of firms that create new technologies by combining several discrete ideas. These ideas are created via private investment and spr…
An Experiment on Network Density and Sequential Learning
Krishna Dasaratha, Kevin He
We conduct a sequential social-learning experiment where subjects each guess a hidden state based on private signals and the guesses of a subset of their predecessors. A network de…
Learning from Neighbors about a Changing State
Krishna Dasaratha, Benjamin Golub, Nir Hak
Agents learn about a changing state using private signals and their neighbors' past estimates of the state. We present a model in which Bayesian agents in equilibrium use neighbors…