Working Papers
Consumer Reviews and Dynamic Price Signaling - JMP (w/ Jacob Kohlhepp) - NEW VERSION
[SSRN] [PDF] [Slides]
Pricing decisions are crucial for managing a firm's reputation and maximizing profits. Consumer reviews reflect both the product quality and its price, with more favorable reviews being left when a product is priced lower. We study whether such review behavior can induce a firm to manipulate the review process by underpricing its product, or pricing it below current consumers' willingness to pay. We introduce an equilibrium model with a privately informed firm repeatedly selling its product to uninformed but rational consumers who learn about the quality of the product from past reviews and current prices. We show that underpricing can arise only when the firm reputation is low and then only under a specific condition on consumers' taste shock distribution, which we fully characterize. Rating manipulation unambiguously benefits consumers, because it operates via underpricing.
[SSRN] [PDF] [Slides]
Pricing decisions are crucial for managing a firm's reputation and maximizing profits. Consumer reviews reflect both the product quality and its price, with more favorable reviews being left when a product is priced lower. We study whether such review behavior can induce a firm to manipulate the review process by underpricing its product, or pricing it below current consumers' willingness to pay. We introduce an equilibrium model with a privately informed firm repeatedly selling its product to uninformed but rational consumers who learn about the quality of the product from past reviews and current prices. We show that underpricing can arise only when the firm reputation is low and then only under a specific condition on consumers' taste shock distribution, which we fully characterize. Rating manipulation unambiguously benefits consumers, because it operates via underpricing.
Delegated Recruitment and Hiring Distortions (w/ Jacob Kohlhepp) - NEW VERSION
Revise and Resubmit at Journal of Economic Theory [SSRN]
Firms increasingly rely on recruiters to find talent. Recruiters are typically paid using refund contracts, which specify a payment upon a successful candidate suggestion and hire, and a refund if a candidate is hired but leaves for any reason during an initial period of employment. We study how recruiters and refund contracts shape talent selection. When a firm needs to fill a position, it engages a recruiter who observes private signals about a candidate's productivity and decides whether to suggest this candidate to the firm. There is variation in both the candidates' productivity and in the quality of information available about productivity. We characterize the unique equilibrium and show that refund contracts induce artificial risk aversion in both the recruiter's suggestion strategy and the firm's hiring strategy relative to a first-best benchmark. This risk aversion leads to candidates with lower expected productivity but more informative signals ("safe bets") being favored over candidates with higher expected productivity but less informative signals ("diamonds in the rough"). Our findings imply that delegated recruitment generates statistical discrimination.
Revise and Resubmit at Journal of Economic Theory [SSRN]
Firms increasingly rely on recruiters to find talent. Recruiters are typically paid using refund contracts, which specify a payment upon a successful candidate suggestion and hire, and a refund if a candidate is hired but leaves for any reason during an initial period of employment. We study how recruiters and refund contracts shape talent selection. When a firm needs to fill a position, it engages a recruiter who observes private signals about a candidate's productivity and decides whether to suggest this candidate to the firm. There is variation in both the candidates' productivity and in the quality of information available about productivity. We characterize the unique equilibrium and show that refund contracts induce artificial risk aversion in both the recruiter's suggestion strategy and the firm's hiring strategy relative to a first-best benchmark. This risk aversion leads to candidates with lower expected productivity but more informative signals ("safe bets") being favored over candidates with higher expected productivity but less informative signals ("diamonds in the rough"). Our findings imply that delegated recruitment generates statistical discrimination.
Efficient Information Aggregation in DeGroot Model
[paper]
We introduce a social planner in DeGroot model who aims to improve the time asymptotic information aggregation in finite observational networks. We show that in any connected network it is possible to achieve the best information aggregation by reassigning the attention individuals pay to each others’ opinions. We provide an algorithm that constructs a solution to this problem. We also identify the necessary and sufficient condition on the network for achieving the best information aggregation in average-based updating learning model for homogeneous private signals. Finally, we demonstrate an approach of increasing the speed of learning.
[paper]
We introduce a social planner in DeGroot model who aims to improve the time asymptotic information aggregation in finite observational networks. We show that in any connected network it is possible to achieve the best information aggregation by reassigning the attention individuals pay to each others’ opinions. We provide an algorithm that constructs a solution to this problem. We also identify the necessary and sufficient condition on the network for achieving the best information aggregation in average-based updating learning model for homogeneous private signals. Finally, we demonstrate an approach of increasing the speed of learning.
Work in Progress
Bayesian Echo Chambers
[slides]
I study the impact of echo chambers on social learning outcomes in a setting featuring agents who are aware of the presence of echo chambers and are fully Bayesian. I introduce a novel sequential learning model, where the agent’s private signal is correlated with her neighbors’ signals conditional on the state of the world (echo chambers), and agents sequentially learn about the changing state of the world by observing their neighbors’ actions and their own private signals. I introduce a measure of echo chambers in this social learning environment, that depends both on the network homophily and the signal correlation, and analyze how the presence of echo chambers affects opinion polarization and asymptotic learning accuracy.
[slides]
I study the impact of echo chambers on social learning outcomes in a setting featuring agents who are aware of the presence of echo chambers and are fully Bayesian. I introduce a novel sequential learning model, where the agent’s private signal is correlated with her neighbors’ signals conditional on the state of the world (echo chambers), and agents sequentially learn about the changing state of the world by observing their neighbors’ actions and their own private signals. I introduce a measure of echo chambers in this social learning environment, that depends both on the network homophily and the signal correlation, and analyze how the presence of echo chambers affects opinion polarization and asymptotic learning accuracy.