The Politics of Attention (with Lin Hu)

We develop a theory of how the competition for voters' limited attention shapes policy outcomes. Our analysis builds on an otherwise standard Downsian model where candidates with varying ideologies propose policies, whereas voters incur costs from attending to politics, which we model as a process that converts the news about policies into voting decisions. We analyze equilibria where policies and voting decisions are jointly determined by the cost of attention and properties of the news technology. Two salient patterns emerge as the cost of attention increases due to, e.g., greater media choices, or as news becomes more noisy due to, e.g., media slant and the rise of fake news. First, more ideology-based outcomes can be sustained in equilibrium. Second, any equilibrium that captures significant voter attention exhibits an increasing degree of policy polarization or issue ownership.

Social Media, Fake News and Political Accountability (with Davin Raiha)

Social media has proliferated throughout the developed world. Blogs, tweets, and posts have become important sources of political news and information for many. But what is the impact of the emergence of social media on politics and political behavior? Does it improve or compromise political accountability? This paper explores how social media affects political accountability in ways that are different from conventional media. Compared to conventional media, social media enables dissenting viewpoints, harsh criticisms, and even fake news to emerge, creating doubts about politicians that can lead to detrimental behaviors on the parts of citizens and politicians. We show how doubts can reduce politicians' incentives exert policy efforts, cause distraction and encourage cosmetic behaviors. We show how it can reduce the ability of citizens to hold politicians accountable, and adversely affect the competence of the candidate pool. 

Optimal Incentive Contract with Endogenous Monitoring Technology (with Ming Yang)

Recent technology advances give firms more flexibility to utilize employee performance data at a reduced and yet significant cost. This paper develops a theory of optimal incentive contracting where the monitoring technology that governs the above described procedure is a subject of the contract designer's strategic choice. In otherwise standard agency models with moral hazard, we allow the principal to partition the agent's raw performance data into any finite categories and to pay for the quantity of information that the output signal carries. Through analysis of the trade-off between giving incentives to the agent and saving the cost of data processing and analysis, we obtain characterizations of the optimal incentive contract such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group monitoring as a best response to high monitoring cost, and matching the intensities of monitoring different tasks to the agent's endogenous tendencies to shirk. We examine the implications of these results for workforce management and firms' internal organizations. 

Intermediated Implementation (with Yiqing Xing)

Many real-world problems like sales, taxation and health care regulation, feature the interactions between a principal, one or more intermediaries and agents with hidden characteristics. In these problems, intermediaries can specify the full menu of the multi-faceted consumption bundles that they offer to agents, whereas the principal is limited to regulating some but not all aspects of the bundles that agents consume, due to legal, information and administrative barriers. We develop a theory of how the principal can implement in these situations any target social choice rule that is incentive compatible, individually rational and feasible among agents. We show that when intermediaries have private values and are perfectly competitive, the principal's goal can be achieved by imposing a per-unit fee schedule that allows intermediaries to break even under the target social choice rule. When intermediaries have interdependent values or market power, per-unit fee schedule cannot generally be used to achieve the principal's goal, whereas regulating the distribution of limited aspects of sold bundles can.  We examine the applicability of our results to the regulation of real-world intermediaries. 

Efficiency in Dynamic Agency Models

We examine a dynamic agency model where the agent's hidden action can affect current and future signals. We show that when players interact for a large number of instances, asymptotic efficiency can be attained if the monitoring technologies satisfies two general conditions called measure concentration and informativeness, and if the agent can be penalized by reductions in the instantaneous consumption or the future payoff. We use this result to establish a Folk Theorem for discrete-time agency models with high discount factors, and to identify signal processes that yield asymptotic efficiency in discretized continuous-time models. 

Robust Incentive Contract with Disagreement Over Performance Evaluation and Compensation 

We examine a dynamic agency model where the agent can disagree over the performance evaluations assigned by the principal and create frictions if the actual incentive pay falls short of what he thinks he deserves. The main result is a characterization of the max-min incentive contract, which gives the principal the best profit guarantee against all disagreement processes. When the horizon is long, the max-min contract is near-efficient and resembles the efficiency wage contract. A key step in the proof is the construction of a simple test contract, which satisfies the above described properties even if disagreements can depend arbitrarily on past efforts and performance measures or exhibit persistence over time.

A Folk Theorem with Virtually Enforceable Actions

This paper proves a Folk Theorem for infinitely repeated private monitoring games with virtually enforceable actions. In these monitoring situations with scarce signals, players depart from the efficient outcome occasionally to acquire the information that detects the profitable deviations of their opponents. In a finite horizon setting with monetary transfers and public communication, I devise a novel Budget Mechanism with Cross-Checking (BMCC) which---through linking the players' action choices over time---virtually implements the efficient outcome at a vanishing incentive cost as the horizon grows and the players become patient. As the building block of my equilibrium construction for the infinitely repeated game, BMCC outperforms public-strategy mechanisms in scarce signal environments and carries important policy applications for labor contract design with costly subjective performance evaluation.

Work In Progress

Optimal Menu with Endogenous Learning

Differentiated Experiments

Robust Voting Mechanism