Revealed preferences over experts and quacks and failures of contingent reasoning
Why do we choose ex-ante useless tests (quacks)?
In many economic scenarios, people resort to different tests to obtain information about the payoff-relevant states of the world. This paper studies how people evaluate and choose between useless tests (quacks) and genuinely useful ones (experts). Using a novel graphic experiment, I recover individual preferences over tests. I find people fail to distinguish between experts and quacks. Their quack choices are not driven by standard explanations, including belief updating bias, best-responding bias, and an intrinsic preference for information. The main culprit is the failure in reasoning the contingency value of tests for their decision problems.
Measuring tastes for equity and aggregate wealth behind the veil of ignorance, with Jan Heufer and Jason Shachat. (under review)
Is social preference behind a veil of ignorance the same as risk preference?
We propose an instrument to measure individuals’ social preferences regarding equity and efficiency behind a veil of ignorance while controlling for idiosyncratic risk preferences. We construct a battery of portfolio and wealth distribution choice problems sharing a common budget set. A given bundle induces the same distribution over an individual’s wealth in both problems. The portfolio choice solely reflects an individual’s risk attitude, providing a benchmark to evaluate whether their wealth distribution choice exhibits equity or efficiency preferring tastes. Experiments show clusters of social preference types, which are unexpectedly independent of risk preferences.
Will bayesian markets induce truth-telling? —An experimental study
An experimental test of a market-based elicitation mechanism for private signals.
This paper tests the performance of the Bayesian market (Baillon (2017)), a new mechanism that incentivizes truth-telling from crowds. A participant in a Bayesian market trades a belief asset whose value is determined by other participants’ trading positions. In the truth-telling Bayesian Nash equilibrium, a participant will reveal her private signal through buying or short-selling an asset when she believes others are also truthful. I create three Bayesian markets in the lab, varying in the belief uncertainties regarding participants’ truthfulness in the market. I find Bayesian markets effective when participants reasonably believe others are truthful. They are less effective when participants’ beliefs are subject to noise and updating biases. A further investigation of participants’ bids and ask prices demonstrates how bubbles are formed and impede the performance of Bayesian markets. With belief uncertainty, participants exhibit under-inference bias or ignorance in processing their private signals. The speculators in the market further amplify the updating bias, creating a speculative trend about the belief asset. This finding provides new insights into the role of belief uncertainty and updating biases in the evolvement of market bubbles.
Reputation Scheme mainly as a monitoring device, with Shuaiping Dai and Lijia Tan. (preliminary draft upon request)
A reputation scheme alleviates adverse selection as an informational device and deters moral hazard as a monitoring device. The latter is the main drive for cooperation.
This paper studies how reputation schemes build trust and promote cooperative behaviors in an open innovation interaction. An initiator develops a risky project internally or together with a partner. Cooperation is socially beneficial but entails post-cooperation exploitation from the partner; therefore, the initiator turns down the cooperation in the equilibrium. We find the partner’s reputation records, both partially and fully, boost cooperation. Our theoretical investigations show that a reputation scheme serves as (1) an informational device for the initiator to infer the partner’s hidden type (in the reputation consumption stage); and (2) a monitoring device to deter the partner’s undesirable hidden actions (in the reputation production stage). Using a mixed experimental design with two stages and three reputation intensities, we separate the reputation’s production and consumption stages and distinguish its informational and monitoring role. We find the reputation scheme is more effective in breeding cooperation as a monitoring device.
Commitment and communication in Bayesian persuasion: theory and experiment, with Yun Wang. (draft preparation)
Communication limits the commitment in Bayesian persuasion but promotes a signaling role of information design.
We study Bayesian persuasion with communication. A sender (she) has partially conflicting interests with a receiver (he) and attempts to influence his action. She commits to an information structure about the state, privately learns a realization of the signal, and sends the receiver a cheap talk or partially verifiable message. The considered communication protocols impose different limits on the sender’s commitment power and the overall information transmission. Our equilibrium analyses predict a negative relationship between persuasiveness and communication credibility, while information transmission is invariant to communication protocols. We designed a new graphic Bayesian persuasion experiment and tested our model in the lab. More than half of our subjects follow the partially revealing mechanics of Bayesian persuasion in the benchmark. They react to different communication protocols qualitatively in line with the theoretical predictions. In addition, we find the sender’s informativeness in persuasion is negatively correlated with her truthfulness in communication, implying a signaling role of information structure. The identified signaling mechanism is new to the literature.
Dynamic belief updating and information acquisition. (pilot completed)
Misperception in random sequences + biases in information processing = over- or under-acquisition of information?
Revealed randomization with loss, with Jason Shachat. (pilot completed)
Why do people randomize their choices of lotteries? Will they randomize more when loss is (un)avoidable?