Research
Abstract: When governing entities levy financial penalties for rule violation, they may aim to maximize compliance or revenues. Agents may be uncertain of these objectives; further they may also not know enforcers' detection ability for rule violation. Utilizing a framework of verifiable disclosure game, we investigate how rule enforcers leverage the options to hide or reveal their privately-informed detection ability and how agents respond. Our model derives multiple equilibria. To examine the selection among those equilibria, we conduct laboratory experiments where the enforcer’s objective is known to the agent in transparent treatments, but unknown to the agent in the opaque treatment. In transparent treatments, unraveling occurs. However, under the opaque treatment, only compliance-maximizing enforcers with strong detection ability reveal their detection ability, and agents violate the rule when enforcers hide. Our results outline that when the enforcement objective is opaque to agents, strategic withholding information related to the detection ability benefits revenue-maximizing enforcers.
Working Papers:
Is There a Better Way to Elicit Valuations than the BDM? [Paper] Under Review
(with Alexander L. Brown and Michael Tsoi)
Abstract: The dominant-strategy Becker-Degroot-Marschak (BDM) mechanism is the prevailing mechanism for eliciting individuals’ valuations within economic research. However, recent research has highlighted systematic bidding mistakes under the BDM mechanism. This paper provides the means to have the largest comprehensive standardized test of all such elicitation mechanisms that are strategically-equivalent but cognitively-simpler than the BDM mechanism. We examine a BDM design for induced-value sellers in a controlled, laboratory environment. Treatments vary across three additional formats of elicitation mechanisms: (1) a descending price clock mechanism that satisfies refinements of dominant strategy, namely obviousness; (2) a BDM mechanism with additional contingent protocols that improves subjects' understanding of the payoff function; and (3) a dynamic multiple price list with descending prices that simplifies the structure of the game. Our experimental results show that (3) appears to improve the game form misconceptions of the BDM mechanism but cannot improve overall accuracy of bids. Meanwhile, contrary to previous theoretical findings and online experiments, neither (1) nor (2) provides more accurate elicited values than the BDM mechanism in the laboratory.
“Hot” and “Cold” Punishment in Public Goods Provision [Paper]
(with Andy Cao, Catherine Eckel, Phatchaya Piriyathanasak, Samuel Priestley, Nanyin Yang, and Sora Youn)
Abstract: Previous studies have shown that punishment opportunities can reduce free riding effectively in public goods production and that negative emotions toward free riders play an important role in precipitating punishment. By varying the timing of punishment in a public good game, we develop a novel punishment rule, the "Pre-Punishment" rule, which is designed to involve a lower level of emotional arousal compared to the classical "Post-Punishment" rule. We employed biometric measures (eye trackers and skin conductance response) in a lab experiment to capture the psychological responses, which will shed light on the mechanism mediating punishment behavior, the response to punishment, and the impact on cooperative behavior. Our results show that this new punishment rule works equally well in increasing contribution compared to the Post-Punishment rule. However, the biometric finding indicates that the effectiveness of Pre-Punishment rule does not rely on subjects' emotional arousal. This study provides useful suggestions for policymakers and managers for designing proper penalty rules to increase cooperation, and will also contribute to the public good game literature by uncovering the psychological processes underlying the effectiveness of punishment institutions.
On the Roles of Mandatory Return Option and Consumers' Heterogeneous Perceptions for Experienced Goods: Experimental Evidence [Draft coming soon] [Slides]
(with Yongzhi Xu)
Abstract: Previous literature has documented that a mandatory return option increases seller's uniform price and buyer's purchasing tendency in online sales platforms. However, limited attention has been given to its effect on experience goods--where the good's true value is drawn from a random distribution, and only the buyer can learn it after purchase. This paper provides the first experimental examination of two distinct channels influencing behavior in a post-price mechanism of experienced goods: (1) whether there is a mandatory return option that the buyer can utilize or not, and (2) the degree to which buyers share different perceptions for the range of the random distribution that draws the experienced good's true value. Our results show that a mandatory return option decreases the seller's uniform price for the experienced good. Conversely, for experienced goods with more heterogeneous perceptions, such heterogeneity benefits the buyer but hurts the seller by generating a lower price and a lower return rate. Our findings provide insights regarding the potential negative impacts of a mandatory return option on market behavior, particularly when buyer's perception about the experienced good's value varies in terms of its possible range.