Weekly Economics Webinar by Lata Gangadharan
September 23, 2020 @ 1:20 pm - 2:30 pm
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Title: Improving compliance with Regulations: Insights from Experiments.
Speaker: Lata Gangadharan, Professor of Economics, Monash University
The talk will be based on two papers:
Inter-firm social dilemmas with agency risk (EER, forthcoming)
Abstract: Many social dilemmas involve decisions made by firms. We design a laboratory experiment that represents firms’ principal-agent problem and includes an inter-firm social dilemma and stochastic agent performance. Agents’ unobservable effort affects the likelihood of a bad outcome occurring, such as a regulatory violation. This harms the agent’s principal but can also damage others, thus creating an inter-firm social dilemma. In our baseline treatment, we omit the agency problem, and principals make their “firm’s” effort decision directly. In the second treatment, principals can only offer an unconditional wage contract to their agent, although a non-contractual (ex-post) bonus can be paid. In a third treatment, principals can condition wages on the stochastic outcome, and a fourth treatment combines the conditional wage with a non-contractual bonus. We find that principals use a combination of a conditional wage and the non-contractual (ex-post) bonus to help overcome the agency problem and incentivize agents to choose higher effort. Fixed wage, unconditional contracts lead to significantly lower effort levels, even when augmented with bonuses. Similarly, conditional contracts on their own also perform poorly. Only the combination of conditional wage contracts and discretionary bonuses is effective in limiting agency risk to address the inter-firm social dilemma problem.
Deterrence Using Peer Information
Abstract: We study a mechanism for crime deterrence that utilizes insider information contained in social networks. Regulators may have limited information about a crime but happen to identify a suspect. We propose a mechanism where this suspect can re-direct the penalty to another person from the network who is deemed to be more responsible. The regulator examines the criminal activities of both and obtains two noisy signals about their actions. The one with the higher signal is punished and the other goes free. We show theoretically that, for a given probability and magnitude of the penalty, crime levels are lower with this mechanism than in the case where the first suspect is automatically punished. In equilibrium, crime levels depend on the given criminal’s position in the network and on the network structure. Our experiment confirms that this mechanism effectively deters crime, but the magnitude is above the Nash equilibrium predictions and is less sensitive to changes in the network structure than theory predicts. Level-k reasoning helps to explain these patterns.