Inducing Environmental Disclosures: A Dynamic Mechanism Design Approach

Abstract

This paper studies the design of voluntary disclosure regulations for a firm that faces a stochastic environmental hazard. The occurrence of such a hazard is known only to the firm. The regulator, if finding a hazard, collects a fine and mandates the firm to perform costly remediation that reduces the environmental damage. The regulator may inspect the firm at any time to uncover the hazard. However, because inspections are costly, the regulator also offers a reward to the firm for voluntarily disclosing the hazard. The reward corresponds to either a subsidy or a reduced fine, depending on whether it is positive or negative. Thus, the regulator needs to dynamically determine the reward and inspection policy that minimizes expected societal cost in the long run. We model this problem as a dynamic adverse selection problem with costly state verification in continuous time. Despite the complexity and generality of this setup, we show that the optimal regulation policy follows a very simple cyclic structure, which we fully characterize in closed form. Specifically, the regulator runs scheduled inspections periodically. After each inspection, the reward level decreases over time until a subsequent inspection takes place. If a hazard is not revealed, the reward level is reset to a high level, restarting the cycle. In contrast to the reward level, the mandated remediation level is constant over time. Nonetheless, when subsidies are not allowed in the industry, we show that the regulator should dynamically adjust this remediation level, which then acts as a substitute for a subsidy. Our analysis further reveals that optimal inspection frequency increases not only when the inspection accuracy decreases, but also when the penalty for not disclosing the hazard increases.

Evolutionary Game Analysis of Green Production Supervision Considering Limited Resources of the Enterprise

“…This holds true for global development. Under the influence of multiple complex factors, however, large amounts of pollutants are released into the environment every year-including, for example, the occurrence of random environmental accidents [2], the dispersion of the location of occurrence, the profit maximization of the enterprise, and the imperfection of government regulation [3,4]. Against this background, how to reduce environmental pollutant emissions has become a fundamentally important research topic in the field of environmental safety management.…”

Economically Motivated Adulteration in Farming Supply Chains

“…The socially responsible operations literature studies supplier behaviors that are socially undesirable but do not directly impact the product's functional quality. For example, Wang et al (2016) studies a regulator's optimal reward and inspection policy to motivate a company to voluntarily disclose a privately-observed, stochastically-occurring environmental hazard. Chen and Lee (2017) analyze how a company can employ contingency payment, supplier certification, and process audit to prevent unethical actions by a supplier.…”

Dynamic regulation on innovation and adoption of green technology with information asymmetry

“…The implication is that firms bear no cost under these contracts. However, in our study, termination imposes a cost on the firm because it is responsible for emissions (as in Wang et al, 2016). Hence, the firm bears that cost and therefore has incentives to hide the green technology, notwithstanding the extent of its R&D efforts.…”

“…The principal's optimal contract combines changes in the agent's business size and payments to induce constant maximal effort. Wang et al (2016) examine an adverse selection problem in which the agent privately observes an environmental hazard; the optimal regulation has a simple cyclic structure that combines inspections with time‐dependent subsidies. Research that simultaneously addresses the moral hazard and adverse selection problems is scant.…”