Designing combinatorial exchanges for the reallocation of resource rights

Abstract

We describe the design and implementation of a combinatorial exchange for trading catch shares in New South Wales, Australia. The exchange ended a decades-long political debate by providing a market-based response to a major policy problem faced by fisheries worldwide: the reallocation of catch shares in cap-and-trade programs designed to prevent overfishing. The exchange was conducted over the Internet to lower participation costs and allowed for all-or-nothing orders to avoid fragmented share portfolios. A subsidy was distributed endogenously to facilitate the transfer of shares from inactive to active fishers. Finally, prices were linear and anonymous to ensure that sellers of identical packages received the same payments. These features were crucial to mitigate economic distortions from introducing catch shares and to gain broad acceptance of the program. However, they led to computationally challenging allocation and pricing problems. The exchange operated from May to July 2017 and effectively reallocated shares from inactive fishers to those who needed them most: 86% of active fishers’ bids were matched and their share deficits were reduced by 95% in high-priority share classes. Similar reallocation problems arise in fisheries with catch-share systems worldwide as well as in other cap-and-trade systems for resource rights, e.g., water and pollution rights. The implemented exchange illustrates how computational optimization and market design can provide policy tools, able to solve complex policy problems considered intractable only a few years ago.

Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response

“…This paper combines these two strands suggesting a new approach to pricing in electricity markets that substantially reduces or even eliminates the need for side-payments. Our approach can well be relevant to other non-convex markets such as those used in transportation (Caplice andSheffi 2003, Garrido 2007) or for the trading fishery access rights (Bichler et al 2019).…”

Fisheries Governance

“…Australian fisheries management since the 1990s has been neoliberal, working towards privatising resource access rights in ITQs and allocating them through market mechanisms (Bichler et al, 2019;Organisation for Economic Co-operation and Development, n.d.) as the best way to meet the objectives of ecologically sustainable development and economic efficiency in Commonwealth and state fisheries legislation (Commonwealth of Australia, 2017; Minnegal & Dwyer, 2008). Not all fisheries were put under ITQ management in the 1990s or subsequently, but even non-ITQ fisheries were strongly influenced by the governance mode prioritising the prevention of overfishing over the social benefits of fisheries, and favouring profitable operating styles over ones that generate more jobs.…”

Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment

“…In CEs, a set of items is allocated between multiple agents who can be sellers and buyers at the same time, e.g. for the reallocation of catch shares (Bichler, Fux, and Goeree 2019). In domains without money, a popular example is combinatorial course allocation, where course seats are allocated to students in large business schools (Budish 2011).…”