On the Optimal Size and Composition of Customs Unions: An Evolutionary Approach

Abstract

Customs unions enable countries to freely access each other’s markets, which is thought to increase intra-regional trade and economic growth. However, accession to a customs union also comes with the condition that all members need to consent to a common external trade policy. Especially if countries feature different economic structures, this may act as a force against the creation of large customs unions. In this paper, we propose a new mathematical approach to model the optimal size and composition of customs unions in the form of a bi-objective combinatorial non-linear problem. We also use a multi-objective evolutionary algorithm (NSGA-II) to search for the best (non-dominated) configurations using data on the trade flows and economic characteristics of 200 countries. Our algorithm identifies 445 different configurations that are strictly preferable, from a global perspective, to the real-world landscape of customs unions. However, many of these non-dominated configurations have the feature that they improve outcomes for the world as a whole, on average, but not for all individual countries. The best configurations tend to favour the creation of a few large customs unions and several smaller ones.

Intelligent computational methods for economics

“…Economics explores the behavior of people, companies, governments, and various decision‐makers to explain how their decisions produce value and satisfy (or fail to satisfy) human needs and desires. Driven by advances in artificial intelligence (AI) and reinforced by the acumen of generated and collected open data, there is now a significant and growing field that utilizes the concept of a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics, with AI capable of perceiving the world around them and taking actions to advance specified goals (Athey & Imbens, 2019; Mullainathan & Spiess, 2017; Saber et al, 2022).…”