Abstract

This paper explores the analytical application of the Economic Complexity Index (ECI) to the emirate of Abu Dhabi. The ECI is a novel approach that leverages machine learning (ML) and network science and redefines what constitutes a robust economy, beyond traditional GDP-centric and Ricardian Trade views. The ECI assesses a nation's economic landscape through the following metrics: relatedness, product complexity, relative comparative advantage, and proximity. While traditionally applied at the national level, the Statistics Centre – Abu Dhabi (SCAD) aimed for the analytical model to be applied at a sub-national level. It ranks the emirate's economic complexity against other countries, and regions within those countries, both with and without Abu Dhabi's oil and gas. It also provides recommendations for products and areas for specialization. The model highlights the advantage of capital and the potential to compete in capital-intensive sectors. It offers a powerful insight into Abu Dhabi's strengths therefore enabling decision-makers to monitor diversification policies. Following the model's deployment, SCAD aims to build Abu Dhabi's ECI Optimization analytical tool. This tool will transform insights into action even more seamlessly in the future.