Dr. Richard Sebaggala

Dr. Richard Sebaggala is a Trade Economist with over fifteen years of experience in international trade, investment, and development policy research across Africa. His work focuses on translating complex economic data into actionable policy and regulatory insights that support export competitiveness, regional integration, and inclusive growth.

He holds a PhD in Applied Economics from the University of Agder, an MSc in Quantitative Economics from Makerere University, and a BA in Economics. He is also a senior lecturer in economics and a long-standing research fellow, contributing to policy research, capacity building, and academic leadership in Uganda.

He has led and contributed to several flagship trade and industrial policy assignments, including major studies for the Uganda Free Zones Authority under the African Continental Free Trade Area (AfCFTA), covering market entry strategies for Ugandan exporters and assessments of opportunities and constraints within Special Economic Zones.

Dr. Sebaggala has served as an Economist and policy advisor on nationally significant assignments commissioned by TradeMark Africa for Uganda's Ministry of Trade, Industry, and Cooperatives, including the National Export Development Strategy (2025/26–2030/31) and the National Trade Policy Development and Implementation Plan. In these roles, he led analytical work on sector competitiveness, trade diagnostics, and investment facilitation reforms to advance Uganda's export-led growth agenda.

He has advised governments and private-sector stakeholders on trade compliance, export diversification, customs cooperation, and rules-of-origin implementation within the East African Community (EAC) and COMESA frameworks.

Dr. Sebaggala brings strong quantitative expertise, including Computable General Equilibrium (CGE) modelling, panel data econometrics, and advanced trade policy analysis, with specialized training from regional and international institutions. In recent years, he has integrated artificial intelligence and machine learning techniques into trade and macroeconomic analysis to enhance evidence-based decision-making for governments, regional bodies, and development partners.