02269cas a2200313 a 4500 AALejournalIMF022671 230101c9999 xx r poo 0 0eng d 20.00 USD 9798400207013 1018-5941 BD-DhAAL BD-DhAAL Che, Natasha. High Performance Export Portfolio : Design Growth-Enhancing Export Structure with Machine Learning / Natasha Che, Xuege Zhang. Washington, D.C. : International Monetary Fund, 2022. 1 online resource (52 pages) IMF Working Papers <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required Electronic access restricted to authorized BRAC University faculty, staff and students This paper studies the relationship between export structure and growth performance. We design an export recommendation system using a collaborative filtering algorithm based on countries' revealed comparative advantages. The system is used to produce export portfolio recommendations covering over 190 economies and over 30 years. We find that economies with their export structure more aligned with the recommended export structure achieve better growth performance, in terms of both higher GDP growth rate and lower growth volatility. These findings demonstrate that export structure matters for obtaining high and stable growth. Our recommendation system can serve as a practical tool for policymakers seeking actionable insights on their countriesa' export potential and diversification strategies that may be complex and hard to quantify. Mode of access: Internet Economic Development, Innovation, Technological Change, and Growth imf Economic Growth and Aggregate Productivity imf Export Diversification imf Macroeconomic Aspects of International Trade and Finance imf Trade imf Zhang, Xuege. IMF Working Papers; Working Paper ; No. 2022/075 Full text available on IMF https://elibrary.imf.org/openurl?genre=journal&issn=1018-5941&volume=2022&issue=075 IMF e-Library