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SYGG: Symposium Quantum Science and more in Ghana and Germany

SYGG 1: Quantum Science in Ghana and Germany

SYGG 1.4: Hauptvortrag

Dienstag, 11. März 2025, 11:45–12:10, WP-HS

Forecasting the Economic Health of Ghana Using Quantum-Enhanced Long Short-Term Memory Model — •Peter Nimbe¹, Henry Martin², Dorcas Attuabea Addo³, and Nicodemus Songose Awarayi¹ — ¹University of Energy and Natural Resources — ²Kwame Nkrumah University of Science and Technology — ³University of Education

This research aims to develop a 12-month prediction system for Ghana’s economic health using quantum-enhanced machine learning model and macroeconomic datasets obtained from Bank of Ghana. The model aims to deliver timely forecasts and provide actionable insights and recommendations for policy interventions, fiscal adjustments, and trade strategies. The predictive model aims to assist government officials, businesses, and stakeholders in making informed decisions, while promoting Ghana’s advancement toward achieving the United Nations Sustainable Development Goals (SDGs). By providing timely economic insights, it will aid in better resource distribution, promote equitable growth, and support sustainable development across various sectors. The evaluation of the model is based on key metrics including loss, mean squared error, root mean squared error and mean absolute error. The results have shown that the quantum-enhanced machine learning model is very effective for forecasting the economic state and health of Ghana’s economy. These results highlight the potential of quantum machine learning in financial and economic forecasts and propose directions for future work as quantum computing advances.

Keywords: Economic health; Quantum-enhanced machine learning; Macroeconomic datasets; Financial forecast; Policy interventions