用机器学习预测加纳通胀，助力经济稳定与增长
Navigating Inflation in Ghana: How Can Machine Learning Enhance Economic Stability and Growth Strategies
- 基于2010-2022年数据，用时序机器学习模型预测通胀趋势
- 模型提供可靠通胀预报，支持政策制定者科学决策
- 为非洲国家经济治理提供数据驱动新范式，适合政策研究者
通货膨胀仍是许多非洲国家面临的持续挑战。本研究探讨机器学习（ML）在理解与管理加纳通胀中的关键作用，强调其对国家经济稳定与增长的重要性。利用2010至2022年的综合数据集，研究采用先进的机器学习模型，特别是擅长时间序列预测的模型，以预测未来通胀趋势。方法设计旨在提供准确可靠的通胀预测，为政策制定者提供宝贵洞察，并倡导经济决策向数据驱动模式转变。本研究旨在通过应用机器学习推动经济分析领域的学术进步，并为将先进科技工具融入经济治理提供实践指导，最终展示机器学习在提升加纳经济韧性、通过有效通胀管理支持可持续发展方面的潜力。
原文摘要 · Abstract (English)
Inflation remains a persistent challenge for many African countries. This research investigates the critical role of machine learning (ML) in understanding and managing inflation in Ghana, emphasizing its significance for the country's economic stability and growth. Utilizing a comprehensive dataset spanning from 2010 to 2022, the study aims to employ advanced ML models, particularly those adept in time series forecasting, to predict future inflation trends. The methodology is designed to provide accurate and reliable inflation forecasts, offering valuable insights for policymakers and advocating for a shift towards data-driven approaches in economic decision-making. This study aims to significantly advance the academic field of economic analysis by applying machine learning (ML) and offering practical guidance for integrating advanced technological tools into economic governance, ultimately demonstrating ML's potential to enhance Ghana's economic resilience and support sustainable development through effective inflation management.
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