IMF Staff Country Reports

Kingdom of Lesotho: Selected Issues

September 11, 2024

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Format: Chicago

International Monetary Fund. African Dept. "Kingdom of Lesotho: Selected Issues", IMF Staff Country Reports 2024, 289 (2024), accessed October 8, 2024, https://doi.org/10.5089/9798400287947.002

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Summary

This Selected Issues paper delves into few applications of machine learning (ML), with a particular application to economic forecasts in Lesotho. Amid delayed and often revised gross domestic product data, this paper explores the potential of ML to provide real-time insights into growth and inflation trends, crucial for informed policymaking. By leveraging nontraditional data and employing a variety of ML models, the paper presents a comprehensive analysis of current economic activity, evaluates the accuracy of standard statistical measures, and forecasts future inflation trends. The findings underscore the efficacy of ML in reducing prediction errors and highlight the significant role of alternative data in circumventing the limitations posed by traditional economic indicators. This paper contributes to the broader debate on the application of advanced computational techniques in economic forecasting, offering valuable insights for policymakers in Lesotho and similar countries grappling with data constraints and the need for timely economic analysis.

Subject: Economic forecasting, Inflation, Machine learning, Prices, Technology

Keywords: Africa, C. GDP Nowcasting, D. GDP evaluation, E. inflation forecasting, Ensemble Nowcasting model, GDP Nowcasting result, Global, Inflation, Machine learning

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