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Can AI-Driven National ESG in Big Data Help Improve Macroeconomic Forecasting?

Author

Listed:
  • Hao XIAO

    (School of Economics & Trade, Hunan University; Institute of African Studies, Hunan University, Changsha, Hunan Province, China, 410079)

  • Xiaofen LI

    (School of Economics & Trade, Hunan University, Changsha, Hunan Province, China, 410079,)

  • Junyi YANG

    (School of Economics & Trade, Hunan University, Changsha, Hunan Province, China, 410079,)

  • Xinjian YE

    (School of Economics & Trade, Hunan University, Changsha, Hunan Province, China, 410079,)

Abstract

This study introduces a novel predictive framework for predicting South Africa's macroeconomic trends using national ESG in big data based on AI technology and deep learning. This study utilizes the GDELT database and AI-driven indicator construction methods to extract meaningful insights from 10.76 million news, generating ESG in big data at the national governance level. By combining traditional macroeconomic indicators with national ESG in big data, this study evaluates the predictive performance of econometric, machine learning, and deep learning models. The rolling out-of-sample prediction analysis shows that the LSTM model achieves the highest prediction accuracy. Subsequently, LSTM models with and without national ESG in big data were designed to evaluate the extent to which incorporating national ESG in big data improves prediction accuracy. This study demonstrates that national ESG in big data enhances the accuracy of macroeconomic forecasting, particularly improving the short-term forecasting performance of the models.

Suggested Citation

  • Hao XIAO & Xiaofen LI & Junyi YANG & Xinjian YE, 2025. "Can AI-Driven National ESG in Big Data Help Improve Macroeconomic Forecasting?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 84-103, July.
    • Handle: RePEc:rjr:romjef:v::y:2025:i:2:p:84-103
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    Keywords

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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