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Artificial Intelligence and Inflation Forecasting: A Contemporary Perspective

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  • Pijush Kanti Das
  • Prabir Kumar Das

Abstract

The growing complexity of economic systems and the enormous data availability make the application of traditional forecasting methods challenging in accurately predicting economic parameters. A notable shift from econometric models to artificial intelligence (AI) algorithms has significantly affected economic forecasting. This article focuses on the application of AI techniques, specifically in the domain of inflation forecasting. We conduct a comprehensive review by surveying seminal literature on the application of AI in inflation forecasting from the contemporary perspective. This study serves as a pioneering work by consolidating major contributions in the field, offering future researchers’ insights into a diverse array of state-of-the-art AI-based techniques and data sources relevant to inflation forecasting. JEL Classification: E17, E31

Suggested Citation

  • Pijush Kanti Das & Prabir Kumar Das, 2025. "Artificial Intelligence and Inflation Forecasting: A Contemporary Perspective," South Asian Journal of Macroeconomics and Public Finance, , vol. 14(1), pages 133-164, June.
    • Handle: RePEc:sae:smppub:v:14:y:2025:i:1:p:133-164
    DOI: 10.1177/22779787251318831
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    Keywords

    Artificial intelligence; inflation; forecasting; systematic review;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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