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Artificial Intelligence and Inflation Forecasting: A Contemporary Perspective

Pijush Kanti Das et al.

South Asian Journal of Macroeconomics and Public Finance2025https://doi.org/10.1177/22779787251318831article
AJG 1ABDC C
Weight
0.37

What the paper says

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

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https://doi.org/https://doi.org/10.1177/22779787251318831

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@article{pijush2025,
  title        = {{Artificial Intelligence and Inflation Forecasting: A Contemporary Perspective}},
  author       = {Pijush Kanti Das et al.},
  journal      = {South Asian Journal of Macroeconomics and Public Finance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/22779787251318831},
}

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Artificial Intelligence and Inflation Forecasting: A Contemporary Perspective

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.