Harnessing AI for Economic Forecasting

Authors

  • Kai Evans
  • Taylor Mitchell
  • Dana Scott

Keywords:

artificial intelligence, forecasting, economic models, accuracy, adaptability

Abstract

This paper explores the integration of artificial intelligence (AI) in economic forecasting models. Traditional forecasting methods often suffer from a lack of precision due to their reliance on historical data and linear models. By incorporating AI, specifically machine learning algorithms, these models can improve accuracy and adaptability to new data trends. We analyze several case studies where AI-driven approaches have led to significant improvements in forecasting accuracy over traditional models. The findings suggest a promising future for AI in the field of economic research, offering potential for more robust decision-making processes in economic policy and business strategies.

This is a free preview. The complete article is available with a valid subscription.

Author Biographies

Kai Evans

PhD
Massachusetts Institute of Technology
77 Massachusetts Ave, Cambridge, MA 02139, USA

Taylor Mitchell

PhD
Kyiv School of Economics
Dmytrivska St, 92-94, Kyiv, 01135, Ukraine

Dana Scott

PhD
University of Toronto
27 King's College Cir, Toronto, ON M5S, Canada

References

Ola, M. H. Financing mix and Financial Performance: Evidence from listed Consumer and Industrial Goods Sector in Nigeria.

Babayev, F. (2020). GIDA SANAYİSİNDE YENİLİKÇİ GELİŞİM. In Econder 2020 3rd. International Economics, Business and Social Sciences Congress (p. 240).

Fikrat, B. F. (2023, January). THE ROLE OF AGRİCULTURE İN ENSURİNG ECONOMİC DEVELOPMENT. In Publisher. agency: Proceedings of the 1st International Scientific Conference «Research Retrieval and Academic Letters»(January 26-27, 2023). Warsaw, Poland (p. 73).

Petkov, Vasil S (2013), Advantages and Disadvantages of Fiscal Discipline in Bulgaria in Times of Crisis, [online]. [cit.2017-08-30]. Available at https://ieas.repec.org/a/wyz/journal/id332html

Published

2024-08-15

Issue

Section

Articles