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Artificial Intelligence in Economic Analysis: An Overview of Techniques, Applications and Challenges

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  • Velu Suresh Kumar

    (PG & Research Department of Economics, H.H. The Rajah’s College (Autonomous), Pudukkottai - 622 001, Tamil Nadu, India.)

Abstract

The integration of Artificial Intelligence (AI) into economic analysis has revolutionized the field, addressing the challenges posed by the increasing volume and complexity of data. This paper, explores AI's transformative impact on various economic domains, including macroeconomic forecasting, market behavior analysis, policy assessment, and microeconomic studies. Key methodologies such as machine learning, deep learning, and natural language processing are examined for their ability to uncover patterns, improve forecasting accuracy, and optimize decision-making. Applications ranging from demand forecasting and dynamic pricing to labor market analysis and central bank policy formulation highlight AI's versatility and effectiveness. While AI offers substantial opportunities, the paper also addresses critical ethical and practical challenges, including data privacy, algorithmic bias, and model transparency. By analyzing contemporary techniques and case studies, this research underscores the potential and limitations of AI in shaping the future of economic analysis and policymaking.

Suggested Citation

  • Velu Suresh Kumar, 2024. "Artificial Intelligence in Economic Analysis: An Overview of Techniques, Applications and Challenges," Post-Print hal-05078645, HAL.
    • Handle: RePEc:hal:journl:hal-05078645
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