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Machine learning for economics research: when, what and how

Author

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  • Ajit Desai

Abstract

This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.

Suggested Citation

  • Ajit Desai, 2023. "Machine learning for economics research: when, what and how," Staff Analytical Notes 2023-16, Bank of Canada.
    • Handle: RePEc:bca:bocsan:23-16
    DOI: 10.34989/san-2023-16
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    Cited by:

    1. Zhang, Ditian & Tang, Pan & Tang, Chun & Lai, Xiaobing, 2025. "Interpretable machine learning unveils nonlinear drivers of global energy risk spillovers: A TVP-VAR approach," Economic Modelling, Elsevier, vol. 151(C).
    2. Archana Dilip & Zukiswa Mdingi & Olivier Sirello & Bruno Tissot, 2026. "The evolving role of central bank statistics," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistics and beyond: new data for decision making in central banks, volume 66, Bank for International Settlements.

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    Keywords

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    JEL classification:

    • A1 - General Economics and Teaching - - General Economics
    • A10 - General Economics and Teaching - - General Economics - - - General
    • B2 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925
    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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