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Natural Language Processing-Driven Use-Cases for Economic Analysis Using Unstructured Data

Author

Listed:
  • Csanad Temesvari

    (Magyar Nemzeti Bank)

  • Beata Horvath

    (Magyar Nemzeti Bank)

  • Livia Reka Onozo

    (Magyar Nemzeti Bank; Budapest University of Technology and Economics)

Abstract

Economic text data, such as news articles or retail trade item names, are an alternative, feature-rich, high frequency information source that can provide insight into economic trends and generate timelier and more accurate estimates. We trained multiple deep learning models for two distinct research tasks: 1) the creation of a sentiment index derived from the categorisation of financial and economic articles into three sentiment categories; and 2) the classification of retail trade item names into appropriate tariff categories. Our models consistently outperformed their baseline counterparts for retail trade item classification, while our sentiment index was able to accurately predict economic downturns where high-frequency data were not available.

Suggested Citation

  • Csanad Temesvari & Beata Horvath & Livia Reka Onozo, 2026. "Natural Language Processing-Driven Use-Cases for Economic Analysis Using Unstructured Data," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 25(1), pages 27-52.
    • Handle: RePEc:mnb:finrev:v:25:y:2026:i:1:p:27-52
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    References listed on IDEAS

    as
    1. Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
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      JEL classification:

      • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
      • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
      • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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