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

Author information:

Csanád Temesvári https://orcid.org/0009-0002-5724-4287: Magyar Nemzeti Bank, Analyst. E-mail: temesvarics@mnb.hu

Beáta Horváth https://orcid.org/0009-0001-0269-4881: Magyar Nemzeti Bank, Senior Economic Analyst. E-mail: horvathbea@mnb.hu

Lívia Réka Ónozó https://orcid.org/0009-0002-7595-8531: Magyar Nemzeti Bank, Supervisory Advisor; Budapest University of Technology and Economics, PhD Student. E-mail: onozol@mnb.hu

Cite as (APA):

Temesvári, C., Horváth, B., & Ónozó, L.R. (2026). Natural Language Processing-Driven Use-Cases for Economic Analysis Using Unstructured Data. Financial and Economic Review, 25(1), 27–52. https://doi.org/10.33893/FER.25.1.27

Column:

Study

Journal of Economic Literature (JEL) codes:

C43, C45, C60

Keywords:

Natural Language Processing, Deep Learning, macroeconomic nowcasting, classification

References:

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