Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
Metadatos:
Mostrar el registro completo del ítemAutor/es:
Galiani, Sebastián
Gálvez, Ramiro
Nachman, Ian
Fecha:
2024-11-02Resumen
This article conducts a comprehensive analysis of specialization trends within and across fields
of economics research. We collect data on 24,273 articles published between 1970 and 2016 in
general research economics outlets and employ machine learning techniques to enrich the
collected data. Results indicate that theory and econometric methods papers are becoming
increasingly specialized, with a narrowing scope and steady or declining citations from outside
economics and from other fields of economics research. Conversely, applied papers are covering
a broader range of topics, receiving more extramural citations from fields like medicine, and
psychology. Trends in applied theory articles are unclear. (JEL A11, A14)
Por motivos relacionados con los derechos de autor este documento solo puede ser consultado en la Biblioteca Di Tella. Para reservar una cita podés ponerte en contacto con repositorio@utdt.edu.///De acuerdo a las condiciones editoriales acordada entre los autores y la revista Economic Inquiry (e-ISSN 1465-7295) este artículo podrá descargarse libremente de este Repositorio a partir del 02/11/2025///Citar: Galiani, S., Gálvez, R. H., & Nachman, I. (2024). Specialization trends in economics research: A large‐scale study using natural language processing and citation analysis. Economic Inquiry. Portico. https://doi.org/10.1111/ecin.13261
URI:
https://repositorio.utdt.edu/handle/20.500.13098/13136https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4460244