Specialization trends in economics research: A large‐scale study using natural language processing and citation analysis

C-Tier
Journal: Economic Inquiry
Year: 2025
Volume: 63
Issue: 1
Pages: 289-329

Authors (3)

Sebastian Galiani (University of Maryland) Ramiro H. Gálvez (not in RePEc) Ian Nachman (not in RePEc)

Score contribution per author:

0.335 = (α=2.01 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:bla:ecinqu:v:63:y:2025:i:1:p:289-329
Journal Field
General
Author Count
3
Added to Database
2026-01-25