ECIN Replication Package for "Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis"
Principal Investigator(s): View help for Principal Investigator(s) Sebastian Galiani, University of Maryland; Ramiro H. Gálvez, Universidad Torcuato Di Tella; Ian Nachman, Brown University
Version: View help for Version V3
| Name | File Type | Size | Last Modified |
|---|---|---|---|
| specialization | 08/02/2024 12:57:PM |
Project Citation:
Galiani, Sebastian, Gálvez, Ramiro H., and Nachman, Ian. ECIN Replication Package for “Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis.” Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-08-02. https://doi.org/10.3886/E198921V3
Project Description
Summary:
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We conduct 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.
Scope of Project
Subject Terms:
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Citation Analysis;
Fields of economics research;
Natural language processing;
Machine learning
JEL Classification:
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A11 Role of Economics; Role of Economists; Market for Economists
A14 Sociology of Economics
A11 Role of Economics; Role of Economists; Market for Economists
A14 Sociology of Economics
Manuscript Number:
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ECIN-Sep-2023-0387
Time Period(s):
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1/1/1970 – 12/31/2016
Collection Date(s):
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1/1/2023 – 1/31/2023
Data Type(s):
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aggregate data;
other;
text
Collection Notes:
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Some of the project's data is downloaded from Constellate and the Semantic Scholar API. We cannot share the raw downloaded data, but we are providing scripts to download all the data from scratch. Note that the downloaded data may differ, as APIs are updated. If you are unable to replicate the full paper, the authors can share the data they downloaded privately. Please refer to the README file for more details.
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