Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/328192 
Authors: 
Year of Publication: 
2025
Series/Report no.: 
IZA Discussion Papers No. 18062
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
We examine the uptake of GPT-assisted writing in economics working paper abstracts. Using data from the IZA DP series, we detect a clear stylistic shift after the release of ChatGPT-3.5 in March 2023. This shift is evident in core textual metrics–mean word length, type-token ratio, and readability–and reflects growing convergence with machine-generated writing. While the ChatGPT launch was an exogenous shock, adoption is endogenous: authors choose whether to use AI. To capture this behavioral response, we combine stylometric analysis, machine learning classification, and prompt-based similarity testing. Event-study regressions with fixed effects and placebo checks confirm that the change is abrupt, persistent, and not explained by pre-existing trends. A similarity experiment using OpenAI's API shows that post-ChatGPT abstracts resemble their GPT-optimized versions more closely than pre-ChatGPT resemble theirs. A classifier, trained on these variants, flags a growing share of post-March 2023 texts as GPT-like. Rather than suggesting full automation, our findings indicate selective human–AI augmentation. Our framework generalizes to other contexts such as e.g. resumes, job ads, legal briefs, research proposals, or programming code.
Subjects: 
GPT adoption
academic writing
text analysis
natural language processing (NLP)
machine learning
event study
linguistic metrics
AI-assisted writing
diffusion of technology
JEL: 
C55
C88
O33
C81
L86
J24
Document Type: 
Working Paper

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