ESGDICT: Stata module to provide machine-learning generation of the built-in ESG dictionary that qta requires

Wu LiangHai (), Wu Hanyan () and Xu Huihui ()
Additional contact information
Wu LiangHai: Anhui University of Technology
Wu Hanyan: Nanjing University of Aeronautics and Astronautics
Xu Huihui: Anhui University of Technology

Statistical Software Components from Boston College Department of Economics

Abstract: esgdict learns the built-in dictionary that qta uses for its keyword-frequency, cosine-similarity and Jaccard methods, instead of requiring the researcher to hard-code the keywords. It reads a corpus of environmental, social and governance (ESG) reports, screens the documents, tokenises the text, and returns a dictionary file organised into the four dimensions Environmental, Social, Governance and General_ESG. The resulting file is passed directly to qta through its esgdictionary() option.

Language: Stata
Requires: Stata version 16
Keywords: text processing; dictionary; ESG (search for similar items in EconPapers)
Date: 2026-10-10
Note: This module should be installed from within Stata by typing "ssc install esgdict". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/e/esgdict.ado
http://fmwww.bc.edu/repec/bocode/e/esgdict_ml.py
http://fmwww.bc.edu/repec/bocode/e/esgdict.sthlp

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