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Annual Review of Economics

Volume 15, 2023

Text Algorithms in Economics

Abstract

This article provides an overview of the methods used for algorithmic text analysis in economics, with a focus on three key contributions. First, we introduce methods for representing documents as high-dimensional count vectors over vocabulary terms, for representing words as vectors, and for representing word sequences as embedding vectors. Second, we define four core empirical tasks that encompass most text-as-data research in economics and enumerate the various approaches that have been taken so far to accomplish these tasks. Finally, we flag limitations in the current literature, with a focus on the challenge of validating algorithmic output.

Keyword(s): JEL C18, JEL C45, JEL C55, large language models, text as data, topic models, transformer models, word embeddings
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/content/journals/10.1146/annurev-economics-082222-074352
2023-09-13
2024-04-30
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/content/journals/10.1146/annurev-economics-082222-074352
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Text Algorithms in Economics
Annual Review of Economics 15, 659 (2023); https://doi.org/10.1146/annurev-economics-082222-074352
/content/journals/10.1146/annurev-economics-082222-074352
/content/journals/10.1146/annurev-economics-082222-074352
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