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Journal of Financial and Quantitative Analysis Vol. 59 No. 6 2024

Measuring Firm Complexity

Tim Loughran; Bill McDonald

University of Notre Dame

open access

Abstract

In business research, firm size is both ubiquitous and readily measured. Complexity, another firm-related construct, is also relevant, but difficult to measure and not well-defined. As a result, complexity is less frequently incorporated in empirical designs. We argue that most extant measures of complexity are one-dimensional, have limited availability, and/or are frequently misspecified. Using both machine learning and an application-specific lexicon, we develop a text solution that uses widely available data and provides an omnibus measure of complexity. Our proposed measure, used in tandem with 10-K file size, provides a useful proxy that dominates traditional measures.

DOI
10.1017/s0022109023000716
Volume
59
Issue
6
Pages
2487-2514
Language
en
Sources
bibtex:phds-export.bib crossref openalex

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