Principal Component Analysis and Factor Analysis in Accounting Research

Abstract

ABSTRACTPrincipal component analysis (PCA) and factor analysis (FA) are both variable reduction techniques used to represent a set of observed variables in terms of a smaller number of variables. While both PCA and FA are similar along several dimensions (e.g., extraction of common components/factors), researchers often fail to recognize that these techniques are designed to achieve different goals and can produce significantly different results. We conduct a comprehensive review of the use of PCA and FA in accounting research. We offer simple guidelines on how to program PCA and FA in SAS/Stata and emphasize the importance of the implementation techniques as well as the disclosure choices made when utilizing these methodologies. Furthermore, we present a few intuitive, practical examples highlighting the unique differences between the techniques. Finally, we provide some recommendations, observations, notes, and citations for researchers considering using these procedures in future research.Data Availability: The data used in this paper are publicly available from the sources indicated in the text.JEL Classifications: C38; C88; M41.