Nonprofessional Investor Judgments: Linking Dependent Measures to Constructs

• 成果类型: Article
• 署名作者: Asay, H. Scott; Hales, Jeffrey; Hinds, Cory; Rupar, Kathy
• 署名单位: University of Iowa; University of Texas System; University of Texas Austin; Queens University - Canada; University System of Georgia; Georgia Institute of Technology
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/TAR-2021-0551
• 发表日期: 2023
• 页码: 1-32
• 关键词: operating cash flows; financial-statement; Unintended consequences; Fair value; measurement subjectivity; presentation format; analysts reactions; FORECAST ACCURACY; earnings; disclosure

摘要

There is limited evidence on the construct validity of the dependent measures commonly used in the literature on nonprofessional investor judgments. In this paper, we first survey the literature to understand the types of dependent measures typically used by researchers. We then conduct factor analyses to uncover linkages between dependent measures and the constructs underlying these nonprofessional investor judgments. Our results suggest that, while the wide variety of dependent measures can appear on their face to represent many nuanced economic constructs, these measures capture three distinct factors. These factors relate to nonprofessional investors' (1) expectations regarding future firm performance and value, (2) holistic perceptions of the firm, and (3) evaluations of the risk associated with investing in the firm. Next, we provide recommendations for selecting, analyzing, and reporting dependent measures in future research. Finally, we provide directions for future research to further our understanding of the judgments made by investors.