Investors' Perceptions of Earnings Quality, Auditor Independence, and the Usefulness of Audited Financial Information

SYNOPSIS: In this paper I investigate whether nonprofessional investors' beliefs mirror the Securities and Exchange Commission's (SEC) concerns that earnings quality and auditor independence have declined over time. I also examine whether lower perceptions of earnings quality are associated with more or less reliance on a firm's audited financial statements and fundamental analysis of those statements when making investment decisions. My results suggest that the SEC's concerns are valid: Perceived earnings quality for all publicly traded firms has declined overtime, as has perceived auditor independence and the perceived reliability of audited financial information. In contrast, the perceived relevance of audited financial information has increased. In addition, results reveal that lower perceptions of earnings quality are associated with greater reliance on a firm's audited financial statements and fundamental analysis of those statements when making investment decisions. This result suggests either (1) lowe r perceptions of earnings quality lead investors to examine more thoroughly a firm's audited financial statements, or (2) more thorough analysis of a firm's financial statements leads investors to lower their assessments of the firm's earnings quality. Keywords: investor beliefs; earnings quality; auditor independence; reliability; relevance. Data Availability: The data and complete survey are available upon request. INTRODUCTION In this paper I investigate whether investors' beliefs mirror the Securities and Exchange Commission's (SEC) concerns that earnings quality and auditor independence have declined over time. (1) I also examine whether lower perceptions of earnings quality are associated with more or less reliance on a finn's audited financial statements and fundamental analysis of those statements when making investment decisions. Within the SEC, Commissioners Isaac Hunt, Jr. and Laura Unger have recently, and repeatedly, expressed their concerns about earnings quality and earnings management (Hunt 2001a, 2001b; Unger 2001a). Their concerns mirror those of former chairman of the SEC, Arthur Levitt, who expressed concern over earnings management and its effect on resource allocation in his 1998 speech, "The Numbers Game. " In his speech, Levitt notes that management abuses of "big bath" restructuring charges, premature revenue recognition, "cookie jar" reserves, and write-offs of purchased in-process R&D threaten the credibility of financial reporting. Levitt reiterates these concerns in his book, Take on the Street (Levitt 2002). To conduct my investigation I surveyed 414 individual investors who are members of the National Association of Investors Corporation (NAIC). Survey-based research complements archival-based research and experimental studies. Archival-based research provides statistical power and cross-sectional variation, but is less suited for examining individual behavior and beliefs. Experimental studies are excellent for determining how changes in variables affect individual behaviors and beliefs, but are less well suited for gathering large amounts of descriptive data on multiple behaviors and beliefs. Surveys offer a balance between archival-based and experimental studies by gathering data on a multitude of beliefs and practices for moderately large samples of individuals. Results from survey research can be used for building and testing theories, for attempting to explain what underlies market-level decision outputs (e.g., prices, returns, or trading frequencies), and for identifying trends in beliefs and practices. As with all types of research, the survey approach has potential drawbacks. Surveys measure beliefs and not necessarily actions, and surveys might be subject to various response biases. I test for potential biases by comparing statistics from my sample to statistics for the national population of NAIC investors, prior archival-based studies, and a market-level performance metric. …