2001/09/01 by J. Richard Dietrich, Steven J. Kachelmeier, Don N. Kleinmuntz +1 · 147 citations
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · #Accounting #Auditing, Earnings Management, Governance #Bounded rationality #Business #Capital (architecture) #Capital market #Computer science #Decision-Making and Behavioral Economics #Economics #Efficient-market hypothesis #Finance #Financial Markets and Investment Strategies #Financial economics #Financial market #Market efficiency #Microeconomics #Rationality #Set (abstract data type)
paper · doi:10.1111/1475-679x.00011
published in Journal of Accounting Research 39(2), 243-268 (Wiley)
openalex publication_date 2001/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
The AICPA Special Committee on Financial Reporting has urged disclosure of relevant forward‐looking information on risks and opportunities to supplement conventional financial statements. We conduct a laboratory market experiment to assess the effects of such disclosures on capital allocation decisions. We develop two sets of competing hypotheses regarding how capital markets react to supplemental disclosures. One set is based on the assumption of semi‐strong market efficiency, while the other posits that the bounded rationality of individual traders leads to inefficient market prices. We find that explicit disclosure of management’s best estimate of an uncertain quantity improves market efficiency, even though this disclosure is redundant with information in financial statements. Second, we find disclosure of an upper bound of management’s estimate has the potential to bias security prices upward, while informationally equivalent disclosure of both upper and lower bounds removes this bias. These results suggest that experimental market reactions to these supplemental disclosures are inconsistent with market efficiency. Supplemental analyses of individuals’ price predictions and trading behavior support our conclusion that inefficiencies are at least partially attributable to individual information processing biases.