Aggregate Financial Misreporting and the Predictability of US Recessions and GDP Growth

• 成果类型: Article
• 署名作者: Beneish, Messod D.; Farber, David B.; Glendening, Matthew; Shaw, Kenneth W.
• 署名单位: Indiana University System; IU Kelley School of Business; Indiana University Bloomington; Indiana University System; Indiana University Indianapolis; IU Kelley School of Business; University of Missouri System; University of Missouri Columbia
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/TAR-2021-0160
• 发表日期: 2023
• 页码: 129-159
• 关键词: stock-market returns; Investor sentiment; term-structure; Earnings surprises; AGENCY COSTS; INFORMATION; statements; BUSINESS; FRAUD; news

摘要

This study examines the incremental predictive power of aggregate measures of financial misreporting for recession and real gross domestic product (GDP) growth. We draw on prior research suggesting that misreporting has real economic effects because it represents misinformation on which firms base their investment, hiring, and production decisions. We find that aggregate M-Score incrementally predicts recessions at forecast horizons of five to eight quarters ahead. We also find that aggregate M-Score is significantly associated with lower future growth in real GDP, real investment, consumption, and industrial production. Additionally, our result that aggregate M-Score predicts lower real investment one to four quarters ahead partially accounts for why misreporting predicts recessions five to eight quarters ahead. Our findings are weaker when we use aggregate F-Score as a proxy for misreporting. Overall, this study provides novel evidence that aggregate misreporting measures can aid forecasters and regulators in predicting recessions and real GDP growth.