Browsing by Subject "financial misreporting"

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    Aggregate Financial Misreporting and the Predictability of U.S. Recessions
    (SSRN, 2021) Beneish, Messod D.; Farber, David B.; Glendening, Matthew; Shaw, Kenneth W.; Kelley School of Business - Indianapolis
    We rely on the theoretical prediction that financial misreporting peaks before economic busts to examine whether aggregate ex ante measures of the likelihood of financial misreporting improve the predictability of U.S. recessions. We consider six measures of misreporting and show that the Beneish M-Score significantly improves out-of-sample recession prediction at longer forecasting horizons. Specifically, relative to leading models based on yield spreads and market returns, M-Score increases the average probability of a recession across forecast horizons of six-, seven-, and eight-quarters-ahead by 56 percent, 79 percent, and 92 percent, respectively. These findings are robust to alternative definitions of interest rate spreads, and to controlling for the federal funds rate, investor sentiment, and aggregate earnings growth. We show that the performance of M-Score likely arises because firms with high M-Scores tend to experience negative future performance. Overall, this study provides novel evidence that accounting information can be useful to forecasters and regulators interested in assessing the likelihood of U.S. recessions a few quarters ahead.
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    Aggregate Financial Misreporting and the Predictability of U.S. Recessions and GDP Growth
    (American Accounting Association, 2023-09-01) Beneish, Messod D.; Farber, David B.; Glendening, Matthew; Shaw, Kenneth W.; Kelley School of Business
    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.