GAAP Earnings Forecast Quality: Implications for Research
研究发现分析师GAAP盈利预测质量普遍较低，未能纳入税法变化等重大信息，这会削弱盈利反应系数估计、降低盈利意外对收益的解释力，并影响相关研究推断。
ABSTRACT We examine the implications of GAAP earnings forecast quality for accounting research. Using a tax law change with an estimable and material GAAP earnings impact, we find that analysts’ GAAP forecasts generally fail to incorporate this impact, whereas investors respond promptly, suggesting that GAAP forecasts omit earnings information deemed relevant by investors and are of low quality. Analyzing quarterly GAAP forecasts from 2004–2019 and classifying GAAP forecasts that equal their street counterparts when GAAP and street actuals differ as low quality, we again find widespread low GAAP forecast quality. Low quality GAAP forecasts affect research inferences: they dampen GAAP earnings response coefficient (ERC) estimates, reduce the explanatory power of GAAP surprises for returns, affect inferences regarding market rewards for meeting-or-beating via exclusions, and understate the extent that GAAP forecasts incorporate exclusion components. We propose two strategies to mitigate the adverse effects of low quality GAAP forecasts on research inferences. Data Availability: Data are from publicly available sources as identified within the manuscript. JEL Classifications: G14; M40; M41.