We posit that management forecasts, which are predictable transformations of realized earnings without random errors, are more informative than unbiased forecasts, which manifest small but unpredictable errors, even if biased forecasts are less accurate. Consistent with this intuition, we find that managers who make consistent forecasting errors have a greater ability to influence investor reactions and analyst revisions, even after controlling for the effect of accuracy. This effect is more economically significant and statistically robust than that of forecast accuracy. More sophisticated investors and experienced analysts are found to have a better understanding of the benefits of consistent management forecasts.

We test the implications of anchoring bias associated with forecast earnings per share (FEPS) for forecast errors, earnings surprises, stock returns, and stock splits. We find that analysts make optimistic (pessimistic) forecasts when a firm’s FEPS is lower (higher) than the industry median. Further, firms with FEPS greater (lower) than the industry median experience abnormally high (low) future stock returns, particularly around subsequent earnings announcement dates. These firms are also more likely to engage in stock splits. Finally, split firms experience more positive forecast revisions, more negative forecast errors, and more negative earnings surprises after stock splits.

We provide evidence that analyst coverage affects security issuance. First, firms covered by fewer analysts are less likely to issue equity as opposed to debt. They issue equity less frequently, but when they do so, it is in larger amounts. Moreover, these firms depend more on favorable market conditions for their equity issuance decisions. Finally, debt ratios of less covered firms are more affected by Baker and Wurgler's (2002) “external finance‐weighted” average market‐to‐book ratio. These results are consistent with market timing behavior associated with information asymmetry, as well as behavior implied by dynamic adverse selection models of equity issuance.

Human estimation and inference are subject to systematic biases such as overconfidence and over-optimism. In contrast to prior research that has identified multiple negative consequences of these biases, we focus on positive effects. We empirically examine a setting in which over-optimism a) is a related but different bias from overconfidence, b) emerges dynamically in a rational economic framework, and c) generates higher managerial effort. Importantly, this additional effort improves firm profitability and market value.

We investigate whether meeting Wall Street’s expectations affects rank-and-file employees’ satisfaction. Controlling for firms’ underlying financial performance, we find that those currently working for firms that meet or marginally beat analysts’ forecasts experience increased job satisfaction. This positive effect is concentrated among employees who are less transient, receive more nonexecutive stock options, or are more unionized. Furthermore, the positive effect exists only when employees do not incur higher costs associated with reaching the threshold because they overwork, suffer from labor law violations, or experience layoffs. Lastly, more senior or highly skilled employees respond more strongly when their employer meets Wall Street’s expectations. These results suggest that the effect of meeting earnings targets on employee satisfaction is significant when employees’ incentives align more with those of their employer or when employees are not unduly pressured. Data Availability: Data are commercially available.