Essays on Earning Management and Leading Indicator Variables
نویسندگان
چکیده
This dissertation consists of two essays. The first essay provides a rational explanation of the mysterious earnings discontinuity phenomenon. It also develops two new empirical predictions which are supported by the empirical tests. The second essay identifies conditions under which leading indicator variables discourage long-term investment. Essay 1: Discontinuity in Earnings Distribution: A Theory and Evidence This paper presents a rational model of financial reporting in which investors use reported earnings not only to infer true (pre-managed) earnings but also to update their beliefs about the precision (inverse of the variance) of earnings. In the model, overreporting earnings has two opposing pricing effects. For example, when earnings are positively auto-correlated, inflating a positive (reported) earnings surprise has a positive pricing effect because investors infer higher (pre-managed) earnings for both current and future periods. However, investors also infer a lower earnings precision from the higher earnings surprise, leading to a lower pricing weight placed on the higher surprise. This is the negative pricing effect of over-reporting earnings. For firms whose earnings are strongly positively auto-correlated, the trade-off between the two opposing effects creates a pooled report right above the prior mean of the earnings distribution and a no-reporting "hole" right below the prior mean in equilibrium (i.e., an earnings discontinuity around the prior mean). The pricing function of reported earnings exhibits an overall "S-shape" and a negative slope for medium (positive and negative) earnings surprises. The above theoretical results are consistent with existing empirical findings. What distinguish the paper are two new empirical predictions: (1) no earnings discontinuity exists for firms whose earnings are negatively or weakly positively auto-correlated, and (2) the earnings discontinuity is more pronounced for firms with more positively auto-correlated earnings (higher auto-covariance or lower variance). The paper also presents empirical evidence supporting the two predictions. Essay 2: When Leading Indicator Variables reduce Long-term Investment
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