Gaming the Float: How Managers Respond to EPS-based Incentives

atypical amount. In Table 9, we report the percentage of splits that are accretive, dilutive, or neither for
the full sample and subsamples. We find little evidence that managers use atypical split ratios and timing
to generate accretive rounding effects. Given the lack of economic significance, we do not formally report
statistical significance. Across all splits, 31.8% have an accretive effect and 29% have a dilutive effect. This
difference is roughly the same whether the split occurred during the quarter or after quarter end. Similarly,
we see no meaningful difference between accretive and dilutive when distinguishing between typical and
atypical split ratios.
[Insert Table 9 Here]
When we look exactly where we expect to see an effect - late splits that are of atypical split factors -
we see a large difference. However, only 13 splits satisfy these criteria, far from an economically meaningful
effect. To summarize, we find very little evidence that splits are used to have an accretive effect on current
period EPS.
3.3 Additional Implications
In this section, we discuss a few additional implication of TSM. Because TSM is achieved by changing shares,
any per-share metric will be affected. This suggests that cross sectional variation in a variety of per share
metrics such as analyst forecast error or dispersion, and even stock prices, may be the endogenous outcome
of TSM. We briefly examine how TSM may relate to i) analysts’ forecast errors, ii) the nominal stock price
puzzle, and iii) idiosyncratic return volatility.
3.3.1 Scale invariance of forecast volatility
The observation that firms with higher EPS levels have lower variance in forecast errors than what would
otherwise be expected was first documented in Degeorge et al. (1999). More recent work has attempted to
understand why this scale invariance exists. Cheong and Thomas (2011) test three potential explanations
and find results that, on net, suggest managers suppress the natural variation due to scale. Importantly,
forecast error variance is computed at the per-share level, which means it is a function of the magnitude
of rounding. Ball (2011) describes how rounding net income at the share level can introduce noise, and
suggests that this could contribute to a lack of variance with scale. We build on this by positing that scale
invariance is the endogenous outcome of TSM. In fact, the lack of variation with scale is essentially our main
prediction. To see this, consider a simple example.
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