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

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Two firms are the same in all ways except for their distributions of net income. Firm A’s net income is distributed uniformly over [9, 11), and Firm B’s net income is uniformly distributed over [8, 12). So both firms have the same expected net income but B is more volatile than A. If both managers equally value meeting EPS forecasts, then each will choose shares outstanding such that the probability of meeting expectations is the same across both firms. If Firm A has 100 shares outstanding, then the probability that the firm meets earnings is 1/2. 16 If the manager of B also wants to meet forecasts half of the time, the firm will need 200 shares outstanding. 17 From here it is easy to show that the two firms will have identical variance in forecast errors. For each firm, one fourth of the time the firm will miss EPS forecasts by one penny, one-half of the time they meet expectations, and one-fourth of the time they beat expectations by a penny. 18 In this way, the scale invariance of forecast errors is the equilibrium outcome of managers’ incentive to meet EPS forecasts. Furthermore, we would expect forecast error variance to drop after a split. If nothing changes about Firm A other than that it issues a two-for-one stock split, the variance in forecast errors drops to zero (all possible net income outcomes generate EPS = 0.05). We do not think our results completely explain the puzzle of scale invariant forecast errors. Cheong and Thomas (2011) find that the scale invariance is not present in per share cash flow forecasts, for example. A simple rounding based explanation is not consistent with this important finding. Therefore, it seems reasonable to conclude that target size management can explain some of the scale invariance results, but the active smoothing of earnings by managers also plays an important role. 3.3.2 Nominal price puzzle Weld et al. (2009) document that nominal per-share stock prices have remained remarkably constant across time (1933-2007). This is surprising given significant inflation over the same period. The authors estimate that if real stock prices had remained constant over this period, prices today would average around $450. Furthermore, the authors make the observation that existing theories of stock splits fail to predict that nominal share prices would remain constant. The authors conclude that social norms drive managers to use stock splits to keep nominal prices at some fixed level. While our results may not fully explain the nominal price puzzle, TSM may contribute to the constant 16 For simplicity assume that forecasts are unbiased. The firm needs net income within ± 0.5 = 5%, or any net income |E[EP S]| ∈ [9.5, 10.5). The firm will generate net income in this range 10.5−9.5 = 1 of the time. 11−9 2 s 17 Set the probability of meeting forecasts equal to 1/2 and solve for s: 1/2 = 100 12−8 . 18 For Firm A, Var = 1 4 (0.09 − 0.10)2 + 1 2 (0)2 + 1 4 (0.11 − 0.10)2 = 1 2 (0.01)2 . For Firm B, Var = 1 4 (0.04 − 0.5)2 + 1 2 (0)2 + 1 4 (0.06 − 0.05)2 = 1 2 (0.01)2 . 24
price levels observed in the data. Firms are required to round EPS to the penny, and this remains true despite the penny declining in real value. Because the norm of rounding to the penny has been stable, so should nominal EPS levels. If managers choose shares outstanding to maintain a constant nominal level of EPS, then it may not be surprising to also find constant nominal price levels over time. In each quarter, we compute the median price-per-share and median earnings-per-share. We plot these median values over time in Figure 3. Due to Compustat earnings data limitations, we limit the sample to post 1970. Weld et al (2009) argue that managers choose shares outstanding to keep prices constant, whereas we argue that managers choose shares outstanding to keep earnings per share constant. The figure shows that, not surprisingly, prices and earnings levels are strongly related. It is also evident that there is variation in both price-per-share and earnings-per-share medians. [Insert Figure 4 about here] It is difficult to distinguish between the incentive for constant nominal EPS generating constant nominal prices from the incentive for constant nominal prices generating nominal EPS. We attempt to provide some evidence that the incentive for constant EPS does affect aggregate price levels. To do so, we use time series variation in net income volatility. Our earlier results suggest that firms respond to increases in net income volatility by reducing EPS levels. Therefore, we predict that changes in aggregate net income volatility should predict changes in aggregate EPS levels. If managers are choosing constant EPS levels and not constant price levels, then this variation should also show up in price levels. Otherwise, it is less clear why aggregate per share price levels should be a function of lagged aggregate net income volatility. We compute correlations between median price-per-share, median earnings-per-share, and median Net Income volatility (measured for each firm using the prior 12 quarters) over time. Median prices and median earnings are highly correlated, 0.68. The correlation between median EPS and median NI volatility is -0.38, and significant at the 1% level. This is consistent with our cross-sectional results which suggest that firms decrease EPS as a response to an increase in volatility. More interestingly, median nominal prices are also negatively correlated with trailing 12-quarter NI volatility (ρ = −0.16, pvalue = 0.025). This suggests that managers’ incentives for certain EPS levels contribute to variation in price levels. Our results do not suggest that social norms have no role. In fact norms may be the primary determinant of constant nominal prices. We merely suggest that TSM is an explanation for stock splits that is consistent with constant nominal price levels. 25
Page 1 and 2: Gaming the Float: How Managers Resp
Page 3 and 4: earnings will choose more shares ou
Page 5 and 6: targets. Managers change the target
Page 7 and 8: it does not increase as the firm’
Page 9 and 10: meeting that forecast. This leads t
Page 11 and 12: 2.2 Time series determinants of sha
Page 13 and 14: ealized but before they are reporte
Page 15 and 16: A and incentive compensation in Pan
Page 17 and 18: elationship between incentive compe
Page 19 and 20: the view that increases in forecast
Page 21 and 22: In columns 2 and 3, we measure our
Page 23: atypical amount. In Table 9, we rep
Page 27 and 28: management tools. 27
Page 29 and 30: De Angelis, D. and Y. Grinstein (20
Page 31 and 32: A Appendix We show that a drop in a
Page 33 and 34: Figure 1: Example of the relationsh
Page 35 and 36: Figure 3: Median Shares Outstanding
Page 37 and 38: Table 2: Determinants of Shares Out
Page 39 and 40: Table 4: Shares Outstanding: First
Page 41 and 42: Table 6: Changes in Shares Outstand
Page 43 and 44: Table 8: Changes in Shares and Acco

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