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

More documents

Recommendations

Info

elated to the variance (variance is e2 12 ) of the earnings and positively related to s. If payoffs are fixed and homogenous across managers, then all managers will prefer the same probabilities of meeting, beating, and missing EPS forecasts. Holding these payoffs constant, it follows directly that managers of firms with volatile earnings will need to choose higher shares in order to obtain the same EPS outcome likelihoods. This positive relation between net income volatility and shares outstanding is our main prediction: H1: Managers of firms with highly volatile and unpredictable earnings will choose more shares outstanding compared to firms with stable, predictable earnings, all else equal. This prediction is difficult to test empirically for a variety of reasons. First, forward-looking volatility is not observable. Second, the volatility of earnings that is important for our purposes is the part that is unpredictable. More precisely, the variance that is important is the variance in the difference between realized earnings and expected earnings. For example, if a firm has volatile earnings due to predictable seasonal variation, then this volatility would not reflect the likelihood that the firm will generate earnings different from forecasts. Third, as pointed out in the large literature on earnings smoothing (e.g. Beidleman (1973), Subramanyam (1996), Healy and Wahlen (1999)), the variance in earnings is itself a choice variable. To address the first two concerns, we use three proxies for net income volatility; i) variance around the mean over the last twelve quarters, ii) variance around a seasonally adjusted expected mean over the last twelve quarters, and iii) variance around the expectation implied by analysts’ forecasts over the last twelve quarters. We expect to find a positive relationship between these measures of net income volatility and shares outstanding. The last concern, that net income volatility is jointly determined with the number of shares, makes identification difficult. To address causality, we use a source of plausibly exogenous variation in the probability that the firm meets EPS forecasts and relate this to changes in shares outstanding. Specifically, we use an exogenous drop in analyst coverage as a shock to the probability that the firm meets earnings forecasts. Our reasoning is simple, if the consensus forecast is thought of as the sample mean (or median) of individual analysts’ noisy forecasts, then the variance of this estimate is decreasing in the number of analysts, i.e. the noise in the forecast is a decreasing function of the sample size. Therefore, a drop in analyst coverage increases the variance in the EPS forecast simply because fewer analysts are sampled. Increasing the volatility of the forecast is equivalent to increasing the volatility of earnings around the forecast. In the Appendix, we show explicitly that an increase in forecast noise decreases the probability of 8
meeting that forecast. This leads to a variant of our main hypothesis: H1a: Managers increase shares in response to an exogenous decrease in analyst coverage. Next, we discuss how manager payoffs might relate to variation in shares outstanding. All else equal, we expect a positive relationship between the sensitivity of payoffs to negative earnings surprises relative to positive surprises (concavity) and shares outstanding. The more shares are outstanding, the lower is the probability of missing earnings. However, because this rounding effect is symmetric, it also decreases the probability of beating earnings. A manager with convex payoffs (higher sensitivity to meeting than missing) should prefer a small range. In this case, the probability of missing is high, but the probability of beating is high as well. A manager who incurs large costs when missing relative to beating (concave payoffs) will prefer a larger range to minimize the chances of incurring those costs. H2: Managers with payoffs that are concave (convex) in earnings surprises will choose higher (lower) level of shares outstanding. Similar to net income volatility, payoffs are neither observable nor exogenous. However, there is considerable evidence that CEO’s receive compensation that is concave in earnings surprises. Bonuses in CEO compensation contracts are often tied to EPS thresholds based on analyst forecasts (Murphy (1999), De Angelis and Grinstein (2011) and Kim and Yang (2012)). Also, the negative stock price reactions to negative earnings surprises are significantly larger than the positive reactions associated with beating forecasts. 11 Given that most CEOs have substantial ownership stakes in the company, this creates a stronger incentive to avoid missing earnings expectations compared to the incentive to beat those targets. Burgstahler and Dichev (1997) and Degeorge et al. (1999) show empirically that the distribution of EPS outcomes is consistent with the view that managers respond to incentives to meet or beat EPS targets. Furthermore, prior literature has documented a connection between EPS outcomes and managerial compensation. For example, Cheng and Warfield (2005) find that managers with high equity ownership are less likely to miss EPS targets. We expect managers with larger bonuses tied to accounting targets to have more shares outstanding, and hence wider rounding ranges. We would also expect managers who have more ownership and more equity 11 Payne and Thomas (2003) and Skinner and Sloan (2002) show differences in the source of this effect, but both generally find stronger negative reactions. 9
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: it does not increase as the firm’
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 and 24: atypical amount. In Table 9, we rep
Page 25 and 26: price levels observed in the data.
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

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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?