Compensation

Earnings management is presumably costly, as managers might face several adverse consequences (e.g., job loss, reputational damage, etc.) if they are unable to compensate for current-period earnings management through strong future

performance. Similarly, I design the incentive structure such that engaging in earnings management is costly if Period 2 performance is not sufficient to compensate for the earnings management. As indicated previously, participants in the Delay condition earn less than participants in the No Delay condition, though this result is only

marginally significant, even though they face identical compensation structures. After combining data across experiments, this effect is significant (p = 0.035, one-sided).31

(participants were drawn from the same population within several days of each other, but participants were not randomly assigned across experiments).

In addition, I find that this effect is mediated by participants’ EM DECISION (p = 0.077, one-sided). These results are consistent with horizon-induced optimism leading participants in the Delay condition to engage in costly earnings management,

5.3 Innate Optimism

Recent work in behavioral finance and accounting examines how optimism affects managerial decisions, but most of this work focuses on optimism as a stable individual trait. In contrast, the differences I observe across conditions cannot be attributed solely to differences in participants’ innate optimism. Unlike stable-trait optimism, horizon-induced optimism is unlikely to be attenuated by screening out optimistic individuals unless more optimistic individuals are more likely to exhibit horizon-induced optimism. To test this possibility, I invited participants in

Experiments 1 and 2 to complete a follow-up survey. 117 participants completed Scheier, Carver, and Bridges’ (1994) LOT-R, a measure of innate measure. 32, 33 I find no evidence that individuals with higher stable-trait optimism are more susceptible to horizon-induced optimism. Instead, the results are directionally consistent with the idea that the effect of TIME DELAY on CONFIDENCE and FORECAST OPTIMISM is decreasing in stable-trait optimism (p = 0.254, two-sided and p = 0.113, two-sided, respectively). These findings provide weak evidence that less optimistic individuals might be more likely to exhibit horizon-induced optimism than more optimistic individuals. However, these findings provide relatively strong evidence that screening

32 _{I find no evidence that Time Delay affects participants’ propensity to complete this follow-up survey}

(p = 0.573, two-sided). In addition, while CONFIDENCE and FORECAST OPTIMSIM affect

participants’ propensity to complete this follow-up survey (p = 0.050, two-sided and p = 0.070, two- sided, respectively), these self-selection effects do not interact with Time Delay (p = 0.215, two-sided and p = 0.528, two-sided, respectively).

33 _{This measure asks participants to indicate their agreement with statements such as, “I’m always}

managers based on measures of innate optimism is unlikely to be an effective intervention for horizon-induced optimism.

5.4 Measures of Optimism

My primary analyses rely on two measures of participants’ optimism – CONFIDENCE and FORECAST OPTIMISM. When both measures are included with TIME DELAY as predictors of EM DECISION, I find that CONFIDENCE and

FORECAST OPTIMISM both remain significant for Experiment 1 (p = 0.027, one- sided and p < 0.001, one-sided, respectively) and for Experiment 2 (p = 0.073, one- sided and p = 0.052, one-sided, respectively). While these two measures of optimism are correlated (ρ = 0.559 and ρ = 0.551 in Experiments 1 and 2, respectively), it’s possible these two measures are capturing slightly different facets of optimism (Cronbach’s alpha = 0.651 and 0.690 in Experiments 1 and 2, respectively). For example, CONFIDENCE might capture a general sense of participants’ optimism while FORECAST OPTIMISM might capture a more deliberative and calculative measure of participants’ optimism. Importantly, however, my time delay manipulation significantly affects both measures of optimism, suggesting that horizon-induced optimism is likely to affect behavior that is influenced by either or both facets of optimism.

CHAPTER 6

CONCLUSION

I use two experiments to examine how the amount of time between the current period and the period when the earnings management reversal occurs affects optimism and earnings management, holding constant participants’ incentives, participants’ innate optimism, and the information environment. My results indicate that optimism about future performance is increasing in the length of this time delay, and this horizon-induced optimism increases participants’ propensity to engage in behavior that is analogous to accruals-based and real earnings management.

My findings extend prior work by providing evidence that a fundamental feature of the earnings management setting can systematically induce optimism and increase earnings management, even holding constant factors to which earnings management has previously been attributed (e.g., agency frictions, capital market pressure, and innate optimism). My findings also indicate that optimism is most likely to be important in settings where there is a significant amount of time between the decision and the realization of its outcome. Consistent with this idea, prior work finds that management forecast optimism is increasing in the forecast horizon (Choi and Ziebart 2004; Hirst, Koonce, and Venkataraman 2008), although these authors attribute this result to management incentives to intentionally bias their forecasts. My results suggest that the amount of time between the forecast and the outcome might contribute to this pattern of forecast optimism, even absent these strategic reporting incentives.

My findings might also have implications for the debate on reporting frequency, and future work might examine how the effect of horizon-induced optimism on earnings management depends on reporting frequency. Because the length of the time delay to the next period is decreasing in reporting frequency, one possibility is that horizon-induced optimism could work against myopic behavior as reporting frequency increases. However, another possibility is that horizon-induced optimism could exacerbate myopic behavior as reporting frequency increases, because the number of time delays between periods is increasing in reporting frequency.

The primary limitation of my study is my inability to assess the magnitude of the effect of horizon-induced optimism on either managers’ beliefs or earnings management behavior in the real world. However, there is reason to expect that managers would be susceptible to these same errors given the neural mechanisms underlying optimism. In addition, optimism appears to affect various managerial decisions, suggesting that optimism is not fully disciplined by the strong incentives and institutional forces in these settings. The incentive structure in my experiment is designed to capture several important aspects of managers’ incentives to manage earnings with the expectation of compensating for that behavior through strong future performance. The examination of other features of the reporting environment not captured in my study provides a potential avenue for future research.

APPENDIX

Panel A. Accruals Management Proxy (Experiment 1)

You can earn a second round bonus of $0.50 if you correctly answer at least [Period 1 Score – 3] questions in the second round. However, if you're willing to borrow 4 correct responses from the second round to add to your first round score, you can earn a first round bonus of $0.50 in addition to the second round bonus of $0.50. If you choose this option, you would have to correctly answer at least [Period 1 Score + 1] questions in the second round in order to keep this first round bonus and earn the second round bonus.

Please choose the bonus option you believe is most favorable to you:

 Option 1: If you answer at least [Period 1 Score – 3] questions correctly on the second round, receive a $0.50 second round bonus.

 Option 2: If you answer at least [Period 1 Score + 1] questions correctly on the second round, receive a $0.50 first round bonus and a $0.50 second round bonus.

Panel B. Real Earnings Management Proxy (Experiment 2)

You can earn a second round bonus of $0.50 if you correctly answer at least [Period 1 Score – 3] questions in the second round. However, if you're willing to trade five easy questions for five medium questions on the second round, you can earn a first round bonus of $0.50 in addition to the second round bonus of $0.50. If you choose this option, you would have to correctly answer at least [Period 1 Score – 3] questions in the second round with 10 easy, 10 medium, and 5 hard questions in order to keep this first round bonus and earn the second round bonus.

Please choose the bonus option you believe is most favorable to you:

 Option 1: If you answer at least [Period 1 Score – 3] questions correctly on the second round with 15 easy, 5 medium, and 5 hard questions, receive a $0.50 second round bonus.

 Option 2: If you answer at least [Period 1 Score – 3] questions correctly on the second round with 10 easy, 10 medium, and 5 hard questions, receive a $0.50 first round bonus and a $0.50 second round bonus.

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