the effects of the Sort and Auction treatments suggests that the selection effect is stronger than the effect of strategic anticipation. The effect of selection is so strong that it can overcome the direct effect of lower incentives to yield coordination at high effort levels in the Reverse Sort treatment. In the Sort and Reverse Sort treatments, extreme groups (most likely to be selected into contracts) behave significantly differently than border groups, illustrating the power of selection.
To understand why selection is so powerful, recall from Table 4 that Round 1 choices, partic- ularly choice of 40, are by far the best predictor of dropout times. The tendency of the auction to assign subjects who chose 40 in Round 1 to Contract 2 is important because those subjects were extremely likely to also choose 40 in Round 11 regardless of their circumstances.
Figure 3: Comparison of Border and Extreme Groups in Block 2 Sort Treatment 0 10 20 30 40 11 12 13 14 15 16 17 18 19 20
Contract 1, Extreme Contract 1, Border Contract 2, Extreme Contract 2, Border
Reverse Sort Treatment
0 10 20 30 40 11 12 13 14 15 16 17 18 19 20
Contract 1, Extreme Contract 1, Border Contract 2, Extreme Contract 2, Border
Figure 4 illustrates this point. The data for this figure come from all subjects who chose 40 in Round 1. The left hand panel displays the distribution of their choices in Round 11, broken down by the contract they were assigned in Block 2. For either contract, subjects who chose effort level 40 in Round 1 almost always chose 40 in Round 11. This is not because they failed to learn across Block 1. Most groups had low minimum efforts by the end of Block 1, and even the subset of initially optimistic subjects learned to adjust their choices during the course of Block 1. Only 36% chose 40 in Round 10, and only 10% chose something other than 0 in Round 10 if they were in a group with a minimum effort of 0. Rather, these subjects returned to their initial optimism when the game restarted with a new group and, possibly, a new contract. The right hand panel demonstrates how general this phenomenon was. It reports average effort in Round 11 broken down by treatment and contract. In all cases the average is close to 40.
Figure 4: Round 11 Behavior by Subjects Choosing 40 in Round 1
0 10 20 30 40 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Distribution of Round 11 Choices
Random Auction Sort Reverse Sort
0 10 20 30 40 Effort
Average Round 11 Choice
Contract 1 Contract 2
Subjects who chose 40 in Round 1 were far more likely to choose 40 in Round 11 than other subjects (85% vs. 39% in Contract 1 and 90% vs. 56% in Contract 2).26 Initial optimism is not
26Based on Probit regressions, we find that the likelihood of choosing 40 in Round 11 does not vary significantly
transient but instead seems to represent a subject’s type. The auction tends to assign subjects who chose 40 in Round 1 to Contract 2, leaving others behind in Contract 1. The Sort treatment shares a tendency to assign subjects who chose 40 in Round 1 to Contract 2 and therefore yields similar outcomes to the Auction treatment.
5
Conclusion
The primary purpose of this paper was to investigate how endogenous assignment to incentive contracts affects the efficacy of high performance pay as a tool for escaping a productivity trap. The impact on groups that receive such performance pay is much greater when assignment is en- dogenous, with groups achieving almost perfect coordination at the efficient equilibrium. However, at a global level, this is entirely offset by the negative impact on groups that keep the original incentive contract with low performance pay. Our design makes it possible to identify a lower bound on how much of the increased effect of high performance pay with endogenous contract as- signment is due to selection rather than strategic anticipation. We find that selection accounts for substantially more of the increase than strategic anticipation, even though the impact of selection is presumably underestimated due to the Sort treatment’s imperfect replication of the selection process in the Auction treatment. The effect of selection is sufficiently strong that it can over- come the direct effect of incentives, as manipulating the assignment process in the Reverse Sort treatment generates higher productivity with low performance pay.
While a number of studies have found that selection accounts for a high proportion of the effect of performance pay, the flavor of our results is rather different. In the existing literature, selection has an effect by choosing people who are good at performing some task – solving puzzles, multiplying numbers, etc. In our experiment, selection chooses people who are optimistic about coordinating at efficient outcomes (or believe that others are optimistic). Selection is primarily based on beliefs rather than abilities.
Our finding that high performance pay increases productivity by matching optimists with each other is related to Becker’s work (1973) on the marriage problem and Kremer’s work (1993) on the assignment of workers to firms. Becker considers the allocation of men and women into marriages in which the “productivity” of each marriage is assumed to depend on the ability levels of each of the partners. Becker then provides conditions under which the efficient allocation of
partners results in assortative matching.27 Similarly, when the productivity of each worker in an organization depends positively on the productivity of co-workers, incentives exist for relatively high-skilled workers to form firms that exclude their lower-skilled counterparts (Kremer, 1993).
A surprising finding from our experiments is the minuscule total effect, averaging over both contracts, of endogenous assignment to incentive contracts. The underlying issue is that assigning more optimists to Contract 2 necessarily means assigning more pessimists to Contract 1. This implies that labor mobility plays a central role in determining the total effect of endogenous assignment to incentive contracts. In future work we hope to explore the implications of making labor markets open versus closed, in the sense defined previously, as well as allowing firms to choose an incentive contract rather than exogenously assigning incentive contracts to firms.
Our experiments take advantage of the control available in the laboratory. The insights we could draw from our data would be limited without our Sort and Reverse Sort treatments, but it is hard to imagine a real-world setting that would mimic these treatments. A natural question is how our results apply to labor markets in the field. Real labor markets are far more complex than our lab experiments. In the simple environment of our experiments, the data suggest that workers generally do not take into account the implications of endogenous assignment to incentive contracts and the resulting effects of selection. What are the odds that workers in more complex field settings understand these subtle issues? This implies that strategic anticipation plays an even smaller role in field settings than in the lab, a conjecture that we hope to verify in the future. More generally, we hope that future research will establish a relationship in field settings between selection for optimists and organizational success. For example, there has been movement towards “agile” software development over the past two decades. Many specific processes for software development (e.g. Extreme Programming, Scrum, etc.) fall under the umbrella of agile software development. There are a number of common features associated with agile software development, but of particular interest to us is a focus on small self-organizing teams. These provide a very different work environment from more traditional top-down organizations and there exists evidence that these different organizational forms attract software developers with different personality traits (e.g. Yilmaz, O’Connor, Colomo-Palacios, and Clarke, 2017, employing the
27Specifically, Becker (1973) shows that in a transferable utility matching market, if there are complementarities in
production, then any core allocation, and consequently, any competitive equilibrium, exhibits assortative matching. In other words, individuals sort themselves into matches with likely mates such that the ablest male is matched with the ablest female.
Big Five, find that extroversion is more prevalent among members of agile software development teams). It would be interesting to know whether, as our research suggests, there is selection based on beliefs about the likelihood of cooperation and/or efficient coordination within teams and whether this type of selection plays an important role in organizational success. We view this and similar issues as promising directions for future work.
Finding field evidence for negative effects due to selection is also of interest to us. The literature on entrepreneurship provides an interesting example of this. Less than 10% of new businesses are started by teams of non-relatives rather than individuals or relatives (Shane, 2008), but firms founded by teams tend to do better. This can be attributed in part to preferences for working alone rather than in a team and/or pessimism about the profitability of teams. Specifically, Cooper and Saral (2013) find that entrepreneurs are significantly less willing to join teams than otherwise similar business people. In other words, entrepreneurship tends to attract individuals whose preferences and beliefs make them less likely to succeed as entrepreneurs!28
Our paper and much of the related literature stresses workers’ choices of jobs as a source of selection, but firms can and do actively use applicants’ characteristics when choosing who to hire. Personality testing, particularly use of the Big Five, became popular starting in the late 1980 and early 1990s. One recent study finds that about 20% of large firms use personality testing (Piotrowski and Armstrong, 2006). To the extent that they correctly identify the characteristics associated with success, this practice should have a positive effect like the Sort treatment. It re- mains controversial whether or not personality testing is useful for employers. While some argue that that personality tests are good predictors of “soft skills” like persistence and willingness to follow organizational norms (Barrick and Mount, 2012), others claim that the usefulness of per- sonality testing is limited, partially because job candidates have a strong incentive to manipulate the test results (Stabile, 2001).29 It remains to be seen if some form of behavioral testing including instruments more familiar to experimental economists will prove useful to firms when hiring new employees.30
28Cooper and Saral’s experiment is designed to limit the possibility that beliefs can explain the relative disinterest
of entrepreneurs in joining teams, stressing the role of preferences. We think it is likely that beliefs also play an important role, a conjecture that we hope to explore in the future.
29For other papers discussing the usefulness of personality testing, see Morgeson, Campion, Dipboye, Hollenbeck,
Murphy, and Schmitt, 2007; Ones, Dilchert, Viswesvaran, and Judge, 2007.
30Unilever is an example of a firm using personality tests that mirror standard experimental tasks like the trust
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