[Research Seminar] IRISK: “Yoy will not regret it: On the practice of randomized incentives” B. CORGNET – EM Lyon

Speaker: Brice CORGNET
EM Lyon Business School

Date and Location – Thursday April 27th 2023 from 14:00 to 15:00
in Lille campus (R217) and on Zoom

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ABSTRACT

Business scholars have long emphasized setting specific goals and providing clear expectations as a key driver of work performance (e.g., Vroom, 1987; Nadler and Lawler, 1977; Harter et al., 2003; Kim and Mauborgne, 2003; Rock, 2008; Latham, 2012). A common advice to managers is thus to
“make the performance-reward link clear and objective” (Lam et al., 2022). The study of incentives in Economics also emphasizes that noisy output measures should be avoided because they produce risk, thus increasing the cost of motivating workers (see Holmström, 1979; Milgrom and Roberts, 1992; Laffont and Martimort, 2002; Besanko et al., 2017). Furthermore, the theory of incentives has overwhelmingly focused on deterministic schemes that stipulate the exact rewards paid for a given level of output (see Grossman and Hart, 1983; Fudenberg and Tirole, 1991; Laffont and Martimort, 2002; Bolton and Dewatripont, 2004; Dranove et al., 2017). Although randomized schemes can be optimal in the presence of informational asymmetries and risk-sharing issues (see e.g., Baron and Myerson, 1982; Arnott and Stiglitz, 1988; Strausz, 2006; Herweg et al., 2010; Jehiel, 2015; Kadan et al., 2017; Ederer, Holden and Meyer, 2018), they have often been dismissed for practical reasons, as expressed in Brito, Hamilton, Slutsky and Stiglitz (1995, p. 190): “Third, it is unclear whether randomization is only a theoretical curiosity or whether it could be implemented in practice.” Yet, more recently, behavioral scholars have called for an empirical examination of randomized schemes (Babcock, Congdon, Katz and Mullainathan, 2012). In this paper, we emphasize that randomization can be effectively implemented in a broader range of situations than envisioned by the current literature, thus answering the legitimate doubts of theorists while providing echoing the enthusiastic call of behavioral scholars. In particular, we show that randomized incentives can be optimal even in the absence of informational and risk-sharing issues. We argue this is the case because randomized incentives trigger regret motives. We illustrate this point with the case of bonus schemes that are paid when a given target is met. Randomly selecting the value of the target after the completion of the task will lead high-ability regretful workers to exert a high level of effort to avoid missing out on the bonus. That is, randomized incentives create counterfactuals that exacerbate regret motives.