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Effort and Selection Effects of Performance Pay In EFFORT AND SELECTION EFFECTS OF PERFORMANCE PAY IN KNOWLEDGE CREATION∗ y Erina Ytsma It is well-documented that performance pay has positive effort and selection effects in routine, easy to measure tasks, but its effect in knowledge creation is much less understood. This paper studies the effects of explicit and implicit, market-based incentives commonly found in knowledge work industries in a multi-tasking model and estimates the causal effort and selection effects of performance incentives in knowledge creation by exploiting the introduction of performance pay in German academia as a natural experiment, and using a newly constructed dataset of the universe of German academics. I find that performance incentives attract more productive academics, and research quantity increases by 14 to 18%, but there is no increase in the highest quality output. JEL J33, M52, O31 1 INTRODUCTION Knowledge work is an important pillar of present-day economies. It has become rapidly more prevalent over the last four decades and exhibited consistent growth in occupational employment share1(Autor, 2019). Furthermore, knowledge creation has long been considered an important driver of economic growth (Romer, 1986; Lucas, 1988). Yet much is still unclear about how to motivate knowledge workers, including how they respond to performance pay. This paper sheds ∗I would like to thank Laurence Ales, Pierre Azoulay, Oriana Bandiera, Tim Besley, Jordi Blanes-i-Vidal, Kenneth Corts, Pablo Casas-Arce, Baran Duzce, Florian Englmaier, Jeff Furman, Maitreesh Ghatak, Bob Gibbons, De Gruyter, Rosario Macera, Bentley Macleod, Michal Matejka, Bob Miller, Steve Pischke, Andrea Prat, Carol Propper, John van Reenen, Mark Schankerman, Axel Schniederjuergen, Ananya Sen, Chris Stanton, Scott Stern, Neil Thompson, Fabian Waldinger, the ministries of education of the German states and seminar and conference participants at DRUID 2016, the 31st EEA Congres, ESNASM 2017, ESEM 2017, ESEWM 17, IOEA 18, SIOE 18, BePE 2018, AEA 2019, GEIRC 2019, EAA 2019, GSE-OE 2019, AAA 2019, NBER Personnel Economics Summer Institute 2019, MAS Midyear 2020, CMU MAC 2019, MIT TIES, MIT IDE, MIT OE Lunch, Universidad Carlos III, Copenhagen Business School, Carnegie Mellon Tepper, UANDES, Universite Laval and MPI Munich for helpful comments, information or data. A previous version of this paper was titled “Career Concerns in Knowledge Creation”. yCarnegie Mellon University, Tepper School of Business. Tepper Building Room 4123, 5000 Forbes Avenue, Pittsburgh, PA 15213. e-mail: [email protected]. Phone: +1-412-268-1117. 1Knowledge work is defined here as non routine cognitive jobs that comprise a host of intellectual tasks. 1 light on the effect of performance pay on knowledge creation by causally identifying the effort and selection effects of performance incentives in academia. It is by now well-understood that performance pay increases productivity in routine tasks and settings in which output is readily measurable (e.g. car window replacement, fruit picking, students’ test scores), through increases in effort or by attracting the most productive individuals (Lazear, 2000; Shearer, 2004; Bandiera, Barankay and Rasul, 2005; Leuven et al., 2011; Dohmen and Falk, 2011). However, it is not clear that performance pay would have the same effects in the context of knowledge work. For one, knowledge work generally comprises multiple, complex tasks, the output of which is often not measurable or only a noisy signal of effort. Multi-tasking problems are therefore likely to arise (Holmstrom and Milgrom, 1991; Hellmann and Thiele, 2011). Secondly, because quality dimensions such as impact and novelty are valuable outcome characteristics for many types of knowledge work, incentive systems may need to be structured differently, with a longer time-horizon and allowing for (early) exploration and experimentation (Azoulay, Graff Zivin and Manso, 2011; Manso, 2011; Ederer and Manso, 2013). Finally, knowledge workers may be particularly highly intrinsically motivated. Higher-powered extrinsic incentives may crowd-out this intrinsic motivation, thus potentially reducing knowledge output (Benabou and Tirole, 2003; Bénabou and Tirole, 2006; Besley and Ghatak, 2005, 2018). In this paper, I study the effect of performance incentives on the quantity and quality of knowl- edge output and the productivity of knowledge workers attracted by high-powered incentives both empirically and theoretically. I present a simple multi-tasking model with explicit and implicit, market-based incentives commonly found in knowledge work industries and use this to derive testable implications for both average incentive effects and heterogeneous responses across ability types. I test the model’s predictions by exploiting the introduction of performance pay in German academia as a natural experiment, and using a newly constructed dataset of the universe of German academics2. The specifics of the roll-out of the performance-related pay scheme give rise to a differential incidence of performance incentives across tenure and age cohorts. This allows me to causally and separately identify the effort and selection effects in a difference-in-differences framework. The theoretical model presented in this paper builds on Gibbons and Murphy (1992) and features both explicit performance incentives (bonuses for performance on the job) and implicit, market-based incentives (wage supplements negotiated in contract talks). This combination of explicit and implicit incentives is a common feature of pay structures in knowledge work industries3. The model also incorporates multi-tasking issues as output has two dimensions, quantity and quality, the latter of which is less precisely measured (c.f. Holmstrom and Milgrom (1991)). Both output dimensions increase with effort as well as agent ability and agent ability is imperfectly known by the market and the agent (i.e. there is symmetric uncertainty about agent 2This dataset is also used in Ytsma (2021). 3Market-based wages determined in contract negotiations (career concerns) and on-the-job performance bonuses are common performance incentives in academia and knowledge creation jobs more generally (Bonatti and Hörner, 2017), as well as managerial jobs (Gibbons and Murphy, 1992) and professional jobs such as in law (Ferrer, 2016), finance (Hong, Kubik and Solomon, 2000; Chevalier and Ellison, 1999) and software development (Lerner and Wulf, 2007). 2 ability). The market then uses output measures as signals of both effort and agent ability, to inform agent pay. This, in turn creates incentives for the agent to exert effort. Because quality is less precisely measured, the incentives to exert effort toward quality are relatively weaker. Yet because the market takes both quantity and quality output into account to update believes about agent ability, incentives to exert quality are not absent either and they are stronger for higher ability academics, for whom exerting effort towards both quantity and quality is assumed to be relatively less costly. In equilibrium, and relative to a flat wage, output quantity goes up unambiguously in response to performance pay, but output quality increases only if the quality output measure is sufficiently precise. These responses are not uniform across ability types. Performance pay increases quantity effort the most for the lowest ability workers, and least for workers of intermediate ability. Quality effort on the other hand increases the most or decreases the least for the most able workers and decreases the most for those of intermediate ability. That is, there is no simple substitution of quantity for quality, rather the degree to which there is substitution varies across ability types and depends on the noise with which output dimensions are measured. Furthermore, the higher-powered incentives attract workers of higher ability (in expectation), since they can expect to earn more under performance pay. In order to empirically analyze the effect of performance pay in academia, I constructed a data set comprising the affiliations, research productivity measures and related information of the universe of academics in Germany by consolidating information from various, unstructured data sources. To estimate the effort effect, I use the fact that any contract signed or renegotiated after the implementation of the reform necessarily falls under the new performance pay scheme, while any existing contract continues to fall under the old age-related pay scheme. Academics who start their first tenured affiliation before the reform therefore fall under the age-related pay scheme, while those who start their first tenured affiliation after the reform are paid according to the performance pay scheme. If the timing of the start of the first tenured affiliation is exogenous, any difference in the change of productivity from before to after the reform between academics who start their first tenured position just before the reform and those who start a first tenured position directly after the reform can be interpreted as the causal effect of performance pay on effort. I find that performance pay increases research quantity and quality-adjusted quantity by at least 14 to 18% on average4. At the same time, the average quality of publications5 decreases by 9 to 10% in response to performance pay. The response in output quantity is equivalent to treated academics publishing almost one extra paper every three years, while the decline in average quality is equivalent to a decrease of almost 0.22 in the
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