We extend evidence on the interaction between financial incentives and cognitive abilities by focusing on the effect of task-specific abilities. In a memory-intensive task situated in an accounting context, the effect of accounting education on performance is stronger under financial incentives as compared to flat rate pay. Subjects with more accounting education respond stronger to financial incentives. Hence using incentives efficiently may involve targeting them at high-ability individuals. More generally, taking into account the incentive-ability interaction seems important when interpreting observed behavior in cognitively demanding lab and field economic environments.Financial incentives, Cognitive ability, Performance, Experiment

Ondrej Rydval

English

Research Papers in Economics

 
JENA ECONOMIC 
RESEARCH PAPERS 
 
 
 
 
# 2011 – 050 
 
 
 
The Effect of Financial Incentives and Task-specific 
Cognitive Abilities on Task Performance 
 
 
 
 
by 
 
 
 
 
Ondřej Rydval 
 
 
 
 
 
www.jenecon.de 
 
ISSN 1864-7057 
 
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The Effect of Financial Incentives and Task-specific 
Cognitive Abilities on Task Performance 
 
Ondřej Rydval 
Max Planck Institute of Economics, Kahlaische Strasse 10, 07745 Jena, Germany 
Tel: +49-3641-686-641, Fax: +49-3641-686-667, E-mail: rydval@econ.mpg.de 
 
Abstract 
We extend evidence on the interaction between financial incentives and cognitive abilities by 
focusing on the effect of task-specific  abilities. In a memory-intensive  task  situated in an 
accounting context, the effect of accounting education on performance is stronger under financial 
incentives as compared to flat rate pay. Subjects with more accounting education respond 
stronger to financial incentives. Hence using incentives efficiently may involve targeting them at 
high-ability individuals.  More generally, taking into account  the incentive-ability interaction 
seems important when interpreting observed behavior in cognitively demanding lab and field 
economic environments. 
 
 
Keywords: Financial incentives, Cognitive ability, Performance, Experiment 
JEL classification: C81; C91; C93; D83 
Jena Economic Research Papers 2011 - 050  2 
1. Introduction 
Economists widely believe that, absent strategic considerations such as agency problems, 
financial incentives represent the dominant and effective stimulator of human productive 
activities. In cognitively demanding tasks, however, even if incentives and other motivational 
factors  sufficiently induce effort, both financial and cognitive resources may be wasted for 
individuals lacking cognitive abilities (or skills, or capital) to perform the task. This prediction 
has been expressed only informally in Camerer and Hogarth’s (1999) capital-labor-production 
framework  and by others.
1
Broadly in line with the above prediction, two between-subject experimental studies document a 
positive interaction between incentives and abilities. In an accounting task, Awasthi and Pratt 
(1990) find that incentives (rewarding correct choice) improve performance compared to flat rate 
pay only for  subjects  with  high  perceptual differentiation. Similarly,  Palacios-Huerta (2003) 
reports that raising incentives (piece-rate and tournament) improves performance in a Monty 
Hall Three Door task only for subjects with superior schooling outcomes (but this effect could be 
partly due to intra-group communication).
  Furthermore,  empirical tests are sparse,  and  –  likely due to the 
complexity of measuring cognitive effort duration (other than as a direct correlate of cognitive 
production) let alone effort intensity – they have examined only the reduced-form relationship 
between incentives, abilities and performance. Nevertheless, even this relationship has important 
implications for designing efficient incentive schemes in firms, experimental settings and 
elsewhere, as well as for interpreting observed (variance of) behavior in cognitively demanding 
lab and field economic environments. 
2
We extend the above evidence by focusing on the interaction between incentives and more task-
specific, as opposed to domain-general, cognitive abilities. Their role in cognitive production is 
central to Camerer and Hogarth’s capital-labor-production framework and has been extensively 
studied in cognitive science and behavioral decision research (see, e.g., Anderson, 2000, and 
Bonner and Sprinkle, 2002, for reviews). Moreover, unlike in the above two choice tasks, our 
 
                                                 
1 See, e.g., Awasthi and Pratt (1990), Libby and Lipe (1992), Libby and Luft (1993), and Wilcox (1993). 
2 Rydval and Ortmann (2004) review the papers in more detail. They also illustrate that both abilities and incentives 
are important for performance in an IQ test, but they lack an independent measure of ability that would enable them 
to study the incentive-ability interaction. 
Jena Economic Research Papers 2011 - 050  3 
performance measure allows us to study the incentive-ability interaction in a more continuous 
fashion. Last, we pay closer attention to motivational issues and the role of effort input. 
We use a dataset from Libby and Lipe (1992; henceforth LL). In the experiment, 117 accounting 
and auditing students performed a task called free recall. They were presented with 28 sentence-
long accounting expressions used in auditing a company’s internal control system. At their own 
pace, subjects  memorized  the items, then completed a brief  demographic questionnaire, and 
finally recalled (typed in) the items in any order. 
Subjects were randomly assigned into three treatments.  The $FLAT treatment featured a $2 
participation fee. The  incentivized  treatments in addition featured combined piece-rate and 
tournament incentives, namely, $0.1 per correctly recalled item and $5 if among the best five 
performers in the treatment. The incentives were announced prior to memorizing in the $MEMO 
treatment, but only prior to recalling in the $RECALL treatment.
3
Subjects reported their attained accounting credits (henceforth education; on average about 20 
credits) and auditing job experience (henceforth experience; on average about three months for 
the third of subjects with experience).
 LL’s main finding is that 
performance – the number of correctly recalled items – is significantly higher (by about two 
items on average) in $MEMO and $RECALL compared to $FLAT. Performance also varies 
considerably across subjects, the reasons for which we analyze below. 
4 LL interpret the variables as proxies for task-specific 
cognitive  ability,  potentially reflecting subjects’  differential  familiarity with the  memorized 
items. The proxies do not vary across the treatments but vary substantially across subjects and 
are only weakly correlated with each other. Noting a significant correlation between education 
and performance in $RECALL,
5
                                                 
3 LL labeled the treatments FLAT, ENCODING and RETRIEVAL, respectively. 
 LL speculate that the impact of incentives on performance may 
depend on subjects’ accounting knowledge. We analyze this hypothesis in more detail. 
4 Subjects also reported the number of auditing credits but this variable does not vary across subjects. 
5 LL also report a significant correlation between performance and auditing grades in $RECALL, but the grades are 
not available for further analysis. 
Jena Economic Research Papers 2011 - 050  4 
2. Results and discussion 
In Column 1 of Table 1, we first replicate the average incentive treatment effect reported by LL.
6 
Column 2 then shows that the effect remains about the same after accounting for the significant 
positive effect of education and experience. There is also a significant negative interaction (i.e., 
substitution) effect between education and experience.
7
Column 3 suggests, however, that the incentive treatment effect in fact stems from a significant 
interaction  between incentives and  education.  Performance on average improves by about a 
quarter of an item with each additional accounting credit in $FLAT, but by about 50 percent 
more in the incentivized $RECALL and $MEMO treatments (note the results are remarkably 
similar in $RECALL and $MEMO despite the differential timing of incentives). The effect of 
experience – about three items per each additional month – as well as the education-experience 
interaction effect remain about the same as in column 2 and do not differ across the treatments. 
The incentive treatment dummies are individually and jointly highly insignificant and hence are 
omitted.  In sum, what  seems to drive  the  incentive treatment effect reported by LL  is  that 
incentives better foster performance of subjects with more education. To illustrate, the average 
performance of subjects with above-median education is 10.2 items in $FLAT versus 13.6 items 
in $RECALL and $MEMO (combined), whereas the figures are 9.6 and 10.7 items, respectively, 
for the remaining subjects with lower education. 
 
We  next  examine  whether  our  findings  are  affected by motivational problems, which may 
involve quite a different incentive-ability interaction than the one portrayed above. In general, 
subjects in $FLAT could lack intrinsic motivation to perform, while the motivation of subjects in 
$MEMO and $RECALL could be “crowded out” by the piece-rate or tournament incentives (in 
the sense of Deci et al., 1999, or Gneezy and Rustichini, 2000) or by the delayed announcement 
of  the  incentives  in $RECALL.  We observe  the following. First, in the bottom decile of 
performance  with one to four recalled items, five subjects come from $FLAT, three from 
$RECALL and five from $MEMO, so low performance is not overly specific to any treatment. 
Second, low performance does not seem to arise from (initial) motivational problems, since only 
                                                 
6 For reasons that remain unclear, we are unable to exactly replicate the results for $FLAT and $RECALL, but the 
discrepancy is negligible. 
7 However, for all the reported regressions, log-linear “production function” specifications that would more naturally 
accommodate the education-experience interaction perform much worse in terms of statistical significance and fit. 
Jena Economic Research Papers 2011 - 050  5 
two bottom-decile performers come from the bottom decile of memorizing time (which was 
unobtrusively measured).
8 Third, the bottom-decile performers on average have only slightly 
lower education and experience compared to the remaining subjects. Most importantly, column 4 
shows that our results change rather little when excluding the eight worst performers with just 
one or two recalled items; the incentive-education interaction becomes even larger and more 
significant.
9
As a second robustness check, we examine whether including memorizing time, i.e., initial effort 
duration  input, affects our results. This is not an attempt to estimate a formal capital-labor-
production model, since we observe neither other effort inputs (their duration and intensity) such 
as recalling effort,
 
10 nor other likely relevant cognitive ability inputs such as short-term memory. 
Furthermore, since memorizing time is endogenous  to  recall performance, we use  only the 
residual variation therein, after removing the effect of incentives, education and experience.
11 In 
an unreported background estimation, we find that memorizing time is higher in $MEMO and 
decreases with more education and experience.
12
3. Conclusions 
 This may simply mean that more education and 
experience facilitates faster reading and memorizing of the items. In any case, column 5 shows 
that the residuals from the background estimation have  a significant positive impact on 
performance. Most importantly, comparing vis-à-vis column 3, our results are virtually intact, 
and the incentive-education interaction is slightly smaller but still highly significant. 
In line with the previous two studies, we find a positive incentive-ability interaction, in our case 
for a more task-specific form of cognitive ability. All three studies suggest that using incentives 
efficiently may involve targeting them at high-ability individuals. The findings may naturally be 
specific to the production settings, incentive schemes and cognitive ability proxies, among other 
                                                 
8 Two subjects took only about a minute and 10 subjects took between two to three minutes to memorize, yet their 
average performance reached almost seven items. 
9 Excluding all bottom-decile performers yields similar findings. In all the robustness checks, the preferred model 
specification is the one in column 3. 
10 Recall time was measured, but this seems to be a direct correlate or byproduct of performance and furthermore is 
likely confounded by differences in subjects’ typing speed. 
11 Still, the residual variation could subsume various forms of unobserved heterogeneity. 
12 The decrease is faster in $MEMO but not significantly so. The regressors are jointly significant at the 5% level. 
We exclude six “outliers”, namely, two (four) subjects with markedly low (high) memorizing times. Their inclusion 
weakens the background estimation results but not the results in column 5. 
Jena Economic Research Papers 2011 - 050  6 
things.  Also, the studies  do not address  whether low-ability individuals waste cognitive 
resources, since effort is insufficiently observed. 
More generally, studying the incentive-ability interaction falls short of testing the capital-labor-
production framework. As acknowledged in its  various  informal  accounts,  disciplining the 
framework requires identifying relevant cognitive, non-cognitive (personality) and motivational 
constructs,  and  structural  relationships among them.  For a specific  task,  there are likely 
numerous fixed and variable effort and ability inputs,  augmentable to various extents by 
incentives.  Further, not only objective  abilities  but also their  subjective (self-perceived) 
counterparts may affect effort and performance. 
 
 
 
 
Jena Economic Research Papers 2011 - 050  7 
Acknowledgements 
The paper’s earlier version has been circulated as Jena Economic Research Paper 2007-039. We 
thank Robert Libby and Marlys Gascho Lipe for sharing their  dataset, and Colin Camerer, 
Randall Filer, Jan Hanousek, Glenn Harrison, Robin Hogarth, Štěpán Jurajda, Jan Kmenta and 
Andreas Ortmann for helpful comments on earlier versions. Any remaining errors are our own. 
Jena Economic Research Papers 2011 - 050  8 
References 
Anderson, J.R., 2000. Cognitive Psychology and its Implications, fifth ed. Worth, New York. 
Awasthi, V.,  Pratt, J., 1990. The effects of monetary incentives on effort and decision 
performance: The role of cognitive characteristics. Accounting Review 65, 797-811. 
Bonner, S.E.,  Sprinkle, G.B., 2002.  The effects of monetary incentives on effort and task 
performance: Theories, evidence, and a framework for research. Accounting, Organizations 
& Society 27, 303-345. 
Camerer, C.F., Hogarth, R., 1999. The effects of financial incentives in experiments: A review 
and capital-labor-production framework. Journal of Risk and Uncertainty 19, 7-42. 
Deci, E., Koestner, R., Ryan, R., 1999. A meta-analytic review of experiments examining the 
effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin 125, 627-668. 
Gneezy, U., Rustichini, A., 2000. Pay enough or don’t pay at all. Quarterly Journal of Economics 
115, 791-811. 
Libby, R.,  Lipe, M.G., 1992. Incentives, effort, and the cognitive processes involved in 
accounting-related judgments. Journal of Accounting Research 30, 249-273. 
Libby, R., Luft, J., 1993. Determinants of judgment performance in accounting settings: Ability, 
knowledge, motivation, and environment. Accounting, Organizations & Society 18, 425-450. 
Palacios-Huerta, I., 2003. Learning to open Monty Hall’s doors. Experimental Economics 6, 
235-251. 
Rydval, O.,  Ortmann, A., 2004. How financial incentives and cognitive abilities affect task 
performance in laboratory settings: An illustration. Economics Letters 85, 315-320. 
Wilcox, N., 1993. Lottery choice: Incentives, complexity, and decision time. The Economic 
Journal 103, 1397-1417. 
Jena Economic Research Papers 2011 - 050  9 
Table 1: Regressions of recall performance on incentive treatment dummies and cognitive 
ability proxies.
a 
 
REGRESSOR  (1)  (2)  (3)  (4)  (5) 
intercept 
9.805***  2.913  4.483  6.367**  4.319* 
(0.651)  (2.911)  (2.812)  (2.481)  (2.441) 
$RECALL 
1.800  2.083*          
(1.113)  (1.072)          
$MEMO 
2.537**  2.530**          
(1.216)  (1.236)          
Education 
   0.323**  0.244*  0.171  0.260** 
   (0.136)  (0.135)  (0.120)  (0.116) 
Education * $RECALL 
      0.115**  0.135***  0.090** 
      (0.051)  (0.050)  (0.045) 
Education * $MEMO 
      0.119**  0.177***  0.106** 
      (0.059)  (0.053)  (0.048) 
Experience 
   3.248**  3.345***  2.469**  3.377*** 
   (1.326)  (1.284)  (1.219)  (1.010) 
Education * Experience 
   -0.137**  -0.141**  -0.111**  -0.141*** 
   (0.061)  (0.058)  (0.055)  (0.046) 
Memorizing time residuals 
            0.022*** 
            (0.0027) 
Joint significance  *  **  **  ***  *** 
# observations in 
$FLAT,$RECALL,$MEMO  41,38,38  41,38,38  41,38,38  40,35,34  41,37,33 
 
a OLS estimates with heteroskedasticity-robust standard errors  in parentheses. *,**, and *** 
denote significance at the 10%, 5% and 1% level, respectively. 
Jena Economic Research Papers 2011 - 050

A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation.

Cognitive Psychology and its Implications, fifth ed.

Determinants of judgment performance in accounting settings: Ability, knowledge, motivation, and environment.

How financial incentives and cognitive abilities affect task performance in laboratory settings: An illustration.

Incentives, effort, and the cognitive processes involved in accounting-related judgments.

Learning to open Monty Hall’s doors.

Lottery choice: Incentives, complexity, and decision time.

Pay enough or don’t pay at all.

The effects of financial incentives in experiments: A review and capital-labor-production framework.

The effects of monetary incentives on effort and task performance: Theories, evidence, and a framework for research.

The Effect of Financial Incentives and Task-specific Cognitive Abilities on Task Performance

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