Download The effect of risk aversion on effort under an incentive pay contract

The effect of risk aversion on effort under an
incentive pay contract
Master thesis Human Resource Studies
Theme: Pay for performance
Tilburg University
Author:
Gies Janssen
Anr: 275828
Bloemhof 49
6707AR, Wageningen
Internal tutor:
Dr. N.V. Zubanov
Room P1.148
Tilburg University
External tutor:
Dr. M. Verhagen
Room P1.145
Tilburg University
1
Abstract
This research explores the issue of pay for performance in the field of HRM. With agency theory as a
basis, a theoretical model is developed in order to explain the relation between risk aversion and
effort discretionally exerted by individuals under an incentive pay contract. In a situation when
greater outcome uncertainty comes with greater effort, a negative relationship is expected between
risk aversion and effort. In another situation, however, when a performance below a certain
threshold leads to heavy consequences such as loss of livelihood, the negative relationship between
risk aversion and effort is expected to be mitigated by risk-averse people working harder to try and
prevent the loss. Two experiments, corresponding to the above situations, have been developed in
which respondents (N=142) had to choose their level of effort. The results indicate a negative
association between risk aversion and effort. This effect is mitigated when a minimum amount of
output is required. This research adds to the model of Holmström (1979) which describes the
structure of an incentive pay contract under information asymmetry.
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Index
1.
Introduction..................................................................................................................................... 4
2.
Theoretical review ........................................................................................................................... 5
3.
2.1.
Incentive pay and risk aversion ............................................................................................... 5
2.2.
Theoretical model ................................................................................................................... 7
2.3.
Hypotheses. ............................................................................................................................. 9
Method .......................................................................................................................................... 11
3.1.
The sample. ........................................................................................................................... 11
3.2.
Instruments ........................................................................................................................... 12
4.
Results ........................................................................................................................................... 13
5.
Discussion ...................................................................................................................................... 16
6.
Literature ....................................................................................................................................... 21
Appendix 1: RP index ............................................................................................................................. 24
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1. Introduction
Although the issue of pay for performance (or incentive pay) has received much attention in
economic literature (Lazear, 2000a), it is a relatively underexposed subject in human resource
management. Theories exist in economics that attempt to explain the existence of incentive pay and
its effects on performance. One such theory is summarized in the model of Holmström (1979), in
which a contract whereby the wage is determined as a function of output emerges as an optimal way
of incentivizing the worker to perform in the absence of close monitoring. In this model, the worker’s
total pay consists of two parts: the first is a fraction of the output they produce, and the second is
the flat wage independent of output. The first part acts to motivate the worker to exert effort to
produce more output, whereas the second part serves as a guarantee to the worker since the output
is typically uncertain. The empirical study of U.S. factory workers by Lazear (2000b) has shown large
positive effects of incentive pay on performance as compared to the flat pay system.
Still, there are many aspects of incentive pay to be further investigated (Lazear, 2000a). Given a great
variety of implementations of incentive pay, it is interesting to study factors contributing to the
effectiveness of such pay system. One such factor is individual attitudes to risk. Previous research has
found that more risk-averse employees prefer fixed salary, whereas less risk-averse ones increasingly
prefer incentive-based pay schemes (Cable & Judge, 1994; Deckop, Merriman & Blau, 2004). Apart
from workers with different attitudes to risk self-selecting into different pay schemes, another
interesting question to explore is the effect of individual risk aversion on effort given the incentive
pay system. This will be our main research question. The practical relevance of this question is
obvious: to the extent that risk aversion determines the chosen level of effort under a given pay
system, performance outcomes will depend on employees’ individual characteristics over and above
the pay system’s configuration. Selecting workers with certain attitudes to risk could thus help
further improve performance. We also hope for this research to contribute to the academic debate
on the effectiveness of incentive pay, by testing empirically one simple extension of the classical
incentive pay model of Holmström (1979).
The second issue we explore in this study is whether the negative link between risk aversion and
effort can be mitigated by setting a minimum output level hitting below which leads to a great loss,
for instance, the loss of employment or livelihood. It turns out that, while more risk averse
individuals do exert lower effort under a given incentive pay contract, setting a reasonable minimum
output level mitigates this negative relationship.
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Our data come from a sample of 142 respondents. We measure their risk aversion by means of a
questionnaire and collect their responses as to the level of output they would choose in two
hypothetical situations under an incentive pay agreement: one with and one without the minimum
performance level. This paper consists of three sections. In the first section, various underlying
theories are used to explain the relationships between the concepts of risk aversion, effort and
incentive pay. The second section develops empirically testable hypotheses based on the first
section’s theoretical exposition. The third section explains our empirical method and discusses the
results.
2. Theoretical review
2.1. Incentive pay and risk aversion
Incentive pay is a shorthand for a wage scheme in which part of the total wage is a function of
performance. Agency theory which is applied to analyzing the relationship between two parties with
interests that do not correspond (Baiman, 1990), provides a rationale for incentive pay. There is an
agent and a principle whose outcomes depend on each other’s actions. The principle wants the agent
to act in the principal’s best interest, but cannot fully monitor his actions. To overcome the problem
of information asymmetry, incentive contracts are used to align the actions of the agents with the
interest of the principle (Holmström, 1979).
The study of Holmström (1979) models a situation in which principal and agent interact so that the
agent undertakes to produce certain output and the principal promises to pay him a salary. If the
principal had full information on the agent’s actions, or effort, an efficient wage contract could be
drawn paying per unit of the observed effort its marginal product. In most real-life situations,
however, the principal cannot fully monitor the agent’s actions, hence actions cannot be contracted
upon. The feasible option here is to contract not on effort but on the outcomes of the agent’s
actions. This is less efficient than contracting on effort since, because output is not a perfect signal of
effort, the agent will require a premium to bear the risk of failing to achieve an outcome
commensurate with his effort. Still, such a contract is more efficient than a flat pay, since when the
pay is flat the agent has no incentive at all to exert effort.
In essence, there is agreement that monetary incentives have a positive effect on performance
outcomes, as long as the incentive plan is designed well (Lazear & Gibbs, 2008). Lazear and Gibbs
(2008) provide reasons for the positive effect of incentives on outcomes, which can be summarized
into three groups. First, the response to incentives by employees tends to be strong. An incentive
plan with bad configuration might result in agents exerting effort in order to produce output which is
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in their best interest, but which is undesirable for the principle. The caveat in this argument is that
people tend to underestimate the influence of environmental factors, while in fact environmental
factors are major determinants for stimulating actions by employees.
Second, an employee might exhibit intrinsic motivation to perform a certain job. However, this
intrinsic motivation might not cause the employee to perform the job in such a way that is beneficial
to the employer (Baiman, 1990). For example, an employee can be intrinsically driven by
perfectionism on his or her job. Therefore however, he or she might fail to attain targets which are
based on output produced. In this case an external motivator, like incentive pay, can point the effort
of the employee to the direction that is preferred by the employer.
Third, a structure of pay for performance has an effect on other HR practices. For instance self
selection occurs, where employees that are risk averse by nature, prefer fixed pay over variable pay
(Cable & Judge, 1994), or performance pay might lead to more investments in human capital,
because the return on investment is increased (Lazear & Gibbs, 2008)
Turning to the available empirical evidence, a well-known study by Lazear (2000b) finds that by
introducing a piece rate pay, productivity among factory workers increases by 44 percent. Half of this
percentage is attributed to the incentive effect of the piece-rate scheme and the other half to self
selection. These data are a convincing indicator, for they are from the real world, rather than from
laboratory studies. This is the most striking example among numerous studies that support the
positive effect of incentive pay on performance (e.g. O’Shaughnessy, 1998; Jensen & Meckling, 1976;
Cadsby, Song & Tapon, 2007). There are however some studies that question the merely positive
effects and point out the dangers and downsides of incentive pay. Yet those studies, are mainly
aimed on problems with executives with too much influence over their own compensation schemes
(e.g. Bebchuck & Fried, 2005; Gordon, 2005; Fogarty, Magnan, Markarian & Bohdjalian, 2009), which
is a problem of a political nature. Since this study focuses on a hypothetical call center case where no
politics are present, these studies need no further consideration.
One study (Hudson and Maioli, 2010) is worth mentioning, because it points out that a problem of
incentive pay is the short-term orientation of it. For example, when brokers sell mortgages, they
receive their bonus, but the responsibility of whether one could pay his mortgage is the responsibility
of the company. One could say that in this case brokers were not responsible for problems they
caused, and that the incentive system was thus not designed correctly. This does not stand for itself,
since research by Fogarty et al. (2009) also revealed that due to difficulty in setting up the right
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performance indicators, incentives of agents were not aligned with the preferences of the principle
with the collapse of a company as a consequence. Not downplaying the problems of performance
pay, agency theory in itself provides a realistic and usable perspective on problems of cooperative
effort (Eisenhardt, 1989).
Two additional assumptions are that the agent is both risk and effort averse (Baiman, 1990). The
assumption that agents are risk averse is justified because, filling in one function at a time, they have
only limited opportunity to diversify their investments of time and effort. For principals, on the other
hand, the assumption that they are risk neutral is justified because they can invest in different
activities at the same time (Eisenhardt, 1989). Also, since principals as entrepreneurs take risks daily
in running their businesses, a more positive attitude to risk than that of employees is expected of
them.
Yet, even though agents are assumed to be risk averse, the extent to which they are will be different
per individual (Hsee & Weber, 1999; Deckop et al., 2004). In the next section we will show, that lower
score on risk aversion implies a lower level of effort. This happens because it is increasingly expensive
to pass risk to the agents who are more risk averse (MacCrimmon & Wehrung, 1986 in Eisenhardt,
1989; Cadsby et al., 2009).
2.2. Theoretical model
The model as initially developed by Holmström (1979) and later expanded by Holmström and
Milgrom (1987) treats risk as a constant factor. The article by Lundesgaard (1999) provides a less
complex variant of this model with formulae that are comparable to the ones used in this research.
The representation is as follows:
ε
With outcome as the noisy observation of effort, . Noisy as a result of the uncertainty, ε.
Uncertainty in this case is a stochastic variable, independent of effort.
In extension to this model, Cadsby, Song and Tapon (2009) have introduced risk as financial
uncertainty which is positively correlated to the amount of effort which is exerted by the agent. As a
consequence the risk averse employee will exert less effort in order to reduce his exposure to risk
(Cadsby et al., 2009). Less risk averse employee on the other hand will tolerate a higher exposure to
risk and therefore exert more effort.
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An economic model is used to explain the relation between an individual’s attitude towards risk in
association to the exertion of effort under an incentive contract. This model postulates on the model
by Cadsby et al. (2009). Consider the following model of individually produced output:
1
Here equals output produced by a certain individual, . The produced output is the only variable in
this formula which is observable to the principle (Holmström, 1979). Is the amount of effort
exerted by the individual, . For this research, output is determined by a single performance
indicator, which is sales. In a different context, alternative performance indicators can be of
relevance though. The purpose is to relate the amount of effort exerted to output produced in the
best possible way. The ratio between effort and output however is not 1:1. It is determined by ,
which is a variable where ~, σ . Is a random variable which is amongst others determined
by random fortunate or unfortunate events, like politics, economic climate, competitor’s actions and
so on (Eisenhardt, 1989). It also follows a normal distribution where ~0, σ . This same
approach to demonstrate the relation between effort and output is used by the Holmström-Milgrom
model (1987)
The employee’s expected wage depends among others on the output produced by him. The
following formula is relevant for this relation:
2
The base salary , is only needed to compensate for the minimum utility of the employee so that he
does not leave the firm (Lal & Srinivasan, 1993). The incentive part , is dependent on the output
delivered. The more output produced, the higher the total wage will be. For this research, is
assumed to be equal for all employees in the same department.
3
To maximize utility, the employee chooses to exert a certain amount of effort. This function is
determined by the expected wage, ) , minus the difficulty of effort, * , minus the cost of risk,
+. Because the random variable, , has an average of zero, it does not influence the expected wage.
Difficulty of effort is determined by , and the extent to which and employee is risk averse is
determined by - . Standard economics suggests that the disutility of effort increases quadratic with
the effort exerted. This is not based on scientific evidence, but on what is used in comparable
research (Cadsby et al, 2009; Siebert & Zubanov, 2010; Das, 1996; Lazear & Gibbs, 2008). To
compensate for the disutility of effort a certain compensation is required. For a less risk averse
employee, risk is cheaper to bear, so he can sell more effort for the same price per unit of output.
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4
max 2 ) 3 * 3 + 4 3 , 1
3 - var
2
Because the employee wants to maximize his utility, the derivative of the utility function can be used
to determine the chosen amount of effort, . The derivative has the following configuration:
5
72
4 3 , 3 2- 9: 0
78
As demonstrated by formula 5, an increase in effort is accompanied by financial uncertainty for
; <=. This corresponds to the observation of Cadsby et al. (2009) that effort and risk
exposure are positively correlated (see also formula 6).
6
4 , 2- 9:
Ceteris paribus, the chosen amount of effort , declines when the employee has a higher score on
risk aversion - (formula 6). In other words, a more risk averse employee will exert less effort since
the cost of effort increases with increased risk aversion.
2.3. Hypotheses.
Agency theory and the economic model are used to develop a theoretic foundation for this research.
This leads to the following hypotheses.
According to formula 1, a low - will result in a higher . Thus:
H1. There is a negative association between an employee’s risk aversion and his effort under
incentive contracts.
Although the first hypothesis is of main importance for this research, the data permit to investigate
another relationship as well. The first hypothesis is based on the assumption that when an employee
produces small output, there will be no consequences. In reality however, a company requires a
minimum level of output from its employees, ? . If this target is not achieved, the employee risks
being laid off, receiving no more wage.
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A ? B= 0
In order for this minimum level of output to be produced, the employee should at least exert a
chosen amount of effort which is higher the minimal expected amount of effort for the minimum
level of output to be produced. The minimal amount of effort to be exerted in order to produce at
least the minimum amount of output is determined as follows:
9
8
? 4 ?
There are however two uncertainties in the expected minimal effort. First, the individual ratio
between effort and performance, , might differ from the expected ratio, 4. Second, instead of
4 0, individual fortunate or unfortunate events might occur which result in a negative or positive
score on .
Although there is no clear theoretical foundation for what the effect will be, one of the arguments is
in prospect theory by Kahneman and Tversky (1979). This theory states that people have a tendency
to be risk averse in situations of sure gains, but risk seeking in a situation of sure loss. A situation
where minimum output is required with the penalty of losing your standard of living, provides a
situation of sure loss, which bring great disutility. In order to prevent this disutility from happening,
people are prepared to incur a greater risk, which means they are allowed to take more effort. The
following situations illustrate the difference between a person who is highly risk averse by nature,
and one who is less risk averse. For this, figure 1 should be considered. This figure presents a logical
relation between effort and utility.
Figure 1: Difference in the effort-utility relation between a situation with- and a situation without a
minimum output required.
With the presence of minimum output, the expected utility remains less than without a minimum
requirement, for the possibility of not attaining the minimum requirement remains at any effort
level. For high levels of effort the chance is smaller than for low levels of effort.
10
A highly risk averse person would normally choose a relatively low level of effort to maximize his
utility. The requirement for minimum output however, present the possibility of high disutility when
the target is not achieved. The employee does not directly determine his output, but can only choose
his effort. Because the disutility of the possibility of being laid off might be bigger than the disutility
being faced with larger financial uncertainty, the expected merely negative relation between risk
aversion and effort will at least be mitigated. (Tversky & Kahneman,1992).
The second hypothesis is:
H2. The presence of a minimum required amount of output will mitigate the negative
association between risk aversion and effort, and the average effort will be higher.
These hypotheses are tested empirically according to the method explained in the next section.
3. Method
3.1. The sample.
The initial plan for this research was to test the hypotheses by using a sample of employees from
companies where incentive pay was practiced. A total of 73 companies were asked through multiple
channels (mail, phone, website, personal connections) to participate in the research. One company
was willing to participate, but unfortunately the number of respondents (N=11) was not sufficient to
perform a regression analysis. As an alternative, a new method was developed for investigating the
expected relation between risk aversion and effort – by running a thought experiment.
The population in this research consists of roughly 300 members and members of a student
association which is connected to Wageningen University. This sample consists of students and
recent graduates. Due to legislation it is prohibited to send mass mail to large groups of people for
the purpose of for instance a questionnaire. Therefore these people were invited for participating in
the following manner. The student association works with a forum where all members are allowed.
To attract participants, a new topic was opened with an invitation to fill in the questionnaire on a
specially developed website. After two weeks the website was deactivated. The total number of
usable responses was 106. An additional sample of 59 represents a second population which consists
of friends and family. These respondents have been invited by an email with an invitation to fill in the
questionnaire on a comparable website. The number of respondents who completed the
questionnaire was 36. The most important difference between the samples is that the second sample
contains more respondents that are employed instead of studying. Since there is no significant
correlation between working or not and risk aversion (r=.082, p=.619) nor between working or not
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and effort in both situations (r1=.184, p=.275; r2=.037, p=.829), both samples are combined in order
to produce a total of N=142. The demographics of these respondents are displayed in table 1.
Table 1. Demographic characteristics (N=142)
Variable
Age
•
18-20
•
21-25
•
25-30
•
31+
Gender
•
Male
•
Female
Familiar with working at a call centre
•
Yes
•
No
Live with
•
Parents
•
Friends
•
Own
•
Partner
•
Other
Occupation
•
Yes
•
N0
Frequency
Percentage
38
70
28
6
26.8%
49.3%
19.7%
4.2%
72
70
50.7%
49.3%
40
102
28.2%
71.8%
4
48
61
14
15
2.8%
33.8%
43.0%
9.9%
10.6%
36
106
25.4%
74.6%
3.2. Instruments
We measure risk aversion with the help of the questionnaire developed by Hsee and Weber (1999)
(appendix 1). This scale was originally used to measure risk taking for amounts of money that are
appropriate for their research. To make a connection with the real wage for this sample, the scale is
adjusted to measure risk aversion for money values that resemble possible daily wages (Holt & Laury,
2002). A reasonable salary for working 8 hours at a call center would be around €80. To make
matters easy for the respondent, €100 is given as the expected gains for the uncertain choice. Hsee
and Weber (1999), call their scale the risk preference (RP) index. The RP index has a scale from 1
(most risk averse) to 8 (most risk seeking). In these seven items, choosing for the safe option in the
higher numbers results in a high score on the RP index. As for hypotheses not the RP index, but risk
aversion is relevant, the RP index is transformed as +DE <8=DBF 9 3 +H F78, which results in
a scale ranging from 1 (least risk averse) to 8 (most risk averse). A score higher than 3 on the scale for
measuring risk aversion would signify one as risk averse, because it means a choice is made for the
safe option with the lower expected outcome. The average score in this sample is 4.18, which means
the employees are typically risk averse. This corresponds to what is explained in the theory
(Wiseman & Gomez-Mejia, 1998).
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For determining the amount of effort that respondents are willing to exert, a hypothetical situation is
developed. The case is presented as follows:
“Imagine the following situation: You work in the company called Merx where you are
responsible for finding new customers. You try to do this by making phone calls to potential
customers. There is no-one to tell you what to do, so you can make as many (or as few) calls
as you like. You work eight hours a day, five days a week. Making one phone call takes exactly
five minutes, not more, and not less. Hence the maximum number of phone calls you can
make in a day is 96, but then of course you will have no breaks. With every phone call there
is 1 chance in 6 that you will acquire a new customer. This does not mean that there is
guaranteed to be one new customer with every six phone calls. You could be unlucky and
acquire no new customers during the whole day (but that's of course unlikely), or you could
be lucky and attract more than one new customer with every six calls. Your persuasive skills
are of no influence. Your base salary is €5 a day. In addition to your base salary, you will
receive €5 for every new customer.”
For testing the second hypothesis, in which a minimum effort is required, an additional situation is
framed. All respondents should experience that attaining the minimum is essential, therefore the
alternative is posed as a drastic penalty. The situation looks as follows:
“Image the same situation as in the first example, except that now you must earn at least
€40,- per day in order to afford rent, food, clothes etc. If you earn less than this, you risk
losing your home and starving. There are no alternative sources of income you can rely on.”
Before the second situation is presented, the respondent is asked to estimate how many calls he or
she would make. Hereafter the second situation is given, followed by the same question. After being
exposed to both hypothetical situations the respondents are asked to provide demographic
information reported in table 1.
4. Results
The essence of this research is to identify the effect of risk aversion on effort, under an incentive pay
contract. In table 2, the descriptive statistics and the correlation matrix for the different variables
relevant for this research are presented. As anticipated, the table shows a significant correlation
between risk aversion and effort for both situations (r1=-.330, p = .000; r2=-.286, p=.001). In addition,
the descriptive statistics shows that respondents exert more effort in the second situation than in the
first, respectively 80.82 calls versus 75.62 calls. A paired sample T test reveals significant difference
between the two situations (t=-5.544, p<.000), which means that the respondents in general make
more phone calls when a minimum output of €40 is required. The correlation between risk aversion
and gender, suggest that men are less risk averse than women (r=-.196, p=.019). This finding is in
13
correspondence with for instance literature by Chauvin and Ash (1994). Respondents who are
familiar with working at a call centre prove to be more risk averse (r=.173, p=.040). Incentive based
system as described might - in an adjusted way - be applied in the more Angle Saxon countries. If that
were the case for this sample, an opposite effect of self selection would have occurred. Since, to our
knowledge, most call centers either apply a more mitigated form of incentive pay or a fixed salary,
this argument is not valid. Since there is no theoretical foundation for this correlation, there is no
reason to assume a causal relation between risk aversion and familiarity with working in a call centre.
The positive correlation between age and effort for situation 1 (r=.190, p=.024) indicates that
without a minimum output required, older respondents choose to exert more effort. A logical
explanation could be that older respondents are familiar with, and thus require, a higher standard of
living and thus aim for a higher output.
Table 2: Descriptive statistics and correlations (N=142)
1. Risk aversion
2. Effort situation 1
3. Effort situation 2
Mean
4.18
s.d.
1.21
75.65
14.70
-.330
80.82
11.85
-.286
23.64
4. Age
.49
5. Gender (0=female, 1=male)
6. Familiar working at a call centre
.72
(0=no, 1=yes)
.25
7 Occupation (0=no, 1=yes)
***
. Significant at p<.01 (two-tailed tests).
**
. Significant at p<.05
1
2
3
4
5
6
***
***
*
.669
**
.116
5.54
.010
.502
.451
**
.190
-.196
**
.173
.068
-.136
.029
-.110
.437
.153
.081
.101
.128
-.024
.428
***
-.009
.105
-.031
To determine whether an inverse of the variable ‘effort’ is most suitable for regression analysis or for
instance a linear form should suffice, a graph is made (figure 2). The line is drawn through the
average effort for each score on risk aversion. The frequencies of scores on risk aversion taken into
account, both lines indicate that simple linear regression is the method that would produce results
which correspond best with the situation. For both regression analyses, control variables are
incorporated to determine whether a second model would provide better information. The change in
expanatory power is singificant for the first model, but is no longer significant when control variables
are included, for both situation 1 and situation 2 (table 3).
14
Figure 2: Line through average effort for each score on risk aversion.
We now proceed with the regression analysis. The first hypothesis is to test wheter there is a
negative association between an individual’s risk aversion and his chosen amount of effort. The
regression analysis provides a significant negative standardized beta (β =-.330, p =.000), which means
there is a negative association between risk aversion and effort. H1 is therefore confirmed.
Table 3: Results multiple regression analysis
Independent variable
Risk aversion
Age
Gender (0=female, 1=male)
Familiar with working at a
call centre (0=no, 1=yes)
Occupation (0=no, 1=yes)
Constant
2
Adjusted R
F Change
***
. Significant at p<.01
**
. Significant at p<.05
1
# calls situation 1
***
-.330
2
# calls situation 1
***
-.333
-.169
-.025
3
# calls situation 2
***
-.286
-.072
.060
***
92.369
***
.102
***
17.063
***
83.489
.124
1.858
4
# calls situation 2
***
-.306
.074
-.054
-.052
.120
***
92.520
***
.075
***
12.465
***
90.416
.080
1.176
As given in the theoretical model it is explained that when a minimum amount of output is required,
the negative assiociation between risk aversion and effort should at least be mitigated. Regression
15
analysis for situation 2 display that a negative assocation between risk aversion and effort exists, but
that this relation is weaker than in situation 1 (β =-.286, p =.001). H2 is therefore confirmed. To give
an indication of the effect of risk aversion on effort for this sample consider the following. For the
first situation an increase of one standard deviation in risk aversion, results in decrease in effort of
just over 5%. In the second situation the decrease equals just over 3.5%. Ceteris paribus, scoring one
standard deviation lower on less risk aversion would mean an increase in effort of 5% for the
situation without a minimum output and 3,5% increase for the situation with a minimum
requirement of €40.
5. Discussion
This paper has explored a relatively new area in the field of HRM, which is pay for performance. The
way in which this research is done, by using a theoretical model to support hypothesis, has been
acknowledged to increase the strength of the study (Guest, 2001). The purpose of this research is to
discover whether employees working under incentive contracts choose to exert less effort when they
are more averse towards risk. In addition we investigate whether this effect will be mitigated when a
minimum amount of output is required. We derive hypotheses regarding the behavior of individuals
under these two setups from relevant theories, and then test them by means of a regression analysis
applied to the survey run among mainly students and recent graduates.
Our results show that both hypotheses are confirmed. This indicates that in general there is a
negative association between risk aversion and effort (H1). When a minimum amount of output is
required, the negative effect of risk aversion on effort holds, but in a more mitigated form. Also there
will be a general increase in the chosen amount of effort (H2). The outcome of the first hypothesis is
in line with the laboratory study which has been done by Cadsby et al. (2009). To our knowledge the
testing of the second hypothesis is the first in its kind and can therefore not be compared to existing
empirical studies. Setting a minimum boundary for output in incentive contracts mitigates the
negative effect of risk aversion hence this provides a new area for research.
Previous research has indicated that individual attitudes towards risk differ per individual and per
situation (e.g. Hsee & Weber, 1999). In general most people are risk averse, but the extent to which
they are, differs. Agency theory is based on the assumption that the agent is both effort and risk
averse (Baiman, 1990), but as any individual he wants to maximize his utility. In order to maximize
output as required by the principal, incentive contracts are used to align the agent’s actions with the
principal’s goals (Jensen & Meckling, 1976).
This research indicates that differences in individual attitudes toward risk have a direct influence on
the amount of effort which the agent chooses to exert, when incentives are used to align actions of
16
the agent with the principal’s requirements. The consequence is that incentive contracts prove to be
more effective when agents are less risk averse.
A figure 2, it is noticeable that in the case of extreme risk aversion (score of 7), the amount of effort
is higher than for a slightly less risk averse person (score of 6). One logical explanation could be that
people who are extremely risk averse are also extremely cautious not to lose their job. Even though
this has not been mentioned in situation 1, people could have developed their own assumptions
when answering the question. Second, the number of respondents with a score of 7 on risk aversion
is only six. This small number could also be the reason for the bias.
Looking at the regression in general, there could be an additional explanation for why people exert
more effort when a minimum amount of output is required. The argument can be found in goal
setting theory, for the requirement of minimal output offers a goal. The theory indicates that people
exert more effort when aim to attain a goal (Locke & Latham, 1984, 1990a as cited in Latham &
Locke, 1991). This effect can manifest itself apart from the effects of increased financial uncertainty
and the possible consequences for not producing the minimal effect. For this situation though, it is
unlikely, that the existence of a goal is the only reason for why more effort is exerted, for with higher
risk aversion, the difference in effort for both situations increases (figure 3). With the existence of a
goal as the only cause for more effort in when a minimum output is required, the difference between
both situations would not increase with an increase in risk aversion. Also, the goal in this situation is
€40. The expected amount of effort to be exerted should thus be: (€40 - €5) / €5 = 8 successes, which
on average requires 8 * 6 = 48 calls. Even in the situation with no required minimum this target is
easily achieved, which means that the mere existence of a goal, does probably not influence the
amount of effort in this case.
Would there be a minimum requirement of say €70 euro’s, than the expected amount of phone calls
would be 78. In this example, the target would be challenging, which might cause the effect of risk
aversion on effort to be mitigated even further than as displayed in the second situation (figure 3).
17
Figure 3: regression line for the effect of risk aversion on effort
This research provides two practical implications for principals who control a workforce which works
under incentive based contracts. The first implication stems from the first part of the research, which
indicates that risk averse employees do exert less effort than their more risk loving coworkers. For
the selection of new employees, the principal should test the extent to which the agent is risk averse,
because it is a good indicator of the amount of effort that will be exerted. Research by Holt and Laury
(2002) indicated that risk aversion increases when the amount of money at stake is raised. The
practical implication of this is that especially for employees who have to face uncertainties where
large amounts of money are involved, it is essential that their attitude towards risk is not on the
extreme negative end. As far as this research concerns, ceteris paribus, the highest performance will
be achieved by risk loving employees. It is evident that in practice factors like politics, short term
orientation and greed play a part (Hudson & Maioli, 2010).
Second, because there’s an increase in effort in general – especially for the more risk averse – and
because the principal does not always have the luxury of choice, the principal should set a minimum
level of output which has to be produced by the agent. This target should be attainable, but
challenging, so it provides a goal. Most relevant for this research though, it generates the possibility
of loss. Losing the job by not achieving the target gives greater disutility than the disutility which
comes with bearing the uncertainty of the outcome. The disutility of uncertainty is therefore partly
countered, which results in more effort.
18
This study comes with several limitations. The fact that the sketched situation is merely hypothetical
is a disadvantage because respondents reply in the way they think they would react. When they
choose to exert a certain amount of effort they will probably have the corresponding expected
reward in mind, but there is no real reward in the given situation. The advantage of this method is
that the abstract concept of effort is easy to measure, because the only relevant variable is the
number of phone calls. If the situation were real, one would also have to incorporate other aspects
such as quality differences and commercial capability differences between employees, which could
cause difficulty in the measurement of effort. A second limitation is in the measurement of risk
aversion. This however is inherent to one time measurement of the concept, since it could be
different in another situation (Kahneman & Tversky, 1979; Hsee & Weber, 1999). Because the
questionnaire began with the measurement of risk aversion the state was as neutral as possible, so
respondents would not be confronted with potential loss or potential gains that would cause
additional bias. A third limitation is the question of generalizability as a consequence of homogeneity
of the sample on several demographic characteristics. All respondents are well educated, relatively
young and born and raised in the Netherlands. Future research should evaluate whether comparable
results will be found for other samples. A special focus should be placed on either age or standard of
living, for it seems to result in lower levels of risk aversion. This could have to do with the relatively
low amounts of money which was at stake in this questionnaire, but our data provide no definite
answer to that question.
An additional interesting issue for future research would be to test this hypothesis in practice. Since
we couldn’t manage to find enough respondents in the given time and since results by Cadsby et al.
(2009) are based on experiments, the ultimate challenge would be to test these hypotheses in the
real world. Both in the hypothetical and the experimental environment the given situation in which
testing takes place is controlled. In a natural environment, self selection would most likely already
have occurred (Cable & Judge, 1994). In addition there will be many other determinants for effort,
for instance locus of control (Cable & Judge, 1994), intrinsic motivation and stress, which could alter
the investigated relation (Cadsby et al. 2009).
Putting this research in a broader perspective, evidence is provided that an individual’s attitude
towards risk is an apparent extension to the classical incentive pay model by Holmström (1979),
because it is an important determinant in the optimal use of incentive contracts. The initial model
defines risk as an additive error term independent of effort. In addition to the additive term, this
research also defines risk as a term which is positively related to effort. An example of this logic is
19
given in the hypothetical case as described in the method section, but the logic can be applied to
many other situations. Imagine a simplified situation of for instance a banker selling mortgages. Let
us say there is a given chance of selling a mortgage given the banker’s ability. Reaching more
potential customers means putting more effort in his work. By calling few customers, the banker will
earn little, but variance is small as well. When reaching out to more customers the expected earnings
are higher, but variance – or uncertainty – also increases.
A general issue of consideration lies in context of generalizing these results. Although low risk
aversion results in more effort, there’s also the danger of greed and recklessness (Hellwig, 2009).
Worth mentioning is that excessive risk taking is seen as one of the causes for the financial crisis. The
practical implication is that although low risk aversion results in more effort, other characteristics,
like morality and long term orientation are important to prevent excesses in the system (Hudson &
Maioli, 2010). The final conclusion is that low risk aversion in itself is no guarantee for better (long
term) performance, but under the right conditions, it is an important positive contribution to both
the employee’s effort and his output.
Acknowledgement
I would not have been able to complete this research without the help of Nick Zubanov and Marcel
van Assen. I thank them for their great support and the fact that they would always take time to
support me when needed. I thank Marinus Verhagen for his willingness to be the second commenter
and assessor. In addition I thank the correspondents of for participating in this research.
20
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Appendix 1: RP index
Item
Choose between option A or B
1
A 100% chance to receive €20
B
50% chance to receive €200 if heads or €0
2
A 100% chance to receive €40
B
50% chance to receive €200 if heads or €0
3
A 100% chance to receive €60
B
50% chance to receive €200 if heads or €0
4
A 100% chance to receive €80
B
50% chance to receive €200 if heads or €0
5
A 100% chance to receive €100
B
50% chance to receive €200 if heads or €0
6
A 100% chance to receive €120
B
50% chance to receive €200 if heads or €0
7
A 100% chance to receive €140
B
50% chance to receive €200 if heads or €0
Scale for measuring risk aversion (adjusted variant of Hsee & Weber, 1999).
24