Review of Behavioral Economics, 2018, 5: 61–84
Comparing Female and Male Response
to Financial Incentives and Empathy
Nudging in an Environmental Context
Natalia V. Czap1, Hans J. Czap1, Marianna Khachaturyan2and
Mark E. Burbach3∗
1Department of Social Sciences (Economics) and BEEP Lab, University of
2Independent Researcher, Brazil and BEEP Lab research fellow
Conservation & Survey Division, School of Natural Resources, University of
In the environmental context the combination of ﬁnancial and
non-ﬁnancial incentives (speciﬁcally, empathy nudging) has been
shown to be more eﬀective than either of them individually (Czap
et al., 2016). We investigate whether there are gender diﬀerences
in the eﬀectiveness of ﬁnancial and non-ﬁnancial incentives by
using data from a framed laboratory experiment on environmental
conservation behavior. Speciﬁcally, we compare the change in
conservation eﬀorts of females and males in response to ﬁnancial
incentives and empathy nudging applied separately and simulta-
neously. Our ﬁndings show that ﬁnancial incentives aﬀects males
more than females, while empathy nudging aﬀects only females.
The combination of incentive and nudge lead to a synergetic eﬀect
for females, but not for males. This implies that policy makers can
increase the eﬀectiveness of environmental policy by accounting for
these gender diﬀerences, especially as the number of farms headed
by females in the US increases.
Gender diﬀerences, Environmental behavior, Behavioral economics,
Experimental economics, Empathy nudging, Financial incentives
JEL Codes: C91, D91, Q2, Q5, J16
The authors gratefully acknowledge the funding from the US Department of Agriculture,
National Institute of Food and Agriculture, Policy Research Centers Grant Program (award
ISSN 2326-6198; DOI 10.1561/105.00000079
Supplementary material available from:
©2018 N. V. Czap, H. J. Czap, M. Khachaturyan and M. E. Burbach
62 Natalia V. Czap et al.
From a traditional, and perhaps still mainstream, economic theory perspective
ﬁnancial incentives are the most eﬀective tool for encouraging economic agents
to perform desired actions. In practice a number of environmental campaigns
attempt to inﬂuence behavior by focusing on ﬁnancial incentives (Evans et al.,
2013). In the environmental context this is reﬂected by the increased push away
from command-and-control regulations to emissions charges and cap-and-trade
schemes. The empirical evidence suggests that these market-based approaches
are more cost eﬀective than command-and-control regulation (e.g., Seskin
et al., 1983; Spoﬀord, 1984;
Krupnick, 1986). The prevalence of monetary
incentives in public policy may be due to the majority of such policies being
designed by men, with the heavy inﬂuence of economists, who assume that their
target individual is homo economicus whose behavior is gender-neutral. In the
spheres where an eﬃcient well-functioning market is achievable, such incentives
and this assumption are reasonable. In case of environmental and resource
economics such well-functioning markets are rare (Schubert, 2017). Moreover,
there are situations when negative and positive non-monetary feedback is not
only cheaper, but also simpler to implement than monetary rewards
or monitoring (Dragone et al., 2017). In addition, it has been shown (e.g.,
Steg et al., 2014) that normative considerations are an important predictor of
pro-environmental behavior. Here the question arises how far non-pecuniary
incentives and soft nudges can substitute for potentially costly pecuniary
incentive-based schemes or, if not substitute, how far these incentives and
nudging can augment pecuniary incentive schemes.
In addition to the need to better understand the role of non-pecuniary
incentives augmenting pecuniary incentives, gender diﬀerences in responding
to these incentives are becoming more relevant as there are more female farm
operators than ever before. Speciﬁcally, even though currently the farming
landscape is dominated by male principal operators, the number of female
principal operators is growing. The share of the USA farms headed by women
increased from 5.2% to 13.9% between 1978 and 2007 (Hoppe and Korb, 2013).
The total number of women operators in the US, principal and secondary, was
# 2012-70002-19387). We want to thank Prof. Emeritus Gary D. Lynne for the many
illuminating and thought-provoking conversations we had on the metaeconomic framework
and dual-interest theory, for his mentorship and support, for his instrumental help in
attracting funding for the project and developing the experimental framework. We are very
grateful to Shannon Moncure (who left this world way too early) and Stephanie Kennedy
for their exceptional assistance in administering the experiment. Furthermore, we thank
Darin Dolberg for technical support.
Spoﬀord (1984) estimates that in the Lower Delaware Valley the command-and-control
approach was up to 22 times more expensive than the least cost method. Other studies
have found smaller diﬀerences, typically in the range of 30% to 600% (Tietenberg and Lewis,
Financial Incentives and Empathy Nudging in an Environmental Context 63
about 1 million according to the 2007 census, out of which about 300,000 were
principal operators (Hoppe and Korb, 2013). Women tend to head smaller
farms and they are disproportionally more likely to operate a sustainable
agriculture than a conventional farm (Fremstad and Paul, 2016). In a US
Department of Agriculture, Economic Research Service report Bigelow et al.
(2016, Fig. 5 on p. 8) state that in 2014 across the 48 contiguous States, 54%
of cropland and 28% of pastureland was rented out, which underlines the need
for gender diﬀerence research not only for operators, but for landowners in
general (p. 37): “Given the expansive role of land ownership and landlord-
tenant relations in the agricultural economy, an analysis of how male and
female landlords diﬀer provides new insights to policymakers aiming to level
the playing ﬁeld across diﬀerent groups of agricultural stakeholders.” These
developments warrant an investigation as to whether one type of incentive is
more eﬀective for one gender versus another and whether a combination of
incentives approaches is in order.
In this paper we experimentally investigate whether there are gender
diﬀerences in the responses to ﬁnancial incentives, empathy nudging, and a
combination of both. We deﬁne empathy as the ability to put oneself into
the shoes of others, imagining and experiencing their feelings. “Nudging for
empathy” implies an invitation to “walk in my shoes” or to “walk in the
shoes of others”. As such, empathy nudging is subtler than “traditional”
types of nudging (such as switching default, choice architecture, or requiring
active choice) and weaker than directly asking for a favor. We designed a
framed laboratory experiment in which the participants made an environmental
conservation decision in the context of downstream water pollution. We
compared conservation behavior in four situations: no nudging, ﬁnancial
incentives, empathy nudging, and combined ﬁnancial incentives and empathy
nudging. We ﬁnd that ﬁnancial incentives is eﬀective for both genders, while
empathy nudging is eﬀective for females, but not for males. The combination
of incentives and nudging lead to a synergetic eﬀect for females, but not for
In the next section we discuss relevant research on empathy nudging and
gender diﬀerences in response to nudging, and derive the hypotheses of this
study. In Section 3we explain the experimental design and procedures. In
Section 4we analyze the results. In the last section we conclude and discuss
the implications for environmental policy.
2 Previous Research and Study Hypotheses
Findings from behavioral economics and psychology suggest that when it
comes to changing behavior, small, low-cost changes can make lasting and
signiﬁcant impacts on individual decisions and the eﬀectiveness of public
64 Natalia V. Czap et al.
policies. Several national governments recognized the power of such nudges
and started to implement them in their decisions. For example, in 2010
the UK government created the Behavioral Insights Team,
and in 2014 the
US government established the Social and Behavioral Sciences Team.
Executive Order issued by President Obama on September 15, 2015 titled
“Using Behavioral Science Insights to Better Serve the American People” advised
governmental agencies on how to use these insights in policies. The Joint
Research Center of the European Commission published a comprehensive
report in 2016 titled “Behavioural Insights Applied to Policy: Overview across
32 European countries”
that concludes that “systematic application of BIs
[behavioral insights] throughout the policy cycle can advance evidence-based
policy-making” (p. 2). As a result, nudging has gained traction as a publicly
accepted and supported approach to improve policy outcomes in, among others,
environmental, health, and ﬁnancial contexts.
Numerous papers show that nudges are eﬀective in changing behavior (e.g.,
Gneezy and Rustichini 2000a,b; Fryer et al., 2008; Gneezy et al., 2011; Marteau
et al., 2011; Clark et al., 2014; Lanzini and Thøgersen, 2014; Strohacker et al.,
2014; Czap et al., 2015, 2016; Chang et al., 2016; Jalava et al., 2015). However,
the change is not always in the expected
desired direction, as exempliﬁed
by the research of Gneezy and Rustichini (2000a,b), Gneezy et al. (2011),
and Sudarshan (2017) who demonstrated that when there are both ﬁnancial
incentives and non-ﬁnancial nudges, ﬁnancial incentives can crowd out intrinsic
motivation or non-pecuniary nudges and, thus, can result in a decrease in
the desired behavior rather than an increase. Along similar lines Noussair
and Tucker (2005, p. 658) argue that non-monetary sanctions can substitute
monetary sanctions “at least in some populations and in the short run”. A
number of recent studies (e.g., Bolderdijk et al., 2013; Evans et al., 2013; Steg
et al., 2014; Steinhorst et al., 2015) presented evidence that there are negative
consequences of using monetary framing in the context of pro-environmental
behavior. In some cases the ﬁnancial incentive, such as the introduction of
a small fee for a shopping bag, aﬀects only the individuals who are already
exhibiting desired behavior (for example, they choose the reusable bags more
often), while having no eﬀect on non-users (Rivers et al., 2017).
Empathy nudging has only recently garnered attention in the economics
literature. Much of the past research on empathy has been in sociology and
psychology. Batson and Ahmad (2001), for example, demonstrate that it is
possible to induce empathy by having the subjects read a note from another
individual and then exploring whether the subject was able to imagine how
the sender felt. Schultz (2000) induces empathy by instructing the subjects to
2Also known as the Nudge Unit: http://www.behaviouralinsights.co.uk/.
The team ceased to exist when the new administration of President Trump came to
the White House.
Financial Incentives and Empathy Nudging in an Environmental Context 65
imagine the perspective of an animal that was being harmed by environmental
pollution. He found that the subjects who received such instructions had
signiﬁcantly higher scores in biospheric environmental concerns (i.e., concerns
about the value of all living organisms) than the control subjects. Evidence
from the studies of Shelton and Rogers (1981) and Berenguer (2007) suggests
that inducing empathy can improve environmental attitudes and behavior. In
economics, empathy nudging in the environmental context has been shown to
be less eﬀective than ﬁnancial incentives (Czap et al., 2015). The combination
of ﬁnancial incentives and empathy nudging, however, had a statistically and
economically signiﬁcant impact on pro-environmental choices, compared to
each one applied individually. The ﬁnding that the combination works better
than the sum of the parts, is theoretically supported by the metaeconomic
framework and dual-interest theory (Hayes and Lynne, 2004, 2013; Lynne, 2006;
Sheeder and Lynne, 2011; Lynne, 2006) and the closely related dual-motive
theory (Cory, 2006; Tomer, 2012), which assert that individuals are motivated
not only by self-interest, but by a shared empathy-based other-interest.
To the best of our knowledge there is very little research that deals with
gender-speciﬁc diﬀerences in the eﬀectiveness of nudges. Fryer et al. (2008)
demonstrated that the introduction of ﬁnancial incentives exacerbates gender
diﬀerences by increasing male performance on a SAT-style math test, while
leaving female performance unchanged. Jalava et al. (2015) reported that
boys are only motivated to improve performance by rank-based incentives,
whereas girls also react positively to symbolic rewards. Clark et al. (2014) show
that an informational nudge signiﬁcantly increases retirement contributions
by young male employees and signiﬁcantly decreases retirement contributions
by older male employees. Females, in contrast, do not display any signiﬁcant
change in behavior. Czap et al. (2014) found that females change behavior
more in response to emotionally-based punishment for past behavior (receiving
- a frowney face) that tries to induce empathy, than males. At the same
time, neither males nor females respond much to punishment in the form of
monetary ﬁnes, suggesting potential retaliation.
This paper expands this analysis by looking into gender speciﬁc diﬀerences
in empathy and ﬁnancial nudges. As the number of female operators in the
US increases (Hoppe and Korb, 2013), understanding these diﬀerences will
help environmental policy-makers better tailor the policy design and improve
As evident from the above discussion, in addition to the scarce number of
papers, there is also inconsistent evidence on gender diﬀerences, suggesting
that any gender diﬀerences observed are highly context and nudge dependent.
Given this situation, our paper contributes to this literature by looking at the
evidence from a framed (in the environmental context) laboratory experiment
on gender diﬀerences in the eﬀectiveness of ﬁnancial incentives and empathy
nudging. In the following paragraphs we develop the testable hypotheses.
66 Natalia V. Czap et al.
First, we will investigate the eﬀectiveness of a ﬁnancial incentive in compar-
ison to an empathy nudge for each gender separately. In environmental studies
females are found to be more environmentally concerned than males (e.g.,
Mohai, 1992; Zelezny et al., 2000; Caiazza and Barrett, 2003; Xiao and Dunlap,
2007; Knez et al., 2013). However, such concern may not necessarily result in
behavioral diﬀerences: Luzar and Cosse (1998), for instance, did not ﬁnd a
signiﬁcant gender diﬀerence in the willingness to pay for rural water quality.
Khachaturyan and Czap (2016) show that in laboratory experiments gender
diﬀerences in pro-environmental behavior depend on framing and decision
context. Following that we will test:
In environmental decisions, the relative eﬀectiveness of em-
pathy nudging and ﬁnancial incentives depends on gender.
Using fMRI recording, Spreckelmeyer et al. (2009) found that for men the
expectation of a monetary reward activated a wider network of mesolimbic
brain regions than the expectation of a social reward. For women the prospect
of either reward activated identical brain regions. Social stereotypes posit
that women are more selﬂess and more concerned with others (Eagly and
Steﬀen, 1984), that women are more empathetic (Lennon and Eisenberg, 1987;
Han et al., 2008
), whereas men are more rational (Fischer, 1993). According
to Strauss (2004), the stereotypical expectation that women are empathetic is
based on the perceived existence of “women’s intuition”. Eckel et al. (2008) in
their review of the studies on gender diﬀerences in economic decisions establish
that women are overall more egalitarian compared to men. Eckel et al. (2008)
also conclude that even though gender-based stereotyping exists, “gender
stereotype conformity” (p. 434) is not always present. As mentioned above,
Czap et al. (2014) found that negative emotional feedback aimed at inducing
empathy (via sending a frowney emoticon after the decision is made) is more
eﬀective than negative monetary feedback (ﬁne) for both males and females in
the context of environmental decisions. In this paper we are considering the
eﬀect of empathy nudging and ﬁnancial incentives applied before the decision
is made and we will test whether:
Males are motivated more by ﬁnancial incentives than by
Females are motivated more by empathy nudging than by
Following the dual-interest theory (Lynne, 2006; Lynne et al., 2016), each
type of nudging appeals to diﬀerent interests, thus, it is plausible that:
Both females and males are motivated more by a combination
of empathy nudging and ﬁnancial incentives than by either individual nudge.
Financial Incentives and Empathy Nudging in an Environmental Context 67
Next, we compare the diﬀerences in impact of ﬁnancial incentives and
empathy nudging between genders. Stereotypically females are considered to
be more empathetic than males. However, one should be cautious as gender
diﬀerences in empathy could be a result of conforming to stereotypes, social
desirability, and expectations. According to Brody (1997, p. 370), “stereotypes
may generally reﬂect reality, partially because they help to shape reality”.
Strauss (2004) argues that women acquire the self-concept of being more
empathetic which, consequentially, aﬀects their behavior. Studies that ﬁnd
women to be more empathetic than men are typically based on self-reported
measures (Eisenberg and Lennon, 1983; Schieman and van Gundy, 2000;
Goldenfeld et al., 2005; Toussaint and Webb, 2005; Baron-Cohen, 2009), in
which case there can be stereotype-conﬁrming bias (Karniol et al., 1998) since
both males and females are aware of the stereotype of females as being more
emotional and more caring than males. According to Ickes et al. (2000),
gender diﬀerences in empathy are found in two cases; ﬁrst, when subjects know
they are being evaluated on empathy and, secondly, when “empathy-relevant
gender role expectations and obligations are made salient” (p. 95). Rueckert
and Naybar (2008) suggested a possible neural basis for gender diﬀerences in
empathy based on their study of the correlation between the Levy Chimeric
Faces Task and Mehrabian and Epstein Empathy Questionnaire. Knickmeyer
et al. (2006) found fetal testosterone to be related to empathetic behaviors
among their 4-year old female subjects, suggesting the existence of gender
diﬀerences. Fukushima and Hiraki (2006) used electroencephalography and
reported signiﬁcant gender diﬀerences in neural activity: females expressed
more empathy towards another person, who was experiencing a negative
outcome in a gambling game than males. In the fMRI study by Singer et al.
(2006) both females and males displayed activation in pain-related brain areas
toward a fair player receiving an electric shock, while only females display
empathy-related activation towards an unfair player. Based on these results,
we expect to ﬁnd gender diﬀerences in the response to nudging and, thus, we
In environmental decisions incentives and nudging aﬀect
According to stereotypical gender-based beliefs, it is easier to inﬂuence
women than men (Eagly and Wood, 1982). This eﬀect is even found in the
neuroimaging studies on pre-adolescents. Girls are more likely to switch
behavior in response to both monetary and social punishment than boys,
while boys are relatively more sensitive (exhibit longer FRN
reward than girls (Ding et al., 2017). Men have also been shown to prefer
competition (Niederle and Vesterlund, 2007), while women tend to shy away
68 Natalia V. Czap et al.
from it. Jalava et al. (2015) found that boys are motivated only by rank-based
incentives, while girls can be also motivated by a symbolic reward. Introducing
monetary incentives for blood donations does not aﬀect men, while it crowds
out women’s willingness to donate (Mellström and Johannesson, 2008). Czap
et al. (2014) found that negative emotional feedback inducing empathy in
females is more eﬀective than in males, while a ﬁne is counterproductive in
encouraging conservation and sharing behavior. This leads us to:
Empathy nudging has stronger impact on behavior of females
Financial incentives have stronger impact on behavior of
males than females.
The study by Czap et al. (2015) showed that the combination of both
incentives and nudging is highly eﬀective in encouraging pro-environmental
behavior. Since the expectation is that empathy nudges are more eﬀective for
females and ﬁnancial incentives are more eﬀective for males, the combination
of both should lead to a reduction in the diﬀerence between males and females:
Both genders are equally motivated by a combination of
ﬁnancial incentives and empathy nudging.
We further investigate diﬀerences in the degree of heterogeneity of the
response. From the policy-making perspective a policy tool that produces
a more homogeneous and predictable response is more attractive than one
that produces a wide range of responses. Thus, we will check whether there is
substantial variability in responses to ﬁnancial incentives and empathy nudging
between genders. Czap et al. (2014) showed that men display signiﬁcantly less
variance in terms of environmental choices. Ex-ante this leads us to expect
that we will ﬁnd a similar pattern when it comes to the impact of ﬁnancial
incentives and empathy nudging:
Males display lower variation in their response to a policy
change than females.
3 Experimental Design and Procedures
3.1 Context of the Game and the Players
We tested the hypotheses presented above using data from a framed laboratory
experiment in the context of farmers’ conservation behavior, speciﬁcally down-
stream water pollution. Downstream water pollution is a negative externality
resulting from agricultural operations by upstream farmers leading to chemical
runoﬀ and soil erosion. The downstream water users incur the social cost of
Financial Incentives and Empathy Nudging in an Environmental Context 69
pollution, as they have to clean water more thoroughly than they would have
to without pollution.
The experiment was presented as a game with two players: an Upstream
Farmer (UF) and a Downstream Water User (DWU). The UF farms upstream
and decides whether to use conservation tillage (CT) or intensive tillage (IT)
on a part or an entire plot of their land. If a farmer implements CT the levels
of soil erosion and chemical runoﬀ into the downstream river are lower than if
that farmer uses IT. The DWU, therefore, beneﬁts from CT usage upstream
since they are getting cleaner water downstream and, thus, spend less on water
cleanup. However, implementing CT is more expensive than implementing IT,
as it increases uncertainties regarding farm yields and planting and harvest
3.2 Assigning Participants to the Roles
The downstream pollution situation represents a dictator game (Kahneman
et al., 1986) in a context. Research shows that the division of the pie depends
on several factors, including the feeling of entitlement to serve as a divider
(e.g., Cherry et al., 2002; Cherry and Shogren, 2008; Oxoby and Spraggon,
2008). Typically, the feeling of entitlement is achieved by linking the divider’s
role to a superior performance on a task or a trivia quiz. Given that our
participants are making decisions in an agricultural context, we designed a
farming knowledge quiz.
The quiz was comprised of 10 questions related to
agricultural practices, technologies, and policies that tested the participants’
knowledge of basic farming issues. We had two major reasons for using a
farming quiz instead of typical trivia questions. First, many farmers have been
working on their lands for generations. As such, many farmers have a strong
sense of their right to have complete private property rights on their land and,
thus, the right to farm the way they see ﬁt. In our experiment, having earned
the position to be a farmer by showing one’s better knowledge of farming
issues might instill a feeling of entitlement in the participants to make farming
decisions in the experiment. Second, the participants, who performed better
on the farming quiz, were more likely to have a farming background and, thus,
could more easily identify with the role of a farmer.
Before the participants started working on the quiz, they were informed
that their performance on the quiz would determine their role in the subsequent
game. They were also told that those participants who performed better on
the quiz would have more control over their take-home payoﬀs. Based on
the quiz results, the participants were ranked by their performance with the
speed of quiz completion used to break the ties. The top 50% performers were
assigned the role of UF, while the rest took on the role of DWU.
70 Natalia V. Czap et al.
After the completion of the game, we asked the UF players whether they
agreed with the following statement: “Since my performance on the farming
quiz was in the top 50% and my partner’s was in the bottom 50%, it was
fair that I was playing the role of a farmer who decided on the level of CT”.
Overall, 74% of the UF players agreed to that statement, which suggests that
the manipulation worked.
3.3 Treatments and the Players’ Payoﬀs
The game consisted of 20 rounds. For the ﬁrst 10 rounds all participants
played the same game to establish a baseline of conservation behavior under
the agricultural conservation policy (referred to as Old Policy). After 10 rounds
the conservation policy changed to New Policy. For the second 10 rounds a
variation of New Policy was implemented and the participants were assigned
to one of 4 treatments: No incentives/nudging,Financial incentives,Empathy
nudging, and Empathy nudging & Financial incentives. We used “partners
matching”, meaning that the UF-DWU pair was playing together for 20 rounds.
3.3.1 Old Policy
Each farmer was told that they had 500 acres of land. The UF had to decide
how many acres of land to put under conservation. The payoﬀ to the UF
consisted of two parts: payoﬀ from farming and governmental subsidies. The
payoﬀ from farming was equal to [1500
] tokens. The size of the
governmental subsidy depended on whether the farmer’s conservation level
exceeded the “conservation compliance” level of 250 acres. If CT was equal or
greater than 250, then the subsidy was 300 tokens. If CT was lower than 250,
then the subsidy was 200 tokens. As such, only 100 tokens of the subsidy were
conditional to conservation compliance.
The payoﬀ to the DWU consisted of two parts: payoﬀ from using water
and a tax that was used to pay the farmers’ subsidy. The payoﬀ from using
water was equal to [500 + 2
]tokens. The tax was equal to a third of the
governmental subsidy. Thus, if the UF’s conservation level was equal to or
exceeded the conservation compliance level, the tax was 100. If the UF did
not comply, the tax was 66.67. The relation between the subsidy received by
the UF and the tax paid by the DWU modeled the real world in the sense
that the population pays taxes that are later used for subsidies. The subsidy
per farmer was greater than the tax per citizen.
The proﬁt-maximizing decision was for the UF to choose
= 0, resulting
in a total payoﬀ of 1700 for the UF and 433 for the DWU. If the UF chose
to adopt conservation on their entire plot of land (
= 500), then the total
payoﬀ for the UF was 800 and for the DWU was 1400. If CT was equal to the
compliance level of 250, then the total payoﬀ for the UF was 1300 and for the
DWU it was 900.
Financial Incentives and Empathy Nudging in an Environmental Context 71
3.3.2 New Policy
As mentioned above, after round 10 the participants were told the agricultural
conservation policy had changed and were provided with a new set of instruc-
tions and payoﬀs. The participant pairs were randomly assigned to one of the
In the No incentives/nudging treatment the UF received the subsidy of
300 tokens regardless of the conservation level. In the Financial incentives
treatment, the subsidy of 300 tokens was given to the UF only if their conser-
vation level was equal or exceeded the compliance level (if the conservation
was below compliance, the subsidy was not given). In the Empathy nudging
treatment, the setup and payoﬀs for the players were the same as in the No
incentives/nudging treatment (subsidy of 300 tokens regardless of conservation).
Nudging for empathy was implemented by asking the DWU to send the UF one
nudging message from a list of 12 possible messages (see the description in the
next subsection). The message was passed to the UF before they choose CT
receiving the message carried no monetary consequences for
UF. The Empathy nudging & Financial incentives treatment was a
combination of the Empathy nudging and Financial incentives treatments: the
DWU was sending a nudging message to the UF and the 300 tokens subsidy
was given to the UF conditionally on conservation compliance.
3.4 Empathy Nudging Messages
The empathy nudging messages were developed on the basis of the Interpersonal
Reactivity Index (IRI) (Davis, 1980, 1983), which takes a multidimensional
approach to empathy and includes four subscales (perspective-taking, fantasy
scale, empathetic concern, and personal distress). We used two subscales of
IRI, perspective taking and fantasy. The perspective taking subscale “assesses
the tendency to spontaneously adopt the psychological point of view of others”
(Davis, 1983, p. 113). The fantasy subscale “taps respondents’ tendencies to
transpose themselves imaginatively into the feelings and actions of ﬁctitious
characters” (Davis, 1983, p. 114). These two subscales reﬂect the idea of
empathy as feeling with the other person and imagining “oneself in the shoes”
of another person, which is necessary for us to construct the messages nudging
for empathy conservation (Lynne et al., 2016).
The original perspective taking subscale and fantasy subscale contain 7
statements each. Examples of perspective taking subscale statements are: “I
sometimes try to understand my friends better by imagining how things look
from their perspective” and “Before criticizing somebody, I try to imagine how
I would feel if I were in their place.” Examples of fantasy subscale statements
are: “I really get involved with the feelings of the characters in a novel” and
“When I am reading an interesting story or novel, I imagine how I would feel if
the events in the story were happening to me.” The ﬁrst step in developing the
72 Natalia V. Czap et al.
empathy nudging messages was choosing the key phrases from each statement.
Several statements included similar phrases such as “look at everybody’s side”
and “look at both sides of the question.” After eliminating similar phrases,
we ended up with 6 distinct key phrases. On the second step we used the 6
key phrases to write a message that the DWU could send to the UF. During
each round the DWU was choosing to send one from a list of 12 messages
(see Appendix), each starting with “Before choosing the level of CT this year,
please . . . ”. The second part of the message contained the key phrase and was
written using either personal (e.g. . .. see your decision from my point of view)
or general appeal (e.g. . .. see your decision from the DWU’s point of view).
The experiment was conducted at a major Midwestern US University. The
experimental subjects were recruited on campus via emails and ﬂyers posted
and distributed across campus. In total 400 students and members of the
community participated in the experiment, with 100 in each of the treatments.
One half of the participants were females. The average age was 26.3 years old.
About 71% of the subjects had a farmer family member and about 37% grew
up in rural areas. The experiment was computerized and administered using
the experimental software
-Tree (Fischbacher, 2007). We ran 26 sessions.
Each session lasted 60–90 minutes. The earnings in the game were in tokens.
At the end of the experiment the total amount of tokens earned was converted
into dollars at the rate of $1 = 500 tokens. The money was paid privately in
cash. The experiment was incentive-compatible with an average take-home
earning of $43.6. This amount was much higher than the average participants’
opportunity cost, which was around the minimum wage.
Participants were making decisions privately and anonymously. Their
earnings were tracked only by a 5-digit random number. First, the participants
took the farming quiz described above (see subsection 3.2). Next, they read
the instructions for Rounds 1–10 on their computer screens. They also received
a printed summary of experimental instructions and a table showing possible
payoﬀs for the UF and the DWU. The summary of instructions was read aloud
to make it public information. Next, participants were given a set of questions
checking their understanding of the instructions and ability to calculate payoﬀs.
The game did not start until all participants correctly answered the questions
and calculated the payoﬀs. At this point the participants were reminded about
their performance on the farming quiz (top 50% or bottom 50%) and got as-
signed their role (UF and DWU, respectively). After the ﬁrst 10 rounds of the
There were 8 sessions with 18, 4 with 16, 6 with 14, 4 with 12, 1 with 10, 1 with 8, and
2 with 6 participants, respectively.
8The questions are available upon request.
Financial Incentives and Empathy Nudging in an Environmental Context 73
game were completed, the participants received a new set of instructions, corre-
sponding to the appropriate treatment, for Rounds 11–20. As done previously,
they also received a summary with instructions and payoﬀs, which was again
read aloud. The UF and the DWU group stayed unchanged till the end of the
experiment. The decision of the UF was communicated to the DWU each round.
Both players knew that they were playing with the same partner. However, they
did not know any other information about the partner, including the gender.
4 Experimental Results
During the Old Policy part of the game the UF females put 204 acres (out
of 500) under conservation, compared to 198 acres by the UF males. The
levels are not statistically diﬀerent, but they are well above predictions based
on the payoﬀ-maximizing assumption, which is to place zero acres under
conservation. Since the DWU was a passive party in this game, there were
no strategic considerations for the UF to behave this way. To compare the
relative eﬀectiveness of empathy and ﬁnancial nudging by gender, we calculated
the percentage change of CT from Old Policy to each of the 4 treatments.
When the participants switched from Old Policy to No incentives/nudging, the
average CT went down by 19% for females and 10% for males (Fig. 1). This
indicates that the removal of the conservation compliance as a condition of
receiving the subsidy led, as expected, to a decrease in conservation. Financial
incentives and empathy nudging were equally eﬀective for females as compared
to conservation under Old Policy. However, for males we observed that only
ﬁnancial incentives were eﬀective. When incentives and nudging were combined,
it produced a synergetic eﬀect for females, but not for males.
To evaluate the treatment eﬀects on the absolute changes in conservation
levels, we estimated a regression model for each gender separately (Table 1)
controlling for the conservation levels before the policy change. We observed
two similarities and two diﬀerences between the reactions to nudging within a
gender. The similarities are: (1) in the absence of incentives and nudging the
average conservation eﬀort by males as well as females decreases (by 22 and 45
acres respectively), and (2) ﬁnancial incentives are eﬀective for both genders
as compared to no incentives/nudging (the coeﬃcient is statistically signiﬁcant
at 5% for both genders). The diﬀerences are: (1) for females empathy nudging
is as eﬀective as ﬁnancial incentives (
01 of the
coeﬃcients), while for males empathy nudging is not eﬀective at all; (2) for
females the combination of empathy nudging and ﬁnancial incentives is more
eﬀective than one alone (
01), while for males the combination is
more eﬀective than empathy nudging (
01), but not more eﬀective
than ﬁnancial incentives (
285). Overall these results support
Hypothesis 1(that the relative eﬀectiveness of nudges depends on gender)
74 Natalia V. Czap et al.
Financial incentives Empathy nudging Empathy nudging &
Figure 1: Percentage Change in Average Conservation in Response to the Policy Change by
Note: The numbers show the percentage change from Old Policy.
Table 1: Average Treatment Eﬀect by Gender
Intercept 12.6 6.18
Treatment 2 - Financial Incentives (
Treatment 3 - Empathy Nudging (Yes = 1) 49.8** 13.0
Treatment 4 - Empathy Nudging & Financial
Incentives(Yes = 1)
Old Policy CT†0.76*** 0.87***
Number of observations 89 111
R-squared (adjusted) 0.59 0.70
Note: †Average CT under Old Policy (control variable). Dependent variable: Average CT under
New Policy. Standard errors are in parentheses. ‡OLS regression (no heteroscedasticity according
to the Breusch-Pagan test). Signiﬁcance: **p-value <0.05; ***p-value <0.01.
and 1a (that males are motivated more by ﬁnancial incentives). We found
partial support for Hypothesis 1c (that both genders are motivated more by a
combination of incentives and nudging) and no support for 1b (that females
are motivated more by empathy nudging).
To evaluate the gender eﬀect, we estimated regression models for each
treatment separately (Table 2). The models included a gender variable (Female)
and the interaction between gender and the past behavior (Old Policy CT).
Financial Incentives and Empathy Nudging in an Environmental Context 75
Table 2: Average Gender Eﬀect by Treatment
No nudging &
incentives/ Financial Empathy Financial
Intercept 11.3 62.7 −3.05 68.0
(30.6) (20.4) (20.0) (48.1)
Female (Yes = 1) 13.5 −47.0 65.2** 73.4
(65.8) (37.9) (29.7) (60.4)
Old Policy CT †0.85*** 0.80*** 0.98*** 0.85***
(0.12) (0.10) (0.08) (0.18)
Female *Old Policy CT −0.14 0.18 −0.22* −0.24
(0.26) (0.17) (0.12) (0.22)
Number of observations 50 50 50 50
R-squared (adjusted) 0.53 0.69 0.81 0.53
Note: †Average CT under Old Policy. Dependent variable: Average CT under New Policy.
Standard errors are in parentheses. ‡OLS regression (no heteroscedasticity according to the
Breusch-Pagan test for the ﬁrst three regressions; Heteroscedasticity-robust standard errors for
empathy nudging & ﬁnancial incentives). Signiﬁcance: *p-value <0.1; **p-value <0.05; ***p-
The regression results indicate that the strongest predictor of behavior is what
the participants were doing before the policy changed, as indicated by the
highly signiﬁcant coeﬃcient in front of Old Policy CT. We found no gender
diﬀerence, neither in the No incentives/nudging nor the Financial incentives
treatments: the coeﬃcients in front of Female and the interaction term are
not statistically signiﬁcant. In the Empathy nudging treatment, we observed
that females placed 65.2 more acres of land under conservation than males.
This gender diﬀerence is both statistically and economically signiﬁcant as
the total amount of land available is 500 acres. The results also showed the
gender diﬀerence in the response to the policy change. After empathy nudging
was introduced, males continued conservation at the same level as in the
prior rounds: the coeﬃcient in front of Old Policy CT is very close to one
(0.98). For females, in contrast, the dependence on the previous policy was
lower by 0.22 (the coeﬃcient in front of Female * Old Policy CT). In the
combination of empathy nudging and ﬁnancial incentives we found that females
placed 73.4 more acres of land under conservation than the males did, which
is economically quite signiﬁcant as it represents close to 15% of available land.
However, the heteroscedasticity robust estimate is statistically insigniﬁcant. In
this treatment there was no gender diﬀerence in response to the policy change.
To summarize, we observed two similarities and one diﬀerence between the
reactions of each gender within a treatment. The similarities are: (1) in the
absence of nudging there is no statistically signiﬁcant diﬀerence in the conser-
76 Natalia V. Czap et al.
Table 3: Heterogeneity in Response to Change in Policy by Gender
No nudging &
incentives/ Financial Empathy Financial
nudging incentives nudging incentives
Female 8222 6002 4076 7358
Male 5245 3240 2267 5301
p-value of one-tail F-test 0.136 0.082 0.079 0.219
vation levels of males and females; and (2) ﬁnancial incentives is statistically
and economically eﬀective in increasing conservation and does so by a similar
degree for both genders, as evident by the similar coeﬃcients in Table 1and
the statistically insigniﬁcant diﬀerence in Table 2. The key gender diﬀerence is
that empathy nudging aﬀects females substantially more than it aﬀects males.
Overall these results oﬀer support for Hypothesis 2(that incentives/nudging
aﬀect genders diﬀerently). We also found support for Hypothesis 2a (that
empathy nudge has stronger eﬀect on females), while 2b (ﬁnancial incentives
have stronger eﬀect on males) is not supported. Hypothesis 2c is weakly
supported in the sense that the combination of incentives and nudging is
eﬀective in changing behavior for both genders.
Lastly, we compared the heterogeneity of female and male responses to a
change in policy. We cannot use the coeﬃcient of variation (which accounts
for both the standard deviation and the mean) because some of the means are
negative. Instead, we performed a one tail
-test for diﬀerence in variances.
There is some support (at 10%) that the variance of the change in conservation
level in response to the policy change by females is higher than by males in
case of ﬁnancial incentives and empathy nudging treatments (Table 3). In the
cases of no incentives/nudging and the combination of incentives and nudging
the variances are similar. Based on that, we conclude that Hypothesis 3
(males have lower variability in response to the policy change) is only weakly
supported. From a policy perspective, this is relatively good news, because
the more homogenous the behavior the easier it is to tailor public policy.
5 Conclusion and recommendations
This paper joins a very short list of papers that discuss gender diﬀerences
in response to nudges. The current paper experimentally studied nudging in
the context of agricultural policy and the impact of ﬁnancial incentives vs.
empathy nudging on conservation behavior. We found that for women ﬁnancial
Financial Incentives and Empathy Nudging in an Environmental Context 77
incentives and empathy nudging are equally eﬀective, but the combination
of the two is by far more eﬀective. For men, ﬁnancial incentives was a lot
more eﬀective than empathy nudging and the combination of the two is not
much more eﬀective than the ﬁnancial incentives alone. When it comes to the
eﬀectiveness of the nudges based on gender, we found that ﬁnancial incentives
did not result in signiﬁcantly diﬀerent outcomes between males and females,
whereas empathy nudging did – females reacted signiﬁcantly more to empathy
nudges individually as well as to the combination of the incentives and empathy
Empathy nudging is a potentially attractive tool for policy makers. With
more research and testing in the ﬁeld it can become a part of innovative
policy solutions which “seek the best of both worlds by combining pecuniary
instruments with nonpecuniary interventions” (Delaney and Jacobson, 2016,
p. 26). While the studies by Czap et al. (2015) and Czap et al. (2016) show
that on average ﬁnancial incentives is more eﬀective than empathy nudging
and the combination of incentives and nudges vastly more powerful than each
one individually, the analysis in this paper demonstrates that this is gender
dependent. Disentangling gender eﬀects is particularly important in situations
when the gender distribution of the decision makers does not correspond
to a 50 : 50 ratio. Understanding gender eﬀects is also critical when the
responses are expected to be heterogenous, such as when home-grown values,
perceived societal norms, personal predispositions, and beliefs are likely to
inﬂuence behavior. In contrast to the market context where the preferences
can be induced by ﬁnancial incentives, in social and environmental contexts
non-pecuniary factors can dominate the decisions. Currently the agricultural
industry is still dominated by male farm operators. As such the current paper
implies that the best policy is still based on ﬁnancial incentives only, or perhaps
in conjunction with empathy nudging as such nudging is quite cheap. However,
if the current trend of increased female ownership and management of farm
operations (Hoppe and Korb, 2013) in the US continues, the most eﬀective
policy design will shift to one incorporating more soft nudges, such as the
empathy nudges used in the experiment. From a practitioner’s perspective,
these nudges can be provided through letters speciﬁcally addressed at farm
operators to walk-in-the-shoes of others aﬀected by farming practices, through
education meetings in which extension oﬃcers provide verbal and non-verbal
cues to be more empathetic to the wildlife, and through local eﬀorts to build
a sense of community and belonging with the ecosystem.
78 Natalia V. Czap et al.
Appendix List of empathy nudging messages
Personal appeal General appeal
Before choosing the level of CT this year, please. . .
1. . . .
see your decision from my
point of view
7. . . .
see your decision from the
DWU’s point of view
2. . . .
understand my situation
better by imagining how your
decision looks from my perspec-
8. . . .
understand the DWU’s situ-
ation better by imagining how
your decision looks from the
3. . . .
look at both your and my
9. . . .
look at both your and the
4. . . . put yourself in my place 10. . . .
put yourself in the DWU’s
5. . . .
try to put yourself in my
shoes for a while
11. . . .
try to put yourself in the
DWU’s shoes for a while
6. . . .
imagine how you would feel
in my place
12. . . .
imagine how you would feel
in the DWU’s place
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