The effects of resource scarcity on charitable giving Financial deprivation and the childhood environment influence donations to charity

FACULTY OF ECONOMICS AND BUSINESS

Lies Polet R0263272

Thesis submitted to obtain the degree of

MASTER IN DE TOEGEPASTE ECONOMISCHE WETENSCHAPPEN: HANDELSINGENIEUR

Major Marketing

Promoter: Prof. Dr. Efthymios Altsitsiadis

Assistant: Angelos Stamos

Academic year 2014-2015

The effect of resource scarcity on charitable giving

Financial deprivation and the childhood environment influence donations to charity

Generous people helping others in need are making a wonderful gesture; however, it is still not self-evident in

society that wealthier people share their resources with people in poor countries. Pro-social behavior is linked to

life history strategy, a theory dealing with the trade-off between investment in growing and maintaining knowledge

or skills versus investment in activities related to reproduction. Features of the childhood environment partly

determine individuals’ adult life history strategies. This means people will respond differently to resource scarcity

depending on characteristics of their childhood environment. This paper details an experiment investigating the

donation behavior of people with different financial backgrounds, both financially deprived and not. The result

suggests that, people from wealthy childhood backgrounds donate higher amounts than people from poor

childhood backgrounds when feeling financially deprived.

FACULTY OF ECONOMICS AND BUSINESS

I

Acknowledgements

I would like to express my gratitude towards my promotor Prof. Dr. Efthymios Altsitsiadis

who gave me the opportunity to learn something by giving me the chance to solve problems

on my own and by only intervening when I still had difficulties. Moreover, I would like to

thank his assistant Angelos Stamos for his patience when I had difficulties with

understanding something, his rapid and efficient responses on my questions and for taking

the time necessary when we had to meet. Next, I would like to thank Mike Watson, a native

English speaker, for carefully reading my text. His corrections and suggestions improved

the language of my thesis. I also want to thank my colleagues with whom I could share

questions or problems and all the respondents who filled in my online survey to be able to

collect my data. Finally, I would like to thank my friends and family for supporting me.

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Table of Contents

Acknowledgements .............................................................................................................. I

General Introduction ............................................................................................................ 1

1 Literature ................................................................................................................... 3

1.1 Pro-social behavior ......................................................................................... 3

1.1.1 Definition............................................................................................... 3

1.1.2 Resource scarcity and pro-social behavior .......................................... 4

1.1.3 Donation behavior ................................................................................ 5

1.1.4 Relevance ............................................................................................ 5

1.2 Financial deprivation ....................................................................................... 5

1.2.1 Definition............................................................................................... 5

1.3 Life history strategy ........................................................................................ 6

1.3.1 Definition............................................................................................... 6

1.3.2 Life history strategy and financial deprivation ...................................... 7

1.3.3 Life history strategy and pro-social behavior........................................ 9

1.4 Hypothesis .................................................................................................... 10

2 Method .................................................................................................................... 12

2.1 Instruments ................................................................................................... 12

2.2 Data .............................................................................................................. 12

2.3 Participants ................................................................................................... 13

2.4 Procedure ..................................................................................................... 14

3 Results .................................................................................................................... 17

3.1 Preliminary data analysis .............................................................................. 17

3.1 Donation amounts......................................................................................... 17

3.1.1 Perceived childhood SES ................................................................... 17

3.1.2 General attitude towards donations ................................................... 20

General conclusion ........................................................................................................... 23

Appendices ....................................................................................................................... 26

List of figures ..................................................................................................................... 34

List of tables ...................................................................................................................... 35

Sources ............................................................................................................................. 36

1

General Introduction

Studies in pro-social behavior have greatly multiplied in recent years. If the terms pro-social

behavior and helping behavior sound familiar to you, you have probably heard of them

within a psychological context. Within a sociological context, the terms solidarity or solidary

behavior tend to be used more often. Economists prefer to use the terms cooperation or

cooperative behavior. However, in all three fields, people use the term altruism. An

interesting example of pro-social behavior is donation behavior; a well-known

contemporary topic. Numerous people donate to charity on a regular basis. Moreover, most

of the income of nonprofit organizations and charities comes from donations.

Consequently, it is useful to get more insight into donation behavior.

A central issue of our society today is financial security. Human beings do not want to worry

about their finances in the future. People experience financial deprivation when they feel

that their financial state is relatively inferior compared to other people. They will actually

change their moral behavior when people feel deprived. It would, thus, be of interest to

learn how financial deprivation is linked to other factors, for example, pro-social behavior.

Research has shown that deprivation of resources can create stress (Caplan & Schooler,

2007). Moreover, stress and resource deprivation threaten social engagement (Collins &

Feeney, 2004; McBride et al., 2006). Lim and Han (2003) found out that, in times of financial

crisis, something which is definitely linked to financial insecurity, it is assumed that social

life is threatened. However, a financial crisis turns out to enhance social solidarity (Kim,

2004; Lim & Han, 2003). How does donation behavior change when people feel financially

deprived? Does financial deprivation increase or decrease the size of donations? The

present study provides a more evolutionary perspective on the topic of charitable giving

combined with life history strategy; something which has received considerable research

attention because it has provided new perspectives on understanding human behavior.

To clarify the purpose of this paper, the concept of life history strategy has to be introduced.

Life history strategy has not only been useful in the study of animal behavior (Ellis,

Figueredo, Brumbach & Schlomer, 2009), it also has been important in human behavioral

ecology and child development (Belsky, Steinberg & Draper, 1991; Del Giudice, 2009).

Organisms have to allocate their time, resources and energy efficiently in order to survive

and reproduce. This theory deals with the trade-off between investment in somatic effort;

which means people, for example, invest in growing and maintaining knowledge or skills,

versus reproductive effort; which focuses on activities related to intra-sexual competition

and reproduction. In addition, features of one’s childhood partly determine the life history

strategies that adults enact later in life (Belsky et al., 1991; Kuzawa, McDade, Adair & Lee,

2010). Consequently, people respond differently to resource scarcity depending on their

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childhood experience, captured in the socio-economic status (SES) of the individual’s

early-life environment. There has been much research about the relationship between

perceived childhood SES and life history strategies. However, little research has focused

on the link between life history strategies and pro-social behavior.

The aim of this paper is to investigate donation behavior in the context of life history

strategies and financial deprivation. Pro-social behavior, such as charitable donations, will

probably differ depending on whether people use different life history strategies. This

difference in donation behavior will probably only appear when people feel financially

deprived.

This paper is divided into four sections. The first section introduces the research about the

different concepts and formulates the hypothesis. Pro-social behavior is first described in

general. After that, resource scarcity is linked to pro-social behavior. The concept is

specified further by mentioning donation behavior, a well-known example of pro-social

behavior. The discussion of the concept ends with an explanation of why pro-social

behavior is such an interesting subject to study and with the formulation of the hypothesis.

Next, the second concept, financial deprivation, is defined. The literature section ends with

the third concept, life history strategy, which is first linked to financial deprivation and then

related to pro-social behavior. The second section provides an overview of the

methodology. The first part explains which instruments are used. In addition, this method

section describes data and participants and ends with a description of the procedure used.

In the third section, the results of the experiment are discussed. The final section contains

conclusions, implications and directions for further research. It also explains how the

findings of this present study can contribute to the literature and why the results are

relevant.

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1 Literature

This first section will give an overview of some relevant, interesting research that has been

published on the topics pro-social behavior, financial deprivation and life history strategy.

1.1 Pro-social behavior

1.1.1 Definition

Batson (1998) defined pro-social behavior, which is mostly motivated by empathy, as the

broad range of actions intended to benefit one or more people other than oneself.

This kind of behavior is intriguing because it is influenced by many factors. It is suggested,

for example, that pro-social behavior increases with age. It is also very interesting to

investigate why some people behave pro-socially whilst others do not. Two possible

answers are the motives egoism and altruism. Egoism is caused by self-interest, whilst

altruism is preferring to benefit another rather than ourselves. There are a lot of forms of

pro-social behavior in our daily lives. They range from charitable donations to voluntary

work or simply helping other people. In this paper, the focus is on pro-social behavior and

more specifically on donations to charity. This can be explained with an example. Imagine

a workplace with members of work teams who have two main goals. They definitely want

to get their job done. Moreover, they like to maintain social relationships with their

colleagues. The outcome of group work may vary depending on whether the workers

handle the situation primarily in terms of task output, and then focus on social relations, or

vice versa. These workers have a mental model of their peer relations in terms of

“friendship” when they put priority on relationships with colleagues above tasks. However,

they could also hold a mental model of their peer relations in terms of “professional

colleagues”, when they think that their tasks are more important.

Does pure altruism actually exist? Is this human behavior sincere or do humans behave

differently when they are not rewarded for such behavior? Social psychologists started

focusing on the internal rewards resulting from pro-social behavior instead of only

considering the material rewards for helping others. Possible internal rewards are the warm

glow of being a moral person or the avoidance of feeling guilty. Batson (1991) and many

other empirical studies and experiments proved that true altruism does exist and is mostly

triggered by empathy.

The work of Piaget and Kohlberg gave rise to the investigation of the relationship between

the level of pro-social behavior and children’s and adolescents’ socio-cognitive

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development (Eisenberg & Fabes, 1998). Because young people are often punished by

their parents when they behave in a certain way, children will base their moral behavior on

the consequences of their own behavior. As a result, the punished behavior will be judged

to be bad. When young people grow up, they will carry forward this moral evaluation of

their behavior without questioning whether such social rules are correct or not. In late

adolescence, people are capable of basing their moral judgment on abstract ethical rules.

The subjective evaluation of a situation, including motivational and cognitive aspects,

determines the magnitude of solidarity of a given person in a given situation. This

evaluation differs from person to person and implies goals, the perception of a situation, as

well as the mental model of the relationship. The last aspect is about questioning whether

the other person is a friend, an enemy or a competitor and, also, the expectations of the

other person. People are not necessarily aware of these questions. Kurt Lewin (1936)

defined behavior as a function of person and situation. Not only personal traits, skills,

abilities or an actor’s learning history will influence this subjective evaluation of a given

situation. There are also some situational factors, for example, the presence of others in

the situation. This example is a purely situational factor; however, there are more stable

factors which appear across situations like institutional and cultural influences. Both social

psychologists and sociologists study these factors, although social psychologists

investigate the circumstances and sociologists investigate more the structural and

institutional determinants.

1.1.2 Resource scarcity and pro-social behavior

Scarcity of financial resources causes financially dissatisfied people. These people mostly

think directly about acquiring financial resources to enhance their situation (Blalock, Just &

Simon, 2007; Bowles & Park, 2005; Callan et al., 2008; Haisley, Mostafa & Loewenstein,

2008; Neumark & Postlewaite, 1998). An example of this phenomenon is the fact that

financially dissatisfied people start participating in the lottery more frequently (Blalock et

al., 2007; Callan et al., 2008; Haisley et al., 2008). Besides this, when people start feeling

unhappy and financially dissatisfied, they become egoistic and try to improve their own

situation instead of helping others; which is confirmed by the fact that people want to

acquire more financial resources in order to enhance their personal situation. If people are

worrying about themselves, their worries could keep them from helping others. Indeed, this

could even lead to people harming others. Moreover, resource scarcity may awaken

antisocial behavior that damages welfare, for example, theft. On the other hand, as was

mentioned earlier, financial crisis, which is definitely linked to scarcity of resources, could

also enhance social solidarity (Kim, 2004; Lim & Han, 2003) despite all these negative

elements related to resource scarcity. So, whether resource scarcity results in more or less

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pro-social behavior probably also depends on other factors. In this study, in a later

discussion, childhood environments will also be taken into account.

1.1.3 Donation behavior

What drives a human being to donate a sum of money to a charitable organization?

Donations can be seen as market transactions with a zero price. However, incentives for

these contributions may have adverse effects on voluntary contributions. Bénabou and

Tirole (2006) found that introducing explicit rewards for pro-social behavior could actually

discourage such behavior. This happens because others may perceive that the person is

possibly behaving pro-socially in order to get the rewards. It has actually been proven that

people behave more pro-socially when others can observe their actions because people

are concerned about how others perceive them. Besides this, there is also a significant link

between the amount donated and the probability that the amount would actually be

donated. Finally, Andreoni et al. (2011) proved that people take longer routes when leaving

a supermarket in order to avoid being asked for charitable donations.

1.1.4 Relevance

To conclude this section about pro-social behavior, some arguments why this behavior is

such an interesting subject to study are mentioned. Firstly, pro-social behavior from the

same individual varies between situations. Secondly, Ligthart (1995) proved that situational

factors can override or interact with the nature of a person even though personality reflects

pro-social behavior. Thus, the situation itself plays a major role in the pro-social behavior

story. Also, a person’s pro-social behavior not only varies depending on the situation, but

different motivations may determine that same individual’s behavior (Ross & Nisbett, 1991;

Smeesters, Warlop, Van Avermaet, Corneille & Yzerbyt, 2003; Van Lange, 2000).

1.2 Financial deprivation

1.2.1 Definition

An important goal for human beings is financial security. The way people think and feel

about their financial state is captured in the term ‘subjective financial wellbeing’. However,

people may compromise their moral behavior when they actually feel deprived. There is a

strong subjective influence, namely social comparison, on this subjective financial

wellbeing. When people feel that their financial state is relatively inferior compared to other

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people, they experience financial deprivation. Both wealthier and poorer people can feel

financially deprived. This experience may shift moral standards.

Fratik (1985) proved that the relative rank of a person’s income determines how happy and

satisfied that human being feels. The feeling of being relatively financial dissatisfied causes

stress, bitterness and anger (Wilkinson & Pickett, 2009). Moreover, it encourages people

to improve themselves (Crosby, 1976; Kawakami & Dion, 1995). As was mentioned earlier,

if people start feeling relatively financially dissatisfied, they want to acquire more financial

resources to enhance their situation (Blalock et al., 2007; Bowles & Park, 2005; Callan et

al. 2008; Haisley et al., 2008; Neumark & Postlewaite 1998). Briers (2006) proved a similar

reasoning that financially dissatisfied people start consuming caloric resources or food

energy in order to meet their financial needs. This is possibly due to the fact that money

and food are related, exchangeable resources.

Christan and Morgan (2005) argued that relative financial deprivation leads to people

decreasing saving and increasing their consumption, mostly their attention-getting

consumption. These people are just trying to reduce the gap in consumption with the other

people to whom they compare themselves. Because people do not own an inherent “scale”

for an ideal desired amount of money, they rely on others to make a judgment about their

financial situation (Bazerman, Loewenstein & White, 1992; Hsee et al., 1999).

1.3 Life history strategy

1.3.1 Definition

Organisms have to make decisions about the allocation of their time, resources and energy

in an efficient way between various tasks to survive and reproduce, favoring allocation

strategies that optimize resource use over the life course and enhance fitness. (Schaffer,

1983; Williams, 1957). The laws of thermodynamics clarify that organisms who allocate

energy for a certain task cannot allocate this energy anymore for another task. For

example, people spending time gathering food, could not use this time sleeping; people

spending effort on parenting, could not use this time to acquire new friends (Kaplan &

Gangestad, 2005; Roff, 2002). As already mentioned in the introduction, this theory deals

with a trade-off between investment in somatic effort and reproductive effort. Somatic effort

refers to an investment resulting in growing and maintaining physiological systems and

embodied capital like knowledge or skills. Reproductive effort focuses on investment in

some activities that are related to intra-sexual competition and reproduction. Kenrick and

Luce (2000) used the analogy of a bank account. Somatic effort can be compared with

building up a bank account, whilst reproductive effort is similar to spending this account in

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ways that will help to replicate the investor’s genes. In the same way that people do not

save money just to have a savings account, organisms will not invest in somatic effort just

to grow, maintain and learn. When people invest in somatic effort, they invest in future

reproduction. Humans save money now to improve their success in the future. In this way,

this trade-off between somatic and reproductive effort can be converted to a trade-off

consisting of choosing between spending resources on current reproduction or on future

reproduction. People who invest largely in reproductive effort can be categorized as people

following a faster strategy. By contrast, people investing in somatic effort, can be

categorized as people following a slower strategy.

Many researchers have found that people start decreasing spending, increasing savings

and becoming more cautious when they face resource scarcity (Carroll, Hall, & Zeldes,

1992). However, life history theory indicates that resource scarcity may produce other

responses. According to this theory, humans, and organisms in general face fundamental

trade-offs when they have to decide how they will allocate their limited energy and

resources. It provides a framework to understand and explain how, why and when people

make these trade-offs in their decisions; ranging from health decisions to economic

investments. Possible fundamental trade-offs arise, for example, when people have to

allocate energy and resources toward current versus future reproduction. So, life history

strategy actually explains how and why humans and other organisms allocate their

resources to different goals (Charnov, 1993; Daan & Tinbergen, 1997; Horn, 1978; Low,

200; Roff, 1992; Stearns, 1992). As a result, this theory has become increasingly useful in

explaining human behavior. Bearing in mind this theory, individuals can be placed along a

continuum, r to K. Low investment in a large number of offspring can be associated with r-

selected individuals. Likewise, high investment in a small number of offspring can be

associated with K-selected individuals (Promislow & Harvey, 1990). The “fast-slow”

continuum is the modern approach to this r-K continuum. These strategies consist of values

ranging from slow to fast (Figueredo et al., 2005).

1.3.2 Life history strategy and financial deprivation

Griskevicius (2013) found that when people are raised in resource-scarce environments,

they may be sensitized to adopt another life history strategy than when being raised in

resource-abundant environments. The resource availability is represented by the socio-

economic status (SES) (Belsky et al. 2012; Miller et al., 2009; Griskevicius et al., 2012). As

a consequence, lower-SES environments sensitize people to adopt a slow or fast life

history strategy, which is different from higher-SES environments. How are the features of

one’s childhood connected to adult ecologies which may lead to following slower versus

faster life courses? This interesting relationship was already briefly mentioned in the

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introduction. Features of the childhood environment partially determine individuals’ adult

life history strategies (Belsky et al., 1991; Kuzawa et al., 2010). As a consequence, people

will respond differently to resource scarcity depending on the characteristics of their

childhood environment. This environment is captured in the socio-economic status (SES)

of one’s childhood. Socio-economic status (SES) is a modern indicator of resource

availability (Simpson, Griskevicius, Kuo, Sung, & Collins, 2012). The mortality rate and the

availability of resources in the local environment are possible cues in modern human

environments. The environmental factors linked to different life history strategies are

manifested in environments by these cues (Kaplan & Gangestad, 2005; Quinlan, 2007;

Worthman & Kuzara, 2005). Humans tend to be more impulsive and will engage in more

risk-seeking behavior if they grew up in a lower SES environment. These kinds of decisions

related to reproduction, where people start using fast or slow strategies, are laden with

risks. As argued earlier, the similarity with the financial world can be highlighted once again.

In this case, the risks associated with the decisions related to reproduction are similar to

those relevant in financial decision making (E. Hill, Ross, & Low, 1997). An investor, who

starts saving money for years, risks dying without reaping the benefits of these years of

investment. Similarly, when organisms decide to delay reproduction because they choose

to invest in growth and maintenance, they may end up not reproducing at all. In contrast,

some organisms spend their money generously, which may possibly cause financial

insolvency in the future. Similarly, if organisms do not invest in somatic effort and start

reproducing too quickly, they may die before their reproductive potential has been reached.

As a consequence, a slower life history strategy can be linked to a preference for less risk

and a faster life history strategy to a preference for more risk. Moreover, humans using

faster life history strategies give in to temptations more quickly and, for example, want to

start a family sooner. Thus, people will adopt faster strategies when their early-life

environments were characterized by higher levels of unpredictability and harshness. Their

future is very uncertain, therefore, people may not live long enough to reproduce if they

delay (Ellis et al., 2009). Organisms living under these conditions do not gain much from

an investment in somatic effort because this investment could easily be wiped out due to

forces that the organisms cannot control. Therefore, such organisms start evolving a faster

strategy. By contrast, organisms living under more predictable conditions can start

investing in somatic effort because they can resist threatening ecological challenges due

to their predictability. An unpredictable environment specifically results in faster

physiological and sexual development (Belsky, Houts, & Fearon, 2010; Ellis, 2004). Faster

sexual development, in turn, results in more offspring and reduced parental investment in

each offspring. Across cultures, in environments characterized by a higher mortality rate,

people are much younger when their first child is born (Griskevicius, Delton, Robertson, &

Tybur, 2011; Low, Hazel, Parker, & Welch, 2008; Wilson & Daly, 1997). This pattern is

consistent with a ‘fast life history strategy’. By contrast, humans who grew up in a higher

9

SES environment are less impulsive, more risk averse and want to delay starting a family.

They approach temptations more slowly; their future is more stable, whereby it is possible

to adopt slow strategies, resulting in delaying reproduction and investing in the future (Ellis

et al., 2009). This results in slower physiological and sexual development, leading to fewer

offspring and a greater parental investment in each child. This pattern is consistent with a

‘slow life history strategy’.

1.3.3 Life history strategy and pro-social behavior

Slow and fast strategies were already linked to certain features. To investigate the link

between life history strategy and pro-social behavior, these features are summarized below

(see Figure 1).

Figure 1: Illustration of correlates of fast and slow life history strategies (Griskevicius V.,

Ackerman J. & Cantu S., 2013)

In the context of mating, people enacting fast life history strategies have more sexual

partners and an earlier sexual debut. With regard to parenting, they have more children

and invest less effort in each child. Moreover, fast strategies are associated with earlier

physiological development and sexual maturity. Conversely, people enacting a slow life

history strategy have less sexual partners. Their sexual debut is postponed compared to

people enacting fast life history strategies. In the context of parenting, slow strategies are

10

associated with fewer children; however, their investment in each child is higher. At the

physiological level, slower strategies correspond with people who develop later

physiologically. However, the most interesting aspect amongst these features is the

difference in reward orientation. People enacting slow strategies tend to be less impulsive

and more risk averse compared to people enacting fast strategies. Moreover, slow

strategies are associated with a higher level of parental care and sociability (Réale et al.,

2010). Ellis (2009) also argued that these people invest more in the future. People showing

more pro-social behavior; more specifically donation behavior, generally think carefully

about their higher donation amounts and act less impulsively. Possibly, they reflect their

higher level of parental care by taking care of other people who are facing difficulties. After

all, people enacting slow strategies think more about the future. Since they care more about

the future, they will care more about the well-being and stability of society. Therefore,

people following slow strategies will behave more pro-socially. On top of that, contrary to

people following fast strategies, they want to invest in long-term stability, which can be

reached by helping others, thus stimulating high group cohesion. Conversely, the latter

group is satisfied with short-term benefits, which are not related to donating money. People

enacting fast strategies do not take into account long-term consequences. When you

donate to charitable institutions, you usually see the results of your monetary donation only

years later, or sometimes not at all. Since they place less value on group cohesion, they

do not care so much about other people and prefer to live individually. People enacting fast

strategies, due to their impulsiveness, risk-seeking behavior and need for short-term

benefits, also do not think so much about providing stability to people in inferior conditions

resulting more often in individualized expenditure decisions. Consequently, by combining

the arguments mentioned earlier slow strategies can be linked to more pro-social behavior

and fast strategies to less pro-social behavior.

1.4 Hypothesis

Human beings who have grown up in a poor environment will enact fast strategies when

they face financial deprivation. Consequently, as argued earlier, these fast strategies will

manifest themselves in less pro-social behavior. Conversely, human beings who have

grown up in a wealthy environment will enact slow strategies when feeling financially

deprived. As a result, these slow strategies will manifest themselves in more pro-social

behavior. More specifically, this research has chosen donating to projects of charitable

institutions as the representation of pro-social behavior. More pro-social behavior

corresponds to higher donation amounts, whilst less pro-social behavior corresponds to

lower donation amounts. Thus, the hypothesis states that people from wealthy

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backgrounds will donate more to charity than people from poor backgrounds. However, this

donation behavior will only appear when they feel financially deprived.

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2 Method

This second section will give an overview of the methodology used. After explaining which

instrument was used, the data and participants will be described. The section ends with the

procedure.

2.1 Instruments

An online survey is mostly used to investigate expectations, intentions, future behavior,

past behavior, average behavior, attitudes and motivation. Since our research was

performed to examine donation behavior, an online survey was distributed via the internet.

More specifically, for this research a self-administered online survey was used. A survey

was useful in this situation because all participants had to answer questions that were

formulated in the same way. The answer possibilities and scales were also equal. Besides

that, practicability and statistical analysis was uncomplicated compared to qualitative

methods. Moreover, participants could be divided into different subgroups which could be

compared in order to find any significant differences. This survey was taken online, which

proved to be a flexible method because of the fact that this survey could be sent quickly to

a lot of possible respondents and the resulting data was available online. The respondents

were asked to fill in the survey online, so that there was no mediator conducting interviews.

This kind of survey, namely a self-administered survey, offers three main advantages. Self-

administered surveys are low cost. The respondent also determines the speed of

completion of their own survey, which gives them control. Finally, respondents do not have

to worry about the judgment of the interviewer, which could distort results in the case of a

study like this one asking about childhood and current financial situations. One

disadvantage of a self-administered survey is the fact that respondents can decide not to

answer the survey. It is also possible that they do not react in a timely manner, do not

complete the survey or do not understand certain questions.

2.2 Data

As was mentioned earlier, data was collected using a self-administered online survey, that

took ten minutes to fill in. The survey was created in Qualtrics, a well-known online survey

software. This survey was distributed via social media and e-mail. Two hundred and twenty-

two participants filled in the online survey. After the survey was closed, some data from the

dataset containing answers such as ‘I don’t know’ to particular questions and some surveys

that were not filled in completely were deleted. Two hundred and seventeen complete and

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useable surveys remained from which to start analyzing data in SPSS Statistics, a software

program used for statistical analysis. So, in total, five participants were omitted from the

sample due to incomplete observations. The fact that the survey contained open-ended

questions may have caused some people who started the survey not to complete it

because it took too much effort to fill in. However, without these open-ended questions, it

became difficult to financially deprive participants. Also, participants had to read three

descriptions of projects to measure pro-social behavior instead of just one. This is

explained further on. Participants, therefore, had to make more effort to read all the

descriptions in order to avoid distortion and to be able to create an average composite

view. Additionally, participants who were assigned to the manipulation condition may have

felt some discomfort about answering a question concerning their expenditure. Participants

wanted to explain why they only donated such a small amount of money to a particular

project. They always wanted to give a reason for their small donation. There was also an

important feature, namely social control, that may have affected the results. If participants

know their responses are being registered, they may behave differently because they do

not want people to think they are greedy, even if they are anonymous.

2.3 Participants

Two hundred and seventeen people (117 females, 100 males; mean age = 47.05 years,

SD = 1.68) participated in the experiment without being rewarded. Because donation

behavior is more likely for people who are financially stable, students, job-seekers and

people who are looking for a place to live were ignored; mostly people younger than 30

years old. Our participants were limited to people who were 65 years old, which is the legal

retirement age in Belgium, or younger. The typical individual donor profile has changed

over years. This donor profile consists of an individual in the middle age range, typically

between 35 and 64 years old. The age limitation applied in this study could create a

potential distortion in the experiment; however, most students would not able to give a

representative image of donation behavior because they are financially dependent on their

parents. As a consequence, not all of them are fully aware of the value of money.

This study made use of two hundred and seventeen participants, of which 46.1 % were

men and 53.9 % women, who were randomly assigned between 2 conditions. More older

people filled in the online survey, respectively, 24.0 % of the participants were between 30

and 45 years old and 66 % of the respondents were between 45 and 65 years old. 82.5 %

of the participants had a relatively positive general attitude towards donations, whilst only

17,5% had a relatively negative general attitude towards donations.

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2.4 Procedure

In a between-subjects design, it is important that participants are randomly assigned to the

experimental conditions in order to isolate the effects of our manipulation of the

independent variable. One important advantage of a between-subjects design is that you

do not have to worry about counterbalancing, where you would normally have to avoid the

difficulties of standard repeated measures designs, characterized by subjects who are

exposed to all conditions. In addition, it is not possible for participants to affect each other’s

performances, since they are assigned to only one of the conditions. However, there are

also some disadvantages associated with between-subjects designs. This type of design,

for instance, requires a lot of participants, which is more time-consuming. If the number of

conditions increases, the number of participants will need to increase too. Furthermore, a

between-subjects design is less sensitive to the effects of the experimental manipulations

than a within-participants design.

This experiment had two between-subjects conditions: financial deprivation and control. In

the financial deprivation condition, participants were asked to list their expenditure over the

past 30 days (Zhou, Vohs & Baumeister, 2009). Additionally, in order to avoid distortion in

our results, participants assigned to the manipulation condition were told that they were

participating in two different experiments; one investigating expenditure in the beginning of

spring and another investigating donation behavior. A similar question was asked in the

control condition; however, participants had to describe the weather over the past days

instead of their expenditure. In order to achieve reliability, it is very important to guarantee

that the dependent variable is measured as accurately as possible, relying on participants

reporting their feelings precisely. In order to assess pro-social behavior, more specifically

donation behavior, three different hypothetical projects were described and participants

were asked to answer an open-ended question, “How much are you willing to donate to

this project”, by indicating a donation amount. (Kleber et al., 2013). Participants were

presented three different regional, humanitarian-aid projects from unfamiliar charitable

organizations. The three projects were all poverty-related and were all displayed each time

in a random order in order to avoid bias. Participants were given the hypothetical

opportunity to donate an amount of money to each project. After each description of the

three projects, they had to type in how much they would like to give to the specific project.

If they didn’t want to donate anything at all, they had to type in the amount zero euros.

One charitable organization was involved in helping children in developing countries. The

aim of their project was to improve the growth and development of children through

partnerships with local organizations. In the Philippines, this charitable organization was

working with the local partner, Virlanie Foundation. They were working around basic health

care, access to water and food problems. The second charitable organization dealt with

15

the lives of thousands of people in Eastern Europe who are impacted by poverty. This

organization’s project in Ukraine was providing material and emotional support but, also,

contributing to educational and spiritual development. The last charitable organization was

an open house for poor people. Their project consisted of a meeting place where people

could inquire, talk, support each other, learn budgeting or learn how to cook together.

By choosing different kinds of poverty-related projects, both domestic and cross-border,

possible distortions were taken into account due to emotional reactions towards particular

projects. Unknown projects were chosen to avoid differing emotional reactions between

participants towards certain humanitarian-aid projects. For example, if a participant’s family

had been confronted with cancer several times in the past, that participant might donate a

higher amount to a charity taking care of cancer patients. The potential disadvantage of

using unknown projects is the possibility that some participants might not donate at all to

these projects because they are not sure that their money will be well spent.

As a further step, participants’ general attitudes towards donations were measured to

investigate if this influenced their donation behavior and to verify if this interacted with the

other independent variables (Batson, 1991; Dickert & Slovic, 2009; Graziano, Habashi,

Sheese, & Tobin, 2007). Three statements (α = .86) were indicated using a 9-point scale

ranging from “don’t agree at all” (1) to “completely agree” (9): “I believe that donations help

to improve the lives of people in need”, “I would regularly donate, if I had enough money

available”, and “I believe that, in general, donations are a meaningful way to help people in

danger of starvation”. Responses were averaged into a composite ‘General attitude’ (α =

.86). Next, to assess the variable socio-economic status (SES), constituted measures from

Griskevicius, Delton and Tybur (2011) were used. Participants were asked to evaluate

three statements on a 9-point scale ranging from 1, strongly dis-agree, to 9, strongly agree.

The three statements (α = .88) used to measure perceived childhood SES were “My family

usually had enough money for things when I was growing up”, “I grew up in a relatively

wealthy neighborhood” and “I felt relatively wealthy compared to the other kids in my

school”. The mean score of perceived childhood SES was 6.22 (SD= 1.27) with scores

ranging from 1 to 9. 13.82% of participants scored below 4.0 and 41.94 % of participants

scored above 7.0, which means participants felt relatively wealthy when they were growing

up. Finally, the current SES of the participants was measured using three statements (α =

.70), namely “I have enough money to buy things I want”, “I don’t need to worry too much

about paying my bills” and “I don’t think I’ll have to worry about money too much in the

future”. Responses were combined in a ‘perceived childhood SES’ composite and a

‘current SES’ composite. The mean score was 6.46 (SD= 0.11) with scores ranging from 2

to 9. 9.22% of participants scored below 4.0 and 41.94% of participants scored above 7.0,

which meant that most of the participants do not worry that much about their financial

16

situation. Perceived childhood SES and current SES were moderately correlated (r= 0.52)

and the likelihood of such a correlation occurring by accident in a sample of 217 people,

was 0, which is much smaller than 0.05. This meant the null hypothesis “perceived

childhood SES and current SES are not associated” could be reject with great confidence

and perceived childhood SES and current SES were significantly associated (r= 0.52, p=0,

n=217).

17

3 Results

The results section consists of a preliminary data analysis followed by a report of the

donation amounts.

3.1 Preliminary data analysis

Responses on the three different projects were combined into a ‘Donation behavior’

composite. Participants donated on average 38.47 euros to a charitable project. A highest

donation amount of 500 euros was registered for this composite, 17.5 % of the participants

did not donate at all (Appendix A). To determine whether the variation of these donation

amounts is relatively high or low, the coefficient of variation was computed by using the

formula standard deviation divided by the mean, which resulted in a normalized standard

deviation of 1.53. Bearing in mind the rule of thumb, implying a coefficient of variation

greater than or equal to 1 indicates a relatively high variation, the conclusion was made

that, the data points were spread out over a wide range of values. Donation amounts were

positively skewed (z(g1) = 26.35, p <.05). As a consequence, the composite ‘Donation

behavior’ was log-transformed using the function lg10 (donation amounts + 1). Since zero

amounts cannot be log-transformed, the arbitrary one was added.

3.1 Donation amounts

3.1.1 Perceived childhood SES

A regression predicting donation amounts from condition, perceived childhood SES, and

their interaction revealed no condition x childhood SES interaction, t(213) = 1.08, p=.28,

β =0.086. Both coefficients and their significance are reported in Table 1.

Table 1: Regression analysis, donation behavior; condition, perceived childhood SES, interaction

condition x perceived childhood SES (SPSS)

Standardized coefficients (β) Sig.

Condition -0.077 0.29

Perceived childhood SES 0.14 0.072

Condition x Perceived childhood SES 0.086 0.28

18

As shown in Appendix B, a R2 of 0.014 was determined, which means that only 1.4 % of

the variability in donation behavior could be accounted for by this model, consisting of the

predictors condition, perceived childhood SES and their interaction condition x perceived

childhood SES.

The influence of condition and perceived childhood SES on donation behavior was further

investigated by eliminating the middle class of the variable perceived childhood SES.

Consequently, only the people characterized with a high childhood SES and a low

childhood SES were analyzed. Next, the continuous variable perceived childhood SES was

made categorical instead of continuous. Afterwards a two-way ANOVA was conducted with

the logged averaged composite donation behavior as dependent variable, the categorical

variables condition and childhood SES as predictors. As can be seen in Appendix C and

Table 2, there was no significant main effect for condition, F(1,54) =0.43, p=.52, or

childhood SES, F(1,54)=3.91, p=.053, and no significant interaction, F(1,54)=1.51,p=.22,

despite the fact that the effect for categorical childhood SES was close to significant.

Table 2: Two-way ANOVA, donation behavior; condition, categorical childhood SES,

interaction condition x categorical childhood SES (SPSS)

F Sig.

Condition 0.43 0.52

Categorical childhood SES 3.91 0.053

Condition x Categorical childhood

SES

1.51 0.22

Observing Figure 2, it would appear that people from high-SES backgrounds donated more

in the financial deprivation condition than people from low-SES background. However,

since the interaction was insignificant, people from low-SES backgrounds did not donate

significantly differently than people from high-SES backgrounds; neither in the control

condition, nor in the financial deprivation condition.

19

Figure 2 : Donation behavior as a function of condition and perceived childhood SES

The analysis was continued by verifying whether people from low-SES backgrounds

donated differently in the control condition and the financial deprivation condition. The

same analysis was executed for the people from high-SES backgrounds too. In order to

conduct these two analyses, the dataset was organized by groups based on the categorical

perceived childhood SES. Afterwards, a one-way ANOVA (Appendix D) was conducted

with the logged donation behavior as dependent variable and condition as the predictor.

As can be seen in Table 3, no significant result was determined for the people from low-

SES backgrounds, F(1,36)=0.19, p=.67, nor for the people from high-SES backgrounds,

F(1,18)=2.75, p=.11.

Table 3: One-way ANOVA, donation behavior; condition (SPSS)

F Sig.

Condition (People with low-SES background) 0.19 0.67

Condition (People with high-SES background) 2.75 0.11

Next, the difference in the control condition between people from low-SES backgrounds

and people from high-SES backgrounds and the difference in the financial deprivation

condition were investigated. The dataset was organized in groups based on condition. A

one-way ANOVA (Appendix E) was conducted with the logged donation behavior as a

dependent variable and the categorical perceived childhood SES as an independent

variable. As shown in Table 4, there was no significant result for the control condition,

1

1,1

1,2

1,3

1,4

1,5

1,6

1,7

Control condition Financial deprivation

Log1

0(D

on

atio

n a

mo

un

ts)

Condition

Donation behavior

low-SES background

high-SES background

20

F(1,31) = 0.33, p=.57. However, in the financial deprivation condition, people from low-SES

backgrounds donated significantly differently compared to people from high-SES

backgrounds, F(1,23)=4.36, p=.048.

Table 4: One-way ANOVA, donation behavior; childhood SES (SPSS)

F Sig.

Perceived childhood SES (control condition) 0.33 0.57

Perceived childhood SES (financial deprivation condition) 4.36 0.048

As can be seen in Figure 3, people from high-SES backgrounds donated significantly more

than people from low SES-backgrounds when feeling financially deprived.

Figure 3 : Donation behavior as a function of perceived childhood SES (financial deprivation)

3.1.2 General attitude towards donations

Did the general attitude towards donations influence the participants’ donation amounts?

Participants with a more positive attitude towards donations would probably have donated

a higher amount of money. In other words, the variable general attitude towards donations

might drive the donation amounts. As a consequence, the general attitude was used as a

control variable in our analysis to verify if this yields different results.

A regression (Appendix F) predicting donation amounts from condition, perceived

childhood SES, their interaction and general attitude towards donations revealed no

condition x childhood SES interaction, t(212)=0.873, p=.38, β =0.23. There was no main

effect of condition, childhood SES or an effect of their interaction, however a main effect of

1

1,1

1,2

1,3

1,4

1,5

1,6

1,7

low-SES background high-SES background

Log1

0(D

on

atio

n a

mo

un

ts)

Childhood SES

Donation behavior (Financial deprivation)

21

general attitude towards donations was determined, t(212)= 8.18, p < .001, β =0.50. Both

coefficients and their significance are reported in Table 5.

Table 5: Regression analysis, donation behavior; condition, perceived childhood SES, interaction

condition x perceived childhood SES, general attitude towards donations (SPSS)

Standardized coefficients (β) Sig.

Condition -0.26 0.19

Perceived childhood SES -0.17 0.35

Condition x Perceived childhood SES 0.23 0.38

General attitude 0.50 <

0.001

As can be seen in Appendix F, a R2 of 0.25 was determined, which means that 25 % of the

variability in donation behavior can be accounted for by this model.

After eliminating the middle class once again, a two-way ANCOVA was conducted with the

logged averaged composite donation behavior as dependent variable, the categorical

variables condition and perceived childhood SES as independent variables and the general

attitude towards donations as the covariate. By doing this, the fact that general attitude

towards donations differed between participants was catered for. Moreover, the possibility

that there was still a difference in donation behavior, taking into account the general

attitude, was investigated. As can be seen in Appendix G and Table 5, there was no

significant main effect for condition, F(1,53) =0.15, p=.70, or childhood SES, F(1,53)=0.29,

p=.59, and no significant interaction, F(1,53)=1.97, p=.17.

Table 6: Two-way ANCOVA, donation behavior; condition, categorical childhood SES, interaction

condition x categorical childhood SES, general attitude (SPSS)

F Sig.

Condition 0.15 0.70

Categorical childhood SES 0.29 0.59

Condition x Categorical childhood SES 1.97 0.17

General attitude 22.006 <0.001

22

Observing Figure 4, it would appear that people from high-SES backgrounds donated more

in the financial deprivation condition than people from low-SES background and that this

effect was reversed in the control condition. However, since the interaction was

insignificant, people from low-SES backgrounds did not donate significantly differently than

people from high-SES backgrounds; neither in the control condition, nor in the financial

deprivation condition. Comparing this figure with Figure 2 without the control variable

general attitude, people from low-SES backgrounds donated more, whilst people from high-

SES backgrounds donated less in both conditions when taking into account the general

attitude.

Figure 4 : Donation behavior as a function of condition and perceived childhood SES

1,05

1,1

1,15

1,2

1,25

1,3

1,35

1,4

1,45

Control condition Financial deprivation

Donation behavior

(General attitude = 0.0632)

low-SES background high-SES background

23

General conclusion

The hypothesis stated that human beings who have grown up in a poor environment will

enact fast strategies when feeling financially deprived, which will manifest itself in less pro-

social behavior, whilst human beings who have grown up in a rich environment will enact

slow strategies when feeling financially deprived, which will manifest itself in more pro-

social behavior. The purpose of this study was to extend our understanding of pro-social

behavior, more specifically donation behavior related to different financial childhood

backgrounds. Human beings enact different life history strategies, ranging from slow to fast

strategies. This difference in strategies could be related to differences in early-life

conditions (Belsky et al., 1991; Ellis et al., 2009). In this research, behaviors which were

consistent with a certain strategy and did not appear in the control condition, emerged

under the financial deprivation condition. In our experiment, resource scarcity gave rise to

different responses based on the participant’s perceived childhood SES. The conclusion

can be made that, in the financial deprivation condition, people from high-SES backgrounds

donated significantly more than people from low-SES backgrounds. This implies that

people who grew up wealthier behaved more pro-socially when feeling financially deprived

compared to people who grew up poorer. The financial deprived feeling enhanced social

solidarity. Besides this, the warm glow of being a moral person or avoidance of feeling

guilty could have triggered the donation behavior of people. The perceived childhood SES

can be associated with children’s socio-cognitive development. As was mentioned earlier,

children will base their moral behavior on the consequences of their own behavior which

could also influence pro-social behavior. On the other hand, few differences were found

between people from high-SES or low-SES backgrounds who were assigned to the control

condition and did not experience conditions of economic uncertainty. Only participants who

were exposed to resource-scarcity cues, donated differently depending on their perceived

childhood SES. Taking the general attitude of participants towards donations into account,

people from low-SES backgrounds donated more, while people from high-SES

backgrounds donated less in both conditions.

This is an interesting result for the prosocial behavior research and more specifically,

donation behavior. To be specific, more insight is gained into how people characterized by

different backgrounds donate. Moreover, once again this result confirms that life history

strategy theory provides additional perspectives in understanding human behavior.

Besides this, the conclusion can be made that, in times of resource scarcity, people from

rich backgrounds will donate more than people from poor backgrounds. In times of financial

crisis, charitable organizations could take this donation behavior into account in order to

target the group which will donate the most.

24

There are several important implications resulting from our findings. The current findings

highlight that differences in donation behavior are shaped by the combination of economic

uncertainty cues and different life history strategies of individuals. Moreover, donation

behavior that might appear illogical and incoherent from an economic perspective can be

logical and coherent from an evolutionary perspective (Kenrick et al., 2009). It is important

to mention that the motivation behind monetary donation is a relevant aspect to investigate.

Considering these findings, in times of resource scarcity, fundraisers could better

understand the effect of different financial backgrounds and, consequently, stimulate

donation behavior. Education affords skills and access to networks. Kaplan and Rauh

(2013) found that the wealthiest individuals in the US economy were those who could

access and apply education. Charity fundraisers could target educated people who

probably grew up wealthier and take into account the incentives for giving. After all,

donations are of crucial importance to charitable organizations. Besides this, the lower

income tax after donating is a possible incentive for individuals. The government could take

these findings into account by taking measures to make it more interesting for people from

wealthy backgrounds to donate. This is very topical given the present situation of collecting

donations for the victims of the earthquake in Nepal in a society currently characterized by

the consequences of the recent financial crisis.

The effects of perceived childhood SES might be even more impressive if the range of this

variable had been less limited. Participants coming from extremely poor environments,

which were not present in great numbers in this experiment, might have resulted in greater

life history effects. Additionally, participants were presented regional, humanitarian-aid

projects from relatively unknown charitable organizations. Although different kinds of

projects, both domestic and cross-border, were averaged to reduce the differences in

emotional reactions towards particular projects, this still forms a potential limitation. The

more projects the averaged composite donation behavior contains, the more representative

the variable donation behavior becomes. Furthermore, people who participated in this

experiment knew that their responses would be registered. Due to social control, donation

amounts may have been increased. People are concerned about how others perceive

them. As argued earlier, personal traits, the presence of others and cultural influences

could also influence the magnitude of solidarity (Lewin, 1936). Similarly, companies could

also donate to improve their good image and build reputation. Finally, only people between

30 and 65 years old were selected, in order to capture the picture of the typical individual

donor. The results should be interpreted in the light of these potential limitations.

In this study, the conclusion can be made that, people from poor childhood backgrounds

and wealthy childhood backgrounds enact different life history strategies and consequently

donate different amounts. One potential reason is the fact that people from different

25

backgrounds have different interpretations of pro-social behavior. Further research in this

area is needed to enhance our understanding of the psychological mechanisms driving

these differences in donation behavior.

26

Appendices

Appendix A: Preliminary analysis

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Donation

behavior

217 ,00 500,00 38,4731 58,74293

Valid N (listwise) 217

Donation behavior

Frequency Percent Valid Percent Cumulative Percent

Valid ,00 38 17,5 17,5 17,5

Total 217 100,0 100,0

Appendix B:

Regression analysis (Donation behavior; condition, SES, condition x SES)

Model Summary

Model R R

Square

Adjusted R Square Std. Error of the

Estimate

1 ,134a ,018 ,004 ,66969

a. Predictors: (Constant), Interaction Condition*Childhood SES, Condition, Childhood SES

27

ANOVAa

Model Sum of Squares Df Mean

Square

F Sig

.

1 Regression 1,742 3 ,581 1,29

5

,27

7b

Residual 95,529 213 ,448

Total 97,271 216

a. Dependent Variable: Log10(Donation behavior)

b. Predictors: (Constant), Interaction Condition*Childhood SES, Condition, Childhood SES

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 1,035 ,209 4,949 ,000

Condition -,110 ,103 -,077 -1,061 ,290

Childhood SES ,049 ,027 ,136 1,807 ,072

Interaction

Condition*Childhood

SES

,084 ,078 ,086 1,081 ,281

a. Dependent Variable: Log10(Donation behavior)

28

Appendix C:

Two-way ANOVA (Donation behavior; condition, SES, condition x SES)

Between-Subjects Factors

Value Label N

Condition 1 control conditon 33

2 financial deprivation 25

Categorical childhood SES ,00

38

1,00

20

Tests of Between-Subjects Effects

Dependent Variable: Log10( Donation behavior)

Source Type III Sum

of Squares

df Mean

Square

F Sig.

Corrected Model 2,521a 3 ,840 1,674 ,183

Intercept 84,566 1 84,566 168,478 ,000

Condition ,215 1 ,215 ,429 ,515

Categorical childhood SES 1,960 1 1,960 3,904 ,053

Condition * Categorical

childhood SES

,759 1 ,759 1,511 ,224

Error 27,105 54 ,502

Total 115,806 58

Corrected Total 29,626 57

a. R Squared = ,085 (Adjusted R Squared = ,034)

29

Appendix D: One-way ANOVA (Donation behavior; condition)

Categorical childhood SES = ,00

ANOVAa

Log10(Donation behavior)

Sum of Squares df Mean Square F Sig.

Between Groups ,119 1 ,119 ,189 ,666

Within Groups 22,634 36 ,629

Total 22,752 37

a. Categorical childhood SES = ,00

Categorical childhood SES = 1

ANOVAa

Log10(Donation behavior)

Sum of Squares df Mean Square F Sig.

Between Groups ,684 1 ,684 2,752 ,114

Within Groups 4,471 18 ,248

Total 5,155 19

a. Categorical childhood SES = 1,00

30

Appendix E: One-way ANOVA (Donation behavior; SES)

Condition = control conditon

ANOVAa

Donation_behavior_log10

Sum of Squares df Mean Square F Sig.

Between Groups ,159 1 ,159 ,330 ,570

Within Groups 14,953 31 ,482

Total 15,112 32

a. Condition = control conditon

Condition = financial deprivation

ANOVAa

Log10(Donation behavior)

Sum of Squares df Mean Square F Sig.

Between Groups 2,302 1 2,302 4,357 ,048

Within Groups 12,152 23 ,528

Total 14,454 24

a. Condition = financial deprivation

31

Appendix F:

Regression (Donation behavior; condition, SES, condition x SES, general

attitude)

Model Summary

Mode

l

R R

Square

Adjusted R

Square

Std. Error of the Estimate

1 ,501a ,251 ,237 ,58627

a. Predictors: (Constant), General attitude, Condition, Childhood SES, Interaction

Condition*Childhood SES

ANOVAa

Model Sum of

Squares

df Mean

Square

F Sig.

1 Regression 24,403 4 6,101 17,750 ,000b

Residual 72,867 212 ,344

Total 97,271 216

a. Dependent Variable: Log10(Donation behavior)

b. Predictors: (Constant), General attitude, Condition, Childhood SES, Interaction Condition*SES

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) ,685 ,426 1,609 ,109

Condition -,369 ,283 -,260 -1,304 ,194

Childhood SES -,060 ,065 -,169 -,934 ,351

32

Interaction

Condition*

Childhood SES

,038 ,043 ,229 ,872 ,384

General attitude ,175 ,021 ,503 8,179 ,000

a. Dependent Variable: Log1(Donation behavior)

Appendix G: Two-way ANCOVA (Donation behavior; condition, SES, condition x

SES, general attitude)

Between-Subjects Factors

Value Label N

Condition 1 control conditon 33

2 financial deprivation 25

Categorical childhood SES ,00 38

1,00 20

Tests of Between-Subjects Effects

Dependent Variable: Log10(Donation behavior)

Source Type III Sum of

Squares

df Mean

Square

F Sig.

Corrected Model 10,474a 4 2,618 7,246 ,000

Intercept ,077 1 ,077 ,212 ,647

General attitude 7,952 1 7,952 22,006 ,000

Condition ,054 1 ,054 ,149 ,701

Categorical childhood

SES

,105 1 ,105 ,290 ,593

Condition * Categorical

childhood SES

,711 1 ,711 1,966 ,167

33

Error 19,152 53 ,361

Total 115,806 58

Corrected Total 29,626 57

a. R Squared = ,354 (Adjusted R Squared = ,305)

34

List of figures

Figure 1: Illustration of correlates of fast and slow life history strategies (Griskevicius V.,

Ackerman J. & Cantu S., 2013) .......................................................................................... 9

Figure 2 : Donation behavior as a function of condition and perceived childhood SES .. 19

Figure 3 : Donation behavior as a function of perceived childhood SES (financial

deprivation)........................................................................................................................ 20

Figure 4 : Donation behavior as a function of condition and perceived childhood SES .. 22

35

List of tables

Table 1: Regression analysis, donation behavior; condition, perceived childhood SES,

interaction condition x perceived childhood SES (SPSS) ................................................. 17

Table 2: Two-way ANOVA, donation behavior; condition, categorical childhood SES,

interaction condition x categorical childhood SES (SPSS) ............................................... 18

Table 3: One-way ANOVA, donation behavior; condition (SPSS) ................................... 19

Table 4: One-way ANOVA, donation behavior; childhood SES (SPSS) .......................... 20

Table 5: Regression analysis, donation behavior; condition, perceived childhood SES,

interaction condition x perceived childhood SES, general attitude towards donations

(SPSS) .............................................................................................................................. 21

Table 6: Two-way ANCOVA, donation behavior; condition, categorical childhood SES,

interaction condition x categorical childhood SES, general attitude (SPSS) .................... 21

36

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