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Gender Differences in a Cooperation Game: Evidence from the Field in Matrilineal, Patriarchal and Gender-neutral

Societies

Sugato Chakravarty* Abu Zafar M. Shahriar

S. M. Zahid Iqbal

Abstract

Research suggests that gender differences in competitive inclination are fueled by different nurturing of men and women. We investigate whether such differences hold if the experimental task is inherently cooperative rather than competitive. We employ a game involving decisions to repay joint liability-based microcredit whose predominant feature is cooperation among borrowing partners for continued access to funds. We recruit male and female subjects from matrilineal, patriarchal, and gender-neutral societies and find that women have a greater willingness to contribute to group repayment in every society. Thus, women appear to be more cooperative than men irrespective of their different nurturing. JEL Codes: C90, C93, G21, J16. Key Words: gender and cooperation, joint liability-based microcredit, matrilineal and patriarchal societies, field experiments.

Current Draft: September, 2015

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* Chakravarty and Iqbal are from Purdue University, 812 West State Street, West Lafayette, IN 47906. Shahriar is from Monash Business School, Monash University, 900 Dandenong Road, Caulfield East, VIC 3145, Australia. The paper has benefited from comments from Jonathan Bauchet, Catherine Barrat, Lee Cohen, Catherine Eckel, Philip Grossman, Elaine Hutson, Asadul Islam, Joyce Jacobsen, Pushkar Maitra, Sandra Maximiano, and the participants of the annual meetings of the American Economic Association in Philadelphia, the Southern Economic Association in Atlanta, and the Western Economic Association in Wellington, as well as the seminar participants at Purdue, Monash and Deakin Universities. We are grateful to Mohammad Yeasin Ali of Bangladesh Development Bank Limited and Colonel Nowroj Ehsan of the Bangladesh Army for providing logistical support for the project. Shahriar also thanks the generosity of the Research Grant from Monash Business School. We are responsible for any remaining errors.

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One often hears the maxim that men and women are intrinsically different

(Lawrence 2006). There is even a bestselling book entitled "Men are from Mars, Women

are from Venus" that explores innate differences between the genders.1,2 In 2005, then

president of Harvard University Lawrence Summers drew the ire of women (and some

men) by suggesting that the under-representation of female scientists at elite universities

may stem in part from innate differences between men and women.3 In the aftermath of

the global financial meltdown in 2007, a 2008 article in The Times speculated that a

reason investor confidence in the banking system collapsed may have been that there was

too much testosterone involved in making crucial financial decisions.4 The same article

further asserted that an influx of talented women on the trading floor might make the

business of risk-taking a saner business altogether. Employing an experimental asset

market, Eckel and Füllbrunn (2015) set out to investigate the veracity of the claim and

report that all-male financial asset markets generate higher speculative bubbles than all-

female markets. The authors suggest that women appear to dislike the competitive milieu

and react negatively to competitive pressures and that there does appear to be an element

of truth in the Times article.5 Gneezy, Leonard and List (2009) introduce a simple

competitive task of throwing a ball in a bucket and find that women in the patriarchal

Maasai society (in Tanzania) are less competitive than men, whereas the results are

reversed in the matrilineal Khasi society (in India) where women display more

competitiveness than men. A notable feature of the above studies is that the underlying

tasks employed among the experimental subjects are inherently competitive in nature.

This raises the question: Can the nature of the task itself have any bearing on the results

reported by these authors?

Specifically, we investigate whether such gender-differentiated behavior,

apparently fueled by different nurturing, continues to hold when the underlying task facing

                                                            1 The book, by John Gray (1992), has sold more than 50 million copies, and the catchy title has become a part of popular culture to underscore the intrinsic differences between men and women. 2 In this article, the term gender denotes the grouping of people into female and male categories. Thus, the term gender difference is applied to describe the results of comparing these two groups. 3 http://www.thecrimson.com/article/2005/1/14/summers-comments-on-women-and-science/ 4 http://www.thetimes.co.uk/tto/life/article1855274.ece. 5 Eckel and Füllbrunn (2015) also conduct a meta-analysis of 35 markets from related studies and confirm the inverse relationship between the magnitude of price bubbles and the frequency of female traders in the market.  

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experimental subjects is cooperative rather than competitive. The specific task that we

employ is a game involving repayment decisions in a joint liability-based microcredit set

up whose predominant feature is cooperation among the members of the borrowing group

for overall group success and for continued access to funds.6 In joint liability-based

microloans, group members’ payoffs enter into the utility function of a borrower in that

group. Consequently, other-regarding (or social) preferences, such as attitude toward

cooperation, play an important role in shaping her/his loan repayment decisions in this

setting (Abbink, Irlenbusch, and Renner 2006; Anthony and Horne 2003).

Among the indigenous peoples in eastern Bangladesh, we discovered three

communities—the Khasi, Patro, and Marma—who have historically evolved in distinct

directions in terms of gender relations. The Khasis have a matrilineal family structure and

a matrilocal residence system, whereas the Patros are organized in a patriarchal structure.

Accordingly, female domination in the Khasi and male domination in the Patro societies

are common knowledge (Chakraborty and Ali 2009). The Marma society, in contrast, is

distinguished from both patriarchal and matrilineal societies because Marma males and

females enjoy equal status within their households and in society (Lewin 1869; Marma

2010; and Roy 2004). Thus, unlike the Khasis or the Patros, gender relations among the

Marmas cannot be characterized by a typical dominant-submissive framework, and we

subsequently characterize them as gender-neutral.

In the literature, microloan repayment experiments have been designed based on

the intuitions provided by public goods experiments (see, for example, Abbink et al. 2006;

and Cassar, Crowley, and Wydick 2007).7 Consistent with this literature, we conducted a

simple microloan repayment experiment with male and female subjects in these three

distinct societies. The game involved a scenario where we extended simulated loans to

groups of five borrowers who were jointly responsible for repayment. Group members

                                                            6 In actual joint liability-based microlending programs, potential borrowers form small groups while applying for loans. Upon approval, each group member individually receives a loan, but the group, as a whole, remains jointly responsible for repayment. Thus, if a borrower defaults, the other members of the group are required to repay on behalf of their defaulting peer. Otherwise, the entire group loses access to any future loans. Upon successful repayment by the group, on the other hand, each borrower becomes eligible for a new loan (see, for an overview, Banerjee 2013, and Chakravarty and Shahriar 2015). 7 Abbink et al. (2006) conduct their microloan repayment experiments with student subjects at the University of Erfurt. They find that a borrower’s willingness to repay joint liability loans decreases with the size of the borrowing group. Cassar et al. (2007) conduct a modified version of this game in South Africa and Armenia. They add a field context to the experiments by recruiting subjects who are likely to participate in actual microcredit programs. They suggest that the willingness to repay increases with the level of personal trust among group members.

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individually invested their loans in a risky project, and once project-returns were realized,

they individually decided whether to contribute to the group repayment. Those whose

projects failed did not have enough money, but those whose projects succeeded had

enough, to contribute. Subjects with successful projects, however, had two choices: They

could either contribute to the group repayment, or they could strategically default. The

game ended if group members as a whole were unable to fulfill their repayment

obligations (i.e., repay the total amount extended to the group with interest). A successful

group repayment, by contrast, enabled each member to receive a new loan, and the game

continued.8 In this task, strategic, or willful, default was compatible with selfish own-

income maximization, whereas a subject’s willingness to repay reflected on her/his

attitude toward cooperation.

The results of our experiments show convincingly that women have a greater

willingness to repay than men in every society. Put differently, women are more

cooperative with their group members irrespective of the gender relations prevalent in a

given society. We further show that although the repayment rates of the women do not

vary substantially across the three societies, men from the matrilineal society display a

greater willingness to repay than men from the patriarchal society. Furthermore,

repayment behavior of the men appears to improve with the level of asset ownership,

whereas the same measure appears to have no significant impact on the females’

willingness to repay. A reasonable conclusion is that the greater willingness to repay

displayed by the women does not appear to be conditional on their access to economic

opportunities. In sum, women are better than men at the cooperative task, and this result is

independent of their different nurturing. We confirm that individual decisions made by

subjects in our cooperative task are not driven by their heterogeneous attitudes towards

risk. In explaining our findings, we take the help of an extensive literature, rooted in

psychology and evolutionary biology, which supports the notion that women can in fact be

naturally better at cooperative activities, exemplified in our group-based microloan

repayment game.

The remainder of our study proceeds as follows. In Section I, we discuss the

relative position of women in the three societies where we conducted our experiments. We

                                                            8 This introduced, in a simple way, the dynamic repayment incentives inherent in actual group-based microloans.

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describe the experimental design in Section II and discuss the results in Section III.

Section IV concludes the paper.

I. Gender Relations in the Khasi, Patro, and Marma Societies

The Khasi and the Patro communities live in the Sylhet district of Eastern

Bangladesh, whereas the Marmas live in the Chittagong Hill Tracts—150 miles away

from Sylhet. Gender relations vary substantially in these three communities. In the Khasi

community, for example, women carry forward the family lineage. Accordingly, women

head Khasi households, and children are known by their mother’s family names. Due to

matrilocal customs, the bridegroom moves to the bride’s house after the wedding.

Unmarried, widowed, and divorced men also live in their mother’s house (Patam 2010).

The matrilineal families give rise to a system in the Khasi society where men frequently

hold roles that seem to mirror those of women in a patriarchal society. For instance, only

the female children among the Khasis inherit ancestral property. A Khasi man spends his

life in a household—headed by his mother, sister, wife, or wife’s mother—where he has

no authority over the distribution of resources. The Patro society, on the other hand,

upholds the male line of lineage and a patriarchal family system. Only the men head a

Patro household and inherit any ancestral property. Consistent with patrilocal customs, the

bride moves to the groom’s house after the wedding. Patro men are allowed to have

multiple wives, but marrying a widow is strongly discouraged (Patro 2010).

Chakraborty and Ali (2009) report sharp contrasts in gender relations in these two

communities. In Khasi households, for example, husbands raise the children, whereas

child rearing is considered to be a wife’s responsibility in Patro households. Therefore, it

is common among the Khasi women to find work outside the village, especially during

lean periods when they are forced to travel further away from home to find employment.

In the Patro community, by contrast, the prospect of women moving around freely is not

considered “appropriate” behavior. However, the sharpest contrast identified by

Chakraborty and Ali (2009) is that although the Patro parents have a strong preference for

male children, Khasi parents are always more welcoming of female children.

Gender relations among the Marmas are different from those among the Khasis or

the Patros. A typical Marma household is headed by a man. However, after the death of

the husband, the wife takes over the head’s role. Unlike a typical patriarchal or a

matrilineal society, Marma men and women participate both in household work and

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income-generating activities outside the household, such as agriculture, forestry, and

various forms of small scale trading. Thus, both men and women play important roles in

the accumulation and consumption of household resources. Although men carry on the

family lineage, the customary law affords Marma men and women equal rights on

ancestral property. Women live with their husband’s family after marriage, but men have

to pay “bridal price” to the bride’s parents. For these and other reasons, the Marmas are

considered to be a gender-neutral society (see, for example, Lewin 1869; Marma 2010;

and Roy 2004).

II. The Experiments

A. Subject Pool and Lab Setting

The experiments with the Khasi and the Patro were conducted in Sylhet, and the

experiments with the Marma were conducted in the Chittagong Hill Tracts.9 These

indigenous communities have customary organizations that are responsible for social

control, preservation of cultural heritage, as well as social conflict resolution—both within

and across communities (Hassan and Ali 2009; and Roy 2004).10 The leaders of these

customary organizations are the gateways to any organized activity involving that

community—including research studies like ours. Therefore, with their help, we prepared

a list of adult men and women in the villages under their jurisdiction who met the

following criteria: (a) their households owned less than half an acre of arable land; (b)

they were not members of any formal microcredit program at the time of data collection.

These criteria were imposed for the following reasons. Owning less than half an acre of

arable land is used as an eligibility criterion for receiving microcredit by some major

microcredit providers in Bangladesh, such as the Grameen Bank, ASA, and BRAC

(Hossain 1988; and Sharma and Zeller 1997). We deliberately avoided recruiting current

microcredit-borrowers because their decision within the experiments might be influenced

                                                            9 Some of the major Bangladeshi microfinance institutions, such as the Grameen Bank, Bangladesh Rural Advancement Committee (BRAC), and Association for Social Advancement (ASA), have lending operations in the two districts where we conducted our experiments (Asiatic Society of Bangladesh 2012). However, access to credit is significantly lower among the indigenous households compared to the non-indigenous Bengali households living in the same region (Barkat et al. 2009; Roy 2012). 10 In the Khasi community, for instance, village-level customary organizations are known as the Jing Alang Darbar (i.e., the Village Committee). The head of the Darbar is known as the Montree (i.e., Minister). The village-level customary organization in the Patro community is the Moral Baishe (i.e., the Committee of Community Leaders), and its head is known as the Moral (i.e., Head of the Community). Marma villages are headed by the village-chief, known as the Karbari.

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by their actual experience with such loans. For instance, an individual who received

support—in repaying actual microloans in the recent past—from her/his partners might

behave differently in the experiments from those who did not receive such support.11

Therefore, after careful consideration, we chose to recruit from only those who were

eligible to participate in an actual microcredit program but were not, as of the time of the

data collection, formally microcredit-borrowers. Using a simple lottery, we selected 450

individuals from this list, of whom 430 participated in our experiments. Of these 430

subjects, 160 are Khasi (70 males and 90 females), 120 are Patro (60 males and 60

females), and 150 are Marma (70 males and 80 females).

In each experimental location, we set up a laboratory either in a community center

or in a school building isolated from any neighboring establishments. We informed

subjects that they would receive 50 Bangladesh Taka (BDT) for their participation. They

were also informed that, depending on the choices that they would make during the course

of the experiments, they would earn additional monies.12

B. Experimental Procedure

Each experimental session involved either five male or five female subjects

belonging to the same community. They had no role in determining who would be present

in their specific sessions. Note that although some microlendeers lend to self-selected

groups, we purposely avoided playing our repayment game with such groups because of

the potential effects of self-selection on repayment decisions.13 All participants were

initially directed to a large room, where we provided experimental instructions in Bengali                                                             11 A subject who was bailed out by her/his partners with actual microloan repayment in the recent past may display a greater willingness to contribute to group repayments due to a fairness effect. Partners’ support could also induce free rider problems and a greater likelihood of observing strategic defaults in the experiments.  12 BDT is the official currency of Bangladesh (one US dollar is equal to 78 BDT). The daily per capita income in Bangladesh is 234 BDT (see World Development Indicators: http://data.worldbank.org/indicator/NY.GDP.PCAP.CD). The participants of our experiments, however, came from the poorest segment of the population, and they participated in the experiments in their leisure period. Thus, it can be reasonably argued that a show-up fee of 50 BDT, along with the opportunity to earn additional monies (our subjects earned, on an average, 144 BDT excluding the show-up fee), was enough to ensure that they took the experiments seriously. 13 Close social ties among the members of a self-selected group may enhance repayment rates if the subjects do not want to upset their partners by not repaying loans. Strong ties in self-selected groups may also hamper repayment discipline if the members show more “forgiveness” toward defaulters (see Besley and Coate 1995; and Wydick 1999). As a robustness check of our main findings, however, we control for the effects of social ties among the members of our randomly selected groups on their loan repayment decisions. See section III.

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(the English version of the instructions is provided in Appendix A). We asked subjects

specific questions to make sure that they had understood the rules of the game and its

tradeoffs.

The experimental task could (and did) have multiple rounds depending on the

repayment decision of the members of a borrowing group. At the beginning of each

session, we used a simple lottery to determine the maximum number of rounds (between 5

and 10) to be played. This information was not disclosed to the subjects. This ensured that

subjects could not game the last period and indulge in the type of last-period “hell for

leather” behavior, which could unravel the whole game.14

Each round of the game had four distinct steps as follows.

Step 1: Each group member received a sum of 50 BDT, characterized as a loan,

which had to be repaid with 20% interest in a single installment. Subjects were informed

that the loan repayment would be a joint responsibility of the group, and that the group as

a whole was expected to repay 300 BDT (i.e., the total amount disbursed to the group plus

the interest payment). Upon repayment of the 300 BDT as a group, each member would

receive another loan of 50 BDT.

Step 2: Each member of a given group was individually invited to step into a side

room where she/he “invested” her/his loan in a risky venture. The risky venture consisted

of a simple ball-drawing game determining if her/his project succeeded in that round or if

it failed. Specifically, the subject drew a ball from a non-transparent jar containing one red

and five green balls. If the subject drew the red ball, it implied that her/his project had

failed and she/he had no money left in that round. Drawing a green ball, conversely,

implied that her/his project had succeeded in that particular round. A subject whose

project succeeded received 120 BDT from the experimenter, which she/he could use to

repay the loan but only in that particular round. The excess monies—left after repaying

her/his loan in a given round—were converted into real currency at the end of the

experiment.15

                                                            14 Abbink et al. (2006) continued their game for a maximum of 10 rounds. A problem with this approach is that when subjects are told that the game consists of a finite number of rounds, say n rounds, their best strategy would be to not repay in the nth round. Following backward induction, it can therefore be argued that non-repayment would be the subgame perfect equilibrium in every round if the end point of the game is known by the subjects. To resolve this problem, Cassar et al. (2007) continued their game only with a 1/6 probability after the sixth round of play. 15 Our choice of the likelihood of project success, project payoff, and interest rates on loans are consistent with that of Cassar et al. (2007). However, the size of our borrowing groups is consistent with that of

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Step 3: Subjects made repayment decisions. A subject whose project failed could

not contribute to group repayment. A subject with a successful project, conversely, had the

choice of either repaying or not repaying (i.e., strategically default on) the loan. However,

the exact amount due by an individual subject—who was both able and willing to repay—

was determined only after all of the group members made their repayment decision. This

amount was revealed to the subject in step 4. After the completion of step 3, subjects

returned to the main area and waited quietly for the next step to begin. Once all of the

members of a group made their repayment decisions, the subjects were again taken to the

private room—one by one—to complete the 4th step of the game.

Step 4: We informed the subject about how many members of her/his group

contributed to group repayment in that round. The identities of the non-contributing

members were never revealed. The debt burden of the group was split equally among

those whose projects succeeded and chose to contribute to the group repayment amount.

Thus, the debt burden of an individual subject (who decided to contribute) decreased with

an increase in the frequency of successful and paying group members. This implied that

the full repayment of the group loan (300 BDT) was possible only if at least three group

members repaid in any given round. The payoff of each contributing member and whether

the game would proceed to the next round were determined as follows.

If all of the members of a group contributed to group repayment, 60 BDT was

collected by the experimenter from each of them (from the 120 BDT she/he received

from the project payoff in that round). Each member of the group received another

loan of 50 BDT, and the game then moved to the next round.

If four members contributed, 75 BDT was collected from each contributing member.

Each member of the group received another loan of 50 BDT, and the game proceeded

to the next round.

If three members contributed, 100 BDT was collected from each contributing member.

Each member of the group received another loan of 50 BDT, and the game proceeded

to the next round.

                                                                                                                                                                                   Grameen Bank’s classic group loan schemes. The effective interest rate on Grameen Bank’s loan is around 22% (Ahmad 2007). We did not allow our subjects to use their project payoff to repay loans in the successive rounds (if any). The underlying assumption is that poor borrowers cannot accumulate enough savings, at least in the short run, from which they can repay loans if their projects fail. See Deaton (1989) for the factors that hinder poor households’ ability to save for precautionary purposes.

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If less than three members contributed, 120 BDT was collected from each

contributing member. However, since the group repayment obligation of 300 BDT

could not be met, no member from the group received any new loans. The game

ended for this group at this juncture.

Steps one through four were repeated for the members of a successful borrowing group.

The game timeline is summarized in Figure 1, and the structure of payouts in a given

round is described in Table 1.

[Insert Table 1 here]

C. Post-Experiment Survey

We had each participant fill out a short survey after the experiment to collect

information on their socio-economic and demographic characteristics, such as age, level of

education, marital status, occupation, and ownership of assets.16 A subject’s age is

measured in years, and her/his level of education is measured by the number of years of

formal schooling. We categorized subjects, based on their marital status, as married

(including divorced, separated, and widows/widowers) or unmarried. Based on their

primary profession, we classified subjects as farmers (whose primary profession is

agriculture or agricultural wage labor) or others (including small business owners, non-

farm wage laborers, students, house wives, unemployed, and others). Assets owned by a

subject’s household—such as the value of the agricultural land, dwelling house, ornaments,

cattle, and other valuables—were measured in BDT. We collected information on the

number of total family members as well as the number of children (age below 15) in each

household and estimated the dependency ratio as the proportion of children in each

household. We further asked subjects whether they had experienced, within the past one

year, (a) a natural disaster such as flooding, river erosion or disordering rain; (b) a bad

harvest; or (c) loss in income due to illness/death of an earning member of the family. We

                                                            16 Our choice of the survey questions is guided by Sharma and Zeller (1997), who provide comprehensive evidence regarding the association between demographic characteristics of the borrowers and their joint liability-based microloan repayment decision in Bangladesh. While examining gender differences in competitive inclination, Gneezy et al. (2009) controlled for the effects of age, education, marital status, income, and occupation of their subjects.

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interpreted a positive answer to any of these questions as an adverse income shock in the

recent past for the subject.

After completion of the survey, we requested that each subject indicate how well

she/he may have known her/his group members (outside the context of the experiment) on

a scale of one (no contact) to seven (frequent contact). Based on each subject’s self-

reported level of communication, we estimated the average level of acquaintanceship that

she/he had with her/his borrowing partners as follows. Suppose a subject’s level of

communication with partner i is Ai. Her/his average level of acquaintanceship with the

group members is estimated as ∑

. A subject’s social ties with her/his borrowing

partners are reflected in the average level of acquaintanceship (see also Abbink et al.

2006).

Summary data from the post-experiment survey are presented in Table 2. The

average age of our subjects was 30 years. On average, the subjects spent five years at

school, 69% of our subjects were married, and 27% reported agriculture as their main

occupation. Overall, the Marma subjects were younger, more educated, and wealthier than

the Khasi or the Patro. However, there is no evidence that the three communities are

different in terms of the degree of social connectedness.

[Insert Table 2 here]

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Subject receives a loan

Subject invests in a risky project

Project fails with probability 1/6

Project succeeds with probability 5/6

Subject defaults because she/he does not have enough money to repay

Subject strategically defaults

FIGURE 1: THE SEQUENCE OF DECISION MAKING IN THE EXPERIMENTS

Subject decides to contribute to group repayment

If at least 3 members of the group contribute to group repayment, the game proceeds to the next round

If at least 3 members of the group contribute to group repayment, the game proceeds to the next round

If less than 3 members of the group contribute to group repayment, the game ends

If less than 3 members of the group contribute to group repayment, the game ends

Subject is informed about the repayment decisions of her/his group members

Subject is informed about the repayment decisions of her/his group members

Subject receives another loan (and the process repeats)

Subject receives another loan (and the process repeats)

Step 1 Step 2 Step 3 Step 4 Step 1

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III. Results

A. Willingness to Repay Loans

Following Cassar et al. (2007), we estimate a subject’s frequency of loan repayment

normalized by the number of times her/his project is successful.17 We use this normalized

estimation to measure a subject’s repayment rate or her/his willingness to repay, which also

reveals her/his degree of cooperation with the group members. We examine whether

repayment rates vary across gender lines using a two-sample t-test (assuming unequal

variances and unequal sample sizes). First, we carry out this test in our pooled sample. Then,

we observe the pattern of any gender differences in each society separately. We utilize data

from the first five rounds of the game to minimize contamination from subjects taking into

account an impending end game and to minimize any potential survivorship bias.18

The results are reported in Table 3. In our pooled sample, the average repayment rate

of women is 17 percentage points higher than that of men (p < 0.01). Upon further

decomposition, we find that women participants have better repayment rates in every society.

Among the gender-neutral Marmas, the average repayment rate of women is 16 percentage

points higher than that of men. In the patriarchal Patro (matrilineal Khasi) society, the

average repayment rate of women is 23 (11) percentage points higher than that of men. These

differences are all statistically significant either at the 5 % or 1% levels. Thus, our univariate

analysis suggests that relative to men, women display a greater willingness to cooperate by

repaying loans in the experiments regardless of their relative roles in society.

[Insert Table 3 here]

Next, we analyze gender differences in repayment rates within a regression

framework. We pool individual observations from the Marma, Khasi, and Patro communities

and estimate the following equation using an Ordinary Least Squares (OLS) regression with

clustered standard errors at the community level.

∗ ∑ (1)

                                                            17 A total of nine subjects did not have any success with their project. We considered their loan repayment rates to be zero. Upon removal of these observations, however, our main results hold. 18 This approach is consistent with that of Cassar et al. (2007) and Giné et al. (2010). Our main results hold even when we include data from the latter rounds.

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On the right-hand side, we introduce a dummy variable for gender (Female: one for

female, zero for male). There are two dummy variables for the three communities: Khasi

equals one if a subject belongs to the Khasi community and zero otherwise; and Patro equals

one if the subject belongs to the Patro community and zero otherwise. We also introduce

community-gender interaction terms, which allow us to compare the repayment rates of men

and women in each community. Thus, the coefficient on the Female dummy (β1) captures the

gender difference in loan repayment rates in the gender-neutral Marma society. The sum of

the coefficients on Female and Female*Khasi (β1 + β4) captures the gender difference in

repayment rates among the matrilineal Khasis; and the sum of the coefficients on Female and

Female*Patro (β1 + β5) captures the gender difference in repayment rates among the

patriarchal Patros. Additionally, the vector X captures the set of control variables representing

the demographic details of our subjects as discussed above.

The results of this baseline specification (Table 4 column 1) suggest that women

choose to repay more frequently than men in all three societies. In the gender-neutral Marma

community, the average repayment rate of the women is 18 percentage points higher than that

of the men (p < 0.05). In the patriarchal Patro community, the average repayment rate of the

women is 30 percentage points higher than that of the men (p < 0.01); whereas among the

Khasis, the average loan repayment rate of the women is 12 percentage points higher than

that of the men (p < 0.05). The fact that gender differences in repayment vary across the three

societies deserves further attention. Consequently, we compare repayment behaviors of the

women and that of the men across the three societies. Our findings suggest that there are no

substantial differences in the repayment rates of women. Thus, the fact that women display a

significantly greater willingness to repay loans in our experiments, which is essentially a

cooperative task, does not appear to be an outcome of their different nurturing. However, it is

a different story while focusing on the men. The average repayment rate of the Khasi men is

17.5 percentage points higher than that of the Patro men (p < 0.01). Put differently, the men

from the society, where they play second fiddle to the women, exhibit a significantly greater

cooperative spirit by displaying a greater willingness to repay group loans in our game than

the men from the male-dominant society.19

                                                            19 Gong, Yan, and Yang (2015) conducted a dictator game with male and female subjects in the matrilineal Mosuo and the patriarchal Yi societies in China. Their findings suggest that men in the female-dominant society are more altruistic than men in the male-dominant society but also that women are not different—in terms of altruistic behavior—across the two societies. However, as List (2007) points out, the standard altruism-related explanation from these games is questionable at best because a simple manipulation of the action set leads to drastic changes in the dictator’s behavior. Furthermore, and relevant to the current paper, strategic concerns are absent in standard dictator games where one party (the dictator) proposes the split of an asset and the receiver

15  

[Insert Table 4 here]

We also see that subjects from relatively wealthier households, and households with

higher dependency ratios, displayed a greater willingness to repay. This is consistent with

Sharma and Zeller (1997) within the context of joint liability loans in Bangladesh.20 The

significant association between household wealth and loan repayment rates deserves further

attention in the present context. A popular belief in the microfinance community has been

that women repay their (actual) microloans more frequently than men because they (the

women) lack access to resources and economic opportunities (see, for example, Armendariz

de Aghion and Morduch 2010; and Morduch 1999).21 We investigate whether the willingness

to repay microloans of our female subjects could indeed be influenced by a similar mindset

by introducing an interaction term between gender and asset ownership in the OLS estimation.

The results (Table 4 column 2) suggest that for participants who do not own any physical

assets (there are 92 subjects in this category: 38 males and 54 females), the repayment rates

are significantly higher for women (p < 0.05). For those who have some physical assets, we

see an incremental positive correlation only with male repayment behavior (p < 0.01). Put

differently, it appears that male repayment behavior in our game is positively correlated with

actual asset ownership, whereas it appears to have no association whatsoever with the women.

Thus, women’s greater willingness to repay does not appear to be a function of their actual

access to economic opportunities in the society that they live in.

Overall, we find that whereas the male subjects’ repayment decisions appear to be

somewhat conditional on heterogeneous socialization, the female participants’ repayment

decisions are unambiguously independent of relative nurturing. Women appear to be

significantly more cooperative than men, irrespective of their relative nurturing.

                                                                                                                                                                                         passively accepts it. In contrast, in our cooperative game, the choice of each group member at every stage decides how others in the group might react and whether the collective good is achieved as a result. 20 Sharma and Zeller (1997) analyze the repayment rates of 128 credit groups belonging to three joint liability-based microcredit programs in Bangladesh: ASA, BRAC, and RDRS (Rangpur Dinajpur Rural Service). They find that loan default rates are negatively associated with the ownership of assets and the dependency ratio of the household of the borrowers. 21 For example, because women have fewer credit opportunities in most developing societies, they adopt more conservative investment strategies (Todd 1996) and exert greater efforts in their projects (Ameen 2004) to ensure continued access to loans. Furthermore, women clients can be monitored more easily by the loan officers because they stay close to home rather than going out to work (Rahman 1999; and Goetz and Gupta 1996). “Thus, ironically, the financial success of many (microcredit) programs with a focus on women may spring partly from the lack of economic access of women…” (Morduch 1999, p. 1584).

16  

B. Familiarity among Group Members and Participant Choices in the Game

Several authors have examined the role of social factors in experimental cooperative

tasks (see, Abbink et al. 2006, for an overview). An important finding in this literature is that

an ex-ante familiarity among group members may be important in establishing cooperation

(see, also, Bohnet and Frey 1999). In our loan repayment game, we randomly formed the

borrowing groups, but it is possible that the level of acquaintanceship among the members of

a given group (outside the purview of the game itself) may have influenced their repayment

decisions in the game. If so, our main findings may not hold after appropriately controlling

for its effects. Here, we examine if this might indeed be the case.

As we mentioned in Section II, based on our recording of each subject’s self-reported

level of communication with the other subjects in her/his group, we estimated the average

level of acquaintanceship that a subject had with her/his playing partners. We regress loan

repayment rates on acquaintanceship and the other explanatory variables introduced in our

baseline specification. The results (Table 4 column 3) suggest that a subject’s familiarity with

her/his playing partners has no association with her/his repayment decision.22 Rather, after

controlling for the effects of acquaintanceship, women appear to have better repayment rates

in our game than that of the men in every society.

C. Attitude toward Risk and Loan Repayment Decision

Given the risky nature of the investment decision that each group member is exposed

to in every round, it is clear that a participant’s attitude toward risk might play an important

role in her/his repayment/default decision in each round, which, in turn, might impact the

well-being of the group as a whole. In particular, participants’ relative level of risk aversion

might explain the results reported in Table 4 if the less cooperative participants with low

repayment rates also happen to be more risk averse.

To examine this issue in greater detail, we conducted a separate risk aversion

experiment to explore whether the observed differences in cooperation might be driven by

heterogeneous risk postures across gender groups. In particular, we executed an additional

risk aversion game, similar to that conducted by Gneezy et al. (2009), for this purpose. We

recruited experimental subjects in each of the three societies, following a procedure similar to

our loan repayment game. From the list of eligible adults who were not members of any

microcredit programs at the time of data collection, we randomly chose 120 subjects, of

                                                            22 This finding is consistent with that of Cassar et al. (2007). These authors suggest that the level of communication among group members does not affect a subject’s decision in microloan repayment experiments.

17  

whom 113 participated in the experiment: 20 (19) Patro men (women), 18 (19) Marma men

(women), and 18 (19) Khasi men (women). We ensured that our new subject pool had no

overlap with the subject pool that played in our loan repayment game. We did this

deliberately to avoid any potential contamination effects, and it also served to provide us with

a view of any potential gender differences in risk preferences in the three societies.

Four to six subjects—belonging to the same community and same gender—

participated in each session. Unlike the loan repayment game, however, subjects participated

individually in the risk aversion experiments. Thus, a subject’s payout from this game was

not affected by the decision of the other participants in the same session. Each subject

received 120 BDT. She/he then decided whether to bet the entire endowment in a risky

lottery. The lottery returned 300 BDT with a probability of 2/5 and nothing with a probability

of 3/5. We took subjects individually to a private room where they revealed their lottery

purchase decision.23 Those who chose not to buy the lottery left the experimental site with

120 BDT (plus the show-up fee). Those who decided to play the lottery chose a ball

randomly from a non-transparent jar containing two green and three red balls. If a red ball

was picked, the participant received nothing from the gamble. If a green ball was picked,

she/he received 300 BDT. Appendix B provides the experimental instructions.

The purpose of conducting this game was to see if we could detect any potential

gender differences in risk taking behavior over similar monetary stakes involved in our main

loan repayment game. In the loan repayment game described earlier, by contributing to the

group repayment pot, a subject risks a maximum of 120 BDT: A subject loses the entire

project return when she/he contributes to the group repayment but the game does not proceed

to the next round because there is not enough contribution by the other group members. By

contrast, if the game proceeds up to the fifth round, and all of the group members repay their

share of the loan in every round, a subject earns a total of 300 BDT. In the additional risk

experiments described above, a subject could invest 120 BDT in the risky bet, and if she/he

selected the lottery option, her/his payoff ranged between 0 and 300 BDT. We choose the

probability distribution of success and failure such that the expected value of the lottery turns

out to be zero. The underlying assumption is that a risk averse individual does not buy a fair

lottery (see, for example, Kreps 1990; and Varian 1992). Thus, subjects who denied buying

this lottery can be considered as risk averse individuals (see also Chakravarty and Shahriar

2015).                                                             23 We took them to a different room so that their decisions to purchase the lottery were not affected by the other subjects’ choice.

18  

Table 5 presents the summary choices, split by gender across the three societies. It is

evident that there are no gender differences in risk preference within any of the three societies.

In the patriarchal Patro, 45% (42%) of the male (female) subjects rejected the fair lottery. In

the gender-neutral Marma, 33% (31%) of the male (female) subjects; and in the matrilineal

Khasi society, 39% (37%) of the male (female) subjects, rejected the fair lottery. A two-

sample t-test (assuming unequal variances and unequal sample sizes) rejects the hypothesis

that men have different risk aversion than women in the three societies where we conducted

our experiments.24 Thus, subjects’ (potentially distinct) attitudes towards risk can be excluded

as an alternative explanation of our findings.

[Insert Table 5 here]

D. Discussion of Findings

Contemporary research suggests that gender differences in attitude toward

cooperation may have an evolutionary or biological natural basis. Biological research, for

instance, suggests that the ability to engage in pro-social cooperative behavior is influenced

by the neuropeptide oxytocin (Carter et al. 1992; Insel and Young 2001; Kosfeld et al. 2005;

Zak, Kurzban, and Matnzer 2005) and that the magnitude of oxytocin release is significantly

higher among women than among men (Carter 2007). Evolutionary psychologists argue that

historically, men and women invested differently in reproductive and child-rearing activities,

which have resulted in different dispositions among them (Gangestad and Simpson 2000; and

Buss and Kenrick 1998). Ancestral men, for instance, competed with other men for sexual

access to women, which resulted in a male disposition that favors aggression and rivalry.

Ancestral women, on the other hand, invested in the development of long-term relationships

with their sexual partners to protect the future of their offspring. Thus, women evolved traits

that favor trustworthiness and cooperation (Wood and Eagley 2002).

Furthermore, studies in neuroscience suggest that male brains are programmed to

systemize and female brains are programmed to empathize (Baron-Cohen 2003). Accordingly,

                                                            24 Gneezy et al. (2009) did not find any significant gender differences in risk taking behavior among the patriarchal Maasai and matrilineal Khasi. Gong and Yang (2012), however, found that women are more risk averse than men in both matrilineal Mosuo and the patriarchal Yi societies in China. Gong and Yan argue that the different findings could possibly be attributed to the different monetary stakes involved in the two risk-taking experiments (p. 64). Our findings suggest that—over similar monetary stakes involved in our main loan repayment game—there is no gender difference in risk taking behavior in any of the three societies where we conducted the loan repayment game.

19  

men are more able to analyze a system in terms of the rules that govern the system.25 Women,

by contrast, are naturally better in empathizing by intuitively sensing others' emotional states.

This explains, at least partially, why women borrowers of the Grameen Bank in Rahman’s

(1999) study may have displayed more sensitivity towards verbal pressures heaped on them

by fellow group members when repayment difficulties arose. By contrast, male borrowers—

under similar conditions—had an easier time shaking off such pressures (see also Morduch

1999). Baron-Cohen et al. further argue that the empathizing-systemizing dichotomy of

gender differences has its root in biology and is therefore not likely to be affected by the

specific social context (Baron-Cohen, Nickmeyer, and Belmonte 2005). In sum, it appears

that there might be a “natural” basis for the results that we uncover.

IV. Conclusion

Recent research in economics provides numerous examples of significant gender

differences in behaviors. Three studies deserve to be singled out for their contribution in

furthering our understanding of what may be fundamentally driving gender-differentiated

behaviors. Eckel and Füllbrunn (2015) highlight the fact that all-male financial asset markets

appear to generate higher speculative bubbles than all-female markets, the implication being

that a mixed male-female trading floor might lead to less testosterone-driven competitive

behavior and our financial markets would be significantly better off as a result. Gneezy et al.

(2009) introduce a simple competitive task of ball throwing in a bucket among distinct

societies and conclude that the lower competitive inclination of women is a product of their

relative environments. In a follow-up study, Andersen, Ertac, Gneezy, List, and Maximiano

(2013) extend their 2009 study by investigating if women are born less competitive or if they

become so through socialization. Using the same competitive task as employed in Gneezy et

al. (2009), across patriarchal and matrilineal societies, they report that girls become less

competitive around puberty in the patriarchal society. However, what struck us is the fact that

all of the above-mentioned studies employed experimental tasks that were inherently

competitive in nature.

That led us to ask a simple question: Would the results reported above still hold if the

fundamental nature of the game employed were to be changed from one that is inherently

competitive to one that is inherently cooperative? Thus began our quest of finding an

appropriate cooperative game that we could introduce among experimental subjects in

                                                            25 Baron-Cohen (2003) argues that this explains why men commit fewer errors, require less time to complete a virtual maze, score higher on engineering and physics, and perform better in navigation and map reading.

20  

similarly distinct societies to see if these reported results would still hold. Eventually, we

turned to group-based microlending, which also has a history of gender-related distinctions,

including the fact that globally, more than 70% of the microcredit-borrowers are women

(Maes and Reed 2012). The advantage of a game involving group dynamics is that it includes

the well-known joint liability feature embedded in most, if not all, of group lending around

the world. The joint liability feature ensures that the group as a whole has to come through

with loan repayments for the individuals in that group to be successful. It is this feature that

makes these types of loans, and games related to such group-based lending, a primarily

cooperative game.

We conducted a (joint liability-based) microloan repayment game within the

patriarchal Patro, matrilineal Khasi, and the gender-neutral Marma societies, all in close

geographic proximity in Eastern Bangladesh. If the underlying nature of the game itself had

no relevance, we would see results similar to those reported by the above authors employing

competitive games. The results of our experiments, however, show that women display

significantly greater willingness to be cooperative by repaying their loans relative to the men

in each of the three distinct societies we investigated. The major conclusion of our study is

that the underlying nature of the game itself is an important determinant of what we would

find in gender differentiated behaviors; and that employing a task that is fundamentally

cooperative rather than competitive brings out a different side among women (and men) in

the patriarchal, matrilineal, and gender-neutral societies. We delve deeper in trying to

understand what may be driving our findings regarding the unconditional superiority of

women across these distinct societies in the cooperative task. We find strong support in the

literature that our findings of women being “naturally” better than men in cooperative games,

independent of their relative socialization, may in fact have an evolutionary or biological

basis.

Our findings also have important implications for the microfinance community at

large. In recent years, the rapid commercialization of microfinance has changed the

institutional logic of lenders across the globe. Although microfinance institutions were

initially motivated by Muhammad Yunus’s vision of poverty alleviation and the

empowerment of women, the more recent entrants in this arena have made profit

maximization their dominant strategy, thereby resembling a commercial bank with

shareholders to satisfy (Battilana and Dorado 2010). This, in turn, has influenced their goals,

client selection, and other management principles, all geared towards generating profits at the

expense of outreach and poverty alleviation. Examples of such behavior include the

21  

observation that many micro-lenders have curtailed outreach to women because they are

costly to reach (e.g., Cull, Demirguc-Kunt, and Morduch 2011; and Wagenner 2012). Against

this backdrop, our findings suggest that micro-lenders operating in Bangladesh and in similar

underdeveloped economies around the world would do better by not scaling back on their

outreach activities to women even in harder to reach areas. By lending to women borrowers,

they would actually be able to maintain relatively lower costs of default (see also D’espallier,

Guérin, and Mersland 2011). In fact, our paper might serve as a clarion call to microfinance

institutions of all stripes to actively support events and provide financial incentives to

encourage women to leave the perimeters of their homes and to join such group-based

microlending programs.

22  

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TABLE 1—PAYOFF ALLOCATION IN A GIVEN ROUND OF PLAY

Outcome of the project Repayment decision of the subject

Subject’s net payout Proceed to the next round?

Failure Default 0

If at least three partners repay Yes

If less than three partners repay No

Success Default 120

If at least three partners repay Yes

If less than three partners repay No

Success Repay

If four partners repay 60 Yes If three partners repay 45 Yes If two partners repay 20 Yes If less than two partners repay 0 No

27  

TABLE 2—SUMMARY STATISTICS

All subjects Mean (Std. Dev.)

Khasi subjects Mean (Std. Dev.)

Patro subjects Mean (Std. Dev.)

Marma subjects Mean (Std. Dev.)

Pooled Male Female Pooled Male Female Pooled Male Female Pooled Male Female

Age 29.6 (10.62)

28.08 (10.71)

30.92 (10.38)

30.80 (10.11)

31.00 (10.75)

30.65 (9.61)

32.33 (12.11)

31.23 (12.54)

33.5 (11.06)

26.1 (8.82)

22.45 (5.42)

29.28 (9.93)

Education 5.31 (4.38)

5.7 (4.4)

4.97 (4.33)

3.17 (3.19)

3.05 (3.08)

3.27 (3.28)

3.89 (3.90)

4.51 (4.04)

3.27 (3.66)

8.72 (3.73)

9.35 (3.22)

8.16 (4.04)

Farmer 0.27 (0.44)

0.33 (0.56)

0.21 (0.41)

0.46 (0.49)

0.67 (0.47)

0.30 (0.46)

0.15 (0.35)

0.15 (0.36)

0.15 (3.56)

0.15 (0.36)

0.16 (0.36)

0.15 (0.36)

Married 0.69 (0.46)

0.52 (0.50)

0.80 (0.39)

0.81 (0.39)

0.75 (0.43)

0.85 (0.35)

0.76 (0.43)

0.73 (0.44)

0.78 (0.41)

0.51 (0.50)

0.21 (0.41)

0.76 (0.43)

Ln(Assets)a 8.93 (4.77)

9.29 (4.61)

8.61 (4.89)

8.13 (4.95)

8.37 (4.85)

7.94 (5.03)

8.27 (5.11)

9.39 (4.58)

7.51 (5.39)

10.31 (3.93)

10.14 (4.23)

10.47 (3.65)

Dependency ratio 0.38 (0.41)

0.40 (0.41)

0.37 (0.41)

0.33 (0.32)

0.36 (0.32)

0.32 (0.31)

0.44 (0.49)

0.51 (0.59)

0.38 (0.36)

0.39 (0.42)

0.35 (0.28)

0.42 (0.52)

Income shock 0.31 (0.46)

0.27 (0.44)

0.35 (0.47)

0.39 (0.49)

0.30 (0.46)

0.45 (0.49)

0.29 (0.45)

0.32 (0.47)

0.27 (0.44)

0.25 (0.43)

0.21 (0.41)

0.28 (0.45)

Acquaintanceship 4.30 (0.54)

4.33 (0.50)

4.27 (0.56)

4.27 (0.50)

4.29 (0.48)

4.26 (0.52)

4.37 (0.56)

4.51 (0.48)

4.22 (0.59)

4.27 (0.56)

4.21 (0.50)

4.33 (0.59)

Number of subjects

430

200

230

160

70

90

120

60

60

150

70

80

a We report the natural logarithm of one plus the market value of household assets of a subject.

28  

TABLE 3—REPAYMENT DECISION BY THE SUBJECTS

Number of times a subject contributed to group repayment divided by number of opportunities to contribute Mean (Standard Deviation)

Pooled 0.53 (0.41) Patro 0.48 (0.41) Marma 0.56 (0.42) Khasi 0.54 (0.40)

Pooled Men 0.44 (0.43) Patro Men 0.37 (0.41) Marma Men 0.47 (0.45) Khasi Men 0.48 (0.43)

Pooled Women 0.61 (0.38) Patro Women 0.60 (0.39) Marma Women 0.63 (0.37) Khasi Women 0.59 (0.38)

Data are drawn from the first five rounds of the repayment game.

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TABLE 4—GENDER DIFFERENCES IN THE CONTRIBUTION TO GROUP REPAYMENT

Dependent variable: Fraction of times repaid divided by opportunities to repay Variables (1) (2) (3) Female 0.179** 0.530** 0.172** (0.041) (0.093) (0.032) Khasi 0.089 0.125 0.084 (0.066) (0.066) (0.060) Patro -0.087 -0.068 -0.103 (0.067) (0.057) (0.046) Female*Khasi -0.059 -0.131 -0.051 (0.037) (0.049) (0.026) Female*Patro 0.122 0.054 0.142** (0.045) (0.055) (0.022) Age -0.002 -0.002 -0.002 (0.002) (0.002) (0.001) Education -0.002 -0.001 -0.002 (0.006) (0.005) (0.006) Married -0.052 -0.058 -0.054 (0.032) (0.029) (0.032) Farmer -0.037 -0.035 -0.038 (0.042) (0.039) (0.047) Assets 0.0163** 0.035*** 0.017** (0.004) (0.002) (0.003) Female*Assets -0.034** (0.006) Dependency Ratio 0.173* 0.158* 0.171* (0.054) (0.047) (0.056) Income Shock -0.039 -0.038 -0.0378 (0.058) (0.066) (0.056) Acquaintanceship 0.050 (0.066) Constant 0.351** 0.140** 0.134 (0.038) (0.031) (0.254) Observations 430 430 430

2R 0.121 0.157 0.125 Notes: Results are from OLS regression. Robust standard errors, clustered at the community level, are in parentheses. Data are drawn from the first five rounds of the repayment game. *** Significant at the 1% level ** Significant at the 5% level * Significant at the 10% level

30  

TABLE 5—RAW DATA SUMMARY FOR THE RISK AVERSION GAME

Number of subjects who rejected buying the fair lottery divided by the total number of subjects in each category (Standard deviation in parentheses)

Patro Men 0.45 (0.51) Marma Men 0.33 (0.48) Khasi Men 0.39 (0.50)

Patro Women 0.42 (0.51) Marma Women 0.31 (0.47) Khasi Women 0.37 (0.49)

The data are from 20 (19) Patro men (women), 18 (19) Marma men (women), and 18 (19) Khasi men (women).

31  

APPENDIX A

Experimental Instructions for Microloan Repayment Game

Thank you for joining us today to participate in this activity and the post-activity

survey. For this activity you will belong to a group of five individuals. You will receive 50

Taka for participation. Based on the decisions you and your group members make, you can

earn more money in addition to the show-up fee. You are not allowed to talk to each other. If

you are caught talking to others, the activity will be stopped and you will be asked to leave. If

you have any questions, please raise your hand. You will be personally attended to. This

activity may consist of multiple rounds, depending on the decision you and your group

members will make. Each round will have four (4) different steps.

Step 1: The Loan

You will receive a bank loan of 50 Taka. The loan has to be repaid—with 20%

interest—in one installment. The loan repayment, however, is the joint responsibility of your

group. That means that your group as a whole is expected to repay 300 Taka. Upon

repayment of 300 Taka as a group, each member of your group—including you—will receive

another loan of 50 Taka.

Step 2: Loan Investment and Earnings

You will be individually taken to another room, where you will invest your loan (50

Taka) in a risky business. In order to determine whether your business is successful or not,

you have to pick a ball from a non-transparent jar. There are one red and five green balls in

the jar.

If you draw the red ball, your business fails and you will earn zero. That means you lose

your investment (the 50 Taka bank loan).

If you draw a green ball, your business is successful and you will earn 120 Taka. You

may use your earnings to repay your loans. The excess monies after repaying loans will

be converted into real currency at the end of this activity.

Step 3: Loan Repayment

Now you will make your decision to contribute to the group repayment of loan.

If your project failed in step 2, you will not be able to contribute, as you have no money.

If your project succeeded in step 2, you have two choices:

You may contribute to the group repayment. If you choose to repay, I will tell you—in

the next step—how much you owe to the bank.

Or you may decide not to contribute at all.

32  

After revealing your repayment decision, you will return to the large room and wait

quietly for the next step to begin. Each of your group members will go through the same

decision making process.

Step 4: Receive another Loan?

After all the members of your group make their repayment decisions, I will again take

you individually to another room. There, I will tell you how many members of your group

contributed to repayment in this round. But I will not reveal the identity of the non-

contributing members, or the reasons for non-contribution.

Suppose your project failed in step 2. In this case, you will have to rely on your partners

for receiving another loan.

If at least three members of your group contribute, you will receive another loan of 50

Taka; and the whole process will be repeated.

If less than three members contribute, you will not receive any new loan; and the

activity will end.

Suppose your project succeeded in step 2 but you decided not to contribute to group

repayment.

If at least three members of your group contribute, you will receive another loan of 50

Taka; and the whole process will be repeated.

If less than three members contribute, you will not receive any new loan; and the

activity will end.

Suppose your project succeeded in step 2 and you decided to contribute to group

repayment.

If all four members of your group contribute, I will collect 60 Taka from you. You will

receive another loan of 50 Taka; and the whole process will be repeated.

If three members of your group contribute, I will collect 75 Taka from you. You will

receive another loan of 50 Taka; and the whole process will be repeated.

If two members of your group contribute, I will collect 100 Taka from you. You will

receive another loan of 50 Taka; and the whole process will be repeated.

If less than two members contribute, I will collect 120 Taka from you. But you will not

receive any new loan. The activity will end at this point.

Payment

There will be a short interview following this activity. You will receive payment for

your participation and any earnings from today’s activity after the interview.

33  

APPENDIX B

Experimental Instructions for Risk-taking Game

Thank you for joining us today to participate in this activity. You will receive 50 Taka

for participation. Based on the decisions you make, you can earn more money in addition to

the show-up fee.

At the beginning of this activity, you will receive 120 Taka. Then, I will offer a

lottery to you. The price of the lottery is also 120 Taka. If you decide to buy it, I will collect

the 120 Taka from you as the price of the lottery. In order to determine the outcome of your

purchase, you will pick a ball from a non-transparent jar. There are three red and two green

balls in the jar. If you draw a green ball, you will receive 300 Taka. If you draw a red ball,

you will receive nothing.

If you decide not to buy the lottery, you will get the 120 Taka for sure.

Payment

There will be a short interview following this activity. You will receive payment for

your participation and any earnings from today’s activity after the interview.

If you have any questions, please raise your hand. You will be personally attended to.