Discussion Paper No. 896

OLDER SISTERS AND YOUNGER BROTHERS:THE IMPACT OF SIBLINGSON PREFERENCE FOR COMPETITION
Hiroko Okudaira
Yusuke Kinari
Noriko Mizutani
Fumio Ohtake
Akira Kawaguchi

March 2014

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Older Sisters and Younger Brothers:
The Impact of Siblings on Preference for Competition *Hiroko Okudaira †Okayama University
Yusuke Kinari ‡Kyushu University
Noriko Mizutani §Institute for Research on Household Economics
Fumio Ohtake **Osaka University
Akira Kawaguchi ††Doshisha University

This version: March 2014*

We are grateful to Yukiko Abe, Peter Kuhn, Edward Lazear, Hodaka Morita, Hideo Owan, Masaru Sasaki,
Kathryn Shaw, and seminar participants at the 2012 Trans-Pacific Labor Seminar in Hawaii for their helpfulcomments. All remaining errors are our own. We also thank Kiyoko Murahima and Shizuka Yamagiwa for theirassistance. Authors acknowledge a research grant from the Japan Society for the Promotion of Science.
Okudaira acknowledges a research grant from Okayama University.
†
Department of Economics, Okayama University, 1-1-3, Tsushima-naka, Kita-ku, Okayama city, Okayama
700-8530, Japan; okudaira@e.okayama-u.ac.jp‡
Graduate School of Economics, Kyushu University; kinari@en.kyushu-u.ac.jp§
Institute for Research on Household Economics; mizutani@kakeiken.or.jp**
Institute of Social and Economic Research, Osaka University; ohtake@iser.osaka-u.ac.jp††
Graduate School of Policy and Management, Doshisha University; akawaguc@mail.doshisha.ac.jp1Older Sisters and Younger Brothers:
The Impact of Siblings on Preference for Competition

This version: March 2014

Abstract
Studies in psychology have long argued the possibility that sibling structure, such as birthorder and the gender of siblings, shapes one’s feminine and masculine personality traits, suchas a preference for competition. In light of recent developments in the economics literature on
the gender gap, this implies that familial environment could explain why some women do opt
for competition, while the vast majority of women do not and, thus, are underrepresented on
the career ladder. By conducting a controlled experiment on Japanese high school students,
this study quantifies the impact of sibling structure on one’s preference for competition, andexamines whether a long-debated sibling hypothesis in psychology is supported from theviewpoint of experimental economics. Consistent with the hypothesis, our results reveal thatmen with older sisters were significantly less likely to enter a competitive environment
compared with only sons. This effect is comparable in size to the effect of being female on
the decision to compete. Our study also found moderate evidence that women with younger
brothers were more likely to compete than only daughters.

Journal of Economic Literature Classification Numbers: C91, D03, J16
Keywords: Sibling competition, Gender gap, Preference for competition, Experiment2

1. Introduction
Despite numerous attempts to do away with the professional gender gap over the
past decades, the so-called “glass-ceiling” on the corporate ladder is still firmly in placein many countries. According to LABORASTA and Eurostat Database, in 2010, theproportion of women in the workplace was similar across countries, ranging from
41.6% in Korea to 47.5% in France. On the other hand, the proportion of women in
managerial positions in the same year was substantially lower and varied significantly
across countries, ranging from 10.1% in Korea to 30–39% in European nations. Recent
developments in the labor economics literature have made a significant contribution in
unfolding the reason behind this gender gap in promotions, showing that otherwise
qualified women shy away from competitive environments simply because they dislike
competition (Niederle and Vesturlund, 2007). A novel component of the Niederle andVesturlund study (2007) was its method of extracting individuals’ true preference forcompetition by using a controlled experiment, where subjects were incentivized withpecuniary rewards. In particular, Niedlerle and Vesturlund (2007) asked students at the
University of Pittsburgh to engage in math-solving tasks under several payment
schemes, including a competitive tournament scheme, and showed that women weresignificantly less likely to enter into such a competitive environment. Given their results,
an important means for increasing female representation in the corporate arena is to findways to induce these “shy” women to voluntarily opt for competition.
To this end, subsequent studies have focused on whether women’s negative
attitudes toward competition are driven by nature or by nurture, as this could thendictate potential changes in policy. For example, if the gender difference in preference
for competition is innate and thus constituted from biological factors, institutional3interventions to increase female representation, such as affirmative action, would bejustified because such traits are not controlled by institutions. 7 Conversely, if
environmental or social factors contribute to such a preference it would lend support for
educational reforms to prompt social learning in women.
In an influential study suggesting for environmental factors in this preference forcompetition, Gneezy et al. (2009) conducted a simple experiment in a patriarchal tribe,
the Maasai, and a matrilineal tribe, the Khasi. They found that Maasai men opted forcompetition significantly more often than Maasai women did, while Khasi womenchose competition more often than Khasi men did. This gender difference between thetribes suggests the importance of socially defined gender roles in shaping attitudes
toward competition. Similarly, a series of studies by Alison Booth and her co-authors
revealed that single-sex schools or classrooms nurture more competitive attitudes andencourage risk-taking behavior in women (Booth et al., 2014; Booth and Nolen, 2012a,
2012b; Booth et al., 2011). 8 There is also evidence that suggests that having same-sex
instructors in introductory math or science courses encourages women to major in mathor engineering (Carrell et al., 2010), indicating that having a same-sex role model is anenvironmental factor that could induce women to make choices that they otherwise
would not.
This paper designed a laboratory experiment to determine whether the gender gap
in preference for competition arises from another environmental factor, namely familial
7‘By-nature’ studies reported that gender differences in competitive attitudes are influenced by thefluctuation of sex hormones (Buser, 2012; Wozniak et al., 2014; Guéguen, 2012; Dreber and Hoffman,
2007; Archer, 2006; Hoffman and Gneezy, 2010). Prenatal exposure to male sex hormones is also known
to predict long-term profitability in financial traders in the City of London (Coates et al., 2009) andperformance in sports, such as rankings for sumo-wrestlers (Tamiya et al., 2012).
8
Fryer and Levitt (2012) obtained evidence suggesting that gender inequality translates into poor female
math performance only after excluding participants from Islamic countries where classrooms aresegregated by gender.

4

environment, to which little attention has been paid in the economics literature. In
particular, we examined whether sibling structure, such as birth-order or the gender ofother siblings, shapes one’s propensity to compete.
Sibling structure may be an especially important environmental contributor topersonality because, according to some psychologists, through interactions with theirsiblings, some women may grow to willingly take part in competition. Based on an
observational study by Koch (1954) on primary school students and their siblings, Brim
(1958) reported a tendency for mixed-gender sibling pairs to assimilate traits more
typically associated with the opposite-sex. For instance, older girls with younger
brothers are reported to have more masculine traits than their counterparts who haveyounger sisters, with masculine traits defined as characteristics like “competitiveness”
or “self-confidence.” Similarly, boys with older sisters are considered to be substantiallymore feminine than their counterparts with older brothers, feminine traits constituting
more expressive characteristics such as “kindness” or “friendliness.” 9 Interestingly, thiseffect was stronger in older sister and younger brother pairs compared with older
brother and younger sister pairs. While the interaction among cross-gender sibling pairs
alone could not explain this particular trend, similar phenomena specific to therelationship of older sisters and younger brothers have been raised in otherpsychological studies (ex. Stewart, 1982).
Sulloway (1996) provides a possible explanation for this trend by suggestingthat the effects unique to an older sister / younger brother relationship arise as a result ofa mixture of birth order and role-taking. Sulloway’s (1996) rationale for the effect ofbirth order on personality traits is based on the idea of sibling competition in
9

Feminine or masculine traits were identified from teachers’ ratings of their students, based on a
personality classification used in several empirical studies (Brim, 1958).

5

evolutionary science. Based on Darwin’s principle of divergence, Sulloway (1996)
argues that siblings differ in their strategies for attracting parental investment dependingon their birth order, which eventually comes to shape their personality traits.
Specifically, first-born children tend to be more dominant, aggressive, and ambitious, aswell as more conservative than later-born children. This is in order to meet their parents’
expectations and standards, thereby defending their stakes against younger rivals inregards to their parents’ allocation of resources (Sulloway, 1996). 10 Thus, first-born
children, regardless if they are male or female, act as the “alpha-male” in their sibling
system (Sulloway, 1996). This could then explain why Brim (1958) observed thestronger “role-taking effect” in older sister / younger brother pairs than for older brother/ younger sister pairs.
However, not all psychologists agree with the view that sibling dynamics,
especially birth order, have systematic influences on personality traits. In fact, this is
one of the longest debated issues in psychology. While birth order effects on personality
were first observed as early by Adler (1928), and have since been tested in thousands ofstudies, a review of the literature by Ernst and Angst (1983) concluded that there were
only negligible birth order effects across personality variables. However, subsequentstudies, including Sulloway (1996), have attacked the critique by Ernst and Angst(1983). One of the core issues at play is who rated the participants’ personality traits ineach of the studies. Some investigations reported observations consistent with Sulloway(1996) when personality traits were rated by family members, but not when they wererated by peers or by the subject him or herself (Jefferson et al., 1998; Paulhus et al.,
1999; Saroglou and Fiasse, 2003). However, other studies compared several ratings (self,
10

Studies have empirically confirmed this birth order theory by directly comparing personality traits(Sulloway and Zweigenhaft, 2010; Healey and Ellis, 2007).

6

peer, and parent) of personality traits and found no difference between these ratings(Marini and Kurtz, 2011).
This paper goes beyond these past psychological studies by obtaining information
regarding one of the key personality traits, preference for competition, using acontrolled experiment similar to that used by Niederele and Vesturlund (2007), rather
than through subjective ratings. In our experiment, Japanese high school students wereasked to solve as many mazes as possible in several tasks with different payment
schemes. In order to examine whether individuals opt for a competitive environment,
the experimenter asked subjects to select whether they wanted to be compensated undera piece-rate or tournament before they started solving mazes. Since the reward under the
tournament scheme depended on the performance of the other members in a randomly
assigned group, entry into a tournament represents a voluntary choice for a competitiveenvironment. We then examined what factors, including sibling structure, accounted fortournament choice, and tested whether a long-debated sibling hypothesis in psychology
is supported from the viewpoint of experimental economics.
Our study supports the implications stated in Sulloway (1996): males who haveolder sisters are significantly less likely to choose a tournament scheme than males who
have no siblings, while females with younger brothers were more likely to choose
tournaments than only daughters were. The magnitude of the effect of sibling structure
on competition preference are quite large, with the older sister effect alone cancellingout the typical aversion to tournament entry generally observed among females.

72. Methods
2-1. Participants
One hundred and thirty-five students from four high schools in the Kyoto area ofJapan participated in the study. Participants attended one of four sessions that took placeon July 16 and 22 and October 1, 2011. Five confederates took part in the experiment tomake up for last-minute participant cancellations, as the experiment had to be conductedin groups of four. Data from the confederates were eliminated from the analysis,
although the exclusion of data from subjects who happened to be in the same group as
the confederates did not significantly affect the results. Each subject was assigned to agroup of four participants and had to solve as many mazes as possible under several
payment schemes. Subjects sat in individual booths and were not told where the othermembers of their group sat or how the others performed until the end of the experiment.
It should be noted that students in the current study had relatively fewer siblings than
the average number of siblings (1.46) reported in the Japanese Survey on Household
Trends (JSHT) conducted by the Ministry of Health, Labour and Welfare. Thus, thepresent sample has relatively lower variation in sibling composition than a larger
representative of teenagers in Japan.

2-2. Experimental design and procedure
Experimental design largely followed the framework used by Niederle and
Versturlund (2007). The experiment consisted of a practice session and six tasks. In thepractice session, subjects solved mazes on a computer screen for one minute to learn thesolutions to the mazes. Figure 1 shows a screenshot of the subjects’ display. Subjects

8

moved cursors from the start to the goal point by using arrow keys on their keyboard.
They could skip as many mazes as they wanted by clicking a skip button on their screen
to move to the next maze. They received no payment for their performance in thepractice session. After completing the practice session, subjects moved on to the actualtasks, where they were required to solve as many mazes as possible in three minutes
under different payment schemes. In Task 1, subjects were paid on a piece rate: theyreceived 25 points for every correctly solved maze. Task 2 employed a tournament
payment scheme: the subject who correctly solved the largest number of mazes in eachgroup received 100 points for every correctly solved maze, while the other threemembers received zero points. Since points earned under the tournament payment
scheme depended on the performance of the other three members in the same group,
subjects were exposed to a competitive environment under the tournament payment
scheme. The two payment schemes were repeated in Tasks 3 and 4, as improvements inperformance between the two payment schemes could reflect a learning effect rather
than an actual response to competition. In Task 5, subjects were asked to choose
whether they wanted to be paid under a piece-rate or tournament scheme before solving
the mazes. The choice in Task 5 was then used to measure each subject’s propensity tocompete.
Importantly, just because a subject chooses to participate in the tournamentscheme in Task 5, it does not immediately indicate that he or she prefers competition.
The choice in Task 5 can also reflect factors not directly related to the preference forcompetition. For example, some might choose the tournament scheme because they
overestimate their relative abilities in a group (overconfidence). Others might choose
the piece-rate scheme because they are risk-averse (risk aversion) or dislike being
9

informed about their performance relative to others (feedback aversion). It is also
possible that some subjects choose the tournament because they know that theirmaze-solving abilities are sufficiently high (performance level).
The goal of implementing Task 6 was to reveal whether the participants’decision to compete in Task 5 could be explained solely by the reasons mentioned above
or because subjects had a higher preference for competition. In Task 6, subjects wereasked to choose whether they wanted to be compensated under the piece-rate or
tournament scheme for their performance in Task 3, the second piece-rate task. If
participants chose the piece-rate scheme, they received 25 points for every correctly
solved maze in Task 3; if they chose the tournament scheme, they received 100 points
for every correctly solved maze in Task 3 if they were the best performer and zero
points if they were not. Because this payment was based on their past performance,
subjects did not solve any mazes in Task 6 but speculated on their relative performancewithin the group. Thus, participants’ choices in Task 6 were influenced by factors suchas overconfidence, risk-aversion, feedback aversion, and performance level, but not by
the preference for competition (Niederle and Vesterlund, 2007). Conversely, choices in
Task 5 involved actual competition as well as speculation on their relative performance.
Thus, the decision to enter competition in Task 5 could be seen as reflecting individual
tastes for participating in competitions, in addition to overconfidence, risk aversion, andfeedback aversion. By examining the differences in payment scheme choices between
Tasks 5 and 6, individual preferences for competition would be revealed.
After completing Tasks 1–5, subjects were asked to guess their rank in theirgroup by entering the subjective probability distribution of their rank. For example, asubject would type 100% for rank 1 and 0% for ranks 2 to 4 if he or she was very10

confident that he or she was the best performer in the group. The estimated expected
ranks were then used to infer the extent of overconfidence for analysis. Unlike in
Niederle and Vesterlund (2007), subjects were not paid for each correct guess of theirrank. 11
To accurately evaluate participants’ attitudes toward competition, students wereincentivized in the following way. At the end of the experiment, subjects drew a lottery
and randomly selected one task among the six for which the reward was actually given.
Students were paid according to the points earned in the selected task, plus 500 points
for a participation fee. Subjects were given prizes for their points instead of cash
because cash transactions were prohibited by the high schools. The prizes consisted ofvarious stationery items, and subjects received different combinations of these items
depending on their performance. 12 Special care was taken not to mention the specificprizes that subjects would receive until the end of the experiment because the subjective
value of the prizes could vary across subjects; subjects were simply told to earn as many
points as possible.
At the end of the experiment, participants were asked to complete aquestionnaire asking about demographic information, including sibling composition.
The information was used to examine the extent to which sibling structure
systematically affected a subject’s choice for the tournament scheme in Tasks 5 and 6,
thereby revealing their preference for competition.

11

This is due to the fact that some students chose a strategy of solving no mazes and picked rank 4 in our
early version of the experiment.
12
Prizes were selected with permission from the high schools. Prizes included three colored clips (25points), a clear folder (50 points), memo-pad (100 points), five colored pens (500 points), a mechanicalpencil plus a plastic school bag (1000 points), and a fabric school bag (1500 points). At the end ofexperiment, students received a combination of these rewards. 100 points are roughly equivalent to 100
JPY, which is about 1 USD at the time of writing.

11

3. Results
3-1. Testing Sibling Hypothesis
Figure 2 presents the proportion of participants who chose to compete in thetournament in Task 5 by gender and sibling composition. The graphs are consistent withthe sibling hypothesis suggested by Brim (1958) and Sulloway (1996). Despite the factthat men generally entered the tournament more often than women did, the gender gap
was remarkably reduced when certain groups of subjects were compared. For example,
while 38% of men who have an older sister entered the tournament in Task 5, 39% of
women who have a younger brother also chose the tournament scheme. However, thevariation in preference for competition by sibling composition is not immediately
evident in Figure 2. As mentioned in section 2, the raw differences in tournament choice
could indicate variation in the other confounding factors, such as overconfidence, risk
aversion, feedback aversion, and performance level.
For this reason, we formally tested our hypothesis by estimating a probit modelof payment scheme choice at Task 5, where the dependent variable equaled one if asubject chose the tournament payment scheme and zero otherwise. This model controls
for performance level, as well as the tournament choice at Task 6 (e.g., overconfidence,risk aversion, feedback aversion). Since the choice at Task 6 did not involve themaze-solving task, but because subjects still had to speculate on how many mazes theother members in their group solved, controlling for the tournament choice at Task 6
removes the factors other than preference for competition. Performance in Tasks 3 and 4
was used to measure the actual performance level of subjects in order to alleviate any
learning effects, as the number of correctly solved mazes increased in later tasks, as

12

reported in Table 1.
Table 2 shows the estimated marginal effects from probit models of tournament
choice in Task 5, where sibling composition dummies and their interactions with afemale dummy are included in columns (a) and (b). The baseline for siblingcomposition dummies is “only sons.” Columns (a) confirms that sibling composition
significantly affected the decision to enter the tournament in Task 5 using a probit
estimation. For instance, having older or younger sisters significantly reduced theprobability of a male entering the tournament compared with men who are only sons.
Similarly, the estimated coefficient for women who have younger brothers is
significantly positive (0.314), although the total effect of having younger brothers
compared with being an only daughter (0.314 and -0.327) only moderately differs fromzero (p-value = 0.0973). In column (b), these effects remained after controlling for
performance level and choice of tournament entry in Task 6, except for the effect ofmen with younger sisters. Conditional upon performance level and the decision in Task
6, compared with only sons, having older sisters reduced men’s propensity to select thetournament scheme by 35%. This decrease is comparable to the negative effect of being
female on tournament choice (-0.371). Having younger brothers increased theprobability of women entering the tournament, although the total effect is only
marginally significant (p-value = 0.1108). 13
As a reference, columns (c), (d), and (e) report estimation results similar to
Niederle and Vesturlund (2007), testing whether women shy away from competition
simply because they dislike it. According to column (a), women are 37.6% less likely
than men to select the tournament scheme. This significant gender effect remains even
13

However, note that a coefficient of “Has any younger brothers” is not significantly estimated.

13

after controlling for subjects’ performance level, as well as other general factors such as
the extent of overconfidence listed in columns (d) and (e). This suggests that women did
not enter the tournament in Task 5 because of the other factors (e.g., overconfidence,risk aversion, feedback aversion, performance level) as was concluded in the Niederle
and Vesturlund study (2007). The estimated negative effect of being female on
tournament choice in column (e) is twice that found in Niederle and Vesterlund (2007).
The Appendix Table presents similar results as Table 2, but with the dependent
variable replaced by tournament choice in Task 6, where no maze-solving activity was
involved. No significant effects were found for either the female dummy or the siblingcomposition dummies in the Appendix Table, indicating that differences relating tosibling composition were due to personal preference for competition, not to
performance level, and the other factors. This is consistent with our findings in Table 2,
where the size of negative effect of being female remains similar across specifications.
Thus, preference for competition plays a major role in explaining the differences bygender and sibling composition in tournament entry in Task 5.
Table 3 tests several hypotheses that attempt to explain why sibling composition,such as having an older sister, may affect preference for competitive environments.
Specifically, we directly test the original sibling hypothesis proposed by Brim (1958)
and Sulloway (1996) by adding birth order terms as well as cross-gender siblingdummies. As in Table 2, the dependent variable was assigned a value of one if a subject
selected the tournament payment scheme in Task 5 and zero if they did not. All analyses
controlled for the same set of explanatory variables as in column (e) of Table 2, butsome estimates are not presented in the table to save the space.
In column (a), birth order and its interaction term with a female dummy are14

included. Columns (b) and (c) include first-born, middle-born, and last-born dummies toaccount for the possibility that the effect of birth order is non-linear. The basis for thesedummies is a dummy of an only child in the family in column (c). Both columns (a) and(b) report no significant estimates for birth order and first-born dummy, but there was asignificant positive estimate for an interaction between middle-born and female
dummies in column (c). The null hypothesis that the total effect of being a middle-born
female child (0.502 and -0.231) is zero can moderately be rejected (p-value = 0.081).
This result is consistent with the birth order hypothesis proposed by Sulloway (1996),
where middle-born children are reported to fare less well than their older and younger
siblings, and thus are more likely to be rebellious.
Columns (d) and (e) examine the possibility that the total number ofcross-gender siblings, rather than the relative order among siblings, is important inshaping preferences for competition. Along these lines, Brunello (2013) found that only
having sisters at the age of 15 significantly increased the probability of engaging inleadership activities in middle and high school for both girls and boys in the U.S., andthat it increased the probability of participating in sports clubs for Japanese boys.
Although no such effect is detected in our analysis in column (e), the number of female
siblings does decrease the probability of men entering the tournament scheme in column(d). Surprisingly, the magnitude of having one sister is comparable to the negative entry
effect observed among women: having one sister reduces the probability of men
entering the tournament by 35.3%.

3-2. How much did they gain or lose?
While some women are averse to entering competitive environments, resulting15

in them being underrepresented on the corporate ladder, women with younger brothers
may gain by making “right” decisions to enter the competition when they are likely towin. To assess the magnitude of sibling structure on subjects’ welfare, Figure 3 shows
how much subjects gained or lost by selecting or avoiding a competitive environment.
Specifically, it indicates the average cost of over or under entry into the tournament in
Task 5, measured by experiment-point. The costs were calculated by estimating the
expected losses or gains from entering the tournament, and then taking the difference
from the actual points earned in Task 5. 14 Tables under the graph show the proportionof those who entered the tournament when they should not have (i.e., their expected
gain for not entering the tournament is higher), along with the proportion of those who
did not enter the tournament when they should (i.e., their expected gain from entering
the tournament is higher). Overall, the cost of under-entry is larger for women than formen, but the cost of over-entry is smaller for women. However, these costs varysignificantly across sibling composition: among women, those who have younger
brothers suffered the least from under-entry as they entered the tournament more often.
On the other hand, men who have older sisters incurred the least over-entry cost by notentering the tournament as much. Interestingly, women who have younger brothers
suffered from the largest over-entry cost among women; older sisters with younger
brothers decided to compete too often, even when they should not have based on theirperformance.
14

The expected gains and losses from entering the tournament were calculated by randomly assigningeach subject into a group of four students 100,000 times in order to estimate their probability of winning
the tournament in Task 5. For instance, for those who correctly solved 12 mazes, the probability ofwinning the tournament was 18.2%, so the expected gain from entering the tournament (218.4 points)
would be lower than the expected gain from choosing the piece-rate (300 points). For those who correctly
solved 13 mazes, the probability of winning the tournament was 36.8%; thus, these participants shouldhave entered the tournament because the expected gain, 477.8 points, was higher than the piece-rate
reward (325 points). It was assumed that the cost of solving mazes is zero for all subjects and that theirperformance was independent of the payment scheme.

16

4. Discussion
This study explored a previously uninvestigated environmental factor that could
have a considerable influence on an individual’s decision to compete. We conducted asimple laboratory experiment similar to the one designed by Niederle and Vesterlund(2007) on Japanese high school students. Our experiment showed that women weresignificantly less likely to choose to compete than men were, which is consistent withthe findings of Niederle and Vesterlund (2007). More importantly, we also found thatthe decision to compete varied significantly according to sibling structure, thereby
supporting the long-debated sibling hypothesis in psychology from the viewpoint ofexperimental economics.
One interesting finding reported here that is consistent with previous studies isthat middle-born females showed a higher propensity to choose the tournament option
in Task 5. According to Sulloway (1996), middle-born children are “losers in …
Darwinian calculus,” not only because the higher reproductive value of the first-born
child encourages parents to invest more in first-borns, but also because a last-born childis “the only member of the family to receive parental investment undiluted by the needsof a younger rival.” Indeed, according to Salmon and Daly (1998), middle-born children
are significantly less likely to nominate their mothers as the person they feel closest to
than first- or last-born children, implying that middle-born children receive less parental
investment. Surrounded by both older and younger rivals, the disadvantaged
middle-born child is required to be even more aggressive in the competition for parental
resources. The results in column (c) of Table 3 hint at this propensity to compete in
middle-born women.
Another interesting finding is that men with older sisters were no more likely to17compete than women were, while women with younger brothers were more likely tocompete when compared with women who are only daughters, although this result isonly moderately significant (column (b), Table 2). This finding is in line with
Sulloway’s (1996) theory, where he suggests a combined effect of birth order andcross-gender sibling dynamics on older sister / younger brother pairs. While Sulloway’s(1996) explanation is derived from evolutionary science, where older siblings haveadvantages when competing for parental investments, other psychological mechanisms
are also thought to play a role. Stewart (1983) observed the behaviors of preschool
children when they were left alone with their infant siblings, and found that older
siblings were most active when caring for their younger cross-gender siblings. Oldersisters in particular tended to give far more care to their younger brothers than wassought (Stewart, 1983). This study, along with that of Brim (1958), indicate thatyounger brothers with “meddlesome” older sisters may not have to compete as much forthe limited resources of parents, which may have provided them with fewer
opportunities to nurture their competitive attitudes. Thus, the systematic trend observedin the preference for competition among older sister and younger brother pairs may
arise not only from sibling competition, as originally suggested by evolutionary science,but also from an interaction specific to this pair, as raised in some psychological studies.
Finally, and most importantly, our study lends support for institutional reforms
that promote interactions between women and younger men. Exposing women toexperiences where they are in a position to overrule younger men may help cultivate
their willingness to compete with men. This tactic may be especially effective inpatriarchal societies and should be started at an early age, as observed by Stewart(1983).
18

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20

The payment

The remaining time.

system for the

Number of solved mazes
for the on-going task.
Number of the current task.

on-going task.

Skip button.
The next maze
will appear uponclicking on thisbutton.

Solve the maze by
moving the cursor
to the finish using
the arrow keys.
Numbers of correctly solved mazes for thecompleted tasks.

Figure 1. Overview of Basic Screen

21Table 1. Summary statistics (mean)

Male

FemaleAge
Number of siblings
Number of female siblings
Birth order

16.90
1.10
0.68
1.51

16.82
0.96
0.60
1.52

Tournament Choice in Task 5 (=1)
Tournament Choice in Task 6 (=1)

0.61
0.37

0.23
0.27

Task 1 performance (piece-rate)
Task 2 performance (tournament)
Task 3 performance (piece-rate)
Task 4 performance (tournament)
Task 5 performance (choice)
Guessed rank in Task 3
Guessed rank in Task 4

11.02
12.00
12.51
12.24
12.95
2.17
2.15

9.88
10.74
11.44
11.63
11.71
2.51
2.54

Average points earned per Task
Cost of over-entry (Task 5)
Cost of under-entry (Task 5)437.7067.07
203.05343.4436.17
288.8341

94

Number of Observations

22

0

.2

.4

.6

.8

(A) Maleolder brosolder sisonly child younger bros younger sis

0

.2

.4

.6

.8

(B) Female

older brosolder sisonly child younger bros younger sis

Figure 2. Proportion of participants who chose to compete in Task 5 by siblingcomposition
Note. The leftmost bar indicates the proportion of tournament entries for subjects who have an older
brother, for instance.

23

Table 2. Probit of decision to compete in Task 5

Female(a)-0.569***(0.110)Submitting the tournament in Task 6
Performance in Task 4
Differences in performances (Task3 - Task4)
Guessed rank in Task 4
Has any younger brothers
Has any younger brothers * female
Has any older brothers
Has any older brothers * female
Has any younger sisters
Has any younger sisters * female
Has any older sisters
Has any older sisters * female

Number of Observations
Log Likelihood
Psuedo R-squared-0.327(0.262)0.314**(0.128)0.060(0.217)-0.032(0.261)-0.250**(0.108)0.334(0.244)-0.245**(0.116)0.440**(0.182)135-73.140.162

Marginal effect (standard error)
(b)
(c )
(d)
-0.371**-0.376***-0.310***(0.148)(0.088)(0.098)0.272**(0.127)0.003
0.012(0.032)(0.024)-0.057-0.0678***(0.040)(0.026)-0.163**-0.172***(0.081)(0.066)-0.283(0.192)0.490***(0.184)0.170(0.190)-0.131(0.316)-0.228(0.203)0.178(0.230)-0.350**(0.193)0.348**(0.156)
135
-64.4
0.262

135
-78.570.0995135-71.590.179(e)-0.323***(0.092)0.220**(0.106)0.010(0.030)-0.0552*(0.033)-0.177**(0.075)135-69.190.207

Note. This table reprents the marginal effects from probit model estimation. The dependent variable is given a value of 1 if the subject
selected the tournament payment scheme in Task 5, else it is assigned a 0. Marginal effects are evaluated for a female with an average
number of correct answers in Tasks 3 and 4, who chooses the tournament option, believes she is ranked second on Task 4, and has ayounger brother. The base for the sibling dummies is an only child. *** p<0.01, ** p<0.075, * p<0.1.

24

Table 3. The impact of sibling structure on the decision to compete in Task 5

FemaleBirth order
Birth order * female

Marginal effect (standard error)
(b)
(c )
(d)
-0.349***-0.493***-0.391***(0.102)(0.125)(0.123)(a)-0.417**(0.187)-0.00218(0.136)
0.0545(0.168)First born

-0.106(0.180)0.082(0.210)First born * female
Middle born
Middle born * female
Last born
Last born * female-0.177(0.252)0.27(0.197)-0.231(0.181)0.502***(0.157)0.102(0.308)0.156(0.362)

Number of female siblings-0.353**(0.181)0.374*(0.216)-0.0302(0.163)0.243(0.204)

Number of female siblings * female
Number of male siblings
Number of male siblings * female
Having same-sex siblings only

0.228
(0.204)-0.219(0.197)

Having same-sex siblings only * female

Number of Observations
Log Likelihood
Psuedo R-squared(e)-0.277**(0.117)135-72.130.173

135-69.000.209

135-66.710.235

135-65.160.253

135-68.610.214

Note. This table reprents the marginal effects from probit model estimation. The dependent variable is given a value of 1 if thesubject selected the tournament payment scheme in Task 5, else it is assigned a 0. All estimations control for a dummy toindicate the choice of tournament in Task 6, the number of correctly solved mazes in Task 4, the difference in performance inTasks 3 and 4, and the guessed rank in Task 4. Marginal effects are evaluated for a female with an average number of correct
answers in Tasks 3 and 4, who chooses the tournament option, believes she is ranked second on Task 4, and for columns (a),(b), and (c) is the first-born child, for column (d) has one brother, and for column (e) has siblings of both gender.. *** p<0.01, **p<0.075, * p<0.1.

25

0

100

200

300

400

(A) Maleolder bros

Should not enter
Should enter

older bros
16.7%
16.7%

older sisolder sis
12.5%
12.5%

only child younger bros younger sis
only child
57.1%
28.6%

younger bros
25.0%
25.0%

younger sis
15.8%
21.1%

0

100

200

300

400

(B) Female

older brosolder sisonly child younger bros younger sis

older brosolder sisonly childyounger brosyounger sis

Should not enter

6.7%

12.5%

5.0%

38.9%

16.7%

Should enter

33.3%

28.1%

40.0%

16.7%

22.2%

Figure 3. Average cost of over-entry (Blue) and under-entry (Red) in Task 5
Note. Bars indicate the average costs of under/over-entry into the tournament in Task 5. The vertical axis
measures the costs in experiment points. Tables under the graph show the proportion of those whoentered the tournament when they should not have (i.e., their expected gain for not entering thetournament is higher), and the proportion of those who did not enter the tournament when they shouldhave (i.e., their expected gain for entering the tournament is higher).

26

Appendix Table. Probit of decision to compete in Task 6 (no maze-solving activity)

Female(a)-0.159(0.188)Performance in Task 3
Differences in performances (Task3 - Task4)
Guessed rank in Task 3
Has any young brothers
Has any young brothers * female
Has any older brothers
Has any older brothers *female
Has any younger sisters
Has any younger sisters * female
Has any older sisters
Has any older sisters * female

Number of Observations
Log Likelihood
Psuedo R-squared-0.248(0.314)0.105(0.188)-0.004(0.146)-0.026(0.183)-0.142(0.088)0.254(0.249)-0.006(0.157)-0.100(0.137)135-79.07
0.0362Marginal effect (standard error)
(d)
(c )
(b)
-0.03640.0397-0.0999(0.084)(0.100)(0.088)0.013
0.0404*(0.018)(0.021)-0.0385**-0.0461**(0.020)(0.020)-0.139**(0.077)-0.358(0.354)0.066(0.148)0.157(0.209)-0.107(0.084)-0.027(0.102)0.117(0.227)0.022(0.152)-0.078(0.104)135-64.050.219

135-81.370.00815135-72.380.118(e)-0.0162(0.095)0.024(0.025)-0.0499**(0.023)-0.178**(0.069)135-67.580.176

Note.This table reprents the marginal effects from probit model estimation. The dependent variable is given a value of 1 if thesubject selected the tournament payment scheme in Task 6, else it is assigned a 0. Marginal effects are evaluated for a female withan average number of correct answers in Tasks 3 and 4, who chooses the tournament option, believes she is ranked second on
Task 3, and has a younger brother.*** p<0.01, ** p<0.075, * p<0.1.

27