Discussion Paper No. 491

VOLUNTARY PARTICIPATION
AND SPITE IN PUBLIC
GOOD PROVISION EXPERIMENTS:
AN INTERNATIONAL COMPARISON

Timothy N. Cason
Tatsuyoshi Saijo
and
Takehiko Yamato

January 2000

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

Voluntary Participation and Spite in Public Good Provision Experiments:
An International Comparison*by
Timothy N. Cason
Purdue University
Tatsuyoshi Saijo
Osaka University
andTakehiko Yamato
Tokyo Metropolitan University

July 1997; revised August 1999
Abstract
This paper studies public good provision in the laboratory using the voluntary contribution
mechanism, in a cross-cultural experiment conducted in the United States and Japan. Our
environment differs from the standard voluntary contribution mechanism because subjects first
decide whether or not to participate in providing this public good. This participation decision
is conveyed to the other subject prior to the subjects’ contribution decisions. We find that only
the American data support the evolutionary stable strategy Nash equilibrium predictions, andthat behavior is significantly different across countries. Japanese subjects are more likely to act
spitefully in the early periods of the experiment, even though our design changes subject
pairings each period so that subjects never interact twice with the same opponent. Surprisingly,
this spiteful behavior eventually leads to more efficient public good contributions for Japanese
subjects than for American subjects.
*This research was partially supported by the Zengin Foundation for the Studies on Economics and Finance, Grant
in Aid for Scientific Research 08453001 of the Ministry of Education, Science and Culture in Japan, the Tokyo Center
for Economic Research, and the Krannert School of Management at Purdue University. We are grateful for the many
helpful suggestions provided by participants at the 1997 Amsterdam Workshop on Experimental Economics, the Fall
1997 Economic Science Association conference, the Purdue University theory workshop, and Andreas Ortmann,
Arthur Schram, Martin Sefton, Shyam Sunder, and Jun Wako. The usual caveat applies.

Voluntary Participation and Spite in Public Good Provision Experiments:
An International Comparison
1.

Introduction
Culture and national character have played a central role in explaining differences inbusiness management and performance across countries, both in the popular press and inmanagement research. Theoretical research in economics, however, almost universally fails to
consider cultural differences, although recent laboratory research has identified the potential
role of cultural norms in influencing economic outcomes—particularly in the context ofbargaining (e.g., Buchan, Johnson and Croson, 1999; Kachelmeier and Shehata, 1992; Roth et al.,1991). This cultural influence often arises through differences in fairness norms. For example, if
someone feels that they are being treated unfairly, this may trigger a spiteful response; i.e., “amalicious desire to harm...another person.”1 If this desire is triggered by harmful actions of theother person towards oneself, this spiteful response should be viewed as (negative) reciprocal
behavior.
In this paper we examine spiteful behavior and cultural differences by studying public
good provision in the laboratory using the voluntary contribution mechanism, in experiments
conducted in the United States and Japan. Our environment differs in three ways from thestandard linear voluntary contribution mechanism (e.g., Isaac and Walker, 1988). First, we
employ two-person groups. Second, the payoffs from the public good are nonlinear. Third, andperhaps most importantly, subjects decide whether or not to participate in funding this public
good in an initial stage, and this participation decision is conveyed to the other subject prior to
the subjects’ contribution (or “investment”) decisions. This allows reciprocity-motivatedsubjects to reward positive participation decisions and to spite negative participation decisions
by their opponent. We find that Japanese subjects are significantly more likely to spite theiropponents for non-participation, even though our design changes subject pairings each period

1 Random House College Dictionary, 1979.

1

so that subjects never interact twice with the same opponent. Surprisingly, this spiteful
behavior eventually leads to more efficient outcomes for Japanese subjects than for American
subjects.
While cultural differences are inconsistent with the standard income-maximizing
economic model, such differences have been well documented in psychology, sociology andanthropology. A major construct in theoretical discussions in these fields is collectivismindividualism (e.g., Hofstede, 1980). More collectivist (Eastern) cultures value group harmony
over individual interests, and they often turn to the principle of equality to resolve disputes. By
contrast, the individualist orientation of many Western cultures places emphasis on individual
inputs and rights, with an overall goal to maximize individual rewards. These are broad
generalizations, of course, but empirical research in these other disciplines has documented
significant cultural differences consistent with this collectivism-individualism construct.2
Cultural differences have also been studied in economics and management. For
example, Buchan, Johnson and Croson (1999) present a detailed review of the literature on
cultural differences in bargaining and in psychology, highlighting how this research suggeststhat culture influences fairness norms. They then provide laboratory evidence from ultimatum
bargaining that supports the hypothesis that Japanese subjects prefer earning distributions thatare more equal than American subjects prefer. In ultimatum bargaining, a spiteful response isrepresented by a rejection of an offer that provides a significantly smaller allocation to the
respondent.3 Their findings are consistent with the interpretation in our experiment that
“unfair” non-participation decisions are more likely to invoke a spiteful response by Japanese

2 For examples: in hypothetical award allocation problems, Japanese students perceive equal earnings as more “fair”

compared to Australian students, even when efforts of the hypothetical workers were unequal (Kashima et al., 1988);
when dividing earnings Chinese subjects more frequently followed an equality rule than American subjects (Leungand Bond, 1984); and Australian children more commonly followed their self-interest than Japanese children whenallocating chocolate rewards (Mann et al., 1985).
3 Buchan et al. actually use the strategy method, in which respondents’ demands of their share of the surplus
determine whether an offer is rejected. Their data indicate that Japanese respondents demand more than American
respondents do, so the Japanese subjects are more likely to reject an offer of a given size.

2

subjects who chose to participate in funding the public good.4 In a very different context withsimple two-stage extensive form games, Beard et al. (1997) find that Japanese subjects are more
willing to reject unequal payoff allocations than are American subjects. This leads to more“secure” play in the Japanese treatments; that is, the first decision maker is less likely to offer aPareto superior but more asymmetric payoff distribution in the sessions conducted in Japan.
Although Saijo and Nakamura (1995) and others document substantial spiteful behavior
by Japanese subjects, not all evidence supports the hypothesis that Japanese subjects act morespitefully than their western counterparts. In their ultimatum game study, Roth et al. (1991)
find that Japanese subjects’ rejection rates (controlling for the offer amount) are no higher andare sometimes lower than American subjects’ rejection rates. Brandts et al. (1997) do not findsignificant differences in public goods contributions across three European countries and Japan,
and Okada and Riedl (1999) are unable to identify significant differences in a coalition
formation game conducted in Japan and Austria. Moreover, some research in management has
downplayed the importance of cultural differences as an explanation for differences in
performance of Japanese and Western manufacturing enterprises, emphasizing instead, forexample, differences in monitoring technology (Aoki, 1988; Aron, 1990).
One possible source of the mixed results in previous economics experiments could beother differences in university subject pools. In nearly all previous experimental economics
research that studies cultural differences, subjects are recruited from one university in eachcountry. We believe that it is important to determine whether between-country differences are
greater than within-country differences in behavior in order to identify cultural or nationality
effects confidently. We therefore collect data at multiple universities within each country. The
results indicate that nationality differences have a greater influence on outcomes than withincountry university subject pool differences.

4 In recent work, however, Roelofs and Sigler (1998) measured the individualism and collectivism values ofAmerican subjects using a questionnaire and find little difference in public goods contribution for subjects whoscored differently on these measures.

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The remainder of the paper is organized as follows. Section 2 describes the laboratoryenvironment and experimental design, and summarizes the hypotheses. Section 3 presents theresults. Section 4 offers our interpretation based on recent research on non-monetary
preferences (e.g., Fehr and Schmidt (1999) and Bolton and Ockenfels (1999)). Section 5
concludes.

2.

Experimental Environment, Design and Hypotheses

2.1

Environment
We compare participation and investment of American and Japanese subjects using a

new version of the voluntary contribution mechanism. The laboratory environment
implements a two-stage game. In the first stage, subjects simultaneously choose whether or notthey participate in the voluntary contribution mechanism. In the second stage, knowing theother subject’s participation decision, subjects who selected participation in the first stage
choose contributions to the public good.
Two subjects, a and b, may fund each public good and subject i (=a,b) has wi units ofinitial endowment of a private good. Each subject who participates in funding the public goodmust allocate wi between her own consumption of the private good (xi) and her public goodinvestment (yi). From the total public good investment, each subject receives y=ya+yb+wy, where
wy is the initial level of the pubic good. That is, the nonexcludable public good available for
consumption by each subject is the sum of the investments of two subjects and the initial levelof the public good. Note that non-participants who choose not to fund the public good stillconsume it, as is the usual case for the voluntary contribution mechanism. Each subject’s
decision problem ismax ui(xi, y) subject to xi+yi=wi,
where ui(xi, y) is subject i’s payoff function. We use an identical Cobb-Douglas type payoff
function to transform contributions toward the public good and consumption of the private4good into each subject’s payoffs: ui(xi, y)= xi αy1−α, where α∈(0, 1). Using a monotonic
transformation, we employ the following payoff function:ui ( x i , y ) =

1−α β
{xα
}
i y
+ 500 .
50

Our experiment sets (wa, wb, wy)=(24, 24, 3), α=0.47, and β=4.45. With these parameters, if bothsubjects participate in funding the public good the Nash equilibrium investment pair of thevoluntary contribution mechanism is (yˆ a , yˆ b ) =(7.69, 7.69), and the payoff level isui (xˆ i , ˆy) =7089, where xˆ i =24-7.69=16.31 and y$ = y$ a + y$ b + w y =18.38. The Pareto efficient level ofthe public good is determined uniquely by the Samuelson condition and the feasibility**

condition. Its symmetric contribution level is (y a , y b ) =(12.02, 12.02). Therefore, the Pareto
efficient level of the public good is 27.04=12.02+12.02+3. Clearly, the level of the public goodwith the voluntary contribution mechanism is less than the Pareto efficient level of the public
good, which is the standard problem of this provision mechanism.
The situation just described represents the case in which subjects have alreadycommitted to participate during stage 1. However, Saijo and Yamato (1999) demonstrate that awide class of mechanisms for funding public goods exists in which subjects have incentives not
to participate. The voluntary contribution mechanism is one of them. Therefore, the voluntary
contribution mechanism is not voluntary from the viewpoint of participation incentives.
Consider now the two-stage game shown in Figure 1. In the first stage, subjects
simultaneously decide whether or not to participate in the voluntary contribution mechanism.
In the second stage, subjects decide how many units of their initial endowment to invest after
learning the other subject’s participation decision. Notice that non-participation is different
from zero investment with participation. Once a subject decides to participate in themechanism, his opponent must choose her investment without knowing the other subject’s
investment. On the other hand, if a subject chooses non-participation, then his opponent
knows that he invests nothing.

5In our experiment, subjects choose integer investments. If both subjects decide toparticipate in the mechanism, then the Nash equilibrium of that subgame is for each subject tocontribute 8, and each earns 7345. No other Nash equilibria arise due to our use of a discrete
strategy choice set. If one subject participates in the mechanism and the other does not, thenthe participant maximizes her payoff at yi=11 and earns 2658. The non-participant invests
nothing and earns 8278. If both choose not to participate in the mechanism, both subjects
receive 706. These payoffs are summarized in the normal form game payoff table shown in
Table 1.
The game in Table 1 is a version of the well-known Hawk-Dove game, sometimes
referred to as “chicken.” Although the usual representation of the public good provision
problem is a Prisoners’ Dilemma game, the proper representation is a game of chicken once
participation in the mechanism is a choice variable. Two pure strategy Nash equilibria exist:
either one of subjects participates in the mechanism. In the mixed strategy Nash equilibrium,
each subject i chooses 0.68 as her participation probability pi. Among these three equilibria, themixed strategy equilibrium is the unique evolutionary stable strategy (ESS) equilibrium.5
2.2

Design and Procedures
We conducted three sessions in Japan and two sessions in the United States. As shownin Table 2, we conducted sessions at two different universities in each country.6 Twenty
subjects participated in each session for a total of 100 separate subjects. Each subject was
randomly paired with each other subject one at a time—a so-called “strangers” design. The
same game was repeated for 19 periods, 4 for practice and 15 for monetary reward, so as not topair the same two subjects more than once. No subject had prior experience in a public good
provision experiment. Sessions required approximately 2 hours to complete. The mean payoff

5 See Maynard Smith (1982).

Our use of a “strangers” design—randomly repairing subjects each period—also makes
coordination on an asymmetric pure strategy equilibrium extremely difficult.
6 We conducted two sessions in Tokyo to test whether a difference in instruction and record sheet wording—“youropponent” versus “the person you are paired with”—affects behavior. As we document below, results aresubstantially unaffected by this difference in phrasing. Saijo et al. (1999) presents additional analysis of the Japanesedata (only) and provides further evidence that the wording does not systematically influence choices.

6

per subject was $26.75 ($1=100 Yen for the Japanese sessions). The maximum payoff among the
100 subjects was $38.75, and the minimum payoff was $12.25.
The twenty subjects in each session were seated at desks in a relatively large room, andeach had a randomly chosen identification number. These identification numbers were notdisplayed publicly. In each period we made ten pairs out of the twenty subjects. The pairings
were determined in advance so as not to pair the same two subjects more than once. Eachsubject received an experimental procedure sheet, a record sheet, payoff tables, 15 investment
sheets, and 4 practice investment sheets. Instructions were given by tape recorder to minimize
the interaction between subjects and experimenters.
Before choosing their investment, subjects decided whether or not they would
participate in the voluntary contribution mechanism. These decisions were collected byexperimenters and then redistributed to the paired subjects. After this redistribution of theparticipation decisions, subjects who decided to participate in the mechanism chose theirinvestment on an investment sheet by circling an integer between 0 and 24. Experimenterscollected these investment sheets and then redistributed them to the paired subjects. During
the redistribution, subjects were asked to fill out the reasons why they chose these numbers.
After this redistribution, subjects calculated their payoffs from the payoff tables. Then the next
round started.
It was common knowledge that every subject had the same payoff function. We
distributed three kinds of payoff tables to avoid any possible misunderstanding. Table 3 is thedetailed payoff table provided to subjects in real rounds: the rows are for the subject’s own
investment numbers and the columns are for the opponent’s investment numbers. We alsopresented a rough payoff table summarizing average payoffs for sets of 9 or 12 payoff cells
shown in Table 3, as well as an iso-payoff map. Most subjects indicated in their postexperiment questionnaire that they used the detailed payoff table (Table 3) only. We gave
subjects three minutes to study these three payoff tables before the practice rounds and ten

7minutes to study them before the real rounds. The payoff function and tables used for practiceand real rounds were different.
The sessions in Japan were conducted in Japanese, and the sessions in America wereconducted in English. The instructions and forms were translated from Japanese to English by
the two bilingual co-authors. The exchange rate used to translate payoffs from Japan toAmerica was $1=100 Yen.
As mentioned in the introduction, our use of multiple university subject pools in eachcountry is an important aspect of the design for our objective to study cultural differences.
Differences in results for any two universities could be due to subject pool effects unrelated to
culture and nationality. To establish a significant cultural difference one must show thatbetween-country differences are greater than within-country differences. We should also
highlight the fact that there exist important similarities between sets of universities acrosscountries. Purdue University and the University of Tsukuba both have a major emphasis on
engineering and science and are both in (relatively) small “college towns” with predominantly
university-resident students. By contrast, Tokyo Metropolitan University and the University ofSouthern California are both situated in major urban centers with many off-campus“commuter” students. Subject pool differences other than nationality and culture are therefore
substantially lower within these sets of universities, and these other subject pool differences are
considerably greater within countries.
2.3

Hypotheses
Our first task is to determine if behavior differs across the two countries. Therefore, wefirst test the following null cultural hypotheses.
Hypothesis 1: The rate of participation is equal across countries.
Hypothesis 2: The mean investment per subject is equal across countries, (a) conditional on one subject
participating and (b) conditional on both subjects participating.
Hypothesis 3: The overall efficiency is equal across countries.

8We also test whether within-country differences are more or less significant than betweencountry differences across sessions.
The second set of equilibrium hypotheses is based on the theoretical discussion above.
Because we reject Hypotheses 1-3 in favor of significant country effects, we test the following
hypotheses separately for each country.
Hypothesis 4: The rate of participation is 68 percent, corresponding to the mixed strategy ESS
participation rate.
Hypothesis 5: (a) Conditional on one subject participating, the mean investment for the participating
subject is 11 units; and, (b) conditional on both subjects participating, the mean investment per subject
is 8 units.

3.

Results

3.1

Between Country Comparison7

Result 1: Hypothesis 1 is rejected in the final third of the sessions.
Support:Panel A of Figure 2 presents the participation rate by period for each of the fivesessions. In the first half of the sessions the variation in participation rates across periods isclearly more significant than any differences across sessions; however, in the final third of thesessions the American participation rates (shown with dashed lines) are always below theJapanese participation rates.
Table 4 presents a formal test of Hypothesis 1 using a random-effects probit model ofthe participation decision, with subjects as the random effect. It presents ten pairwise
comparisons for the five sessions. The alternative to Hypothesis 1 that across-country
differences are more significant than within-country differences is supported: five of the six

7 Unfortunately, subject 11 in the USC session was confused regarding the subject identification numbers andinvestment choices. She was the only subject (of the 100) that participated in this experiment who appeared
confused. She thought the identification numbers were the investment choices, so she typically used her opponent’s
identification number (rather than her opponent’s investment choice) when calculating her payoffs. In what follows
we remove this obviously confused subject from the data prior to analysis, but our qualitative conclusions are
generally robust when statistics are recalculated using this confused subject.

9

across-country comparisons shown in the highlighted box in the lower left of the table are
significant (at the ten-percent level), while none of the four within-country comparisons are
significant.
Panel B of Figure 2 presents the same data pooled within the two countries. The pooled
random effects probit model strongly rejects the hypothesis of no country differences (t=3.05).
We also compared participation frequencies across countries by period using Fisher’s exact test.
This nonparametric test rejects the null hypothesis of equal participation rates at the fivepercent significance level in periods 6, 11, 12, 13, 14 and 15.
Result 2: Hypothesis 2(a) is rejected but Hypothesis 2(b) is not.
Support:Panel A of Figure 3 presents mean investments by the participating subject when

only one subject participates, for each of the five sessions. Substantial variation exists acrossperiods, partly because these means (by session) are often based on a small sample size—
typically three or four subjects due to the high participation rates illustrated in Figure 2. In
addition to the substantial variability, careful inspection of Figure 3A suggests the impressionthat investments are often higher in the American sessions (the dashed lines). For example,
mean investments in the two American sessions exceed those in all three Japanese sessions in 4
periods, and with the exception of the final period a Japanese session always has the lowest
mean investment.
Table 5 formalizes the sessions' comparison with one participating subject using arandom effects model. Four of the six across country investment differences are significant,while only one of the four within country differences is significant. Panel B of Figure 3 presentsmean investments along with standard error bands when pooling the sessions within acountry. This figure indicates that investments with one participant are lower in the Japanesesessions, by about two units on average. Pooling across periods and across countries with arandom effects model, Hypothesis 2(a) is strongly rejected (t=4.56). Moreover, a period-byperiod nonparametric Wilcoxon signed rank test rejects Hypothesis 2(a) at the five- percent
level in periods 3, 8 and 11.

10Figure 4 presents mean investments when both subjects participate. These data fail toreject Hypothesis 2(b), indicating no systematic differences in investments across countries
when both subjects participate. The pairwise session comparisons shown in Table 6 often
support significant within country differences and often fail to detect significant across country
differences. Overall, differences across sessions are small in real terms, and Panel B of Figure 4
indicates that the pooled country effect on investments with both subjects participating is
insignificant (pooled random effects model t=1.89).
3.2

Equilibrium Hypotheses

Result 3: Hypothesis 4 is supported in the American data, but not the Japanese data.
Support:Panel B of Figure 2 presents the participation rate by period, pooled withincountries. With the exception of period 1, the participation rate in the Japanese data exceeds
the mixed strategy ESS prediction of 68 percent in every period. The participation rate in theAmerican data fluctuates around the mixed strategy prediction, exceeding the predicted rate inabout one-half of the periods. We test the null hypothesis that the participation rate is 68
percent using a binomial test. Under this null hypothesis, the probability of observing 48 or
more participation decisions out of 60 (80 percent) is less than five percent. The Japaneseparticipation rate exceeds this critical 5-percent threshold in periods 5 through 7 and periods 10
through 15. For the American sample we have 39 subjects (recall that we omit the confused
subject in the USC session; cf. footnote 6). Under the null hypothesis of a 68 percent
participation rate, the probability of observing 32 or more participation decisions out of 39 (82percent) is less than five percent. The American participation rate exceeds this critical value
only in period 4.
Tests of a mixed strategy equilibrium based on aggregate choice frequencies may mask
differences across individuals’ choice frequencies that may or may not be consistent with amixed strategy equilibrium (Brown and Rosenthal, 1990). We therefore also examined theoverall participation rates separately for each of the 99 subjects. The mean participation rate
among the 60 Japanese subjects was 0.80 (12 of 15 decisions), and the median participation rate11

was 0.87 (13 of 15 decisions). The corresponding mean and median participation rates for the
39 American subjects were 0.69 and 0.73. Note that the ESS rate of 0.68 implies on averageslightly more than 10 participation decisions. Only 14 of the 60 Japanese subjects (23.3%)
participated 10 times or less, while the other 46 Japanese subjects (76.6%) participated 11 times
or more. The frequency of participation rates below and above the ESS prediction was moreeven among the 39 American subjects—17 (43.6%) below and 22 (56.4%) above. Fifteen of the
60 Japanese subjects (25%) and 5 of the 39 American subjects (12.8%) were apparently using apure strategy, as they participated in 15 out of 15 periods. Using the 60 separate subject
observations, the Japanese data reject the ESS prediction of 0.68 at better than the 0.0001
significance level using the non-parametric Wilcoxon signed-rank test. This same test does not
reject the ESS participation rate in the American data (Wilcoxon p-value=0.61).
Result 4: Hypothesis 5 is supported in the American data but not the Japanese data, although theevidence against Hypothesis 5(b) is relatively weak in the Japanese data.
Support:Panel B of Figure 3 presents the average investment pooled within countries

with one subject participating. Mean investment falls below the prediction of 11 for bothcountries, but investments are lower in the Japanese data (Result 2). Over all 136 investmentswith one participant in the Japanese sessions, 43 (32%) were 11; over all 122 investments with
one participant in the American sessions, 77 (63%) were 11. Period-by-period Wilcoxon signed
rank tests reject the null hypothesis of 11 at the five- percent level for the Japanese data inperiods 1 through 4, 8 and 10 through 12. This same test never rejects the null in the American
data. The sample size is slightly smaller for these tests in the American data (an average of 8.1
observations per period for the American data versus an average of 9.1 for the Japanese data),
but this lower power is unlikely to be the main cause of the lack of significance in the American
data.
Panel B of Figure 4 presents the average investment by country when both subjects
participate. The American data reject the Nash prediction of 8 at the five- percent level only inperiods 9, 10 and 11 (Wilcoxon test). The Japanese data reject the Nash equilibrium using this12

same test in all periods except periods 1 and 4. Nevertheless, compared to the case of one
participant (Figure 3B), the Nash equilibrium has substantial drawing power overall. We
therefore conclude that Hypothesis 5(b) is not rejected economically in both countries.
3.3

Efficiency

Result 5: Hypothesis 3 is rejected in the final third of the sessions.
Support:Figure 5 presents the average efficiency—defined as the percentage of the

maximum available earnings realized by subjects—for the Japanese and American sessions by
period. If both subjects participate and choose the Pareto optimal investment of 12, they eachearn 9090.8 If both subjects participate and choose the Nash investment of 8, they each earn
7345, for an efficiency of 7345/9090=81 percent. This is displayed on the figure as a horizontal
dashed line. The horizontal solid line on the figure displays the predicted efficiency of the ESS
equilibrium, 5829/9090=64 percent.
The average efficiency differences in the two countries are not significant at the fivepercent level in any individual period using a Wilcoxon test. Figure 5 suggests, however, that
efficiency in the Japanese data begins to exceed efficiency in the American data toward the endof the sessions. This is due to the greater participation among Japanese subjects (c.f. Figure 2).
When pooling periods into the first, middle and final thirds of the session, a Wilcoxon test
rejects the hypothesis that efficiency is equal across countries, but only in the final third of thesession (p-value<0.01).94.

Summary and Interpretation
The overall pattern of our results can be summarized as follows. The American data areroughly consistent with the mixed strategy ESS equilibrium of this two-stage game (Results 3

8 Asymmetric collusion could generate even higher payoffs, but such coordination is extremely difficult in thisstrangers design that randomly reassigns pairs each period.

9 We would have preferred to use a random effects model for this test that pools observations across periods, as we

do elsewhere in this paper. The efficiency observation is defined for pairs of subjects, however, and in our strangers
design the pairs were randomly reassigned each period. Therefore, random subject or random pair effectspecifications are impossible.

13and 4). In the Japanese data, this equilibrium is generally rejected. Behavior of Japanese andAmerican subjects is typically significantly different (Results 1 and 2). Relative to their
American counterparts, Japanese subjects tended to participate more and invest less when only
one subject of the pair chose to participate. This presents an important puzzle: What isdifferent between Japanese and American subjects that could explain their differences inbehavior? As discussed in the introduction, differences in the propensity to spite one’s
opponent can explain these differences across countries.
To see how these differences arise, consider the initial 5 periods of play. Participation
rates are similar across countries for these initial periods (Figure 2B). However, the investmentby the participating subject when only one subject participates is substantially higher in theAmerican data than in the Japanese data for these initial periods (Figure 3B). That is, theJapanese subjects appear much more willing to “punish” their opponent for not participating.
By investing, say, 7 instead of the best response of 11, the participating subject reduces her
payoff from 2658 to 2210, a difference of 448. This spiteful behavior reduces the nonparticipating subject’s payoff from 8278 (if his opponent invests the best response of 11) to 4018
(if his opponent instead invests 7), a difference of 4260. In this environment, a spiteful subject
can sacrifice only a small amount to punish her opponent severely. This is similar to rejecting a
relatively low offer in the ultimatum game.
But why would subjects reduce their own earnings to punish non-participants,
especially since they never encounter the same subject twice in this strangers design? 10 This is aproblem familiar to experimental economists and it arises repeatedly in bargaining and otherlaboratory games. The evidence seems clear that subjects in many situations do not seek simply
to maximize monetary earnings, and several recent studies have introduced non-monetaryfactors into players’ objective functions (Fehr and Schmidt, 1999; Bolton and Ockenfels, 1999;
Levine, 1998). For example, in Bolton and Ockenfels’ model of equity, reciprocity and
10 We even observe non-payoff-maximizing contributions in the final period 15, even though the final period wasannounced in the instructions (see Figure 3).

14

competition (ERC), individuals are motivated by their relative payoff standing in addition totheir own pecuniary payoff. Their model is consistent with results from ultimatum and dictator
experiments, gift exchange games, and market (Bertrand and Cournot) experiments, among
others.
Similarly, in Fehr and Schmidt’s model subjects have “inequity aversion,” so they preferhigher but equal earnings among participants in their group. Utility payoffs are equal tomonetary payoffs less inequity costs that rise as the difference between a subject’s own andother’s monetary payoff increases.11 In the model some subjects suffer both from earning more
as well as earning less than their counterparts, but the cost of advantageous inequality is
assumed to be no more than the cost of disadvantageous inequality. Fehr and Schmidt
demonstrate that their model can describe many outcomes in ultimatum games, market gameswith both proposer and responder competition, as well linear voluntary contribution
mechanism games with and without punishment opportunities. They even go as far as toderive parameter distributions of the relative tradeoff of monetary gains and inequity aversion
that describes behavior across games, which we can use to assess conveniently the effectivenessof this approach in describing the new data reported here. Applying their distribution ofpreferences to our subjects, it is straightforward to show that when only one subject participates
the optimal contribution is 11 for 30 percent of the subjects (these 30 percent are standard“money-maximizers”), is 6 for 30 percent of the subjects, is 4 for another 30 percent of thesubjects, and is 1 for the remaining 10 percent.12 The mean of this distribution is 6.4.
The distribution of contributions in the Japanese data is remarkably close to thispredicted distribution if one makes allowances for a bit of choice error for the lower
contributions. Figure 6 shows that when they are the only participant, 32 percent of theJapanese subjects contributed 11, 26 percent contributed 6 or 7, 11 percent contributed 3 or 4,
11 In particular, for a two-person game player i’s utility is Ui(x) = xi – αimax{xj-xi, 0} - βimax{xi-xj, 0}, i≠j, where xk

denotes monetary earnings (k=i, j), αι≥βι, and 1>βi≥0.
12 For this calculation one only needs the distribution of α, because the participant’s earnings are always lower than
the non-participant’s earnings. β is only used for cases of advantageous inequality. We use Fehr and Schmidt’s
distribution of α={0, 0.5, 1, 4} in proportions of {0.3, 0.3, 0.3, 0.1}.

15

and 13 percent contributed 0 or 1. However, the point we wish to emphasize is that the Fehrand Schmidt model—and the related models of Bolton and Ockenfels (1999) and Levine(1998)—are culturally neutral. Consequently, they cannot explain the difference in the Japaneseand American results.
One interpretation is that the Fehr and Schmidt model is a good approximation for theAmerican subject pool, but that the distribution of preference types is different than in theJapanese subject pool. Figure 6 shows that when they are the only participant, 63 percent of theAmerican subjects contributed 11, 13 percent contributed 6 or 7, 3 percent contributed 3 or 4,
and 7 percent contributed 0 or 1. That is, one needs to raise the proportion of subjects with α=0
to describe the American data. Alternatively, our results suggest that refitting the Fehr andSchmidt model to the American data is less appealing than simply retaining the standard
money-maximizing model of preferences. After all, the American data are broadly consistent
with this standard model (Results 3 and 4).
A consequence of the low contributions by the Japanese subjects when they are the only
participant is to considerably reduce the incentives for Japanese subjects to forego participation.
In the Fehr and Schmidt model, some subjects prefer not to earn more than the other subject
does, all other things equal. But the incentive to participate in the Japanese data is clear evenbased on only the monetary payoffs. Table 7 summarizes the normal form game for theparticipation decision based on realized average monetary earnings during the first 5 periods inthe two countries. Compare these payoff tables with the theoretical monetary payoffs based on
the stage two Nash equilibrium shown in Table 1. The realized monetary payoff matrix basedon the early Japanese data (Table 7A) indicates that participation is a dominant strategy. The earlyexperience of Japanese subjects indicates that “non-participation doesn’t pay,” and we believe
this is a primary explanation of the high participation rate (rejecting the ESS prediction of 68
percent) observed in the Japanese data. By contrast, for the American data (Table 7B), allmonetary payoffs are reduced compared to the theoretical predictions in Table 1 (except, of16

course when both fail to participate); however, the Hawk-Dove property of this payoff matrix ispreserved.13
To summarize, consistent with models that include relative payoffs in the utility
function such as Bolton and Ockenfels (1999) and Fehr and Schmidt (1999), we find thatJapanese subjects often punish opponents who fail to participate. This punishment occurs eventhough our design allows subjects to interact only once during the experiment (recall that this iscommon knowledge). This (non-myopic best response) behavior by Japanese subjects increases
their participation relative to their American counterparts who behave roughly consistent withthe standard money-maximizing model. Perhaps most striking is that the increased
participation observed for the Japanese subjects eventually increases efficiency compared to theefficiency of the money-maximizing Americans. Evaluated in isolation, spite may not seem tobe a desirable cultural or personality trait; but in strategic environments such as this one, it
improves efficiency.

5.

Conclusion
In this paper we presented a laboratory experiment in two-person public goods

provision, in which subjects first announce whether they will participate in the voluntary
contribution mechanism. The subgame perfect Nash equilibrium of this game applies, ofcourse, to any economic decision-makers regardless of their cultural background. The
evolutionary stable strategy equilibrium of this game involves participation about two-thirds ofthe time. This prediction, as well as many others we test, is supported only for the data
gathered using American subjects. Japanese subjects participated more often than the ESS
prediction. This “over-participation” generated efficiency that exceeds that observed forAmerican subjects toward the end of the sessions.

13 In an earlier version of this paper (Cason et al., 1998) we also presented a simple reinforcement learning model todemonstrate that subjects’ participation decisions respond to their previous experience. In particular, we show that
subjects are more likely to participate if their earnings when participating in previous periods increase relative totheir earnings when not participating in previous periods.

17

Although the data from the Japanese sessions generally fail to support the theoreticalequilibria based on only pecuniary payoffs, they are consistent with alternative utility payoffs
that include nonpecuniary considerations (Bolton and Ockenfels, 1999; Fehr and Schmidt,
1999). We observe Japanese subjects who frequently “punish” non-participants with low
contributions, and this kind of (negative) reciprocal behavior is how we interpret the term
“spite” in our context, as distinct from simple rivalistic behavior in which a subject seeks
merely to earn more than his opponent. The data are inconsistent with such rivalistic
motivations, because such motivations are more likely to lead to less participation than the ESS
prediction since nonparticipation guarantees payoffs greater than or equal to those of the
opponent. It is also unlikely that rivalistic choices would be so close to the Nash equilibrium
when both subjects participate (Figure 4) because rivalistic subjects have a strong incentive to
reduce their public good investment.
Our results regarding the differences across countries are consistent with the hypothesisthat Japanese subjects have a greater propensity to spite their opponents who fail to participate
in funding the public good. This spiteful tendency of Japanese subjects has been identified indifferent previous public good environments (Saijo and Nakamura, 1995), but in the present
setting it leads to more efficient outcomes than realized by American subjects. These
individualized punishments are a special feature of two-person public goods environments,
although spiteful punishments have also been observed recently in larger public goods groups
when punishments can be directed to specific individuals—and this behavior also improves
efficiency (Fehr and Gachter, 1998). In future research we plan to interact Japanese andAmerican subjects in the same sessions in environments such as this and the ultimatum game.
This will indicate whether the lack of a shared cultural background initially increases
disequilibrium behavior (e.g., spiteful rejections).

18

REFERENCES

AOKI, M. (1988): Information, Incentives and Bargaining in the Japanese Economy, Cambridge,
Cambridge University Press.
ARON, D. (1990): “Firm Organization and the Economic Approach to Personnel Management”
American Economic Review Papers and Proceedings 80(2), 23-27.
BEARD, T. R., R. BEIL AND Y. MATAGA (1997): “Cultural Determinants of Economic Success:
Trust and Cooperation in the U.S. & Japan,” Auburn University working paper.
BOLTON, G. AND A. OCKENFELS (1999): “ERC: A Theory of Equity, Reciprocity andCompetition,” American Economic Review, forthcoming.
BRANDTS, J., T. SAIJO, AND A. SCHRAM (1997): “A Four Country Comparison of Spite andCooperation in Voluntary Contribution Mechanisms,” mimeo.
BROWN, J. AND R. ROSENTHAL (1990): “Testing the Minimax Hypothesis: A Re-examination of
O’Neill’s Game Experiment,” Econometrica 58, 1065-1081.
BUCHAN, N., E. JOHNSON, AND R. CROSON (1999): “Understanding What’s Fair: Contrasting
Perceptions of Fairness in Ultimatum Bargaining in Japan and the United States,”
Wharton School working paper 97-03-10.
CASON, T., T. SAIJO, AND T. YAMATO (1998): “Voluntary Participation and Spite in Public Good
Provision Experiments: An International Comparison,” Purdue University Center forInternational Business Education and Research (CIBER) working paper.
FEHR, E., AND S. GACHTER (1998): “Cooperation and Punishment,” University of Zurichworking paper.
FEHR, E., AND K. SCHMIDT (1999): “A Theory of Fairness, Competition and Cooperation,”
Quarterly Journal of Economics, forthcoming.
HOFSTEDE, G. (1980): Culture’s Consequences: International Differences in Work-Related Values,
Beverly Hills, CA, Sage Press.
ISAAC, R.M., AND J. WALKER (1988): “Group Size Effects in Public Goods Provision: The
Voluntary Contributions Mechanism,” Quarterly Journal of Economics 103, 179-200.
KACHELMEIER, S., AND M. SHEHATA (1992): “Culture and Competition: A Laboratory Market
Comparison Between China and the West,” Journal of Economic Behavior and Organization
19, 145-168.
KASHIMA, Y., M. SIEGAL, K. TANAKA AND H. ISAKA (1988): “Universalism in Lay Conceptions ofDistributive Justice: A Cross-Cultural Examination,” International Journal of Psychology 23,
51-64.

19

LEUNG, K., AND M. BOND (1984): “The Impact of Cultural Collectivism on Reward Allocation,”
Journal of Personality and Social Psychology 47, 793-804.
LEVINE, D. (1998): “Modeling Altruism and Spitefulness in Experiments,” Review of Economic
Dynamics 1, 593-622.
MANN, L., M. RADFORD AND C. KANAGAWA (1985): “Cross-Cultural Differences in Children’s
Use of Decision Rules: A Comparison Between Japan and Australia,” Journal of Personality
and Social Psychology 49, 1557-1564.
MAYNARD SMITH, J. (1982): Evolution and the Theory of Games, Cambridge, Cambridge University
Press.
OKADA, A, AND A. RIEDL (1999): “When Culture Does Not Matter: Experimental Evidence from
Coalition Formation Ultimatum Games in Austria and Japan,” University of Amsterdam(CREED) working paper.
ROELOFS, M., AND T. HONEYCUTT SIGLER (1998): “Individualism, Collectivism and the Public
Good: Examining Cultural Values in a Public Goods Experiment,” Western Washington
University working paper.
ROTH, A., V. PRASNIKAR, M. OKUNO-FUJIWARA, AND S. ZAMIR (1991): “Bargaining and Market
Behavior in Jerusalem, Ljubljana, Pittsburgh, and Tokyo: An Experimental Study,”
American Economic Review 81, 1068-1095.
SAIJO, T, AND H. NAKAMURA (1995): “The “Spite” Dilemma in Voluntary Contribution
Mechanism Experiments,” Journal of Conflict Resolution 39(3), 535-560.
SAIJO, T, AND T. YAMATO (1999): “A Voluntary Participation Game with a Non-Excludable
Public Good,” Journal of Economic Theory 84, 227-242.
SAIJO, T, T. YAMATO, K. YOKOTANI, AND T. N. CASON (1999): “Voluntary Participation Game
Experiments with a Non-Excludable Public Good: Is Spitefulness a Source of
Cooperation?” Osaka University working paper.

20

Player 1:
Participate
p1
Not Participate
1-p1Player 2:
Participate
Not Participatep2
1-p27345, 7345

2658, 8278

8278, 2658

706, 706

Nash equilibria: (p1, p2) = (1, 0), (0, 1), (0.68, 0.68)
Evolutionary Stable Strategy (ESS): (p1, p2) = (0.68, 0.68)

Table 1. First Stage Participation Payoffs Based on Nash Equilibrium Investments in theSecond Stage

21

Session Name
Voluntary Participation?
University
Country
Tsukuba
Yes
Univ. of Tsukuba
Japan
USCa
Yes
Univ. of So. Calif.
United States
Tokyo
Yes
Tokyo Metro. Univ.
Japan
Tokyo’b
Yes
Tokyo Metro. Univ.
Japan
PurdueYes
Purdue University
United States
Notes: Each session employed 20 subjects for 4 practice periods and 15 actual periods. Subjects
were randomly re-paired each period.
a One subject in the USC session misunderstood the instructions, and her choices are removed
from the data prior to the analysis.
b The instructions wording in the Tokyo’ session differed slightly from the other 4 sessions as arobustness check. In the Tokyo’ session the phrase “the person you are paired with” replaced
the phrase “your opponent” everywhere in the instructions, record sheets, questionnaires andpayoff tables.

Table 2. Summary of Five Laboratory Sessions

22

2

3

4

5

6

7

8

9

Your Investment Number
10
11
12
13
14

Your
Payoff

0

1

15

16

17

18

19

20

0

706

871 1072 1297 1536 1775 2003 2210 2386 2523 2615 2658 2648 2585 2470 2309 2106 1871 1614 1349 1091

21

22

23

24

858

669

543

500

1

905 1127 1379 1647 1919 2183 2427 2641 2816 2944 3019 3039 3001 2905 2755 2555 2313 2038 1743 1443 1154

894

685

548

500

933

703

552

500

Your

2

1186 1465 1764 2072 2374 2658 2913 3129 3297 3411 3465 3456 3385 3252 3061 2819 2534 2217 1881 1543 1220

Opponent’s

31554 1888 2232 2575 2902 3202 3463 3675 3831 3925 3952 3911 3801 3626 3391 3102 2770 2406 2027 1648 1290

973

721

556

500

Investment

42017 2401 2787 3160 3508 3817 4078 4281 4420 4488 4483 4403 4250 4028 3743 3404 3020 2608 2181 1759 1363 1015

740

561

500

Number52578 3010 3432 3831 4193 4507 4762 4950 5064 5101 5057 4934 4733 4459 4119 3725 3287 2821 2344 1877 1441 1060

760

566

500

6

3244 3718 4171 4590 4960 5272 5515 5681 5766 5765 5677 5504 5249 4918 4519 4065 3568 3045 2516 2000 1522 1106

781

571

500

7

4018 4529 5008 5440 5812 6115 6339 6478 6526 6481 6343 6114 5800 5406 4944 4425 3866 3282 2696 2129 1607 1155

802

576

500

8

4904 5447 5944 6383 6751 7038 7237 7340 7345 7250 7056 6765 6385 5924 5393 4806 4179 3532 2886 2265 1696 1206

825

582

500

9

5907 6475 6984 7422 7779 8043 8209 8271 8225 8073 7816 7458 7007 6472 5867 5207 4508 3793 3084 2407 1789 1259

849

588

500

10

7031 7616 8130 8561 8897 9132 9257 9270 9168 8951 8624 8193 7664 7051 6367 5628 4854 4067 3292 2555 1886 1315

874

594

500

11

8278 8873 9384 9800 10109 10306 10384 10339 10173 9886 9482 8970 8359 7661 6892 6070 5217 4354 3509 2710 1987 1372

899

600

500

12

9653 10250 10750 11142 11416 11567 11589 11480 11242 10877 10390 9791 9090 8302 7444 6534 5596 4654 3736 2871 2092 1432

926

606

500

13

11158 11749 12229 12589 12820 12916 12875 12694 12376 11925 11349 10656 9860 8976 8022 7019 5992 4967 3972 3039 2201 1494

953

613

500

14

12796 13372 13824 14144 14323 14356 14243 13982 13576 13033 12358 11565 10667 9681 8627 7526 6406 5292 4217 3213 2315 1559

982

620

500

15

14570 15123 15538 15808 15925 15888 15694 15344 14844 14199 13420 12520 11514 10419 9258 8055 6836 5631 4473 3394 2433 1626 1012

627

500

16

16484 17003 17372 17583 17630 17513 17229 16783 16179 15426 14535 13521 12399 11191 9918 8606 7285 5984 4738 3582 2555 1695 1042

635

500

17

18539 19016 19328 19471 19439 19232 18850 18299 17583 16714 15704 14568 13324 11995 10605 9180 7751 6350 5013 3777 2681 1767 1074

642

500

18

20739 21163 21409 21474 21353 21047 20559 19893 19057 18064 16926 15661 14290 12834 11320 9776 8235 6730 5298 3978 2812 1841 1107

650

500

19

23086 23447 23617 23594 23374 22960 22355 21566 20602 19476 18203 16803 15296 13706 12063 10395 8737 7123 5593 4187 2947 1917 1141

659

500

20

25583 25870 25954 25832 25504 24972 24241 23319 22218 20951 19536 17992 16342 14614 12835 11038 9257 7531 5899 4403 3087 1996 1176

667

500

21

28231 28433 28420 28190 27743 27083 26217 25154 23907 22491 20924 19230 17431 15556 13636 11704 9796 7953 6214 4625 3231 2078 1212

676

500

22

31034 31141 31020 30670 30094 29296 28285 27071 25669 24095 22370 20516 18561 16533 14465 12393 10354 8388 6540 4855 3380 2162 1249

685

500

23

33993 33993 33753 33273 32557 31611 30445 29071 27505 25764 23872 21852 19733 17546 15325 13106 10930 8838 6877 5092 3533 2248 1287

694

500

24

37111 36993 36622 36001 35135 34030 32699 31155 29416 27500 25432 23239 20949 18595 16214 13843 11525 9303 7224 5337 3691 2337 1326

703

500

Table 3. Detailed Payoff Table Provided to Subjects

23Session
USC
PurdueTsukubaTokyo
0.505
Purdue(0.615)1.648*
0.934
Tsukuba(0.099)(0.350)2.727*
1.888*
0.970
Tokyo(0.006)(0.059)(0.332)2.455*
1.720*
0.690
0.261
Tokyo’(0.014)(0.085)(0.490)(0.794)
Notes: In each cell, the first number is the t-statistic testing the null hypothesis that theparticipation probability does not differ between the row session and the column session, usinga random effects probit model (with the subject as the random effect). The number inparentheses is the p-value associated with the test statistic. The statistics that reject the null
hypothesis of no differences across sessions at the ten-percent level are highlighted withasterisks.
SessionTable 4. Participation Rate Tests Across Sessions: Pooled Across Rounds using aRandom Effects Error Specification

24

Session
USC
PurdueTsukubaTokyo
1.628
Purdue(0.104)0.405
2.961*
Tsukuba(0.685)(0.003)2.485*
6.639*
2.199*
Tokyo(0.013)(0.000)(0.028)1.558
4.234*
1.574
0.793
Tokyo’(0.119)(0.000)(0.116)(0.428)Notes: In each cell, the first number is the t-statistic testing the null hypothesis that the mean
investment with one subject participating does not differ between the row session and thecolumn session, using a random effects model (with the subject as the random effect). The
number in parentheses is the p-value associated with the test statistic. The statistics that reject
the null hypothesis of no differences across sessions at the ten-percent level are highlighted
with asterisks.
SessionTable 5. Mean Investment with One Subject Participating Tests Across Sessions: Pooled
Across Rounds using a Random Effects Error Specification

25

Session
USC
PurdueTsukubaTokyo
2.272*
Purdue(0.023)1.240
1.974*
Tsukuba(0.215)(0.048)1.330
4.611*
3.281*
Tokyo(0.184)(0.000)(0.001)
1.218
1.268
1.084
3.825*
Tokyo’(0.223)(0.205)(0.278)(0.000)Notes: In each cell, the first number is the t-statistic testing the null hypothesis that the mean
investment with both subjects participating does not differ between the row session and thecolumn session, using a random effects model (with the subject as the random effect). The
number in parentheses is the p-value associated with the test statistic. The statistics that reject
the null hypothesis of no differences across sessions at the ten-percent level are highlighted
with asterisks.
SessionTable 6. Mean Investment with Both Subjects Participating Tests Across Sessions:
Pooled Across Rounds using a Random Effects Error Specification

26

Player 1:
Participate
p1
Not Participate
1-p1Player 2:
Participate
Not Participatep2
1-p2
6570, 6570

2049, 4795

4795, 2049

706, 706

Table 7A. First Stage Participation Payoffs Based on Average Payoffs in the Second
Stage Through Period 5 (Japanese Data)

Player 1:
Participate
p1
Not Participate
1-p1Player 2:
Participate
Not Participate
p2
1-p27167, 7167

2400, 7279

7279, 2400

706, 706

Table 7B. First Stage Participation Payoffs Based on Average Payoffs in the Second
Stage Through Period 5 (American Data)

27

1
Not
participate

Participate

2
Participate

1
0

8

2

24

Not
participate

Participate

2

1
11

11

(2658,8278)(8278,2658)

Not
participate(706,706)

8(7345,7345)
Figure 1. The game tree when subjects can choose whether or not to participate in the voluntary contribution
mechanism.

.

Panel A: All 5 Sessions Separately

1.00
0.90
Participation Rate

0.80
0.70
0.60
0.50

USC

0.40

Purdue0.30

TokyoTokyo'

0.20

Tsukuba

0.10

ESS Prediction

0.00
1

3

5

7

9

11

13

15

11

13

15

PeriodPanel B: Pooled within Countries

1.00
0.90
Participation Rate

0.80
0.70
0.60
0.50
0.40
0.30

United States

0.20

Japan
ESS Prediction

0.10
0.00
1

3

5

7

9
PeriodFigure 2: Participation Rate, by Session and by Country

Mean Investment

Panel A: All 5 Sessions Separately

12
11
10
9
8
7
6
5
4
3
2
1
0

USC
PurdueTokyo
Tokyo'
TsukubaNash Equilibrium

1

3

5

7

9

11

13

15

11

13

15

PeriodMean Investment

Panel B: Pooled within Countries

13
12
11
10
9
8
7
6
5
4
3
2
1
0

Japan Mean Investment
Japan+1 Std. Err.
Japan-1 Std. Err.
U.S. Mean Investment
U.S.+1 Std. Err.
U.S.-1 Std. Err.
Nash Equilibrium

1

3

5

7

9
PeriodFigure 3: Mean Investment when only One Subject Participates, by Session and by Country

Mean Investment

Panel A: All 5 Sessions Separately

11
10
9
8
7
6
5
4
3
2
1
0

USC
PurdueTokyo
Tokyo'
TsukubaNash Equilibrium

1

3

5

7

9

11

13

15

11

13

15

PeriodPanel B: Pooled within Countries

10
9
Mean Investment

876Japan Mean Investment

5Japan+1 Std. Err.

4

Japan-1 Std. Err.

3

U.S. Mean Investment
U.S.+1 Std. Err.

2

U.S.-1 Std. Err.

1

Nash Equilibrium

0
1

3

5

7

9
PeriodFigure 4: Mean Investment per Subject when Both Subjects Participate, by Session and byCountry

100%
90%
80%

Efficiency (percent)

70%
60%
50%
40%
United States

30%

Japan

20%

ESS Prediction
All Participate, Nash Prediction

10%
0%
1

3

5

7

9
PeriodFigure 5: Average Efficiency, by Country

11

13

15

80

70

60

Frequency

50

Japanese
American

40

30

20

10

0
0

1

2

3

4

5

6

7

8

9

10

11

12

>12

Investment

Figure 6: Distribution of Investment when only One Subject Participates, by Country (All Periods)