ISSN (Print) 0473-453X

Discussion Paper No. 1114

ISSN (Online) 2435-0982

A JAPAN’S EXPERIMENTAL COMPARISON
OF REBATE AND MATCHING
IN CHARITABLE GIVING

Shusaku Sasaki
Hirofumi Kurokawa
Fumio Ohtake

January 2021

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, JapanA Japan’s Experimental Comparison of
Rebate and Matching in Charitable Giving

Shusaku Sasaki*, Hirofumi Kurokawa†, Fumio Ohtake‡

Abstract
This study uses a Japanese nationwide sample and experimentally compares rebate and matching, bothof which are schemes intended to lower the price of monetary donation. Standard economic theory
predicts that the two schemes will have the same effect on individuals’ donation behavior when their
donation price is equivalent. However, we conduct an incentivized economic experiment through theInternet on 2,300 Japanese residents, and find that matching, which lowers the donation price byadding a contribution from a third-party, increases individuals’ donation expenditures compared torebate, which lowers it through a refund from a third-party. Specifically, the experimental result showsthat the donation expenditure in a 50% rebate treatment drops by approximately ¥126 compared to thecontrol, while in a 1:1 matching treatment with essentially the same price of donation as the 50%
rebate, the expenditure conversely rises by approximately ¥56. This tendency is consistent with theresults of previous experimental studies comparing the two schemes. We further empirically confirm
that the superiority of 1:1 matching over 50% rebate is not conclusively influenced by the participants’confusion or misunderstanding, or budget constraint lines’ difference between the two schemes.
Although the Japanese government have previously enriched rebate’s content, the level of monetary
donations by the Japanese people is still low on an international scale. Based on this study’s findings,
we discuss the possibility that implementing matching into the society effectively encourages their
donation behavior.
JEL Classification code: D91, H20, C91
Keywords: Charitable subsidy, Tax incentive, Framing effect, Online experiment

Corresponding author, Mail to ssasaki.econ@gmail.com; Faculty of Economics, Tohoku Gakuin University
School of Economics and Management, University of Hyogo‡ Graduate School of Economics, Osaka University*†

We thank Charles Yuji Horioka, Shunichiro Sasaki, and the participants at the ABEF’s 13th Annual Conference 2019
for discussions, comments, and encouragement. At the ABEF’s conference, Shusaku Sasaki received Encouragement
Award 2019 for poster presentation. The authors have been supported by the Japan Society for the Promotion of Science(17J07242; 19K13722; 20H05632) and the Behavioral Economics Research Center at the Institute of Social andEconomic Research of Osaka University.

11. Introduction
Non-profit organizations (NPOs) are essential for social stability since they provide complementary
services in fields where public services are not sufficiently provided by governments (Salamon
1994). The NPOs depend on donations from individuals and corporations to continue theiroperations. Thus, the question of how to effectively collect those donations is an important social
issue, and it has been explored both practically and academically (Sargeant and Shang 2017).
A number of countries have adopted rebate as s major scheme with the aim ofencouraging monetary donations from individuals (Giving Japan White Paper Research Society2017). Under this scheme, individuals’ income tax is deducted by a certain amount when they report
the monetary donations they made in that year when declaring their income for the year.
Policymakers expect the scheme to have a positive effect on individuals’ donation behavior, because
it lowers the price of donation. For example, assume one donates ¥10,000 to a charity and receives a¥5,000 tax reduction; this implies that one can donate ¥10,000 to the charity by spending only
¥5,000, and the price of ¥1 donation is ¥0.5.
However, rebate may not induce as much donation behavior as policymakers expect.
Institutional and procedural hurdles can impede donors’ use of the scheme. For example, the U.S. tax
system allows taxpayers to select either a standard deduction or an itemized deduction, the latter ofwhich is an actual deduction. Only if they select the latter, they can have access to the rebate scheme.
In practice, high-income taxpayers usually choose the itemized deduction, while about 70% of
taxpayers choose the standard one. Thus, many U.S. donors do not enjoy the benefits of the rebate
scheme (Kato 2010).
Matching is another major scheme used to lower the price of donation, similar to rebate.
Previous experimental economic studies have suggested that matching encourages individuals’
donation behavior more effectively than rebate. When one donates ¥5,000 to a charity under a 1:1
matching treatment, a third-party, for example a corporation or foundation, matches the amount of
this donation, and consequently ¥10,000 is donated to the charity. In other words, one needs to spend
only ¥5,000 in order to donate ¥10,000 to the charity, and the price of ¥1 donation is ¥0.5 in a 1:1
matching. This is the same as when one donates ¥10,000 under the rebate scheme and receives a
refund of ¥5,000 in the form of an income tax reduction. However, even when controlling for the
donation price and other factors, laboratory experiments have found that the matching framing
increases donation rates and average donation expenditure more than the rebate framing (Eckel and
Grossman 2003, 2006). This tendency has been confirmed in field experiments (Bekkers 2015;
Eckel and Grossman 2008, 2009, 2017). Based on this evidence, the matching scheme is now being
employed in fundraising activities by NPOs around the world.
This study is the first to experimentally compare the rebate and matching schemes inJapan, and to test whether matching is more effective in driving individuals’ donations in the country.
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The investigation is being conducted in Japan even though there is evidence from other countries,
because there are background and environmental factors at play that suggest that the rebate scheme
might not be effective in promoting donation behavior in Japan either. In other words, there is a needto explore another measure that can more effectively encourage Japanese people’s donation
behavior.
First, although the Japanese government has made efforts to improve the rebate scheme,
its utilization rate remains low, and the level of individual donations in Japan is also low on aninternational scale. The Japanese government introduced rebate as a tax incentive in 1962, with thisscheme in force since over than half a century. The 2011 tax reforms enabled individual donors to
select “exemption and deduction from income” or “tax credit,” which are called “shotoku-kojyo”
and “zeigaku-kojyo” in Japanese, respectively (Cabinet Office 2019a). When the former is selected,¥2,000 is deducted from one’s donation amount, and that amount is then deducted from one’s
income. The income after the deduction is multiplied by an income tax rate to calculate one’s income
tax. Japan’s income tax rates follow a progressive system, and therefore the tax reduction for thesame donation amount is larger for higher income groups. In contrast, when the latter is selected,¥2,000 is deducted from one’s donation amount, that amount is multiplied by 40%, and then theamount after multiplication is directly deducted from one’s income tax, regardless of income groups.
Therefore, low- and middle-income groups can receive a larger tax reduction by selecting the tax
credit option over exemption and deduction from income.1 Countries offering both systems are rare,
and the U.S., for example, does not offer the tax credit option. In this sense, Japan’s rebate scheme isprogressive on an international scale. However, the proportion of Japanese donors using the rebate
remains low, and was recorded at 16.7% in 2018 (Cabinet Office 2019b). Furthermore, as is widely
known, the level of individual donations in Japan is much lower than in other countries. Specifically,
the total value of individual donations in Japan stood at 0.14% as a share of nominal GDP in 2016.
This is only about one tenth of the U.S. donations (1.44%), about one quarter of the U.K. (0.54%),
and about a quarter of that of South Korea (0.50%), which is also an East Asian nation (Giving JapanWhite Paper Research Society 2017). This raises the concern that the past improvements to therebate scheme have not had enough impact on promoting Japanese people’s donation behavior.
Second, the cost of using the rebate in Japan could be as high as or higher than in othercountries. In Japan, individual income tax is withheld at source, and the income taxes of employedincome earners are recalculated in December by their employers to correct any excess or deficiency.
Thus, many Japanese workers do not usually need to file tax returns; however, they would need to do
so in order to make use of the rebate scheme. Using the scheme would impose a psychological cost

Imagine that a person with a taxable income of ¥6,000,000 donates ¥50,000. When he/she chooses the exemption
and deduction from income, the refund will be ¥9,600. On the other hand, when the person chooses the tax credit, therefund will be ¥19,200.
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on people because of performing an unfamiliar task, in addition to procedural costs. These costs
could discourage people considering making donations using the rebate scheme from doing so.2
Matching increases the amount donated to a charity by combining the donation amountsof donors with that of a third-party. Since the charities or the third-party are usually responsible forthe add-on donation process, donors’ procedural and psychological costs will be smaller when using
matching than when using the rebate. Thus, if matching is confirmed through experiments to be
more effective than rebate in Japan, there is a potential to substantially increase donations made by
Japanese people by implementing the matching scheme in the society. However, to the best of ourknowledge, there have been no experimental studies in Japan directly comparing matching andrebate.3 This study is quite important from both an academic and a policy perspective in that it is thefirst to conduct such an experimental comparison in Japan.
The remainder of this paper is structured as follows. Section 2 reviews experimental
studies in economics that have compared rebate and matching schemes. Section 3 describes theexperimental design in this study. Following basic results in Section 4, we conduct and present
further analysis in Section 5. Section 6 discusses the results and their practical implications, andconcludes while noting some limitations.
2. Literature Review on Rebate versus Matching
Eckel and Grossman (2003) point out that a matching rate (𝑚) is a function of a rebate rate (𝑟) as
follows: 𝑚 = 𝑟⁄(1 − 𝑟). This formula shows that a 1:1 matching is equivalent to a 50% rebate. In
the former scheme, when one chooses to donate ¥5,000 to a charity, the same amount will be added
to this donation, thus bringing the total amount donated to the charity is ¥10,000. In the latter scheme,
when one chooses to donate ¥10,000 to a charity, half of the amount will be refunded, making theactual donation expenditure ¥5,000. Similarly, a 2:1 matching is equivalent to a 33% rebate, and a
4:1 matching is equivalent to a 20% rebate.4
Standard economic theory predicts that, when the donation price and all other factors areequal, there should be no difference in individuals’ donation behavior for matching and rebate
schemes. However, Eckel and Grossman (2003) reveal that donation rates and average donation
expenditures for matching are higher than for rebate by employing a within-subject design where

According to data released by the by Cabinet Office (2019b), 13.4% of Japanese donors who did not use the rebate
scheme in 2018 stated that it is because they did not file tax returns. This is the third major reason for not using thescheme. The top reason is that they did not know about this scheme (40.9%).
3 In Japan, the possibility that rebate promotes donation behavior has been a subject of economic examination(Yamauchi 1997): however, again, there have been no experimental studies directly comparing rebate and matching.
4 We find in the comparison of consumption and income taxes another example of people’s different reactions under
two essentially equivalent conditions. When all income goes to consumption, the relationship between the income tax
rate (y) and the consumption tax rate (c) is as follows: y= c/(1+c). Blumkin et al. (2012) show that subjects decrease
their labor supply under an income tax system more than the equivalent consumption tax system. Kurokawa et al.
(2020) show that subjects prefer an income tax over the equivalent consumption tax.
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subjects are randomly exposed to both the schemes. Eckel and Grossman find similar results in 2006
when using a between-subject design where subjects are exposed to only one of the two schemes.
Furthermore, this superiority of matching over rebate has been confirmed in multiple field
experiments (Bekkers 2015; Eckel and Grossman 2008, 2009, 2017).
Thus, the relative effectiveness of matching has been robustly observed in various
experimental studies; however, there exist debates on why matching can drive individuals’ donation
behavior more effectively than rebate, and some scholars have conducted multifaceted investigations.
Eckel and Grossman argue that this tendency can be explained by people’s preference (Lukas,
Grossman and Eckel 2010). Specifically, matching has a “cooperative framing.” Within this frame,
since people can additionally gain a conformity utility by collaborating with others to donate, they
will be more likely to donate. In contrast, rebate has a “reward framing.” Within this frame,particularly for individuals with warm-glow (Andreoni 1989, 1990), receiving a refund will reduce
their selfish utility by donating to a charity themselves. In other words, receiving a refund causes
them to feel “greedy” (Benabou and Tirole 2006), and they will be less likely to donate.
However, other researchers raise the concern that the superiority of matching can be
explained by people’s confusion or misunderstanding rather than by their preference (Davis et al.
2005; Davis and Millner 2005). They conjecture if subjects in previous experiments may haveincorrectly understood how each scheme works and the differences between them, and whether they
may have chosen the same amount to be passed on to a charity in both schemes without deliberation,
resulting in higher donation expenditures under matching than those after refund under rebate. Davis(2006) also proposes an “isolation effect,” explaining subjects’ behaviors of ignoring the schemes’
differences and focusing on their initially selected amount. When individuals face a seemingly
complex problem, they often only consider factors that they directly have control over or that havedirect consequences for them. However, Eckel and Grossman have addressed other researchers’
concerns by employing a between-subjects design where subjects face only one of the two schemes,by providing in advance calculation exercises to support their understanding for the assigned scheme,
by afterwards checking their understanding of the experiment, and by providing information on all
combinations of “initially selected amount,” “reward to self,” and “donated amount to the charity,”
to make their decisions more transparent. Then, Eckel and Grossman argue that the superiority ofmatching over rebate is still due to people’s preference rather than their misunderstanding or
confusion.
Furthermore, Blumenthal et al. (2012) note that in Eckel and Grossman’s (2003, 2006)
experimental designs, the matching and rebate rates are equivalent, while the budget constraint lines
are not completely equivalent between the two schemes. For example, when the initial endowment is¥1,000, a 1:1 matching will deliver a maximum of ¥2,000 to a recipient, while a 50% rebate will
deliver only a maximum of ¥1,000 to them. For purely altruistic individuals who care about the5amount donated to a charity (Andreoni 1989, 1990), the budget constraint lines’ slopes are the same
between the two schemes, but the rebate line is partly truncated. A 1:1 matching allows subjects toselect the amount donated to charity of between ¥0-¥2,000, while a 50% rebate allows them to selectan amount between ¥0-¥1,000 only. However, more recent experiments by Lukas, Grossman and
Eckel (2010) and Blumenthal et al. (2012) unify budget constraint lines, and still confirm thesuperiority of matching over rebate.
The purpose of this study is to clarify the difference in effectiveness between rebate andmatching to determine the validity of the strategy for implementing matching schemes in Japan.
Although it is unlikely that this study’s results directly contribute to concluding the above debatesover the mechanisms, the debates must be taken into account when constructing our experimental
design and interpreting our experimental results. As we will show the details in the following section,
our experiment can identify the subjects with confusion or misunderstanding. We further interpret
our experimental results while empirically considering the impact of differences in budget constraintlines between the two schemes.

3.

Experimental Design

3.1. Overview
Between March 19 and March 21, 2019, we conduct an economic experiment through MyVoice.com
Ltd., which offers online surveys and experiments. Around 1 million adults living throughout Japanare registered on the company as response monitors. We sample 2,300 participants from thesemonitors in equal proportions by gender and age (age range: 20 and 69 years old), and conduct theonline survey and economic experiment on this sample.
The experiment in this study is incentivized using “points,” which can be exchanged forgift cards (nationwide gift cards, Amazon gift cards, App Store & iTunes gift cards, book cards, etc.)(MyVoice.com Ltd., 2020). The participants earn 70 points for answering the survey and can earn
additional points, which vary depending on their choices in the experiment, as explained in the next
section. Note that the exchange rate is 1 point = ¥1.5
[Figure 1]
The structure of this survey and experiment can be divided into three main parts (Figure1). First, we present the participants with questions that capture their behavioral economic
characteristics, including social, time, and risk preferences.6 Second, we randomly divide them into
rebate treatments, matching treatments, or a control, and conduct the economic experiment to5
6

One US dollar was approximately equivalent to 111 Japanese yen on March, 2019.
Our questions about social, time, and risk preferences are based on the Global Preference Survey (Falk et al., 2018).

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capture their donation behavior under each assigned condition. Specifically, we construct two groups
for the rebate treatments (50% rebate and 20% rebate) and the matching treatments (1:1 matching
and 4:1 matching). Third, we present participants with questions to capture their socio-economic
attributes, including gender, marital status, number of children, years of education, householdincome, and place of residence, etc., and gather their responses.7
3.2. Procedures
In the introductory page to the experimental part of the survey, participants are informed that, in
addition to the basic reward points for answering the survey, one in ten will have a chance to earnanother reward (See the Figure Appendix A).8 They are also informed that the additional reward
points are worth ¥1,000, and that the following page will ask how much of the ¥1,000 they arewilling to pass on to a social contribution project, assuming they could win and earn this additional
reward.9
Here, to help the participants understand that this experiment is not hypothetical but thatthey will receive a real monetary reward, we set the following check-box confirmations: “If you win
and earn 1,000 yen, your donation decision will be carried out as you answer,” “After winning, you
cannot change your answer. So, please think carefully before answering,” and “If you do not win,
you will not earn 1,000 yen, but your donation decision will not be carried out either.” Theparticipants have to confirm all the checkboxes in order to proceed to the following page. By
implementing the above device, we ensure the incentive compatibility of their choices.
Following this, regardless of the randomly assigned groups, the participants see thefollowing message, and are requested to donate to an organization engaged in afforestation
activities.10

Our survey experiment falls outside the scope of the Japanese government’s Ethical Guidelines for Medical and
Health Research Involving Human Subjects, and there are no national guidelines in Japan for social and behavioral
research. Although this study did not receive an ethical review, all respondents gave their informed consent toparticipate in this survey. After being informed about the purpose of the study and their right to withdraw from thesurvey, respondents agreed to participate. They were provided with the option “I want to stop participating in thesurvey” for all the questions. Completion of the entire survey experiment was considered to indicate respondent
consent. The authors did not obtain any personal information about the respondents.
8 Charness et al. (2016) review incentive schemes for laboratory experiments and report that there is no significant
difference for experimental results between the schemes where incentives are paid to all participants, and the otherschemes where incentives are randomly paid to a part of the participants.
9 Since the additional reward of ¥1,000 is paid to 1 person out of 10, its expected value is ¥100. According to“Giving Japan 2017” (Giving Japan White Paper Research Society 2017), the median amount of Japanese people’s
donation is a few thousand yen. Using the incentive scheme of random payment, we allow participants to choose their
donation amount from the endowment, which is close to that in the real world. Our analyses empirically address theconcern that the random payment may influence the estimated results by controlling for the effect of participants’ risk
attitude.
10 Before the experiment, we contacted the organization and obtained their approval for selecting them as therecipient. To ensure the recipient’s credibility, we selected the recipient among specified public‐service promotion
corporations, which are designated by a cabinet order as ones that significantly contribute to the promotion of public
interest.
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“Afforestation activities are currently being carried out around the world in order to reduce carbon
dioxide emissions and prevent global warming. Your donation will help to support an organization
engaged in the afforestation activities. Your donation will be used by the organization to restore
rainforests in countries, including Indonesia, Myanmar, and Vietnam. Your generous support isgreatly appreciated.”
In addition to the above message, the survey screen for the participants in the four groupsof rebate and matching display an “Important Notice,” which informs them of the content of theassigned treatment (Figure 2).
[Figure 2][Table 1]
Table 1 briefly summarizes how each group works. When one initially selects the option
to pass on ¥A to the organization in the control group, the actual donation expenditure is ¥A, thereward to oneself is ¥1,000 - ¥A, and the donated amount to the organization is ¥A. Table 1 shows acalculation example when A is ¥500 in the control group. Next, by comparing the formulas for eachtreatment group and calculation examples, we understand that a 20% rebate and a 4:1 matching are
equivalent, and a 50% rebate and a 1:1 matching are equivalent. Specifically, when one initiallyselects ¥1,000 in a 20% rebate, ¥1,000 is donated to the organization, while the individual will
receive a refund of ¥200, making the actual donation expenditure ¥800. If one initially selects ¥800
in a 4:1 matching, with the ¥200 additional contribution, the donated amount to the organization
becomes ¥1,000. The two cases are identical in the price of donation. If the initial selection is ¥1,000
in a 50% rebate, ¥1,000 is donated to the organization, while the individual will receive a refund of¥500, making the actual donation expenditure ¥500. If the initial donation is ¥500 in a 1:1 matching,with the ¥500 additional contribution, the donated amount to the organization becomes ¥1,000. Onceagain, the two cases are identical in the price of donation.
Finally, all the participants are asked;“If you win and earn ¥1,000, how much of the ¥1,000 are you willing to pass on to the worldwide
afforestation activities? Please answer in increments of ¥100.”
Participants are required to initially select the amount to pass on to the organization between ¥0 and¥1,000.
Even after the participants read their treatment message, it may be still difficult for them8

to correctly understand the relationship between the “initially selected amount,” “reward to self,”and “donated amount to the charity.” If many of the participants do not understand this relationship,
their selection will be due not to their “preference” as proposed by Eckel and Grossman, but rather
due to their “confusion and misunderstanding” as proposed by other researchers. In order to consider
this concern, we follow the procedure used in previous studies, and display one calculation example(when initially selecting ¥500), along with two calculation exercises (when initially selecting ¥1,000
and ¥0) (See the Figure Appendices B and C). By so doing, we help the participants understand theirassigned schemes.
Furthermore, we set up the survey screen to automatically calculate and display the“initially selected amount,” “reward to self,” and “donated amount to the charity” after theparticipants choose their initial amount (See the Figure Appendix D). Then, if they are satisfied withthe calculated results, they are required to click a button to confirm their selection. These features areuseful in preventing confusion or misunderstanding and the “isolation effect,” as pointed out inprevious studies.

4.

Basic Analysis

4.1. Balance Check
Table 2 reports the means and standard deviations of participants’ gender, marital status, number ofchildren, years of education, household income, and place of residence for each group to check the
random allocation of participants between the five groups. We can confirm that there is no
statistically significant difference in the means between the groups for all the variables in the table.11[Table 2]
In the following sections, we estimate the effects of rebate and matching, while
empirically considering the possibility that, in addition to the distribution of the socio-economic
attributes described above, the distribution of behavioral economic characteristics, including social
preference, time preference, and risk preference, may vary between the groups.
4.2. Results[Table 3]
Table 3 compiles donation amounts by group, in line with the table presented in Eckel and Grossman

When looking at household income, the mean of the control is ¥4.6 million, while the means of the 50% rebate and1:1 matching are in the range of ¥4.9 million, the latter being approximately ¥300,000 higher; however, the difference
is not statistically significant.
119(2003). Row (1) shows the initially selected amount in response to the question “If you win and earn
¥1,000, how much of the ¥1,000 are you willing to pass on to the worldwide afforestation activities?
Please answer in increments of ¥100.” Row (2) shows the actual donation expenditure, which is the
donation amount after refund in rebate. Row (2) is blank in the control and matching, showing that
there is no change from the amount in row (1).
In row (3), by respectively comparing the control and four treatment groups, we find thefollowing. First, the rebate treatments decrease the actual donation expenditure relative to the control.
This tendency is strongly observed in particular for the 50% rebate treatment, where the average
donation expenditure is approximately ¥126 lower compared to the control (p<.01). Assume that anindividual who selects ¥500 in the control is actually assigned a 50% rebate. If they wish to keep thesame donation expenditure as in a situation where they are assigned to the control, they need to
select ¥1,000. However, in reality, although the initially selected amount indeed increases, the extent
of that increase is not large, and the actual donation expenditure after refund becomes lower than in
the control. The results do not show that rebate promotes donation behavior.
Second, the matching treatments increase the actual donation expenditure relative to thecontrol. This tendency is strongly observed in particular in the 1:1 matching treatment, where theaverage donation expenditure is approximately ¥56 higher compared to the control (p<.01). Assume
that the same individual who selects ¥500 in the control is actually assigned to a 1:1 matchingtreatment. If they wish to have the same amount donated to a charity as in a situation where they are
assigned to the control, they only need to select ¥200 or ¥300. However, in reality, their initiallyselected amount changes toward an increase, not a decrease. Specifically, those who select ¥500 in
the control actually select higher amounts, ¥600, ¥700, or more, in the matching treatment. This
result suggests that matching promotes donation behavior, encouraging higher donation expenditure.
Row (4) confirms the above results from a different perspective. If the rebate andmatching treatments have the same impact on donation behavior, then no difference should beobserved when comparing the average actual donation expenditures between a 20% rebate and 4:1
matching, and between a 50% rebate and 1:1 matching treatment, respectively. However, we findthat the average donation expenditure for the 4:1 matching is approximately ¥83 higher than for the
20% rebate (p<.01), and that the 1:1 matching is approximately ¥182 higher than for the 50% rebate(p<.01).
[Table 4][Figure 3]
In Table 4, we use OLS and Type 1 Tobit estimation models and estimate the effects ofrebate and matching on actual donation expenditure, controlling for various covariates. Figure 3 also10presents the mean estimate and 95% confidence interval of the expenditure for each group. Thisshows that the statistical significance of the effects of the 20% rebate and 4:1 matching treatments
compared to the control group depends on the choice of estimation method; however, the direct
difference between the two treatments is robustly observed after controlling for the effects ofsocio-economic characteristics and behavioral economic variables, with a difference ofapproximately ¥80 (p<.01). In contrast, when compared to the control, the negative effect of the 50%
rebate and the positive effect of the 1:1 matching treatments on the actual donation expenditures arelarge and statistically significant at least at the 5% level in all estimation methods and model
specifications. Consequently, a direct difference between the two treatments is robustly observed,
with a difference of approximately ¥170 (p<.01).
In summary, we find through an experiment conducted on a Japanese sample of 2,300
respondents that matching is superior to rebate in encouraging higher donation expenditures. This
superiority is strongly and robustly observed in particular in the comparison of the 50% rebate and1:1 matching treatments.12 Our results are essentially consistent with the tendencies found in a seriesof experimental studies conducted by Eckel and Grossman.

5.

Further Analysis

5.1. Confusion or Misunderstanding
This section examines the relationship between the understanding of how rebate or matchingtreatments work and their treatment effects. As explained in the Procedures section, this economic
experiment provides participants with one calculation example and two calculation exercises tosupport their understanding of the treatment assigned to them. Specifically, we show formulae andthe amounts of “reward to self” and “donated amount to the charity” in the case when they initiallyselect ¥500 in their assigned treatment group. We then provide two calculation exercises asking whatthese two amounts would be, when initially selecting ¥1,000 and ¥0. However, we do not provide
feedback as to whether their answers are correct or incorrect. Thus, there might be some participants
who join the experiment without having their misunderstanding of the calculation process corrected.
If the effects in Section 4 are generated mainly because of the participants with misunderstandings,
the superiority of matching in this study would depend on their confusion and misunderstanding,unlike in Eckel and Grossman’s case.
[Table 5]

Table Appendix A shows the effect of each treatment on the binary choice of whether to donate. Although all thetreatments increase the donation probability, the 20% rebate’s effect is larger than that of 4:1 matching. Considering
the results of Section 4.2, 20% rebate could be less effective than 4:1 matching in increasing the average donation
expenditure (intensive margin), but more effective in increasing the donation probability (extensive margin). There is
no statistically significant difference between 50% rebate and 1:1 matching in increasing the donation probability.
1211Table 5 shows the proportion of correct answers to the calculation exercises in eachtreatment group. The proportions are not high throughout the results, with the proportion ofparticipants who correctly answer both questions being approximately 50%. Matching treatment
results appear slightly easier to calculate. The proportion of correct answers for the 4:1 matching isabout 9% higher than for the 20% rebate (p<.01), while that for the 1:1 matching is about 6% higher
than for the 50% rebate (p<.10). However, that being said, more than half the participants incorrectly
answered either of the questions for the 1:1 matching.
[Table 6]First, we examine whether the superiority of matching over rebate is observed even after
directly controlling for correct answers for both questions. Since we do not provide the exercises tothe participants in the control, we assume that they are all sufficiently aware of the relationshipbetween the “initially selected amount,” “reward to self,” and “donated amount to the charity.” Asshown in Table 1, the relationship in the control is quite simpler than in the four treatment groups,
and therefore this assumption is plausible. Table 6 shows that correctly answering both questions, on
average, increases the actual donation expenditure. However, even controlling for this effect, we stillfind a similar tendency, where matching encourages larger donations than rebate.
[Table 7]
Second, by dividing the participants into one group that correctly answers both questions
and another group that does not, we estimate the effect of the matching scheme while taking therebate scheme as a base. Table 7 shows that, regardless of whether the participants answer the two
problems correctly, matching increases the actual donation expenditure more than rebate. When
comparing the 20% rebate and the 4:1 matching treatments, the average donation expenditure undermatching is about ¥80 higher than under rebate in both the correct-answer and the incorrect-answer
samples (at least p<.05). When comparing the 50% rebate and the 1:1 matching treatments, thesuperiority of matching is more strongly observed within the correct-answer sample, while, even in
the incorrect-answer sample, the average donation expenditure under matching is about ¥150 higher
than under rebate (p<.01).
Based on the above findings, we can reject the concern that the results in Section 4 may
be explained primarily by participants’ confusion or misunderstanding. However, we cannot
overlook the behavior of the incorrect-answer sample when using a rebate or matching as a method
to encourage donations in the real world. Nearly half of the study participant answered questions
12

incorrectly, despite being provided with formulae and one calculation example beforehand. The
proportion of individuals who do not correctly understand the schemes is likely to be much higher inreality. Therefore, the comparative results of the two schemes in the real world will depend on the
behavior of people who misunderstand the schemes. However, the relative effectiveness of matching
can also be observed in the incorrect-answer sample in this study. This study’s results indicate thateven if rebates and matching are provided to a more general population, matching can still promote
donation behavior more than rebates.
Then, who correctly answers the calculation exercises, and who does not? Our simple
correlation analysis shows that those with higher education, higher income, and those living in urban
areas are more likely to answer both questions correctly. In other words, the mechanism behind thesuperiority of matching over rebate may vary across these segments.
5.2 Budget Constraint Lines
The experimental design of this study is based on Eckel and Grossman’s studies (2003, 2006). As
Blumenthal et al. (2012) point out, the price of donation is equivalent between rebate and matching,while their budget constraint lines are not completely the same. Specifically, people who would
spend ¥1,000 on a donation in the control can spend only ¥500 in the 50% rebate. Even if they selectthe same initial amount of ¥1,000, 50% of that amount is refunded to them. In contrast, if they are
assigned to the 1:1 matching, they can maintain the same ¥1,000 donation expenditure.
We confirm that the difference in the budget constraint lines does not critically determine
our experimental results in the following two ways. First, we increase participants’ endowment from
¥1,000 to ¥5,000 and ¥10,000 using hypothetical experimental questions. In this study, after the
incentivized economic experiment, we set questions to ascertain how much of an endowment theparticipants are willing to pass on to the same recipient, when the endowment is changed to ¥5,000
and ¥10,000 under the same treatment. In these situations, there should be fewer cases in whichsome people in the rebate treatments who wish to maintain or increase their own donation
expenditure are unable to do so due to their budget constraint.
[Table 8]
Table 8 shows that even after increasing the endowment, we still find that rebate has theeffect of decreasing the actual donation expenditure and matching has the effect of increasing it. In
particular, the average donation expenditure in the 50% rebate treatment is considerably lower thanin the control, despite the high endowments allowing the participants to initially select higher
amounts. Consequently, the superiority of the 1:1 matching over the 50% rebate is robustly found inboth ¥5,000 and ¥10,000 endowments (p<.01). We also find this superiority in the comparison of the13

20% rebate and 4:1 matching treatments: however, the statistical significance of their difference isrelatively weak (p<.10).
Second, using the estimated parameters for the control group, 13 we calculate thepredicted values for the four treatment groups for “how much they would spend on a donation if they
were assigned the control.” Then, we restrict the participants in 20% rebate and 50% rebate to thosewith a predicted value of ¥800 or less and to those with a predicted value of ¥500 or less,respectively. In other words, we use those who do not face a situation where the budget constraint
causes a decrease in their donation expenditure in the rebate treatments. We also limit theparticipants in the control group to those with the actual donation amount of ¥800 or less and to
those with that of ¥500 or less. We further impose both the restrictions on the participants in the 4:1
matching and 1:1 matching treatments. That is, we use those in the matching treatments who havethe same maximum predicted value and actual donation expenditure as in the rebate treatments. Hereit should be noted that the second restriction to the actual donation expenditure in the matchingplaces the matching scheme’s position at a relative disadvantage. For example, in the case of the 1:1
matching, this restriction excludes those who are predicted to have spent a donation amount of lessthan ¥500 in the control group and actually spent a larger donation amount in the 1:1 matchingtreatment. Since the participants with positive and larger individual treatment effects of matching are
excluded from the analysis, this will diminish the average positive treatment effect.
[Table 9]
We find from Table 9 that 1:1 matching remains superior to 50% rebate under the
disadvantageous condition. In columns 3 and 4, the restriction eliminates the superiority of the 4:1
matching over the 20% rebate. This may be evidence supporting that 4:1 matching’s superiority inthe past sections is accidentally generated by the difference in budget constraint lines.14 In contrast,columns 7 and 8 show that the 50% rebate’s effect of decreasing actual donation expenditure hasdisappeared, while the 1:1 matching’s increasing effect is persistent, despite limiting the analysis
sample in the 1:1 matching to those not only with a predicted value of ¥500 or less but also with theactual donation amount of ¥500 or less. Its effect size is about ¥50 and statistically significant(p<.01). This result strongly supports the relative effectiveness of the 1:1 matching treatment. In
addition, we posit that the superiority of 1:1 matching over 50% is not conclusively influenced byMore precisely, we use the control group’s sample and regress the donation expenditure amount on the following
socio-economic variables: gender, marital status, number of children, years of educations, household income, andplace of residence. We then use the estimated parameters of these variables and predict the dependent variable’s value
for the four treatment groups.
14 However, we also cannot deny the possibility that the additional and disadvantageous restriction to 4:1 matching
decreases its treatment effect more than necessary and it hides 4:1 matching’s superiority. Our sample restriction will
work properly when matching’s superiority is still observed.
13

14

the difference in their budget constraint lines.

6.

Discussion, Limitations and Conclusions

This study uses a Japanese nationwide sample and experimentally compares rebate and matching,both of which are subsidy schemes intended to lower the price of donation and encourage donation
behavior in individuals. The experimental results show that even if the donation price is equal
between matching and rebate treatments, matching, which lowers the price by adding a contribution
from a third-party, increases people’s actual donation expenditure more than rebate, which lowers
the price through refunds. Specifically, the results show that the actual donation expenditure dropsby about ¥126 when assigned to the 50% rebate as compared to the control, while the actual
donation expenditure increases by about ¥56 when assigned to the 1:1 matching (which hasessentially the same donation price as 50% rebate). This tendency is consistent with the results
observed in a series of experimental studies by Eckel and Grossman. We further empirically confirm
that our findings are not critically influenced by people’s confusion or misunderstanding, or thedifference in budget constraint lines in rebate and matching.
Matching has a greater promoting effect on individuals' donation behavior than rebate.
This implies that implementing the matching scheme in Japan has a greater potential to increase
donations among the Japanese people. The Japanese government has so far focused on improving
the rebate scheme, while there remains considerable scope for the implementation of matching.
According to the Economic Planning Agency (2008), the matching scheme in Japan has been
narrowly understood as “a scheme for corporations to match the donations of their employees tocharities,” and frequently adopted for promoting their employees’ social contribution activities.
However, there are only a few corporations that have introduced the matching scheme. For example,
in 2019, about 78% of the corporations that responded to a survey did not implement the scheme(Toyo Keizai Inc. 2020). It is necessary to consider measures to increase the number of corporations
that adopt the matching scheme, as well as to expand this scheme outside of corporations.
It should be noted that matching is not a panacea either. Matching induces larger
donations than rebate, but it does not have a positive effect on all individuals’ donations. Under thematching scheme, some people might wish to increase their out-of-pocket donation expenditure, butothers might wish to reduce it. The latter group may think that even if they reduce their own
out-of-pocket donation expenditure, the donation amount received by a charity through matching issufficient. This phenomenon is known as “crowding out” in economics (Karlan and List 2007; Huckand Rasul 2011). Recent economic studies have begun to explore options to prevent crowding out
and improve the efficiency of the matching scheme, specifically proposing that the matched amountis donated to other charitable projects, setting some thresholds, etc. (Adena and Huck 2017, 2019;
Charness and Holder 2019; Huck, Rasul and Shephard 2015). It is also necessary to consider these15

options before implementing the matching scheme in the Japanese society. In other words, such
options could further increase the superiority of matching over rebate.
We now discuss the limitations of this study. The participants in our economic
experiment receive their endowment as a windfall, as in Eckel and Grossman’s studies. Thus, their
behavior may not be consistent with the behavior of people in the real world, many of who makedonations from their salaries. In addition, participants in previous laboratory experiments could
freely choose an organization as a donation recipient from multiple NPOs, while in this study, we
specify the organization in advance: one engaged in afforestation activities. In other words, our study
participants may include a large sample of people who had no previous intention to donate to theorganization. Our experimental results may be affected by the phenomena where such the people areencouraged to make a larger donation by the matching scheme. Some future research should confirm
the generalizability of this study’s results before promoting the implementation of matching in theJapanese society. Nevertheless, we believe that this study has sufficient academic and policy
significance in that it is the first to experimentally demonstrate the superiority of matching overrebate in Japan.

16

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2019. (In Japanese)
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CitizenContributions

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Accessed: December 4, 2020. (In Japanese)
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Decision Making, 1(1), 13-22.
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Davis, D. D., Millner, E. L., and Reily, R. J. (2005). Subsidy schemes and charitable contributions: A
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Eckel, C.C., and Grossman, P.J. (2003). Rebate versus matching: Does how we subsidize charitable
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contributions matter? Journal of Public Economics, 87(3-4), 681-701.
Eckel, C.C., and Grossman, P.J. (2006). Subsidizing charitable giving with rebates or matching:
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Paper.
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Falk, A., Becker, A., Dohmen, T., Enke, B., Huffman, D., and Sunde, U. (2018). Global evidence on
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19Figure and Tables
Figure 1. The Survey and Experimental Structure

Participants
N=2,300

Survey A

Economic experimentControl
N=460

Treatment 1
N=460

Treatment 2
N=460

Treatment 3
N=460

Treatment 4
N=460

20% rebate

4:1 matching

50% rebate

1:1 matchingｖｖ

Survey B

20ｖ

Figure 2. Treatment Messages
20% rebate:
Important Notice:
For every donation amount you pass on to the charity,

the experimenter will refund 20% of the amount to you.

4:1 matching:
Important Notice:
For every donation amount you pass on to the charity,
the experimenter will match it with an additional 25% of the amount.

50% rebate:
Important Notice:
For every donation amount you pass on to the charity,

the experimenter will refund 50% of the amount to you.

1:1 matching:
Important Notice:
For every donation amount you pass on to the charity,
the experimenter will match it with an additional equal amount.

21

Table 1. Contents of Treatments

Control

20% rebate

4:1 matching

50% rebate

1:1 matching

1. Initially selected amountAA

1,000 yenA

800 yenA

1,000 yenA

500 yen

2. Actual donation expenditureA

0.80*A

800 yenA

800 yen0.50*A

500 yenA

500 yen

1000-A

10000.80*A

200 yen

1000-A

200 yen

10000.50*A

500 yen

1000-A

500 yenAA

1,000 yen

1.25*A

1,000 yenA

1,000 yen

2.00*A

1000 yen

3. Reward to self
4. Donated amount to the charity

22

Table 2. Balance Check

Control

20% rebate

4:1 matching

50% rebate

1:1 matching

N=460

N=460

N=460

N=460

N=460

Mean

Standard
Deviation

MeanStandard
Deviation

MeanStandard
Deviation

MeanStandard
Deviation

MeanStandard
Deviation

Female dummy

0.50[0.50]

0.50[0.50]

0.50[0.50]

0.50[0.50]

0.50[0.50]

Married dummy

0.50[0.50]

0.57[0.50]

0.52[0.50]

0.55[0.50]

0.53[0.50]

Number of sons

0.43

[0.71]

0.49[0.78]

0.47[0.75]

0.52[0.79]

0.46[0.73]

Number of daughters

0.45[0.71]

0.44[0.73]

0.48[0.73]

0.45[0.71]

0.41[0.68]

Educational years

14.54[2.20]

14.56[2.08]

14.59[2.07]

14.45[2.13]

14.58[2.16]

Household income (10,000 yen)462.93[390.94]

479.02[446.37]479.02[406.24]495.43[428.42]493.26[429.19]

No income information

0.17[0.38]

0.20[0.40]

0.18[0.38]

0.18[0.38]

0.18[0.38]

Large city residence dummy

0.37[0.48]

0.35[0.48]

0.35[0.48]

0.33[0.47]

0.38[0.49]

Variable name:Note: Some respondents did not answered annual household income. We imputed the average amout of the income for such respondents while considering that they did not answer it
by using the variable of no income information.

23

Table 3. Basic Descriptive Result
Control

20% rebate

4:1 matching

50% rebate

1:1 matching

Number of observations:

N=460

N=460

N=460

N=460

N=460

Price of donating 1 yen to the charity:

1 yen

0.8 yen

0.8 yen

0.5 yen

0.5 yen(1) Initially selected amount

Mean[Standard Deviation](Standard Error)

Mean[Standard Deviation](Standard Error)

Mean[Standard Deviation](Standard Error)

Mean[Standard Deviation](Standard Error)

Mean(Standard Deviation)[Standard Error]

357.39[340.65]

390.22[318.72]

395.65[333.89]463.26[360.31]413.48[329.51]

AC(2) Actual donation expenditure

312.17(3) Control vs Treatments-45.22E[254.98]

231.63

B[180.16]D(19.84)

38.26

B-A≠0

(22.24)C-A≠0(4) Rebate vs Matching

83.48
C-B≠0

24

-125.76
D-A≠0(19.59)(17.97)56.09(22.10)E-A≠0181.85E-D≠0(17.51)

Table 4. Basic Regression Result

(1)

(2)

(3)

(4)

(5)

OLS

Estimation method:

50% rebate

(8)

(9)

(10)

Basement－－

1,000 yenEndowment:

4:1 matching(7)

Actual donation expenditure

Dependent variable:

20% rebate(6)

Tobit (Type 1)-45.217**-47.491**-40.752***(19.319)(17.827)(14.269)

38.26135.32039.030*81.958***(23.892)(23.871)(20.622)(21.320)-125.761*** -128.272*** -121.341***

Basement－－-20.185-22.410-15.706(19.125)(18.969)(18.054)40.750**37.867**42.097**60.924***(19.152)(18.967)(18.053)(18.387)-92.445***-95.894***-92.593***－

Basement(19.209)(19.057)(18.153)

172.774***

59.972***59.603***56.410***－152.925***(13.233)(19.119)(18.945)(18.018)－

Basememt(19.086)(18.130)(14.577)56.087***55.310***50.863***(17.744)(17.157)(14.880)

Socio-economic attributes

No

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

Yes

Behavioral economic attributes

No

No

Yes

Yes

Yes

No

No

Yes

Yes

Yes

Number of observations

2,300

2,300

2,300

920

920

2,300

2,300

2,300

920

920

1:1 matching－(16.392)

Notes: We use cluster robust standard errors in parentheses for OLS estimations, while we use robust standard errors in parentheses for Type 1 Tobit estimations. *** p<0.01,** p<0.05, * p<0.1. In columns 1-3 and 6-8, we use the sample of all the groups. In columns 4 and 5, we use the sample of 20% rebate and 4:1 matching treatment groups, and incolumns 9 and 10, we use the sample of 50% rebate and 1:1 matching treatment groups.

25

Figure 3. Actual Donation Expenditure by Group

Note: The vertical line represents a 95% confidence interval.

26

Table 5. Proportion of Correct Answers

20% rebate

4:1 matching

50% rebate

1:1 matching

N=460

N=460

N=460

N=460

Number of observations:
Mean

Standard
Deviation

MeanStandard
Deviation

MeanStandard
Deviation

MeanStandard
Deviation

Percentage of correct answers
for the 1st calculation exercise

0.67[0.47]

0.72[0.45]

0.53[0.50]

0.57[0.50]

Percentage of correct answers
for the 2nd calculation exercise

0.65[0.48]

0.69[0.46]

0.63[0.48]

0.66[0.48]

Percentage of correct answers
for both of the calculation exercises

0.52[0.50]

0.61[0.49]

0.43[0.50]

0.49[0.50]

27

Table 6. Further Analysis: Confusion or Misunderstanding (a)

(1)

(2)

OLS

Estimation method:

50% rebate(5)1,000 yenEndowment:

4:1 matching(4)

Actual donation expenditure

Dependent variable:

20% rebate(3)

Basement－

50.844**80.979***－(20.381)(21.593)-26.914-30.413-26.392(19.860)(18.900)(15.745)

53.251**49.424**(23.393)(23.578)-103.896*** -107.884*** -104.122***－

Basememt－

169.526***(20.498)(19.625)(16.484)

75.550***73.658***66.169***(17.959)(17.707)(16.216)38.097***35.835***30.029**11.70749.365***(13.304)(11.998)(11.245)(17.157)(12.085)

Socio-economic attributes

No

Yes

Yes

Yes

Yes

Behavioral economic attributes

No

No

Yes

Yes

Yes

Number of observations

2,300

2,300

2,300

920

920

1:1 matching

Correct Answer(13.396)

Notes: Cluster robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. In columns 1-3,
we use the sample of all the groups. In column 4, we use the sample of 20% rebate and 4:1 matchingtreatment groups, and in column 5, we use the sample of 50% rebate and 1:1 matching treatment groups.

28

Table 7. Further Analysis: Confusion or Misunderstanding (b)

(1)

(2)

(3)

(4)

(5)

(7)

(8)

Actual donation expenditure

Dependent variable:

1,000 yenEndowment:

OLS

Estimation method:
20% rebate versus 4:1 matchingComparison:
Correct or incorrect:(6)

Correct answers

50% rebate versus 1:1 matching

Incorrect answers

4:1 macthing

79.259***81.302***86.535**83.333***

Basement: 20% rebate(22.935)(22.364)(32.257)(27.892)

Correct answers

Incorrect answers

1:1 macthing

209.613***

195.890***151.040***

149.452***

Basement: 50% rebate(25.492)(21.303)(18.629)(16.694)

Socio-economic attributes

No

Yes

No

Yes

No

Yes

No

Yes

Behavioral economic attributes

No

Yes

No

Yes

No

Yes

No

Yes

Number of observations

518

518

402

402

421

421

499

499

Notes: Cluster robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1. In columns 1-4, we use the sample of 20% rebate and 4:1
matching treatment groups, and in columns 5-8, we use the sample of 50% rebate and 1:1 matching treatment groups.

29

Table 8. Further Analysis: Budget Constraint Lines (a)

(1)

(2)

(3)

(8)

(9)

(10)

Basement－－

10,000 yen

5,000 yenEndowment:

OLS

Estimation method:

4:1 matching(7)

Actual donation expenditure

Dependent variable:

20% rebate

(6)

(5)

(4)

Basement-87.913-99.177-79.057(60.801)(61.050)(50.146)106.73997.984102.609183.438**(83.451)(84.422)(72.740)(77.075)－－-177.522-196.865-156.324(128.985)(133.444)(116.442)

119.565101.728114.248282.105*(167.264)(168.612)(149.255)(154.543)－

Basement－

737.273***－

Basememt-501.304*** -519.147*** -479.422***(128.546)(130.099)(123.651)－

400.481***301.522***287.832**

260.143**(62.698)(105.554)(109.433)(113.566)

Yes

Yes

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

No

Yes

Yes

Yes

2,300

920

920

2,300

2,300

2,300

920

920

50% rebate-287.391*** -297.132*** -276.633***(59.675)(58.662)(53.564)

1:1 matching

145.870***

137.849**

122.329**(52.632)(53.115)(55.260)

Socio-economic attributes

No

Yes

Yes

Behavioral economic attributes

No

No

Number of observations

2,300

2,300

(127.355)

Notes: Cluster robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1. In columns 1-3 and 6-8, we use the sample of all the groups. In columns 4 and 9, we use
the sample of 20% rebate and 4:1 matching treatment groups, and in columns 5 and 10, we use the sample of 50% rebate and 1:1 matching treatment groups.

30

Table 9. Further Analysis: Budget Constraint Lines (b)

(1)

(2)

(3)

(4)

(5)

OLS

Estimation method:
20% rebate versus 4:1 matchingComparison:
62.151***

Basement(13.803)

50% rebate

63.834***50% rebate versus 1:1 matching
Basement

－

－

－

－

－

－

－

－

0.499

Basement

1.717

Basement(13.003)141.545***79.628***38.181***-24.805(17.815)(20.203)(12.445)(15.762)

－

－

－

－

(11.353)
1:1 matching(8)

1,000 yenEndowment:

4:1 matching(7)

Actual donation expenditure

Dependent variable:

20% rebate

(6)

－

－

－

－

(11.035)

170.861***168.883***49.443***48.868***(13.996)(14.196)(10.974)(11.605)

Socio-economic attributes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Behavioral economic attributes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Maximum amount restriction for matching

No

No

Yes

Yes

No

No

Yes

Yes

Number of observations

1,309

920

1,235

846

1,191

817

1,108

734

Notes: Cluster robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1. In columns 1 and 3, we use the sample of the control group and 20%
rebate and 4:1 matching treatment groups. In columns 2 and 4, we use the sample of 20% rebate and 4:1 matching treatment groups. In columns 5 and 7, we
use the sample of the control group and 50% rebate and 1:1 matching treatment groups. In columns 6 and 8, we use the sample of 50% rebate and 1:1 matchingtreatment groups.

31Appendix.
Figure Appendix A. The Introductory Page to the Experiment

In a drawing (one in ten), you will win and earn reward points worth 1,000 yen.
Winners will be notified by email at a later date.
――――
You can pass a part or all of the earned 1,000 yen to a social contribution project.
From the next page, the experimenter will introduce to you the content of the
project.
Assuming you could earn 1,000 yen, please answer how much of the 1,000 yen
you will pass on to the project.
――――□ If you win and earn 1,000 yen, your donation decision will be carried out as
you answer.
□ After winning, you cannot change your answer. So, please think carefully
before answering.
□ If you do not win, you will not earn 1,000 yen, but your donation decision will
not be carried out either.

32

Figure Appendix B. The Screen for the Calculation Example (The Case of 1:1 Matching)

For example, if you initially select ¥500 under this scheme, your reward amountwill be ¥500 and the amount donated to the afforestation activities will be ¥1,000.
Initially selected amount = ¥500
Reward to self = ¥1,000 - Initially selected amount (¥500) = ¥500
Donated amount to the charity = Initially selected amount (¥500) × 2 = ¥1,00033Figure Appendix C. The Screen for the Calculation Exercises (The Case of 1:1 Matching)Calculation exercise 1. Please select the correct combination of the amounts
that enter A and B in the text.
If you initially select ¥1,000 under this scheme, your reward amount will be A
and the amount donated to the afforestation activities will be B.

1) A: ¥0 B: ¥1,000
2) A: ¥0 B: ¥2,000
3) A: ¥1,000 B: ¥1,000

Calculation exercise 2. Please select the correct combination of the amounts
that enter C and D in the text.
If you initially select ¥0 under this scheme, your reward amount will be C andthe amount donated to the afforestation activities will be D.
1) C: ¥1,000 D: ¥02) C: ¥0 D: ¥1,000
3) C: ¥1,000 D: ¥1,000
Notes: The numbers of correct answers are 2) and 1), respectively. The initially selected amounts andthe numbers of correct answers are common between 1:1 matching are the other treatments (20%rebate, 4:1 matching, and 50% rebate).

34

Figure Appendix D. The Screen for the Donation Decision

If you win and earn 1,000 yen,

Initially selected amountyen

Reward to selfyenDonated amountto the charityyen

If you are satisfied with the above amounts, please click the "Next" button.
If you want to change them, please select again the amount that you pass on to the charity.

35

Table Appendix A. Whether to Donate (Binary Choice)

(1)

(2)

(3)

(4)

(5)

Whether to Donate (Binary Choice)Dependent variable:

1,000 yenEndowment:

Linear Probability Model

Estimation method:

Basement－

0.053**-0.060**－(0.025)(0.020)(0.024)0.083***

0.080***

0.088***－

Basememt(0.024)(0.023)(0.019)0.080***

0.080***

0.077***－-0.010(0.025)(0.025)(0.023)Socio-economic attributes

No

Yes

Yes

Yes

Yes

Behavioral economic attributes

No

No

Yes

Yes

Yes

Number of observations

2,300

2,300

2,300

920

920

20% rebate

4:1 matching

50% rebate

1:1 matching

0.109***

0.107***

0.116***(0.025)(0.024)(0.021)

0.052**

0.049*(0.025)(0.021)

Notes: We use cluster robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. In columns
1-3, we use the sample of all the groups. In column 4, we use the sample of 20% rebate and 4:1 matchingtreatment groups, and in column 5, we use the sample of 50% rebate and 1:1 matching treatment groups.

36