ISSN (Print) 0473-453X

Discussion Paper No. 1238

ISSN (Online) 2435-0982

PAYING TO AVOID THE SPOTLIGHT

Te BaoJohn Duffy
Nobuyuki Hanaki

Revised September 2024
April 2024

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

Paying to avoid the spotlight∗
Te Bao†John Duffy‡

Nobuyuki Hanaki§

September 7, 2024

Abstract
In the digital age, privacy in economic activities is increasingly
threatened. In considering policies to address this threat, it is useful
to consider what value, if any, people attach to privacy in their economic activities. This valuation may be influenced by a mixture ofconcerns including the desire for personal autonomy, concerns about
the exposure of confidential information, and the risk of reputational
damage due to dishonest or stigmatized behavior. Our focus is primarily on reputational concerns as we assess individuals’ willingness
to pay (WTP) to avoid scrutiny of their potentially dishonest behavior in a simple coin flipping task. We gather and analyze datafrom Japan, China, and the U.S.A. to determine if there are notabledifferences across these nations in WTP. Our findings reveal thatpeople’s WTP to “avoid the spotlight” is positive and economicallysizable across all three countries and is the largest in Japan.

Keywords: Privacy, Monitoring, Surveillance, Willingness to Pay,
Dishonesty, Lying, Social Image Concerns.
JEL Codes: C91, D83, D91.

∗

The experimental protocol used to collect data was approved by the IRB of theInstitute of Social and Economic Research (ISER), Osaka University (No. 20230201
and 20230803). The experiment is pre-registered at aspredicted.org (#147410 for the
CHOICE treatment and #144318 for the control treatments). Funding for this project
was provided by (a) the Joint Usage/Research Center, ISER, Osaka University, (b)Grants-in-aid for Scientific Research Nos. 18K19954, 20H05631, and 23H00055 from theJapan Society for the Promotion of Science, and (c) School of Social Science, UC Irvine.
†
Nanyang Technological University‡
University of California, Irvine, and Institute of Social and Economic Research,
Osaka University§
Corresponding author. Institute of Social and Economic Research, Osaka University,and University of Limassol

1Introduction

In our increasingly digital world, the prospect of maintaining privacy ineconomic matters is under significant threat (Acquisti et al., 2015, 2016).
The majority of financial transactions, including those conducted using
debit and credit cards, online banking, and mobile payment platforms, arenow conducted electronically. These methods are all easily surveilled, withtransaction records accessible through court orders in some jurisdictions,or directly monitored by governments in other settings. Consequently, suchtransactions often lack any privacy protections. The rise of cryptocurrencies partially reflects a pursuit of transactional privacy and independence
from the volatility of sovereign currencies (Herskind et al., 2020). In response, several central banks, initially China, are developing Central Bank
Digital Currencies (CBDCs) to sustain fiat currency demand and thus enable or preserve various monetary policies. However, CBDC transactions
which are linked to electronic ledgers will inevitably lead to a further erosion of privacy (Ahnert et al., 2022; Wang, 2023).
There is a large literature on internet privacy that addresses topics suchas the provision of personal information during online purchases (Beresford
et al., 2012; Preibusch et al., 2013; Jentzsch et al., 2012; Tsai et al., 2011),
and methods to hide various types of information such as browsing history,
contact information, location, and text on smartphone apps (Savage andWaldman, 2015; Skatova et al., 2019). An existing international comparison across US, Germany, and several Latin American countries shows that
Germans value these privacy concerns more than people in other countries.(Prince and Wallsten, 2022). While such concerns for controlling thedisclosure of personal information are certainly important, they are not the1specific focus of our study. Instead, we are interested in privacy surrounding economic transactions—specifically, the desire for economic activities
to be untraceable, as is possible with cash transactions.
There can be several rationales for desiring privacy or anonymity ineconomic transactions. First, privacy can be seen as a form of agency, or
self-determination, allowing individuals to control the disclosure of personal
information according to their own preferences, rather than due to externalpressure. This control can be critical in economic environments where
personal data is both a valuable asset and a protected commodity.
Second, privacy may be desired to mitigate societal stigma associatedwith certain legal but sensitive activities, such as mental health consultations or bankruptcy proceedings. Although legal, these activities can carrya stigma that adversely affects a person’s social standing, and thus theireconomic opportunities.
Third, and most germane to this study, privacy can also shield illicit or
fraudulent behavior. The anonymity enabled by certain economic mechanisms may protect individuals from reputational damage or legal consequences if such activities were exposed.
These mixed motives present a paradox wherein privacy safeguards legitimate desires for anonymity and autonomy while also facilitating potential illegal activity or misconduct.
Our approach to understanding the value of privacy in economic transactions is to elicit individuals’ willingness to pay (WTP) to avoid being
observed in reporting on economic activities.
1

1

Considering the mixed

While the well-known willingness-to-pay and willingness-to-accept gap (see, e.g.,
Plott and Zeiler, 2005, for a review) is also found in the valuation of privacy (Acquisti
et al., 2013), we are not interested in this particular behavioral aspect in this current
paper.

2

motives that people may have for demanding privacy, we elicit the WTP
for privacy in a setting where misconduct is a possibility. In contrast to
most literature exploring the value of privacy,(Tsai et al., 2011; Savage
and Waldman, 2015; Skatova et al., 2019; Prince and Wallsten, 2022), we
elicit people’s WTP for privacy in an incentive-compatible manner. Indeed, Benndorf and Normann (2018) show a large “hypothetical bias” inpeople’s willingness to disclose their personal information, namely, while
five out of six respondents in a non-incentivized survey refused to disclose
their personal information, it was only one of six participants who did thesame in an incentivized experiment. Our incentivized experiment would
not suffer from similar bias.
Our findings have important implications for understanding the acceptability, or reluctance to adopt media of exchange or institutions that forego
privacy rights. Specifically we ask (1) How much are individuals willing to
pay for privacy in economic transactions? (2) Does behavior differ if individuals do not have a private option or cannot pay for privacy? (3) Does
the value of privacy differ across countries? If so, what are the correlatesof those differences?
Using the lie-detection task pioneered by Fischbacher and Föllmi-Heusi(2013), our experimental design directly reveals whether people desire privacy, or the unobservability of their economic activities in order to engage
in lying or other forms of immoral behavior, in an incentive compatible
manner. Specifically, in our main experiment, subjects flip a fair coin ten
times and report the number of heads and tails. For each head that a
subject reports, they receive 100 points. Thus, by reporting 10 heads,
they earn the maximum of 1000 points. There is no explicit penalty for3misreporting.
For this task, subjects can choose between using a fair coin provided on
our experimental software platform (i.e., a virtual coin) for free or using
their own coin by paying a fee. The main difference between the two options
is whether the consistency (or the gap) between the realized and reported
outcomes of the coin flips can be verified or not. Such a verification can bedone if the virtual coin is used, but not if participants’ own coin is used.
We elicit subjects’ WTP to use their own coin, instead of the virtual coin, using the Becker–DeGroot–Marschak [BDM] mechanism (Becker
et al., 1964). To the best of our knowledge, our study is the first to elicit
and compare the WTP for privacy in economic transactions across countries, specifically, China, Japan, and the U.S. in a setting where there issome potential monetary benefit for dishonest behavior.
Our findings reveal that people’s WTP to use their own coin in order
to “avoid the spotlight” is positive and economically sizable; on average,
it is more than 30% of expected monetary gain from lying, across all three
countries and is the largest in Japan where, on average, it is more than 40%
of such a gain. The observed high values placed on privacy in economictransactions suggest the need for a proper balance between fraud prevention
and ensuring privacy in our increasingly digital economy.

2

Experimental Design

As noted above, in our experiment, as in Cohn et al. (2014), subjects flipa fair coin ten times and report the numbers of heads and tails (whichmust add up to ten). For each head that a subject reports, they receive4100 points. Thus, by reporting 10 heads, they earn the maximum of 1000
points. The earned points are converted into the local currency at theend of the experiment using a pre-specified exchange rate that adjusts forpurchasing power differences across countries, so that all of our subjects
face approximately the same monetary incentives. Specifically, 100 points
were converted into 100 JPY in Japan, 1.00 USD in the U.S., and 4 RMB
in China.2
There is no explicit penalty for misreporting the number of heads andtails in any treatment of our study. Therefore, the predicted, profit-maximizing
behavior by homo-economicus participants is to always report 10 heads. A
meta-study of such truth-telling experiments by Abeler et al. (2019), however, shows that most participants do not lie to an extreme extent; rather
they partially over-report the number of heads relative to expected numbers. What we add to this task is a willingness to pay elicitation and somefurther treatments.
Specifically, in our main, CHOICE, treatment, subjects can complete
the task of flipping a coin 10 times using a freely provided virtual coin on
our experimental software platform. Alternatively, they can choose to use
their own coin to complete the 10 coin flips but only if they pay a fee.
Subjects are told that if they use the virtual coin, the experimenters canlater check the realized outcomes of the virtual coin flip. By contrast, if
they use their own coin, it is not possible for the experimenter to observe
the outcome of those coin flips. Subjects are also told that, regardless ofthe coin they use, virtual or own, the experimenters rely only on their own
self-report of the outcome of the coin flip — the number of heads and tails
2

These conversion rates were purchasing power equivalent at the time of the study.

5that they report – to determine their payment.
Prior to the coin flip task, we use the BDM mechanism (Becker et al.,1964) to elicit subjects’ WTP for the right to use their own coin to complete the coin flip task. As noted, there is no cost to using the virtual
coin. Specifically, subjects submit their W T P i in 10 point increments,{0, 10, 20, . . . , 490, 500}. Notice that the upper bound of 500 points inthe WTP elicitation is the expected gain (in points) from using one’s
own coin and reporting 10 as the number of heads. Once participants
submit their W T P i , the computer randomly draws a price (in points)pi ∈ {10, 20, . . . , 490, 500} for each participant. If pi ≤ W T P i , the subject
i pays pi (out of their experimental earnings) and uses his/her own coin,otherwise, s/he uses the virtual coin for free. Subjects who do not want to
use their own coin could simply state that their WTP was 0, thereby ensuring that they would use the virtual coin and this possibility was carefully
explained to them.3
The elicited WTP captures the privacy concerns of subjects associated3
One may be concerned about our use of the BDM method as it is known to be confusing for participants (Cason and Plott, 2014), in particular, when payoffs are presented
in points rather than in local currency. To facilitate participants’ understanding of the
BDM mechanism, we have instructed participants to methodically consider their WTP.
Specifically, we suggest that they consider whether they are willing to pay 10 points to
use their own coin instead of the virtual coin. If the answer is no, they should submit 0.
If the answer is yes, then, they should next consider whether they are willing to pay 20
points to use their own coin instead of the virtual coin. If the answer is no, they should
submit 10. If the answer is yes, they proceed to considering 30 points, etc. We instructedsubjects to repeat this exercise until their answer is no. We also had two questions in
our comprehension quiz to check their understanding of the BDM mechanism. As forthe possibility of additional confusion due to use of points instead of the local currency,
in our pilot sessions in Japan, we used local currency. Namely, in our pilot sessions, eachhead accounted for 100 JPY instead of 100 points, and in BDM procedure, participants
were asked to submit their WTP in 10 JPY increments. The distribution of WTPs in
the pilot sessions is not significantly different from the one we report below using points.
The results of the pilot sessions are available upon request. The reason for using points
in the experiment reported in this paper is to enable international comparisons. Thatis, to homogenize the instructions in points and adjust the exchange rate to the local
currency based on purchasing power parity.

6

with using the virtual coin instead of their own coin. To make this moreformal we adapt the framework of Abeler et al. (2019) who suggest thatreporting behavior in experiments of this type is based on three determinants: (1) the material gain, (2) the self-image concern, and (3) thesocial-image concern. We will here refer to the social-image concern as theprivacy concern.
Following this framework, the utility of reporting the number of heads,
H, when the actual realization is R, ui (H|R), can be written as:ui (H|R) = π i (H) − ci (H − R) − γ i (H − R) if using the virtual coin,ui (H|R) = π i (H) − ci (H − R)

if using one’s own coin.

Here, π i (H) is the monetary gain, ci (H −R) is the cost associated with selfimage concerns, and γ i (H −R) is the privacy concerns of reporting H heads
when the actual realized number of heads was R. Intuitively, the first orderderivatives of ci (H − R) and γ i (H − R) should be non-negative, i.e., thecost of social image concerns and privacy concerns should be greater when
the participant deviates from honest reporting to a larger degree. Whenchoosing their WTP to use their own coin instead of using the virtual coinfor free, each subject i would compare the expected maximized utility ofusing the virtual coin with that of using his/her own coin. Therefore, thesubmitted WTP should be equivalent to the difference between the monetary value of the two maximized expected utilities, and that is primarily
driven by the cost associated with privacy concerns in using the virtual
coin unless the self-image concern dominates all the other considerations.4
4

Another possibility is that participants submit a positive WTP value because they
do not believe the virtual coin is a fair coin despite the fact the coin is in fact fair
and we inform subjects of this fact in the instructions. Although we cannot eliminate

7

In addition to the CHOICE treatment, we also design two control
treatments, VIRTUAL and OWN, where subjects are not given a choice
regarding the type of coin they can use. In the VIRTUAL treatment,
subjects must use the virtual coin. In the OWN treatment, they must use
their own coin. In these two treatments, therefore, there is no elicitation of
WTP to use their own coin instead of the virtual coin, as there is no choiceof the type of coin that will be used. Still, as in the CHOICE treatment,
subjects in these two control treatments report the number of heads andtails and are paid solely on the basis of their own report.
The literature (see, among others, Abeler et al., 2019; Fries et al., 2021;
Gneezy et al., 2018) suggests that participants tend to lie more in moreanonymous situations. In our experiment, this suggests participants reportlarger number of heads in VIRTUAL than in OWN due to their socialimage concerns. While verification of this hypothesis using our control
treatments is interesting (see Appendix A for the result of such comparisons), our main purpose in introducing these two control treatments is to
explore whether and how offering subjects a choice between a virtual coinand their own coin, with the latter carrying a fee (as in our main treatment), affects their reporting behavior relative to the control cases where
there is no choice of which coin to use.

2.1

Questionnaire

After reporting on the number of heads and tails from the 10 trials, participants had to complete a questionnaire in which, in addition to providing
this possibility for submitting a positive WTP, the fact that we have conducted ourexperiment in experimental laboratories where no deception is the rule and participants
are aware of this rule should reduce the impact of such a consideration.

8

information on their age and gender, they were asked the following questions:(1) How many, out of 20 randomly chosen participants in the experiment,
have reported the outcome of coin flips truthfully?
(2) How many have reported a W T P > 0? (only in the main treatment)(3) In general, how willing are you to take risks? Please indicate on
the scale below from 0 to 10, where 0 means you are “completely
unwilling to take risks” and a 10 means you are “very willing to takerisks.”(4) What do you think is the purpose of the experiment?
(5) Please indicate whether you think the following actions can be always
justified, never be justified or something in between using the given
scale. (1: Never justifiable.. . . . . 10: Always justifiable).
(a) Claiming government benefits to which you are not entitled.
(b) Cheating on taxes if you have a chance.
(c) Telling the truth when it is costly for you to do so.
(6) Do you think your country’s government should or should not havethe right to do the following (1: Definitely should have right. 2:
Probably should have right. 3: Probably should not have right. 4:
Definitely should not have right.):(a) Keep people under video surveillance in public areas.
(b) Monitor all e-mails and any other information exchanged on theinternet.
9

(c) Access to people’s bank account balances and their history of
payments.
We will later use the answers to these questions as potential covariates inour regression analysis.
Question (3) is from the Global Preference Survey (Falk et al., 2018).
Question (5) is related to ethics, and question (6) is related to the government’s rights. Questions (5-a), (5-b), (6-a), and (6-b) are from the World
Value Survey Wave 7 (Haerpfer et al., 2022).
From question (5) we construct a variable called “Ethics.” Namely,
Ethics = ((11 - claiming benefit) + (11 - cheating tax) + telling truth)/3.
A Higher value of the Ethics variable indicates a participant considers unethical behavior to be less justifiable.
From question (6) we construct a variable called “Government’s right.”
Namely, Government’s right = ((5-video surveillance) + (5-internet) + (5bank account))/3. A higher value of the Government’s right variable indicates a participant agrees to a larger extent that the government has theright to monitor people.
The English instructions have been translated to Japanese and Chinese
by our research assistants. We then asked different people to translate theinstructions back into English to ensure consistency in the meaning.5
5

The English instructions are available in the online supplementary material. Chineseand Japanese translations are available upon request.

10

3

Results

The experiment was conducted online between October and December 2023
in Osaka (Japan), Irvine (USA), and Wuhan (China).6 A total of 360 students from local universities (120 in each country) participated. In eachlocation, we used the Zoom software to coordinate activity. Subjects arrived via the Zoom waiting room. One by one, we privately welcomed themand checked (via video) that they had brought their own coin to the study
as they had been instructed to do (except for the treatment with a virtual
coin only). They were then given a numerical ID to be used during theexperiment to maintain their anonymity. Once these tasks were completed,they were sent back to the waiting room, where they waited until the startof the experiment.
Once all subjects had been individually welcomed they were broughtback to the main room of Zoom, where the experimenter gave general
instructions and sent each subject a link to the experimental platform.
Clicking on the link, subjects read through the instructions for the experiment online at their own pace and then completed a comprehension quiz.
Once they had answered all the quiz questions correctly, the experimentstarted. For the CHOICE treatment with a WTP elicitation, there were
two rounds of practice (with high and low realized prices) for the WTP
elicitation.7 During the experiment, subjects had their cameras and microphones turned off.
The experiment lasted about 25 minutes on average, including the post6

The experiment is programmed using oTree (Chen et al., 2016).
We have introduced these practice rounds, in addition to questions about WTP and
payoffs in the comprehension quiz, to ensure that subjects understood well the BDM
procedure which can be confusing (see, for example, Cason and Plott, 2014).
7

11

experimental questionnaire. Subjects, on average, earned 13.30 USD, 1130
JPY, and 50 RMB, including 7 USD, 500 JPY, and 20 RMB show-up feesin Irvine, Osaka, and Wuhan.8

3.1

Descriptive statistics

The descriptive statistics regarding participants’ characteristics in each location and treatment are reported in Table 1. P-values from the KruskalWallis (KW) test for differences across the three locations are also reported.
There are some notable differences in participants’ characteristics acrossthe three locations. Namely, there are significantly fewer female participants in Osaka compared to Wuhan and Irvine, especially in the OWN and
VIRTUAL treatments. Participants in Irvine are significantly more willingto take risks than those in Osaka and Wuhan. Those in Wuhan are more
accepting of unethical behaviors and of the government’s right to monitor
people than those in Osaka and Irvine. We will, therefore, control for these
individual characteristics in our analyses below.

3.2

Willingness to pay to use own coin

We begin with the main variable of interest: subjects’ WTP to use theirown coin instead of the virtual coin. We then present the reporting behaviorof participants conditional on the coin they actually used.
Figure 1 shows the cumulative distribution of subjects’ WTP to use
their own coin instead of using the virtual coin for free in Osaka (red dash),
Irvine (cyan dots), and Wuhan (gray long dash). This figure also reports
8

While performance-based payments were equalized based on the purchasing power
parity, we respected the standard show-up fees used in each location.

12

13

Wuhan
60
0.55
(0.50)
21.12(2.13)
4.13(2.62)
6.38(1.89)
4.90(2.89)
3.36(2.69)
5.40(2.21)
2.65(0.67)
1.78(0.85)
2.68(0.85)
2.58(0.94)
8.02(6.05)
13.5(5.89)
714.33(238.93)

CHOICE
Irvine
Osaka
60
63
0.52
0.38
(0.50)(0.49)
21.58
22.60(3.46)(3.82)
5.58
4.40(2.20)(2.32)
7.79
7.45(1.31)(1.35)
2.85
3.29(1.94)(2.51)
2.73
2.57(2.02)(2.18)
6.93
6.21(1.98)(1.98)
1.98
2.25(0.53)(0.71)
2.53
2.17(0.82)(0.87)
3.44
3.10(0.60)(0.82)
3.14
2.98(0.92)(0.85)
9.23
8.25(4.95)(5.04)
12.78
15.35(4.92)(5.14)
619.00626.19(214.42)(205.36)0.03550.00950.36400.00410.00010.00010.00010.00070.32270.00020.00010.00340.02040.1385p-valuea

796.67(158.62)

Wuhan
30
0.73
(0.45)
20.93(1.91)
4.07(2.45)
6.29(1.78)
5.17(2.67)
3.53(2.50)
5.57(1.77)
2.78(0.62)
1.70(0.65)
2.57(0.86)
2.40(0.93)
6.23(5.20)

640.00(201.03)

OWN
Osaka
30
0.33
(0.48)
22.47(2.86)
4.33(2.43)
7.99(1.18)
3.31(2.32)
1.62(0.82)
6.90(2.11)
2.33(0.66)
2.20(0.81)
2.90(0.76)
2.90(0.88)
9.50(6.10)

636.67(140.16)

Irvine30
0.70(0.47)
20.13(2.49)
5.87(2.01)
7.30(1.54)
3.73(1.74)
3.03(1.97)
6.67(1.97)
2.22(0.35)
2.00(0.59)
3.13(0.68)
3.20(0.61)
9.83(3.57)

0.00050.00880.00190.01950.02710.00060.00800.00230.01120.00070.00370.00040.0024p-valuea

776.67(256.88)

Wuhan
30
0.50
(0.51)
21.4(2.01)
3.63(2.39)
7.07(1.86)
3.97(2.57)
2.57(2.30)
5.73(2.57)
2.67(0.69)
1.90(0.92)
2.60(0.86)
2.50(0.94)
5.90(6.32)

636.67(245.63)

607.41(218.26)

VIRTUAL
Irvine
Osaka
30
27
0.60
0.30
(0.50)(0.47)
20.6
22.63(2.70)(3.21)
5.33
4.33(2.44)(2.22)
7.16
7.85(1.66)(1.30)
3.77
2.67(2.14)(2.17)
3.33
2.11(2.38)(1.83)
6.57
6.33(2.06)(1.84)
1.98
2.25(0.63)(0.70)
2.20
2.19(0.96)(1.00)
3.37
3.15(0.72)(0.82)
3.50
2.93(0.82)(0.96)
10.90
10.11(5.74)(6.44)

Note:
a: p-values are for across country comparison (Kruskal-Wallis test).
b: Ethics = ((11 - claiming benefit) + (11 - cheating tax) + telling truth)/3.
c: Government’s right = ((5-video surveillance) + (5-internet) + (5-bank account))/3.
d: Due to a technical problem, some answeres were not recorded. n=58 in Wuhan (main), n=59 in Irvine (main), n=29 in Osaka (own coin)payoffNo. Truthfulreporting
No. WTP>0bank accountclaiming
benefitd
cheating
taxd
telling
truthdGovernment’s
rightcvideo
surveillanceinternet

Ethicsb,dRisk taking

No. Obs.
fraction
femaleAgeTreatment

0.01510.00460.00020.00190.38510.0006

0.28140.02830.02400.12390.02620.00630.0689p-valuea

Table 1: Mean (standard deviation) of participants’ characteristics in each treatment and location

CDF
1.0
0.8
0.6
0.4
0.2
0

100

Mean
(Std. Dev.)

200

300

Wuhan
159.83(126.81)

WTP

400

500

Irvine177.00(146.20)Osaka
225.56(150.48)

Figure 1: Cumulative distributions of WTP to use own coin in Osaka (reddashed), Irvine (cyan dots), and Wuhan (gray long dash).
the mean and the standard deviation of the WTP in each location.
We see that the mean (standard deviation (std. dev.)) WTP in Osaka is
225.56 points (150.48) which is more than 40% of the expected gain (500)from misreporting. This is significantly higher than the WTP in Irvine(mean (std. dev.) 177.0 points (146.20), p=0.0538, Mann-Whitney (MW)test) or in Wuhan (mean (std. dev.) 159.83 points (126.81), p=0.0148,
MW). WTPs are not significantly different between Irvine and Wuhan(p=0.7766, MW).
Table 2 reports the results of ordinary least squares (OLS) regressionsof WTP on country dummies as well as on individual characteristics andsubjects’ answers to our questions. The results largely confirm the nonparametric tests. Compared with Osaka (the baseline), the WTP is significantly lower in Wuhan and Irvine, even after controlling for individual
characteristics in models (2) to (4). In model (2), we control for demo14

Table 2: WTP to use own coin. Results of OLS regression
Wuhan
IrvinefemaleAge
Risk
EthicsGov. right(1)-65.722**(25.56)-48.556*(25.56)(2)-67.102**(27.22)-65.151**(26.05)-21.482(20.54)-0.774(3.62)
20.230***(4.41)-4.511(6.84)
15.634(16.13)

No. Truthful(3)-67.290**(26.74)-61.368**(25.64)-12.568(20.46)-0.164(3.56)
20.412***(4.33)-1.954(6.78)
17.117(15.86)-5.048***(1.89)(4)-58.945**(26.73)-43.901*(26.41)-19.416(20.09)0.183(3.55)
16.569***(4.48)-6.408(6.71)
16.638(15.77)

No. WTP>0
Constant

225.556***
160.747
162.034(17.85)(110.49)(108.58)
Adjusted R2
0.028
0.132
0.162
N
183
180
180
p-valuea
0.50780.94690.8372* p<0.10, ** p<0.05, *** p<0.01
a: p-values for testing H0 : Wuhan = Irvine. Wald test

5.820***(1.93)
76.945(111.48)0.171
1800.6033(5)-58.320**(26.09)-37.457(25.86)-9.156(19.89)0.970(3.47)
16.400***(4.37)-3.719(6.61)
18.412(15.40)-5.691***(1.85)
6.417***(1.89)
69.801(108.83)0.210
1800.4615graphics, risk preferences, ethical considerations, and participants’ views
regarding the government’s rights. In model (3), in addition to these, we
control for the belief about how many others (out of a randomly selected
20 participants) truthfully report the outcome of coin flips. In model (4),instead of beliefs about others’ truthful reporting, we control for the belief
about how many others (out of a randomly selected 20 participants) submit a strictly positive WTP to use their own coin. When we also control
for both beliefs (model 5), the difference between Osaka and Irvine loses
significance. In all of these specifications, there is no significant differencein WTP between Wuhan and Irvine.

15

Among the individual characteristics controlled for in model (2), i.e.,
demographics, risk preferences, views on ethics, and views about the government’s rights, only the self-reported willingness to take risks is statistically significant. Specifically, a higher willingness to take risks is associatedwith a higher WTP to use one’s own coin. This positive and significant
coefficient on the risk measure aligns with findings from the corporate governance literature showing that corporations involved in risky activities
often employ expensive accounting obfuscations and earnings management
practices in order to conceal those risks (see, for example, Li, 2008; Hadani
et al., 2011).
The estimated coefficient of the belief about others’ truthful reportingis negative and significant in models (3) and (5). That is, the more likely
participants believe that others report truthfully, the lower is their WTP
to use their own coin. The estimated coefficient of the belief about others’
submitting a positive WTP value is positive and significant in models (4)and (5). That is, the more likely participants believe that others submit astrictly positive WTP to use their own coin, the higher is their own WTP.
We interpret these two findings as resulting from social norm considerations (Cialdini and Goldstein, 2004). In the first case, participants whobelieve that others are more likely to report truthfully, may be less likely
to misreport themselves in accordance with their perception of the social
norm. Consequently their WTP to use their own coin is lower. In the second case, those who believe that others are more likely to report a positive
WTP value, will seek to conform to this norm and submit a higher WTP.

16

Irvine

Osaka

10

10

8

8

8

6

4

2

Reported Head

10

Reported Head

Reported Head

Wuhan

6

4

2

0
100

200

300

400

500

0
0

100

WTP

N
%

Own
17
28.33%

4

2

0
0

6

200

300

400

500

0

WTP

Virtual43
71.67%

N%

Own
19
31.67%

100

200

300

400

500

WTP

Virtual41
68.33%

N
%

Own
29
46.0%

Virtual34
54.0%

Figure 2: Submitted WTP and the reported number of heads depending on
the coin used. Own coin (black). Virtual coin (gray). The size of the pointis proportional to the number of observations for the same WTP-Report
combination.

3.3

Reporting behavior

Let us next turn to the actual reported number of heads. Figure 2 uses
bubble plots to show the relationship between subjects’ WTP values (horizontal axis) and their reported number of heads (vertical axis) dependingon the coin used (Own coin in black and Virtual coin in gray) in each of
the three locations. Reflecting the higher WTP submitted by the Osaka
subjects, the number of subjects who used their own coin, instead of thevirtual coin, is higher in Osaka as compared to Wuhan and Irvine.
There are several things to note in these figures.

In all the loca-

tions, some subjects submitted WTP=0 and reported 10 heads (as homoeconomicus would do) as can be seen in the upper left corner of Figure 2.
We also see in the upper right corner that some subjects submitted a
WTP=500 and reported 10 heads. While there are positive correlations
between WTP and the reported number of heads when the own coin is

17

18

All (2)Wuhan (1) Wuhan (2) Irvine (1)0.987**(0.40)
Irvine0.008(0.38)
WTP
0.002
0.003
0.001
0.005
(0.00)(0.00)(0.00)(0.00)
Virtual Coin Used
-1.434**-1.900-2.535**0.033(0.67)(1.34)(1.21)(1.28)
WTP×-0.002-0.0040.005-0.006
Virtual Coin Used
(0.00)(0.01)(0.01)(0.01)
Female0.281
0.176(0.30)(0.51)
Age
0.037
0.119
(0.05)(0.13)
Risk-0.002-0.248**(0.07)(0.11)
Ethics
0.020
0.162(0.10)(0.16)
Gov. right-0.081
0.051(0.23)(0.40)
No. Truthful-0.180***-0.221***(0.03)(0.05)
Constant
6.891*** 7.796***
8.710***
9.808***
6.172***(0.67)(1.56)(1.20)(3.32)(1.15)
2
Adjusted R
0.266
0.386
0.220
0.494
0.103
N
183
180
60
58
60
p-valuea
0.601
0.821
0.811
0.136
0.681
* p<0.10, ** p<0.05, *** p<0.01
a p-value for testing H0 : WTP + WTP × Virtual Coin Used = 0. Wald test.

Wuhan

All (1)1.014***(0.38)-0.073(0.38)
0.005**(0.00)-0.943(0.71)-0.006**(0.00)
0.005(0.00)-0.149(1.34)-0.004(0.01)
0.496(0.63)
0.150(0.14)-0.133(0.17)-0.201(0.24)-0.408(0.60)-0.110*(0.06)
2.397(3.85)
0.072
59
0.731

Irvine (2)6.611***(0.97)
0.397
63
0.891

0.006**(0.00)-0.908(1.10)-0.006(0.00)

Osaka (1)Table 3: Reported number of heads and WTP. Regression results

0.002(0.00)-1.917**(0.94)-0.001(0.00)
0.007(0.42)-0.032(0.06)
0.327***(0.09)
0.092(0.16)-0.115(0.28)-0.177***(0.04)
8.467***(1.71)
0.594
63
0.735

Osaka (2)19

All (2)
1.032*(0.57)
Irvine-1.064*(0.61)
Price
0.001(0.00)
Female0.181(0.47)
Age-0.023(0.06)
Risk
0.010(0.10)
Ethics-0.034(0.16)
Gov. right-0.667**(0.33)
No. Truthful-0.106**(0.04)
Constant
7.988*** 7.673***(0.46)(1.66)
2
Adjusted R
0.139
0.233
N
65
63
* p<0.10, ** p<0.05, *** p<0.01

Wuhan

All (1)
1.072*(0.54)-0.728(0.53)
0.004*(0.00)

9.417***(0.44)-0.05917

0.001(0.00)

Wuhan (1)-0.000(0.00)
0.069(0.34)
0.131(0.07)-0.103(0.07)-0.052(0.11)-0.460*(0.22)-0.130***(0.03)
6.736***(1.61)
0.526
16

Wuhan (2)6.892***(0.78)
0.055
19

0.007
(0.00)

Irvine (1)0.010*(0.01)
1.387(1.27)
0.284(0.23)-0.377(0.31)-1.110*(0.53)-1.846(1.08)-0.118(0.11)-5.809(7.22)
0.270
18

Irvine (2)8.110***(0.53)
0.005
29

0.003
(0.00)

Osaka (1)Table 4: Reported number of heads and Price. Results of OLS regressions-0.001(0.00)
0.483(0.64)-0.031(0.07)
0.280**(0.13)
0.211(0.22)-0.268(0.38)-0.147**(0.07)
9.058***(1.68)
0.213
29

Osaka (2)

used in all three locations, none of these correlations is significant at the
10% level once individual characteristics are controlled for (See Table 3).
There is a marginally significant positive relationship between the pricesubjects actually paid and the reported number of heads in Irvine once individual characteristics are controlled for (See Table 4). When the virtual
coin is used, there is no significant relationship between the WTP and thereported number of heads in all three locations (See Table 3).
Figure 3 panels A and B compare cumulative distributions of the reported number of heads between the CHOICE treatment and either the
OWN or VIRTUAL treatment and depending on the coin used for eachof the three locations. The top panel (A) compares CHOICE vs. OWN
when the own coin is used. The middle panel (B) compares or CHOICE
vs. VIRTUAL when the virtual coin is used. The bottom panel (C) compares cumulative distributions regarding the number of misreports whenthe virtual coin is used in CHOICE vs. VIRTUAL. See Appendix A forthe analyses comparing OWN and VIRTUAL treatments.
When the subject’s own coin is used in the CHOICE treatment (shownin red in Figure 3 (A)), the reported number of heads is significantly larger
than in the OWN treatment. This is so even after controlling for individual
characteristics (see Table 5). This finding could be the result of two forces:“sorting” and “licensing.” Regarding “sorting,” recall that in the CHOICE
treatment, those subjects who have submitted a higher WTP to use their
one coin are more likely to be selected to use their own coin. This means
that, their willingness to use their own coin so as to misreport is likely
higher than for participants assigned to the OWN treatment. Regarding“licensing,” the fact that subjects have paid a price to use their own coin

20

(A) Reported number of heads when the own coin is used
Wuhan
Irvine
Osaka
CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

2

4

6

Reported
10 No. of H

8

0.2

0

p<0.001 (MW)

2

4

6

Reported
10 No. of H

80

p=0.022 (MW)

2

4

6

Reported
10 No. of H

8

p<0.001 (MW)(B) Reported number of heads when the virtual coin is used
Wuhan
Irvine
Osaka
CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

2

4

6

Reported
10 No. of H

8

0.2

0

p=0.063 (MW)

2

4

6

Reported
10 No. of H

80

p=0.622 (MW)

2

4

6

Reported
10 No. of H

8

p=0.463 (MW)(C) Misreporting when the virtual coin is used
Wuhan
Irvine
Osaka

-2

CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

2

4

6

8

10

MisReport

p=0.003 (MW)

-2

0

0.2
2

4

6

8

10

MisReport

p=0.458 (MW)

-2

0

2

4

6

8

10

MisReport

p=0.745 (MW)Figure 3: Distribution of the reported number of heads by treatment conditions: (A) when the own coin is used, (B) when the virtual coin is used,and (C) the extent of misreporting when the virtual coin is used. Red(CHOICE) and Black (OWN) in (A). Blue-dashed (CHOICE) and graydashed (VIRTUAL) in (B) and (C).

21

22

All (2)Wuhan (1) Wuhan (2) Irvine (1)0.981***(0.27)
Irvine0.132(0.26)
own coin only
-1.409***-1.563**-1.519***-1.318**(0.31)(0.66)(0.53)(0.61)
virtual coin only
-1.479***-1.763***-1.890***-1.318**(0.31)(0.66)(0.52)(0.61)
choice and-1.992***-2.832***-2.102***-1.660***virtual coin(0.30)(0.63)(0.52)(0.58)
female0.023-0.013(0.20)(0.32)
Age
0.034
0.006
(0.04)(0.08)
Risk
0.034-0.121*(0.04)(0.07)
Ethics-0.0090.049(0.06)(0.09)
Gov. right-0.0550.050(0.16)(0.24)
No. Truthful-0.188***-0.238***(0.02)(0.03)
Constant
8.231***
8.454***
9.529***
11.676***7.684***(0.29)(1.02)(0.53)(1.95)(0.48)
2
Adjusted R
0.184
0.374
0.134
0.495
0.043
N
360
356
120
118
120
p-valuea
0.036
0.049
0.042
0.618
0.498
* p<0.10, ** p<0.05, *** p<0.01
a p-value for testing H0 : virtual coin only = choice and virtual coin. Wald test.

Wuhan

All (1)1.280***(0.27)
0.013(0.27)-1.751***(0.34)-1.918***(0.34)-2.541***(0.33)-0.927(0.66)-0.841(0.65)-1.339**(0.61)
0.235(0.41)
0.016(0.08)
0.107(0.09)
0.095(0.14)-0.406(0.37)-0.092**(0.04)
6.307***(2.19)
0.061
119
0.330

Irvine (2)8.586***(0.37)
0.230
120
0.408

-2.186***(0.52)-2.512***(0.53)-2.939***(0.50)

Osaka (1)Table 5: Reported number of heads and coin used. Regression results-1.668***(0.45)-1.802***(0.46)-2.230***(0.44)-0.267(0.33)
0.011(0.05)
0.208***(0.07)-0.003(0.12)
0.062(0.23)-0.181***(0.03)
8.799***(1.31)
0.471
119
0.323

Osaka (2)

may have justified their reporting a higher number of heads in the CHOICE
treatment as compared with the OWN treatment, where they do not pay
anything to use their own coin.
When the virtual coin is used, the reported numbers of heads and theextent of misreporting (panels B and C) are not significantly different between the CHOICE treatment and the VIRTUAL treatment, except for the
Wuhan subjects. In Wuhan, the reported number of heads is marginallysignificantly higher, and the extent of misreporting is significantly greaterin the VIRTUAL treatment compared to the CHOICE treatment. Whilethe difference in the reported number of heads between VIRTUAL andCHOICE loses its significance once individual characteristics are controlled
for, the extent of misreporting among Wuhan subjects continues to be significant (see Columns Wuhan (1) and Wuhan (2) in Tables 5 and 6).
This is puzzling in light of “sorting.” In the CHOICE treatment, thosesubjects who have submitted low WTPs to use their own coin are more
likely to be selected to use the virtual coin. Thus, these participants have
low costs associated with privacy concerns. In other words, they should be
more willing to use the virtual coin and misreport than the average participants in the VIRTUAL treatment. If participants are mainly concerned
about their self-image (and thus do not misreport, regardless of the type ofthe coin used), however, then we may observe a low WTP and low misreporting. Unfortunately, it is not possible to test this hypothesis using our
data.

23

24

All (2)0.845**(0.34)
Irvine0.158(0.32)
Virtual Coin Only
0.695***(0.25)
Age
0.009(0.05)
Risk-0.001(0.06)
Ethics-0.150*(0.08)
Gov. right
0.141(0.20)
No. Truthful-0.219***(0.02)
Constant
0.380
2.328*(0.31)(1.39)
2
Adjusted R
0.113
0.420
N
203
202
* p<0.10, ** p<0.05, *** p<0.01

Wuhan

All (1)1.553***(0.38)
0.118(0.38)
0.823***(0.31)

1.442***(0.38)
0.128
72

2.041***(0.61)

Wuhan (1)1.168**(0.46)-0.130(0.10)-0.180*(0.09)-0.056(0.12)
0.280(0.32)-0.267***(0.04)
7.732***(2.76)
0.590
71

Wuhan (2)0.683**(0.28)-0.00371

0.384(0.43)

Irvine (1)Table 6: Misreporting. Regression results

0.518(0.43)
0.052(0.10)
0.027(0.10)-0.139(0.14)
0.196(0.37)-0.151***(0.04)
1.039(2.21)
0.093
71

Irvine (2)0.788**(0.33)-0.01760-0.084(0.50)

Osaka (1)-0.083(0.41)-0.050(0.08)
0.267***(0.10)-0.181(0.17)
0.302(0.31)-0.174***(0.04)
2.786(1.99)
0.324
60

Osaka (2)Own coin vs virtual coin in the CHOICE treatment
Wuhan
Irvine
Osaka
CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

200

400

600

800

Earning
1000

0

0.2
200

400

600

800

Earning
1000

0

200

400

600

800

Earning1000

p=0.066 (MW)p=0.331 (MW)p=0.004 (MW)
Wuhan
IrvineOsaka
Own
VirtualOwn
VirtualOwn
Virtualmean
827.06669.76654.74602.44698.28564.71(std.dev) (149.20) (254.05) (234.20) (205.53) (170.90) (214.45)
Figure 4: Distribution of net payoffs depending on the coin used in the
CHOICE treatment. Red (own coin) and Blue-dashed (virtual coin)

3.4

Payoffs

We have seen that subjects who used their own coin in the CHOICE treatment reported significantly more heads than those who used the virtual
coin in the same treatment. They also reported more heads compared tothose in the OWN treatment. What about subjects’ payoffs? Did subjects
in the CHOICE treatment who used their own coin earn more than those
who used the virtual coin taking into account the price they actually paid
to use their own coin?
Figure 4 shows the distribution of the payoffs (net of the price paid touse one’s own coin) in the CHOICE treatment depending on the coin used(own coin in red and virtual coin in blue-dashed) in the three locations.
The mean payoff in points, the standard deviations, as well as p-values
from MW tests are also reported. Except for Irvine, those subjects who
used their own coin obtained significantly higher payoffs than those who
used the virtual coin in the CHOICE treatment. In Wuhan, those who

25

used their own coin earned 827.06 points on average, while those who usedthe virtual coin earned 669.76 points on average (p=0.066, MW). In Osaka,
similarly, the average payoffs are 698.28 points for subjects using their own
coin and 564.71 points for those using the virtual coin (p=0.004, MW). In
Irvine, the average payoffs for those who used their own coin versus thevirtual coin were 654.74 and 602.44 points, respectively (p=0.331, MW).
In general, participants who chose to use their own coins earn a higher
average net payoff than those who used the virtual coin. One may argue
that those who purchased the right to use their own coin were “rational”
in doing so, at least in terms of material payoff.
Interestingly, the net payoffs of those who used their own coin in the
CHOICE treatment are not significantly different from the payoffs earned
by those in the OWN treatment where there was no fee for using theown coin. The average payoffs (standard deviations) in the OWN treatment were 796.67 (158.62) in Wuhan, 636.67 (140.16) in Irvine, and 640.00(201.03) in Osaka. The p-values from a MW test (comparing the net payoff
earnings of those who used their own coin in the OWN vs. the CHOICE
treatments) are 0.788, 0.626, and 0.236 in Wuhan, Irvine, and Osaka, respectively. This finding suggests that participants using their own coin may
have had a target net income level that did not vary across the CHOICE
and OWN treatments.

4

Discussion and conclusion

We have reported on a laboratory experiment that measures participants’willingness to pay to “avoid the spotlight” regarding the reported number26

of heads and tails in a coin-flipping task. We conducted this experiment on
populations in three countries: Osaka (Japan), Wuhan (China) and Irvine(U.S.A). What do we learn from such as study?
First and most importantly, we find that participants’ willingness to pay
to avoid scrutiny is large and economically substantial, amounting to morethan 40% of the expected gain from misreporting in Osaka and around
30% of this expected gain in Wuhan and Irvine. As we noted earlier, there
can be several motives for such privacy concerns, including the desire foragency/autonomy, the fear of disclosure of private information, and the fearof harm to one’s reputation from dishonest or stigmatized behavior. Our
design allows all of these motives to operate and it is not really possible toseparately estimate the values associated with each of them.
Second, there is heterogeneity both across and within countries. The
difference in WTP between Osaka and Wuhan and between Osaka andIrvine are statistically significant at the 5% and 10% levels, respectively,
while the difference between the latter two, Wuhan and Irvine, is not statistically significant. Within each country, the WTP ranged from the minimum to the maximum possible value.
Overall, these findings underscore the substantial value that people
place in avoiding the negative social and psychological implications of being
observed in economic activities, particularly those that may be prone todishonest behavior, highlighting a universal desire for privacy in economic
activities stemming from reputational concerns. These concerns will need
to be addressed in the design of new digital payment systems.
To better understand the source of this substantial WTP as well as
the individual heterogeneity, we examined a variety of individual charac-

27

teristics. Among those that we considered, the participants’ self-reported
willingness to take risks is significantly and positively related to their WTP
to use their own coin. This observation aligns with findings from the corporate governance literature (see, for example, Li, 2008; Hadani et al., 2011)
showing that corporations involved in risky activities often employ expensive accounting obfuscations and earnings management practices in order
to conceal those risks.
By contrast age, gender, and subjects’ views of ethical behavior or of thegovernment’s right to monitor people’s activities are not related to WTP.
Interestingly, WTP is higher among those who believe that others are lesslikely to truthfully report the outcomes of their coin flips, suggesting thatsocial or cultural norms likely play an important role.
In our main treatment, there is no significant correlation between the
WTP to use one’s own coin and the reported number of heads regardless ofthe type of coin eventually used. However, participants who actually paid
to use their own coin reported a significantly higher number of heads thanthose who used the virtual coin in Osaka and Wuhan. As a consequence,
those who used their own coin by paying a price earned significantly morethan those who used the virtual coin for free in these two locations.
What is the driving factor behind the different WTPs for privacy in economic transactions across the three countries? In our regression analysis,
we considered several possible explanations, including people’s self-assessedhonesty and their attitudes toward government monitoring. As noted, noneof these factors turned out to be significant in explaining the differencesthat we observe across countries.
Based on the above findings, we speculate that the observed differences

28

US
China
Japan

Cash

Credit Card

Debit Card

Digital Wallet

Other

12
8
51

40
18
32

31
15
3

12
56
10

5
3
4

Table 7: Payment Methods Usage by Country (in %), Source: FIS (2023)
across the three countries may reflect current cultural norms with regard
to payment methods and, in particular, concerning the use of cash. Indeed,according to FIS (2023), Japan is an outlier in its use of cash relative todigital payments and credit cards which are more widely used in China andthe U.S., respectively.
As shown in Table 7, the share of cash as the method of payment forpoint of sale purchases is 51% in Japan, 12% in the US, and 8% in China.
The higher frequency of cash usage may be associated with a higher level ofprivacy-preserving preference in Japan, and thus, the significantly higher
WTP. The policy implications of these findings are that it might be moredifficult to implement CBDC in Japan than in China, where pilot studiesof the new government issued e-CNY digital currency are ongoing (Orcutt,2023). Alternatively, preferences for transactional privacy might influence
the design and adoption of digital payment systems, ensuring they offersome type of privacy protections.
While some might seek privacy to engage in dishonest or illegal activities, it is important to recognize that there can be other motivations forpaying to “avoid the spotlight.” People may seek to avoid scrutiny because it is closely linked to their sense of personal autonomy and freedom(Van Aaken et al., 2014). For some, the ability to control who has access topersonal information and one’s choices is fundamental to individual liberty

29and self-expression (Oshana, 2016). People may also seek privacy to better
manage their social interactions and personal boundaries, contributing totheir own psychological well-being (Roessler and Mokrosinska, 2013).
In future research, it would be of interest to consider other tasks witheconomic consequences where people face weaker or no material incentives
to dishonestly engage in the task in order to investigate whether such diminished motives matter for the WTP for privacy. While we suspect that
there would be some reduction in the WTP for privacy in such settings,
it could still be the case that individuals have a positive WTP value forprivacy in their economic transactions beyond the desire to avoid detectionof cheating behavior.
Furthermore, the observed high values placed on privacy in economictransactions suggest a need for finding the right balance between fraud prevention and ensuring privacy in our digital economies. Effective fraud prevention, when balanced with privacy concerns, can enhance the functioningof the digital economy (Romanosky, 2016). Getting the right balance, however, can be a complex task because there are not only fraud prevention
and privacy trade-offs but also trade-offs between different aspects of privacy itself, as noted by (Pozen, 2016). Future studies might explore thesevaried trade-offs with the aim of discovering an optimal balance.

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35

Appendix
A

Results of the control treatments
Reported number of head
OWN treatment
VIRTUAL treatment

Misreport(Reported - realized)

CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

2

4

6

8

Reported
10 No. of H

p=0.005 (KW)
p-values (MW)Osaka
IrvineIrvine0.7334Wuhan
0.00170.0002

0

0.2
2

4

6

8

Reported
10 No. of H

p=0.0151 (KW)
p-values (MW)Osaka
IrvineIrvine0.4774Wuhan
0.00690.0264

-2

0

2

4

6

8

10

MisReport

p=0.0001 (KW)
p-values (MW)Osaka
IrvineIrvine0.5061Wuhan
0.00020.0005Figure 5: Cumulative distribution of the reported number of heads in OWN
treatment (left) and VIRTUAL treatment (center) as well as the extent of
misreporting in VIRTUAL treatment (right) in Osaka (red), Irvine (cyan),and Wuhan (gray).

Figure 5 shows the distribution of the reported number of heads in
the OWN treatment (left), the VIRTUAL treatment (center) as well as theextent of misreporting (the reported number of heads - the realized numberof heads) in the VIRTUAL treatment (right) in Osaka (red), Irvine (cyan),and Wuhan (gray).9 The p-values from KW tests as well as MW tests for
all pair-wise comparisons are also reported. The left and the center panels
reveal that for both treatments, there are significant differences between
Wuhan and two other locations in terms of the reported number of heads.
The reported number of heads are not significantly different between Osakaand Irvine in either treatment. Similarly, the extent of misreporting shown
9

In the Wuhan session, the realized outcome of the virtual coin flips were not fullyrecorded for one participant. Thus, there are only 29 observations, instead of 30, for themisreport.

36

Table 8: Reported number of heads (No. Head) and misreporting Resultsof OLS regressions.
Dep. Var.
Treatment
Wuhan

No. HeadOwn (1)
1.567***(0.44)-0.033(0.44)

No. Head No. Head
No. HeadOwn (2) Virtual (1) Virtual (2)0.992**
1.693***
1.014*(0.48)(0.64)(0.61)
Irvine-0.1130.293
0.775(0.45)(0.64)(0.62)
Female0.095-0.741(0.35)(0.46)
Age
0.008
0.069
(0.07)(0.09)
Risk
0.143**-0.019(0.07)(0.10)
Ethics-0.012-0.045(0.11)(0.14)
Gov. Right
0.329-0.173(0.29)(0.34)
No. Truthful-0.152***-0.223***(0.03)(0.04)
Constant
6.400***
7.781***
6.074***
6.448***(0.31)(1.74)(0.46)(2.16)
Adjusted R2
0.150
0.351
0.067
0.332
N
90
89
87
87
p-valuea
0.00040.01610.02740.7116* p<0.10, ** p<0.05, *** p<0.01
a: p-value for testing H0 : Wuhan = Irvine. Wald test

Misreport
Virtual (1)2.779***(0.61)
0.363(0.61)

0.704(0.44)
0.212
86
0.0001

Misreport
Virtual (2)1.573***(0.50)
0.481(0.51)-0.404(0.38)-0.001(0.07)
0.055(0.08)-0.241**(0.12)
0.083(0.28)-0.251***(0.03)
2.620(1.80)
0.573
86
0.0458in the right panel is significantly greater in Wuhan as compared with Irvine
and Osaka.
Table 8 shows the outcome of OLS regressions in which the dependent
variables are the reported number of heads (No. Head) or the extent of
misreporting (Misreport). In one specification (specification 2), we control for individual characteristics. Those who believe others are reporting
truthfully (No. Truthful) tend to report a lower number of heads and also
misreport less. The dummy variable “Wuhan” is significant at the 10%level(and in most specifications at the 5% level) in all the specifications. We
also observe a negative and significant correlation between the “Ethics”
37

WuhanIrvine

Osaka

CDF
1.0

CDF
1.0

CDF
1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0

2

4

6

8

Reported
10 No. of H

p=0.75(MW)p=0.20(KS)

0

0.2
2

4

6

8

Reported
10 No. of H

p=0.89 (MW)p=0.17 (KS)

0

2

4

6

8

Reported
10 No. of H

p=0.23 (MW)p=0.21 (KS)Figure 6: Cumulative distribution of the reported number of head in OWN
treatment (black) and VIRTUAL treatment (gray) treatments. Wuhan(left), Irvine (cyan), and Osaka (right).
variable and the Misreporting amount. Thus, those who consider claiming
public benefits that they are not entitled to, cheating on their taxes, or not
telling the truth when it is costly to do so are more unjustifiable are lesslikely to misreport.
Figure 6 compares the distributions of the reported number of head between the OWN treatment (black) and the VIRTUAL treatment (gray) ineach location. P-values from MW and Kolmogrov-Smirnov (KS) tests arealso reported. These non-parametric tests indicate that neither the distribution nor the median reported number of heads is significantly different
between the two treatments in any of the locations. The reporting of 10
heads, however, is marginally significantly more frequent in the VIRTUAL
treatment than in OWN treatment in Wuhan and Irvine once individual
characteristics are controlled for, but not in Osaka (see, the results of OLS
regressions (model (2) for each location) reported in Table 9). This isconsistent with existing studies (see Abeler et al., 2019) suggesting that
subjects are less likely to misreport when they are concerned about theirsocial images, but if they do misreport, they do so to the maximum extent
to overcome the cost associated with such concerns.
38

Table 9: Reporting 10 heads. Results of OLS Regressions
Wuhan (2) Irvine (1) Irvine (2) Osaka (1)0.204*
0.133*
0.147*
0.048(0.11)(0.08)(0.08)(0.09)
Female0.008
0.025(0.11)(0.09)
Age-0.022-0.002(0.03)(0.02)
Risk-0.0250.035*(0.02)(0.02)
Ethics-0.017
0.002(0.03)(0.03)
Gov. Right
0.027-0.093(0.08)(0.08)
No. Truthful-0.042***-0.014(0.01)(0.01)
Constant
0.233***
1.037
0.033
-0.2650.100(0.09)(0.67)(0.05)(0.39)(0.06)
Adjusted R2
0.029
0.319
0.033
0.074
-0.013
N
60
60
60
60
57
* p<0.10, ** p<0.05, *** p<0.01
Dependent variable =1 if the subjected reported 10 heads, =0 otherwise.
Virtual Coin

Wuhan (1)0.200
(0.12)

39

Osaka (2)0.091
(0.07)-0.111(0.08)-0.000(0.01)
0.042**(0.02)-0.000(0.03)
0.062(0.06)-0.022***(0.01)
0.302(0.32)
0.289
56

Instruction
Note for the readers: for "CHOICE" treatment

Welcome• Welcome to the study. You are guaranteed $7 for showing
up and completing this study.
• These instructions explain how you can earn additional
earnings beyond the guaranteed $7 show-up payment fromthe decisions that you make.
• Additional earnings will be expressed in points. At the endof the experiment, any points you earned will be converted
into US Dollar at the rate of 100 points = $ 1.00.
• Please silence any mobile devices and refrain from any
distractions for the duration of this study. If you have any
questions, please contact the experimenter.
• Today's study starts with the main decision task followed bya questionnaire. Your earning during the experiment will be
paid in private.

The main task
• The main task consists of flipping a two-sided coin 10 times.
For each of the 10 flips, you record whether the coin landed
heads or tails.
• After the completion of 10 flips, you will receive 100 points
for each head that you report and 0 points for each tail you
report.
• Note that your payment is based only on the number ofheads and tails (out of 10 flips) that your report.
heads

tails
https://www.usmint.gov/news/image-library/circulating

The main task
• In completing this task, you have the option to use either• 1) a virtual online coin that we provide to you or• 2) to use your own coin.
• If you use your own coin, then it is not possible for us tocheck how many times your own coin actually landed heads.
• However, if you use our virtual coin, then we will be able toknow the realization of the coin flips.
• Still, regardless of whether you use your own coin or our
virtual coin, we will rely on your own report of the numberof heads and tails to determine your total points.

The main task
• To use the virtual online coin costs you nothing.
• However, to use your own coin you have to first indicate
your willingness to pay (WTP) in points for this option and indoing so, earn the right to use your own coin as explained in
the next slide.

Willingness To Pay• Specifically, we ask how much you are willing to pay (inpoints) to use your own coin.
• The range of values you can state is[0, 10, 20,..., 100, ... 200, ..., 300,... 400 ,..., 500],
that is, the range is from 0 to 500 points in increments of 10
points.
• After you state your WTP, the computer program will draw a
random price between 10 and 500 points, inclusive inincrements of 10 points. Note that this is the same range foryour stated WTP, except that 0 points is not included. All
prices between 10 and 500 points, in increments of 10
points, are equally likely to be chosen.

Which coin to use?
• If your WTP is greater than or equal to the randomly drawn price, thenyou earn the right to use your own coin, but you have to pay the
randomly drawn price in points.
• However, if the random price is greater than your stated WTP, then you
do not earn the right to use your own coin and must use our virtual
coin instead.
• Thus, the higher is your WTP, the greater is the chance that you will
earn the right to use your own coin.
• At the extremes,• if your WTP is 0, then you will never earn the right to use your own
coin,• if your WTP is 500, then you will always earn the right to use yourown coin, but will have to pay the randomly drawn price out ofyour earnings.
• Of course, you are free to choose any WTP in between these two
extremes.

two examples• Example 1:• Imagine you have chosen your WTP to be 200 points.
Then, the computer randomly draws a price of 100
points• In this case, you will use your own coin, but 100 points
will be subtracted from your point earnings as the pricefor using your own coin.
• Example 2:• Imagine you have chosen your WTP to be 200 points.
Then, the computer randomly draws a price of 300
points.
• In this case, you must use our virtual coin, but no points
will be subtracted from your point earnings.

How to determine your WTP?
• In deciding your WTP, please first ask yourself thefollowing question:• At a price of 0 points, would you like to use your own
coin instead of our virtual coin?
• If your answer is no, then your WTP is 0 points.
• If your answer is yes, then, go to the next question:• At the price of 10 points, would you like to use yourown coin instead of our virtual coin?
• If your answer is no, then your WTP is 10 points.
• If your answer is yes, then, go to the next question:• At the price of 20 points, would you like to use yourown coin instead of our virtual coin?
• Continue this process until you find the price at whichyour answer switches from yes to no. This should be your
WTP.

Quiz
To check whether you understood these instructions correctly,
please answer the following questions.
Please click “Next” button on the screen.

Instruction
Note for the reader: for "OWN" treatment

Welcome• Welcome to the study. You are guaranteed $7 for showing
up and completing this study.
• These instructions explain how you can earn additional
earnings beyond the guaranteed $7 show-up payment fromthe decisions that you make.
• Additional earnings will be expressed in points. At the endof the experiment, any points you earned will be converted
into US Dollar at the rate of 100 points = $ 1.00.
• Please silence any mobile devices and refrain from any
distractions for the duration of this study. If you have any
questions, please contact the experimenter.
• Today's study starts with the main decision task followed bya questionnaire. Your earning during the experiment will be
paid in private.

The main task
• The main task consists of flipping a two-sided coin 10 times.
For each of the 10 flips, you record whether the coin landed
heads or tails.
• After the completion of 10 flips, you will be paid 100 points
for each head that you report and 0 point for each tail you
report.
• Note that your payment is based only on the number ofheads and tails (out of 10 flips) that your report.
heads

tails
https://www.usmint.gov/news/image-library/circulating

The main task
• In completing this task, you will use your own coin.
• Because you use your own coin, it is not possible for us tocheck how many times your own coin actually landed heads.
• Still, we will rely on your own report of the number oftimes the coin flip resulted in heads to determine yourtotal points.

Quiz
To check whether you understood these instructions correctly,
please answer the following questions.
Please click “Next” button on the screen.

Instruction
Not for the reader: for "VIRTUAL" treatment

Welcome• Welcome to the study. You are guaranteed $7 for showing
up and completing this study.
• These instructions explain how you can earn additional
earnings beyond the guaranteed $7 show-up payment fromthe decisions that you make.
• Additional earnings will be expressed in points. At the endof the experiment, any points you earned will be converted
into US Dollar at the rate of 100 points = $ 1.00.
• Please silence any mobile devices and refrain from any
distractions for the duration of this study. If you have any
questions, please contact the experimenter.
• Today's study starts with the main decision task followed bya questionnaire. Your earning during the experiment will be
paid in private.

The main task
• The main task consists of flipping a two-sided coin 10 times.
For each of the 10 flips, you record whether the coin landed
heads or tails.
• After the completion of 10 flips, you will be paid 100 points
for each head that you report and 0 point for each tail you
report.
• Note that your payment is based only on the number ofheads and tails (out of 10 flips) that your report.
heads

tails
https://www.usmint.gov/news/image-library/circulating

The main task
• In completing this task, you will use• a virtual online coin that we provide to you• Because you use our virtual coin, we will be able to know
the realization of the coin flips.
• Still, we will rely on your own report of the number oftimes the coin flip resulted in heads to determine yourtotal points.

Quiz
To check whether you understood these instructions correctly,
please answer the following questions.
Please click “Next” button on the screen.