ISSN (Print) 0473-453X

Discussion Paper No. 1238

ISSN (Online) 2435-0982

PAYING TO AVOID THE SPOTLIGHT

Te BaoJohn Duffy
Nobuyuki Hanaki

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§

April 4, 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, that people attach to privacy ineconomic activities. We study this question by eliciting individuals’
willingness to pay (WTP) to avoid detection in an economic experiment involving a coin-flipping task. We collect data from Japan,
China, and the U.S.A. to examine whether there are cross-country
differences. Our findings reveal that people’s WTP to “avoid the
spotlight” is positive and economically sizable 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 IRB of the Institute 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

11Introduction

In our increasingly digital world, the prospect of maintaining privacy ineconomic dealings 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 ordirectly monitored by governments in others. Consequently, such transactions often lack any privacy protections. Indeed, the recent emergence of
cryptocurrencies partly stems from a desire for financial autonomy fromthe uncertainties of government-issued fiat currencies and a critical needfor privacy (Herskind et al., 2020). As a reaction to these stateless digitalcurrencies, central banks from various countries, starting with China, havebegun exploring the creation of Central Bank Digital Currencies (CBDCs)
to maintain demand for their fiat currencies and thus preserve their ability
to implement monetary policies. However, CBDC transactions, linked toelectronic ledgers, will inevitably lead to 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
and Waldman, 2015; Skatova et al., 2019). An existing international comparison across US, Germany, and several Latin American countries showsthat Germans value these types of privacy concerns more than people in2other countries (Prince and Wallsten, 2022). While such privacy concerns
are certainly important, they are not the specific focus of our study. Instead, we are interested in privacy surrounding economic transactions, i.e.,the desire that economic activity is not traceable, as would be possible intransactions using cash.
We are particularly interested in individuals’ willingness to pay (WTP)
to avoid being observed in reporting on economic activities.1 By contrast
with most of the literature on the value of privacy (Tsai et al., 2011; Savage
and Waldman, 2015; Skatova et al., 2019; Prince and Wallsten, 2022), we
use experimental methods that enable us to elicit peoples’ WTP for privacy
in an incentive-compatible manner. Indeed, Benndorf and Normann (2018)
show a large “hypothetical bias” in people’s willingness to disclose theirpersonal information, namely, while five out of six respondents in a nonincentivized survey refused to disclose their personal information, it was
only one of six participants who did the same 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 of Fischbacher and Föllmi-Heusi (2013),
1
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.

3

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.
To the best of our knowledge, ours is the first study 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 is some potential fordishonest behavior.
Our findings reveal that people’s WTP 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 inJapan where, on average, it is more than 40% of such a gain. The observedhigh values placed on privacy in economic transactions suggest the needfor a proper balance between fraud prevention and ensuring privacy in ourincreasing digital economy.

2

Experimental Design

In our experiment, as in Cohn et al. (2014), subjects flip a fair coin ten
times and report the number of heads and tails (which must add up toten). For each head that a subject reports, they receive 100 points. Thus,by reporting 10 heads, they earn the maximum of 1000 points. The earned
points are converted into the local currency at the end of the experimentusing a pre-specified exchange rate that adjusts for purchasing power differences across countries, so that all of our subjects face approximately thesame monetary incentives. There is no explicit penalty for misreporting thenumber of heads and tails in any treatment of our study. Therefore, the4

predicted, profit-maximizing behavior by homo-economicus participants is
to always report 10 heads. A meta-study of this task by Abeler et al. (2019),
however, shows that most participants do not lie to such an extreme extent;
rather they over-report the number of heads relative to expected numbers.
What we add to this task is a willingness to pay elicitation and some further
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
that they report – to determine their payment.
Prior to the coin flip task, we use the Becker–DeGroot–Marschak [BDM]
mechanism (Becker et al., 1964) to elicit subjects’ WTP for the right touse their own coin to complete the coin flip task. As noted, there is nocost 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 upperbound of 500 points in the 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 (inpoints) pi ∈ {10, 20, . . . , 490, 500} for each participant. If pi ≤ W T P i ,5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.
The elicited WTP captures the privacy concerns of subjects associatedwith 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 of6

using 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 the privacy concern in using the virtual
coin unless the self-image concern dominates all the other considerations.2
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.

2.1

Questionnaire

After reporting the number of heads and tails from the 10 trials, participants had to complete a questionnaire in which, in addition to providing
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
Another possibility is that participants submit a positive WTP because they do notbelieve 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 this possibility
for submitting a positive WTP, the fact that we have conducted our experiment inexperimental laboratories where no deception is the rule and participants are aware ofthis rule should reduce the impact of such a consideration.

7

(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.
(c) Access to people’s bank account balances and their history of
payments.
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 govern8

ment’s rights. Questions (5-a), (5-b), (6-a), and (6-b) are from the World
Value Survey Wave 7 (Haerpfer et al., eds, 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 ask different people to translate theinstructions back into English to ensure consistency in the meaning.3

3

Results

The experiment was conducted online between October and December 2023
in Osaka (Japan), Irvine (USA), and Wuhan (China).4 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 (except for
the treatment with a virtual coin only), as we had instructed them to do.
3

The English instructions can be downloaded at https://osf.io/mka75/?view_
only=b4053e8c004d41f7812f31fc8827f5b2. Chinese and Japanese translations areavailable upon request.
4
The experiment is programmed using oTree (Chen et al., 2016).

9

They were then given a numerical ID to be used during the experimentto maintain their anonymity. Once these tasks were completed, they weresent back to the waiting room, where they waited until the start of theexperiment.
Once all the 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.5 During the experiment, subjects had their cameras and microphones turned off.
The experiment lasted about 25 minutes on average, including the postexperimental 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.6

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 to test for differences across the three locations are also5

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).
6
While performance-based payments were equalized based on the purchasing power
parity, we respected the standard show-up fees used in each location.

10

reported.
There are some notable differences in participant’s 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 regresssion analysis.

3.2

Willingness to pay to use own coin

We begin with the main variable of interest: subjects’ WTP to use their own
coin instead of the virtual coin. We then present participants’ reporting
behavior 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
the mean and the standard deviation of the WTP in each location.
We see that the mean (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 and
11

12

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 (red),
Irvine (cyan), and Wuhan (gray).
subjects’ answers to our questions. The results largely confirm the nonparametric tests. Compared to Osaka (the baseline), 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 demographics,
risk preference, ethical considerations, and participants’ views regarding
the government’s rights. In model (3), in addition to these, we control forthe belief about how many others (out of randomly selected 20) truthfully
report the outcome of coin flips. In model (4), instead of beliefs aboutothers’ truthful reporting, we control for the belief about how many others(out of a randomly selected 20) submit strictly positive WTP to use theirown 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 difference in WTP between Wuhan and Irvine.
Among the individual characteristics controlled for in model (2), i.e.,
13

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
1800.4615demographics, risk preference, views on ethics, and views about the government’s rights, only the self-reported willingness to take risks is statisticallysignificant. Specifically, a higher willingness to take risks is associated witha higher WTP to use one’s own coin. We interpret the positive and significant coefficient on the risk measure to indicate participants’ desire to use
their own coin, even when the price for doing so is high.
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’

14submitting a positive WTP is positive and significant in models (4) and (5).
That is, the more likely participants believe that others submit a strictly
positive WTP to use their own coin, the higher is their own WTP. We
interpret these two findings as resulting from social norm considerations.
In the first case, participants who believe that others are more likely toreport truthfully, may be less likely to misreport themselves in accordancewith their perceived norm. Consequently their WTP to use their own coinis lower. In the second case, those who believe that others are more likely
to report a positive WTP, will seek to conform to this norm and submit ahigher WTP.

3.3

Reporting behavior

Let us next turn to the actual reported number of heads. Figure 2 shows,using bubble plots, the relationship between subjects’ WTP (horizontalaxis) and their reported number of heads (vertical axis) depending on thecoin used (Own coin in black and Virtual coin in gray) in each of the threelocations. Reflecting the higher WTP submitted by the Osaka subjects, thenumber of subjects who used their own coin, instead of the virtual coin, ishigher 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 (homoeconomicus) 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 used in all the locations, none of these correlations is significant at the 10% level once individ15

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

WTP

N
%

Own
17
28.33%

4

2

0
0

6

100

200

300

400

500

0

100

WTP

Virtual43
71.67%

N%

Own
19
31.67%

200

300

400

500

WTP

Virtual41
68.33%

N
%

Own
29
46.0%

Virtual34
54.0%

Figure 2: Submitted WTP and 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.
ual characteristics are controlled for (See Table S1 in Online Supplementary
Material (OSM) I). There is a marginally significant positive relationshipbetween the price subjects actually paid and the reported number of heads
in Irvine once individual characteristics are controlled for (See Table S2 in
OSM I). When the virtual coin is used, there is no significant relationshipbetween the WTP and the reported number of heads in all three locations(See also Table S1 in OSM I).
Figure 3 compares the cumulative distribution of the reported numberof heads depending on the coin used in each of 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 the extent of misreportingwhen the virtual coin is used in CHOICE vs. VIRTUAL (C). See OSM II
for the analyses comparing OWN and VIRTUAL treatments.

16

(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).

17

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 S5 in OSM III). This finding could be the resultof two forces: “sorting” and “licensing.” Regarding “sorting,” recall thatin the CHOICE treatment, those subjects who have submitted a higher
WTP to use their one coin are more likely to be selected to use theirown 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 priceto use their own coin may have justified their reporting a higher number ofheads 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 higher inthe VIRTUAL treatment as compared with 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 continues to be significant (see Columns
Wuhan (1) and Wuhan (2) in Tables S5 and S6, OSM III). This is puzzlingin light of “sorting.” In the CHOICE treatment, those subjects who havesubmitted low WTPs to use their own coin are more likely to be selected
to use the virtual coin. Thus, these participants have low costs associated18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)with privacy concerns. In other words, they are more willing to use thevirtual coin and misreport than the average participants in the VIRTUAL
treatment. If participants are mainly concerned about their self-image (andthus do not misreport regardless of the type of the coin used), however, we
may observe a low WTP and low misreporting. Unfortunately, it is notpossible to test this hypothesis using our data.

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 to19use 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 usedtheir own coin obtained significantly higher payoffs than those who used thevirtual coin in the CHOICE treatment. In Wuhan, those who used theirown coin earned 827.06 points on average, while those who used virtual
coin earned 669.76 points (p=0.066, MW). In Osaka, similarly, the average
payoffs are 698.28 points with their own coin and 564.71 points with thevirtual coin (p=0.004, MW). In Irvine, the average payoffs for those who
used their own coin and the virtual coins 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.
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. 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.
CHOICE treatments) are 0.788, 0.626, and 0.236 in Wuhan, Irvine, andOsaka, respectively.

20

4Discussion and conclusion

We have reported on a laboratory experiment that measures participants’willingness to pay to avoid the spotlight regarding the reported number ofheads 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 can 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.
Second, there is heterogeneity across countries. The difference in WTP
between Osaka and Wuhan and between Osaka and Irvine are statisticallysignificant at the 5% and 10% levels, respectively, while the difference between the latter two, Wuhan and Irvine, is not statistically significant.
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. These concerns will need to be addressed in the design of new
digital payment systems.
To better understand the source of this substantial WTP, we examineda variety of individual characteristics. Among those that we considered,
the participant’s self-reported willingness to take risks is significantly andpositively related to their WTP to use their own coin. Age, gender, andsubjects’ views of ethical behavior or of the government’s right to monitor
people’s activities are not related to WTP. Interestingly, WTP is higher
21

among those who believe that others are less likely to truthfully report theoutcomes of their coin flips, suggesting that social 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
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 3, 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

22

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 3: Payment Methods Usage by Country (in %), Source: FIS (2023)
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
for paying 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
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 for privacy in23their economic transactions beyond the desire to avoid detection of 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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28

Online Supplementary Material for Bao, Duffy, Hanaki(2024) “Paying to avoid the spotlight”
This supplementary information contains the following
I Regression results for the reported number of heads, WTP, and theprice paid in the CHOICE treatment
II Results of the control treatments
III Regression results for the reported number of heads, misreporting
and the coin used. Comparison of the CHOICE and the control
treatments

1

I

Regression results for the reported number of heads, WTP, and the price paid in
the CHOICE treatment23

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 S1: 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)4All (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 S2: 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)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 S1: Cumulative distribution of the reported number of heads in
OWN treatment (left) and VIRTUAL treatment (center) as well as theextent of misreporting in VIRTUAL treatment (right) in Osaka (red), Irvine(cyan), and Wuhan (gray).

II

Results of the control treatments

Figure S1 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).7 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 shownin the right panel is significantly greater in Wuhan as compared with Irvine
and Osaka.
7
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.

5

Table S3: 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
0.0458

Table S3 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”
variable and the Misreporting amount. Thus, those who consider claiming
public benefits that they are not entitled to, cheating on their taxes, or not
6

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 S2: Cumulative distribution of the reported number of head in OWN
treatment (black) and VIRTUAL treatment (gray) treatments. Wuhan(left), Irvine (cyan), and Osaka (right).
telling the truth when it is costly to do so are more unjustifiable are lesslikely to misreport.
Figure S2 compares the distributions of the reported number of head
between the OWN treatment (black) and the VIRTUAL treatment (gray)in each location. P-values from MW and Kolmogrov-Smirnov (KS) tests
are also 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 S4). 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.

7

Table S4: 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)

8

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

III

Regression results for the reported number of heads, misreporting and the coinused. Comparison of the CHOICE andthe control treatments.

910

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 S5: 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)11

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)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)Table S6: Misreporting. Regression results

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)