Discussion Papers In Economics
And Business
Nudges for COVID-19 voluntary vaccination:
How to explain peer information?
Shusaku Sasaki
Tomoya Saito
Fumio Ohtake

Discussion Paper 21-07

June 2021

Graduate School of Economics
Osaka University, Toyonaka, Osaka 560-0043, JAPANNudges for COVID-19 voluntary vaccination:
How to explain peer information?
Shusaku Sasaki* Tomoya Saito† Fumio Ohtake‡

Abstract:
Promoting vaccination is a crucial strategy to end the COVID-19 pandemic; however, individualautonomy should be respected at the same time. This study aimed to discover behavioral
economics nudges that can reinforce people’s intention to receive the COVID-19 vaccine without
impeding their autonomous decision-making. In March 2021, we conducted a pre-registered,online experiment with 1,595 Japanese nationwide sample, and randomly assigned them to one ofa control group and three treatment groups that provided the following other-regarding messages:
Message A (“X out of 10 people in your age group answered they would receive this vaccine”),
Message B (“Your vaccination behavior can encourage the vaccination behavior of the people
around you”), or Message C (“If you do not receive the vaccine, the people around you also may
not do so”). By comparing the messages’ effects on vaccination intention, autonomous decisionmaking, and emotional burden, we found that Message B was effective in increasing the numberof older adults who newly decided to receive the vaccine. Messages A and C further reinforced
the intention of older adults who had already planned to receive it. However, Message C, whichconveys similar information to Message B with loss-framing, increased viewers’ emotional burden.
These three messages had no promoting effect for young adults with lower vaccination intentions
at baseline. Based on the above findings, we propose that governments should use different
messages depending on their purposes and targets, such as Message A instead of Message C, toencourage voluntary vaccination behavior.
Keywords: Herd immunity, Behavioral public policy, Nudge, Framing effect, Autonomy
JEL codes: I12, D91, C90*

Corresponding author (ssasaki.econ@gmail.com; 1-3-1 Tsuchitoi, Aoba-ku, Sendai, Miyagi 985-8537,
Japan); Faculty of Economics, Tohoku Gakuin University, and Center for Infectious Disease Education andResearch (CiDER), Osaka University†

Center for Emergency Preparedness and Response, National Institute of Infectious Diseases‡

Center for Infectious Disease Education and Research (CiDER) and Graduate School of Economics, Osaka
University
This research is financially supported by the Japan Society for the Promotion of Science [JSPS Grant
Numbers: 19K13722 (S., Sasaki) and 20H05632 (F., Ohtake)].

11. Introduction
Promoting vaccination is a crucial strategy to end the COVID-19 pandemic. Promotion
measures potentially include options from simple information provision to legal mandates.
However, compulsory measures are rare, and some degree of self-selection is preferred,because public health is guided by the least restrictive alternative, which states that wemust select measures that place the least restrictions on individual freedom and rights, toachieve a public good, including herd immunity (Giubilini, 2021). Since the COVID-19
vaccine has been newly developed and there are uncertainties and ambiguity regarding
its long-term efficacy and adverse reactions, it is important to respect individual autonomy.
Behavioral economics defines nudge as “an aspect of choice architecture that alters
people’s behaviour in a predictable way without forbidding any options or significantly
changing their economic incentives” (Thaler and Sunstein, 2008, p.6). Nudge has beenused for promoting COVID-19 social distancing (Lunn et al., 2020; Sasaki et al., 2021),
and will be relevant in the above setting.
We investigated whether nudge-based messages, which provided information onothers’ vaccination decisions and behaviors, strengthen people’s intentions to receive the
COVID-19 vaccine. This study’s uniqueness is that we used three messages differently
describing others’ information, and compared their effects on people’s vaccination2

intentions, autonomous decision-making, and emotional burden. In addition, this study
contrasted older adults, who is the target of priority vaccination in lots of countries, withyoung adults, who will be eligible for vaccination later.

2. Literature Review
Behavioral science studies have informed others’ decisions and behaviors and attempted
to transform people’s behaviors in socially desirable directions in various policy fields,
including energy savings, tax payment, and charitable giving (Allcott, 2011; Hallsworth
et al., 2017; Shang and Croson, 2009).
This type of intervention is called a social-comparison nudge and can be effectivein encouraging COVID-19 vaccination. Latkin et al. (2021) found that social norms arestrongly associated with people’s trust for the COVID-19 vaccine. In a large-scale surveyof 23 countries, Moehring et al. (2021) actually found that providing information aboutothers’ vaccination intentions strengthened survey participants’ intentions.
Social-comparison nudges have two strengths in implementation over defaults, inwhich people’s choices are pre-determined by socially recommended options. First, they
are less expensive to implement, because they simply add information on mail, homepage,etc. However, the defaults require changes in procedure and setting, which impose larger
3

financial and time costs. Second, they respect people’s autonomous decision-making,because people need to voluntarily choose the socially recommended option if they wish.
The defaults can lead to situations, where the choices of people who are unaware of thesetting are pre-determined. Thus, the defaults pose a higher risk of forcing people to makechoices they might not wish to make than the comparison nudges. Behavioral economics
calls such inconsiderate interventions sludge and suggests they should not be employed(Sunstein, 2020; Thaler, 2018).
However, since the recipients of social-comparison nudges could feel emotional
pain and anxiety, there is scope for social welfare improvements by preventing suchemotional costs. Social-comparison nudges promote behavioral changes, by making
people aware of the disutility of not behaving in the same way as others. If this prompts
those who wish to receive the COVID-19 vaccine but have difficulty in doing so on theirown, their welfare will improve. However, those who can receive it without a nudge or
those unable to receive it will not see any improvement in their welfare when receiving
the nudges. If the nudges generate negative emotions, their welfare will rather deteriorate.
Therefore, messages should ensure that receivers do not experience negative emotions.
There has been a growing body of research on the emotional costs of providing
information (Allcott and Kessler, 2019; Thunström, 2019): however, no study has
4explicitly considered the emotional cost of nudges in COVID-19 vaccination, to ourknowledge. The least restrictive alternative prefers a less emotionally burdensome nudge.
Again, since the long-term consequences of the vaccine have not yet been confirmed, thenudge that recommends vaccination with as little emotional burden as possible andrespect for people’s autonomous decision-making is desirable. This study contributes tothe literature by simultaneously considering the impacts of other-regarding nudges on
vaccination intention and on autonomous decision-making and emotional burden.

3. Experimental Design
3.1. Overview
We conducted a pre-registered, online experiment with a Japanese nationwide sample
over a 3-day period from March 16–18, 2021. We commissioned MyVoiceCom Co. Ltd.,
recruited respondents from their monitors throughout Japan, and conducted the survey.
Since vaccination for ordinary people did not yet start in Japan at the time of conducting
this experiment, we can evaluate the impacts of nudge-based messages for those withstrong intentions to receive the vaccine to those with weak intentions.
In Japan, vaccination for healthcare workers firstly started on February, 2021, andthen that for ordinary older adults (65 years and older) started on April. We collected5

1,595 valid responses, including 798 older adults (65–74 years) and 797 young adults(25–34 years), who would be eligible for vaccination quite later.
We obtained ex-ante approval from the ethics committee of Graduate School of
Economics, Osaka University. We also registered the experimental design with the AEA
RCT Registry (Sasaki, Ohtake and Saito, 2021).

3.2. Nudge-based Messages
We randomly assigned the 1,595 respondents to one of four groups. The messages foreach group are shown in Figure 1. Explanations on the effectiveness of the COVID-19
vaccine, adverse reactions, and how to deal with adverse reactions were the same for allgroups. We created the explanations based on the Japanese actual vaccination program(Prime Minister’s Office, 2021) to have respondents imagine vaccination situations indetail and prevent inconsistency between their experimental choices and real behaviors(Sheeran and Webb, 2016).
For the three treatment groups, we display each nudge-based message in addition
to the above common explanations. Group A conveys the proportion of people willing toreceive the COVID-19 vaccine. Specifically, the message for older (young) adults is “7–
8 (6–7) out of 10 people in your age group answered they would receive this vaccine.”
6

These statistics are from another nationwide survey, which we conducted in January 2021
(Sasaki, Saito, and Ohtake, 2021). We call these messages social-comparison nudges (inshort, comparison).
Groups B and C focus on that respondents’ own vaccination behaviors possibly
influence those of others. This assumes that simple social-comparison nudges strengthen
vaccination intentions. Our pre-survey analysis found that as the vaccination rate of thesame age group increases, the vaccination intention of the respondents also increases(Sasaki, Saito, and Ohtake, 2021), and supports the assumption. Organizational
psychology suggests people prefer to influence others (Bolino, 1999). Another study
reported that people’s disaster evacuation intentions increase significantly when receiving
messages informing their own evacuation behavior can promote those of others (Ohtake
et al., 2020). Using this type of message can make people shift their attention from thedisutility of not following social norms to the selfish utility of influencing others and thesociety.
The message for group B is “Your vaccination behavior can encourage thevaccination behavior of the people around you.” Group C expresses the same content asgroup B using loss-framing: “If you do not receive the vaccine, the people around you
may also not do so.” We call the former gain-framed social influence nudge (influence7

gain) and the latter loss-framed social influence nudge (influence-loss).
Tversky and Kahneman’s (1981) prospect theory states that people’s choices
depend on whether they are framed in terms of gain or loss, even if their substance isessentially equivalent. Although a loss-framed message is theoretically expected to be
more effective for behavioral change than a gain-framed message, their effectivenessempirically depends on contexts (Detweiler et al., 1999; Schneider et al., 2001). Heffner
et al. (2020) reported that both gain and loss framings promote social-distancing intention,
while only the loss framing generates negative emotions. Therefore, compared to the gain
framing, the loss framing will place a heavier emotional burden on the viewer and inhibit
autonomous decision-making in the context of vaccination.

3.3. Outcome Measures
3.3.1 Primary Outcomes: Willingness to Pay for the COVID-19 Vaccine
After each nudge-based message, we set up a question to measure the respondents’
willingness to pay (WTP) for the COVID-19 vaccine. WTP is the maximum amount they
are willing to pay for the vaccine, expressing the strength of their vaccination intentions.
This measure has been used in other studies on the COVID-19 vaccine (Cerda and García,
2021; Wong et al., 2020).
8

The respondents were first asked: “Suppose you can receive this vaccine without
having to pay out-of-pocket, will you visit the vaccination camp and receive it?” Next,
those who answered they would receive the free vaccine proceed to the question on thepayment setting (left panel, Figure 2), while those who answered that they would not,proceed to the question on the receipt setting (right panel). The questions have a Multiple
Price List format, often used to calculate WTP (Anderson et al., 2006). We define WTP
as the midpoint of the amounts around the switching point. For example, a respondent
answers they will receive the vaccine if they need to pay ¥8,000 or less, while they will
not if they need to pay ¥10,000 or more; the WTP is ¥9,000. This means they want toreceive the vaccine even if they need to pay ¥9,000. However, another respondent answers
that they will not receive the vaccine even if they can receive ¥15,000 or less, while they
will if they can receive ¥20,000 or more; their WTP is -¥17,500. This means they do notwant to get vaccinated unless they receive ¥17,500 or more. The WTP for those who
answer that they will receive the vaccine under all choices, including the maximum
amount of ¥30,000, becomes ¥35,000. The WTP of those who answer that they will notreceive it under all choices becomes -¥35,000. One US dollar was approximately
equivalent to 108 Japanese yen on March, 2021.

9

3.3.2 Secondary Outcomes: Autonomy and Emotional Burden
After the WTP question, we presented the following four questions to clarify whether
adding nudge-based messages inhibits respondents’ autonomous decision-making andgenerates negative emotions compared to the common explanations in the control group:“Did you want to receive the vaccine voluntarily?” (voluntary), “Did you think you werebeing forced to receive the vaccine?” (forced), “Did you feel distressed when you
received the explanation of the vaccine?” (distressed), and “Did you feel that the
explanation of the vaccine needed to be improved?” (should be improved). We createdthese questions, considering end-of-life care studies that have long focused on patients’autonomous decision-making (Ngo-Metzger et al., 2008). The questions were rated on a
five-point scale.

3.4 Descriptive Statistics
Appendix Table A shows the descriptive statistics for the older and young respondents.
The distributions of age, gender, marital status, family structure, years of education, andhousehold annual income are almost balanced, while our estimations directly control forthe influence of these variables, since the proportions of respondents living together aged
65 or older and not answering income information are partly unbalanced.
10

4. Results
4.1 Effects on Vaccination IntentionsFirst, we present vaccination intention levels in the control group. The proportion of older
respondents willing to receive the free vaccine is 84.4%, which is higher than for young
adults, at 67.0%. The average WTP is ¥427.1 among older adults and -¥3,300.0 among
the young.
Figure 3 shows the effect of nudge-based messages on vaccination intentions,setting the control group as a baseline. The messages were effective for older respondents.
In group B with the influence-gain nudge, the proportion of older adults willing to receive
the free vaccine increased by around 7% (p<.05) compared to the control group, reaching
91.5%. The WTP also increased by ¥2,797.9 (p<.10). In group C, with the loss-framed
message, the WTP increased by ¥3,361.8 (p<.05) compared to the control group, reaching¥3,789. This is almost nine times higher than that of the control group, at ¥427.1. However,these messages did not have any promoting effect on the young with lower vaccination
intentions at baseline.
Table 1 shows the messages’ effects, using regression analysis and controlling forthe influence of the attribute variables in Section 3.4. According to columns 1 and 2, thepromoting effects for older adults changed little in magnitude and statistical significance11

(in order: 6%, p<.05; ¥2,353.4, p<.10; ¥3,495.8, p<.05).
Furthermore, we changed the WTP variable into the following two variables. The
first changed negative WTP values (below ¥0) to ¥0, and then focused on positive WTP
values in the payment setting. The second changed positive WTP values (over ¥0) to ¥0,
and focused on negative WTP values in the receipt setting. Using the first enables us todetermine the messages’ effects on the vaccination intentions of those who have alreadyintended to receive the free vaccine, and vice versa. Our estimation uses the Tobit model
here, because the threshold of ¥0 biases OLS estimates. The marginal effects are reported
in columns 3, 4, 7, and 8.
The results show that, for older respondents, the influence-gain nudge had theeffect of increasing the intentions of those who did not yet intended to receive the freevaccine, while the loss-framed nudge further strengthened the intentions of the othersubgroup with originally higher intentions. A new finding is that the comparison nudge
had the same impact as the loss-framed message (¥1.148.9, p<.01). The null hypothesisthat the comparison nudge’s effect is equal to the loss-framed message’s is not rejected(p=.47). The failure to find the promoting effect of the comparison nudge in Figure 3 andcolumn 2 of Table 1 may be because this message possibly works to weaken the intentionsof those who have not intended to receive the free vaccine (-¥522.81, p=.49).
12

4.2. Effects on Autonomy and Emotional Burden
Table 2 uses the levels of respondents’ autonomous decision-making and emotionalburden as alternative outcomes. The influence-loss nudge worsened their autonomy andemotional burden compared to the control group. This message led to higher mental stressfor older adults (p<.05) and made the young feel that they are forced to receive the vaccine
and that the explanation of the vaccine should be improved (p<.01 for both).
The above concerns are not observed under the comparison nudge and the gainframed nudge. However, the constant terms make us recognize that autonomy might havealready been inhibited and emotional burden might have been placed for older adults inthe control group. The degrees, to which they feel that they are forced to take thevaccination and the explanation should be improved, are near the maximum value of 5.
The null hypothesis that the constant term is equal to 5 is not rejected (in order p=.72,
p=.99). The common explanations are based on the official ones of the Prime Minister’s
Office (2021). Although this result may suggest that the official explanations should be
improved, the average level of younger respondents who viewed the same explanations
is 3, which is “neutral.” The null hypothesis that the constant term is equal to 3 is not
rejected (in order p=.93, p=.42). It is also possible that older adults felt considerable socialpressure to get vaccinated during March 2021 when we conducted this experiment, which
13was reflected in their responses.
At the end of this experiment, we conducted debriefing, offered respondents anopportunity to change their vaccination decision, but confirmed that few of them changed
the decision (Please see Appendix Table B).

5. Discussion, Limitations, and Conclusions
Our online experiment suggested that other-regarding messages had the following effects
on COVID-19 vaccination intentions. First, the influence-gain nudge increased the
proportion of older adults who will receive the vaccine if it is offered for free. Second,the vaccination intentions of older adults who already intended to receive it further
strengthened because of the loss-framed nudge and the comparison nudge. However, theformer message placed an emotional burden on viewers. Third, these messages did nothave any promoting effect for young adults with lower vaccination intentions at baseline.
The result that the gain-framed message is less emotionally burdensome than theloss-framed one is consistent with that of the COVID-19 social distancing study (Heffner
et al., 2020). As in the study conducted in other countries (Moehring et al., 2021), thecomparison nudge will work in Japan, but may weaken the intentions of older adults who
have not yet intended to receive the vaccine.
14Our findings suggest that governments should use different messages depending
on purposes and targets. First, the gain-framed nudge will be effective for increasing thenumber of older adults who newly decide to receive the vaccine. One option is to include
this message on public posters and websites. Second, the comparison nudge will beeffective for reinforcing the intentions of older adults who have already intended toreceive the vaccine and ensuring their vaccination is carried out. Regarding social welfare,
the governments should use the comparison nudge, instead of the loss-framed nudge thathas the similar promoting effect but increases the emotional burden of the viewers.
However, since the comparison nudge may further weaken the vaccination intentions ofolder adults with originally lower intentions, it is necessary to display this message only
to those who wish to get vaccinated. One option is to include this message on thereservation screen for vaccination or in reminder e-mails.
Our messages had no promoting effect for younger generation. Policymakers needto consider developing other nudge-based messages and adopting monetary incentives, toreliably encourage vaccination of this generation with more vaccine hesitancy. Further,
the messages did not inhibit autonomy or emotion, but did not improve them either. Given
that many of older respondents already felt they were forced to get vaccinated when theyreceived the actual explanations, policymakers need to explore other expressions that are15

more respectful of autonomous decision-making.
This study has one limitation that respondents’ choices are hypothetical. Although
we design the hypothetical question as close as possible to the Japan’s actual vaccination
program, there may exist some gaps between the experimental choices and real behaviors.
However, since existing studies have reported that nudge-based messages can promoteseasonal influenza vaccination behavior (e.g., Milkman et al., 2021), our messages may
be effective also for behaviors. In addition, whether this study’s results are applicable toother countries should be tested by future research.
Despite the limitations, this study makes significant academic and policy
contributions, because no other study has explored desirable nudge-based messages in thecontext of COVID-19 vaccination, considering not only vaccination intentions but also
autonomy and emotional burden. COVID-19 vaccination has recently started worldwide,
and our findings can contribute to the improvement of vaccination programs.

16

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Appendix
Table A. Descriptive Statistics
(1)

(2)

(3)

(4)

(5)

Old respondents (65-74 years)
Control

(6)

(7)

(8)

Young respondents (25-34 years)

Treamet A

Treamet B

Treamet C

Comparison

Influence-gain

Influence-loss

199

200

200

199

Mean

68.95

69.22

69.33

S.D.

2.79

2.72

2.81

Mean

0.50

0.50

S.D.

0.50

Mean

Control

Treamet A

Treamet B

Treamet C

Comparison

Influence-gain

Influence-loss

200

199

199

199

68.95

29.97

30.19

30.40

30.39

2.82

2.67

2.75

2.68

2.89

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.82

0.80

0.84

0.80

0.37

0.40

0.40

0.41

S.D.

0.38

0.40

0.37

0.40

0.48

0.49

0.49

0.49

Divorce / Bereavement (dummy)

Mean

0.13

0.15

0.09

0.14

0.02

0.02

0.01

0.01

S.D.

0.33

0.36

0.29

0.34

0.12

0.12

0.10

0.07

Number of family members living together

Mean

2.45

2.52

2.52

2.52

3.11

2.98

3.02

2.92

S.D.

1.08

1.17

1.02

0.94

1.53

1.28

1.45

1.42

Mean

0.69

0.72

0.71

0.69

0.21

0.13

0.18

0.16

S.D.

0.46

0.45

0.46

0.46

0.40

0.34

0.39

0.37

Educational years

Mean

14.14

14.17

14.20

14.07

14.67

14.79

14.86

14.77

S.D.

2.10

2.07

1.99

2.02

2.05

1.87

2.16

2.21

Household annual income (Unit: 10 thousand yen)Mean

539.95541.25523.50528.64593.00597.74543.22563.07

S.D.

373.05381.40340.89354.39350.52297.69288.14326.61

Mean

0.22

0.20

0.14

0.17

0.22

0.18

0.14

0.20

S.D.

0.42

0.40

0.34

0.38

0.41

0.38

0.35

0.40

Number of observations =Variables:
Age

Female (dummy)

Married (dummy)

Family members living together aged 65 or older (dummy)

No income information (dummy)

Notes: 1) Some participants did not answered annual household income. We imputed the average amout of the income for such respondents while considering that they did not answer it by using the variable of no income information. 2) The
distributions of age, gender, marital status, family structure, years of education, and household annual income are almost balanced, while our estimations directly control for the influence of these variables, since the proportion of young respondents
living together aged 65 or older is lower in Treatment A than in Control and that of old and young respondents not answering income information is lower in Treatment B than in Control. 3) We set a question to ascertain whether respondents read ourdescriptions carefully. We displayed a caution message to those respondents who were found not to have read carefully, while empirically controlling for them.

19

Table B. Change in Selection

(1)

(2)

(3)

(4)

(5)

Old respondents (65-74 years)
Control

Number of observations =Change to "receive"

No change

Change to "do not receive"

(6)

(7)

(8)

Young respondents (25-34 years)

Treamet A

Treamet B

Treamet C

Comparison

Influence-gain

Influence-loss

199

200

200

199

2

2

1

1.01%

1.00%

196

Control

Treamet A

Treamet B

Treamet C

Comparison

Influence-gain

Influence-loss

200

199

199

199

3

8

0

3

5

0.50%

1.51%

4.00%

0.00%

1.51%

2.51%

198

198

196

187

192

193

189

98.49%

99.00%

99.00%

98.49%

93.50%

96.48%

96.98%

94.97%

1

0

1

0

5

7

3

5

0.50%

0.00%

0.50%

0.00%

2.50%

3.52%

1.51%

2.51%

Notes: At the end of this experiment, we explained the research purpose to the respondents and clarified that the information on the vaccination intentions of others was described
differently for each group We then presented them with another question to ascertain whether they would receive the free vaccine and offered them an opportunity to change theirdecision. Few respondents selected a different option from the one in the experiment. More concretely, there are only around 2–3 older respondents in each group who switched andaround 10 in each group for the younger population, with the numbers being similar between groups.

20

Tables and Figure
Table 1. Message Effects on Vaccination Intentions
(1)

(2)

(3)

(4)

(5)

(6)

Older respondents (65-74 years)
Number of observations:

798

Estimation method:
Dependent variable:

Treatment A

Treatment B

Treatment C

Attribute varibales

Comparison

Influence-gain

Influence-loss

(7)

(8)

Young respondents (25-34 years)
797

OLS

Tobit model

OLS

Tobit model

Free-vaccine

WTP

WTP

WTP

Free-vaccine

WTP

WTP

WTP

(binary)(both)(payment)(receipt)(binary)(both)(payment)(receipt)-0.02

749.781,148.86***-522.81-0.01-603.83-153.12-215.40(0.03)(1,023.69)(331.96)(756.07)(0.05)(1,762.50)(424.23)(1,425.63)

0.06**

2,353.35*

726.14

1,881.86**-0.07-2,289.22-312.45-1,908.36(0.03)(1,270.15)(628.11)(870.34)(0.06)(1,530.41)(487.84)(1,279.23)

0.04

3,495.81**

1,754.17**

990.350.06

241.94114.94

1,180.14(0.03)(1,605.95)(702.35)(851.27)(0.04)(1,345.88)(363.58)(1,158.64)

YES

YES

YES

YES

YES

YES

YES

YES

Note: Cluster robust standard errors at prefecture level in parentheses; *** p<0.01, ** p<0.05, * p<0.1

21

Table 2. Message Effects on Autonomy and Emotional Burden

Estimation method: OLS

(1)

(2)

Treatment A

Treatment B

Treatment C

Constant term

Attribute variables

Comparison

Influence-gain

Influence-loss

(4)

(5)

(6)

(7)

Older respondents (65-74 years)

Young respondents (25-34 years)

798

797

Number of observations:
Dependent variable (5-point scale):

(3)

(8)

voluntary

forceddistressedshould be improved

voluntary

forceddistressedshould be improved

-0.02

-0.09

0.04

0.06

-0.11

0.01

0.08

0.08

(0.10)(0.09)(0.10)(0.11)(0.15)(0.11)(0.11)(0.11)

0.10

-0.06

0.07

0.05

-0.20

-0.01

0.10

0.14

(0.13)(0.16)(0.10)(0.12)(0.14)(0.09)(0.09)(0.09)

0.09

0.08

0.17**

0.14

0.01

0.42***

0.18

0.37***(0.11)(0.13)(0.07)(0.10)(0.13)(0.10)(0.11)(0.10)

2.92***

4.67***

3.77***

5.01***

2.42***

2.94***

2.57***

3.50***(0.79)(0.91)(1.01)(1.19)(0.79)(0.61)(0.55)(0.61)

YES

YES

YES

YES

YES

YES

YES

YES

Note: Cluster robust standard errors at prefecture level in parentheses; *** p<0.01, ** p<0.05, * p<0.1

22

Figure 1. Messages
Control group

Treatment group A: Comparison nudge(Top for older adults, Bottom for young adults)

23

Treatment group B: Influence-gain nudge

Treatment group C: Influence-loss nudge

24

Figure 2. Vaccination Intention(left for payment setting, right for receipt setting)25

Figure 3. Message Effects on Vaccination Intention

Note: The numbers show the message effects, setting the control group as the baseline,
while the bars show the 90% confidence interval.

26