Discussion Paper 2023-E004

DISCUSSION PAPER SERIESOsaka University Graduate School of Medicine
Department of Health Economics and Management

What policies did voters choose in the October 2021
general elections in Japan?
Conjoint analysis of policy options

Masaaki Kawagoe*†* Nihon University College of Economics and Osaka University Graduate School of Medicine† The Institute of Economic Sciences, Faculty of Economics, Nihon University funded a project onwhich this study is based. I would like to express my gratitude here.

OHEM Secretariat
Graduate School of Medicine Department of Health Economics and Management
OSAKA UNIVERSITY
1-7 Yamadaoka, Suita, Osaka, 565-0871, Japan

What policies did voters choose in the October 2021
general elections in Japan?
Conjoint analysis of policy options

February 2023

Masaaki Kawagoe*†* Nihon University College of Economics and Osaka University Graduate School of
Medicine†

The Institute of Economic Sciences, Faculty of Economics, Nihon University funded a project onwhich this study is based. I would like to express my gratitude here.

Abstract
This study adopts a conjoint analysis approach to examine voters’ preferences for policy
options during the campaign period of the 49th House of Representatives election held inJapan in October 2021. This study makes the following four contributions. First, it
exemplifies voter’s preference for policy options as their amount of willingness to pay (WTP),
thereby clarifying their priorities on the policies. Second, the WTP estimates greatly differ,depending on whether the voter’s evaluation is based on the current or future tax burden (i.e.,
fiscal deficit), and also on personal characteristics, in particular, age. This may imply that it
is very difficult to build consensus in the policy-making process. Third, the aforementioned
great difference of WTPs due to financing methods is a new direct indication of fiscal illusion(Buchanan and Wagner, 1977). Fourth, elderly voters reveal their altruistic tendency to carefor the younger generation, which may control “silver democracy.”11. Introduction
This study explores voters’ preferences for policy options using conjoint analysis, atechnique widely used in the field of marketing (Rao, 2014). In marketing, when exploring
the needs of products with special characteristics, especially in new product development, aproduct is regarded as a “bundle” of various attributes (color, shape, size, function, etc.). A
consumer compares products A and B with different bundles of attributes, and selects one ofthem. This marketing method is applicable to voting behavior if “consumer” is replaced with“voter,” “attribute” with “policy categories and options therein,” and “product” with“manifest or policy alternative.”
We conducted a questionnaire survey on policy alternatives via the Internet during the
campaign period of the House of Representatives general election held in Japan in October
2021. The results are analyzed to examine voters’ preferences for the policy options. This
study is characterized by the timing of its survey. This was inspired by Horiuchi, Smith, andYamamoto (2018), HSY hereafter, who conducted a survey during the campaign period of
the 2014 House of Representatives election. The second feature of our study is that thepreference for policy options is evaluated as the willingness-to-pay (WTP), differentiating us
from HSY. As a political science study, HSY were interested in a desirable combination ofpolicy options to increase the possibility of winning the election. A focus on WTP, together
with different financing methods to implement policies, provides new evidence on fiscal
illusion that voters pay insufficient attention to the intertemporal budget constraint the
government faces (Buchanan and Wagner, 1977).
The rest this paper is structured as follows. In Section 2, the model is outlined, whereas
the survey design is explained in Section 3. The survey results are examined in Section 4,
and concluding remarks are presented in Section 5.

2. ModelWe use a standard model in the discrete choice experiment literature 1. Random utility
theory allows us to decompose utility gained from commodity 𝑖𝑖 into a deterministic part, 𝑉𝑉𝑖𝑖𝑖𝑖 ,and a stochastic one, 𝜀𝜀𝑖𝑖𝑖𝑖 :1

𝑈𝑈𝑖𝑖𝑖𝑖 = 𝑉𝑉𝑖𝑖𝑖𝑖 + 𝜀𝜀𝑖𝑖𝑖𝑖.

This section is based on Greene (2003) and Aizaki et al. (2015).
2(1)

The fact that individual 𝑛𝑛 selects commodity 𝑖𝑖 rather than commodity 𝑗𝑗 means:
𝑈𝑈𝑖𝑖𝑖𝑖 − 𝑈𝑈𝑗𝑗𝑗𝑗 = 𝑉𝑉𝑖𝑖𝑖𝑖 − 𝑉𝑉𝑗𝑗𝑗𝑗 + 𝜀𝜀𝑖𝑖𝑖𝑖 − 𝜀𝜀𝑗𝑗𝑗𝑗 > 0,

𝑉𝑉𝑖𝑖𝑖𝑖 − 𝑉𝑉𝑗𝑗𝑗𝑗 > 𝜀𝜀𝑗𝑗𝑗𝑗 − 𝜀𝜀𝑖𝑖𝑖𝑖.
(2)
further, suppose there are 𝑘𝑘 determinants of the deterministic part, 𝑉𝑉𝑖𝑖𝑖𝑖 , which is modeled as

below, assumes their linear combination. Here, 𝛽𝛽𝑘𝑘𝑘𝑘 is the weight an individual 𝑛𝑛 gives anattribute k, or the partial utility they gain from the attribute.
𝐾𝐾

𝑉𝑉𝑖𝑖𝑖𝑖 = � 𝛽𝛽𝑘𝑘𝑘𝑘 𝑥𝑥𝑖𝑖𝑖𝑖 = 𝑿𝑿𝑖𝑖 𝜷𝜷𝑛𝑛
𝑘𝑘=1

(3)

The above leads to the following expression of the probability of individual i’s choice:Pr�𝑈𝑈𝑖𝑖𝑖𝑖 > 𝑈𝑈𝑗𝑗𝑗𝑗 � = Pr�𝑉𝑉𝑖𝑖𝑖𝑖 − 𝑉𝑉𝑗𝑗𝑗𝑗 > 𝜀𝜀𝑗𝑗𝑗𝑗 − 𝜀𝜀𝑖𝑖𝑖𝑖 � = Pr ��𝑿𝑿𝑖𝑖 − 𝑿𝑿𝑗𝑗 �𝜷𝜷𝑛𝑛 > 𝜀𝜀𝑗𝑗𝑗𝑗 − 𝜀𝜀𝑖𝑖𝑖𝑖 �= Pr�𝑿𝑿𝑖𝑖𝑖𝑖 𝜷𝜷𝑛𝑛 > −𝜀𝜀𝑛𝑛 � = Pr�𝜀𝜀𝑛𝑛 < 𝑿𝑿𝑖𝑖𝑖𝑖 𝜷𝜷𝑛𝑛 �(4)where symmetry of probability distribution function is assumed, and 𝐹𝐹 is a cumulative= F�𝑿𝑿𝑖𝑖𝑖𝑖 𝜷𝜷𝑛𝑛 �,distribution function.
Furthermore, assume that the stochastic part, 𝜀𝜀𝑖𝑖𝑖𝑖 , independently and identically follows a

Gumbel distribution, and that utility from commodity i is the largest among more than threecommodities belonging to the commodity set, 𝑆𝑆 = {1, 2, … , 𝐼𝐼 } .The probability that
commodity i is selected is modeled by a conditional logit model as follows:
𝑃𝑃𝑛𝑛 (𝑖𝑖) =exp (𝑿𝑿𝑖𝑖 𝜷𝜷𝑛𝑛 ).
𝐼𝐼∑𝑖𝑖=1 exp (𝑿𝑿𝑖𝑖 𝜷𝜷𝑛𝑛 )(5)For example, let 𝐾𝐾 − 1 variables be dummies with values of unity for excellent quality
and null for normal quality. The last K-th, 𝑥𝑥𝑖𝑖𝑖𝑖 , stands for a continuum variable representing
price. This set-up enables us to estimate how much one will pay for the characteristics the kth dummy stands for with its unity value, that is, WTP, by the following formula:
𝑊𝑊𝑊𝑊𝑊𝑊𝑛𝑛 = −𝛽𝛽𝑘𝑘𝑘𝑘,𝛽𝛽𝐾𝐾𝐾𝐾

k = 1, … , K − 1.

(6)

Although WTP could be individually different, a unique value for all the participants isgained if the commonality assumption is adopted. A less stringent case is that thecommonality assumption is limited to a group classified by personal characteristics, resulting
in a group specific WTP, 𝑊𝑊𝑊𝑊𝑊𝑊𝑔𝑔 (𝑔𝑔 = 1, … , 𝐺𝐺 ).

3

3. Outline of the Survey
Our survey is outlined in this section.
(1) Survey period
The survey was conducted during the campaign period of the House of Representatives
election last year because we were interested in how voters evaluated policy options wheneach party made a pledge and competed for policy alternatives in the election. Specifically,
the 49th House of Representatives election was announced on Tuesday, October 19, and thevoting and ballot counting was scheduled on Sunday, October 31. The questionnaire wasdelivered to the monitors on the Friday evening, October 22, and the collection wascompleted on Monday, October 25. In other words, the respondents answered thequestionnaire over the first weekend in the middle of the campaign period. This was likely
when they gained much information, judging from media coverage of the election; five major
newspapers posted their own comparison tables of campaign promises announced by major
parties in their morning editions on Saturday, October 23.
(2) Survey participants
Implementation of the survey was entrusted to a research company. Individuals registeredas monitors with the research company participated if they were interested in thequestionnaire contained in the questionnaire package. The total number of respondents was
set to 1000 each for men and women. The age group compositions of each sex were adjusted
to be equal to their census counterpart. After answering the policy option questions, theparticipants were requested information about their personal attributes. An overview ofparticipants’ personal characteristics is presented in Table 1.
Interestingly, in response to the question asking whether to vote in the coming election,
about 70% of the respondents answered that they “will or have done,” that is, have cast an
early vote. Notably, this is considerably higher than the turnout of 55.93% announced by the
Ministry of Internal Affairs and Communications 2.

2

In general, the percentage of respondents who say they will “vote” in the preliminary polls
conducted by the media exceeds the turnout. For example, according to surveys conducted by NHK
two weeks before the polling date for the five 21st to 25th House of Councilors elections from 2007
to 2019 (Masaki and Aramaki, 2019), the average of the answer of “definitely go to vote (plus castan early vote)” stands at 63%, about 8.5 percentage points higher than the average official outcomes,
54.53%.
4

Table 1 Overview of Participants’ Personal Characteristics

Personal characteristics, N=2,000
Sex

male

femalenumber

1000

1000

share

50.0%

50.0%

Age

18 to 30

31 to 60

number

300

938

762

share

15.0%

46.9%

38.1%

Job

61 and above

self-employed

regular worker

non-regularhousework

student

number

146

640

272

412

75

455

share

7.3%

32.0%

13.6%

20.6%

3.8%

22.8%

widowed or divorced

Marriagemarriednot married

number

650

1126

224

share

32.5%

56.3%

11.2%

no

yes

number880

1120

Children
share

44.0%

individual annual revenue

up to \3 mil.

not working

56.0%\3 to 6 mil. \6 mil. or more no answer

number

1013

473

251

263

share

50.7%

23.7%

12.6%

13.2%

Kishida Administration

supportnot support

number

887

1113

share

44.4%

55.7%

Supporting Political Party

LDP

Komei

CDP (1)

Communist Party

JIP (2)othersnumber

506

46

165

56

149

91

987

share

25.3%

2.3%

8.3%

2.8%

7.5%

4.6%

49.4%

have not decided

will go or have done

will not go

number

1413

199

388

share

70.7%

10.0%

19.4%

VotingA priority in voting

policiescharacters

party

number

765

396

453

187

share

42.5%

22.0%

25.2%

10.4%

volunteer in a year

yes

no

number

1747

253

share

87.4%

12.7%

No party

others

Note 1: CDP = Constitutional Party in Japan
2: JIP = Japan Innovation Party(3) Survey items
Regarding the questions in the survey, presented in Table 2, two or three options (or “levels”
according to conjoint analysis terminology) are provided for each of the seven policy areas(or “attributes”). Six of the seven attributes concern campaign promises announced bypolitical parties. We focus on those that may divide opinions and are likely to attract muchattention in the election. For each attribute, we set up different levels of whether to continue
a conventional policy or to strengthen it in a specified direction.
Participants were asked to answer five questions by choosing one of the three alternatives(Table 3). Two of the three are campaign promises of candidate A and B, and are created byrandomly combining the levels of the seven attributes of Table 2, whereas the last one is for
those who will not choose either.
To obtain WTP, it is necessary to set a variable representing “price” in the case of5marketing, or 𝑥𝑥𝑖𝑖𝑖𝑖 in the previous section, that is, the seventh attribute in our analysis.
However, the appropriateness of the variable is not obvious because it is not always clear at

the time of policy selection how the costs of implementing a particular policy are expected
to be financed. Therefore, we set two types for the seventh attribute: “an increase in tax
burden” and “an increase in budget deficit,” as shown in the last two rows of Table 2. Oneof them was randomly included in the questions posed to our 2000 participants.
Table 2 Outline of the Questionnaire: Attributes and Levels

Policy category (attribute）

Option (level)1) Counter-COVID-19
measures (to reduce humancontacts and reinforce medicalcare supply systems)

a. grant the central
government stronger
authority

b. remain unchanged

2) Measures aiming at ahigher economic growth ratea. encourage economic
growthb. remain unchanged

3) Measures aiming at more
equitable income distribution(by reducing poverty andincome disparities)

a. reduce poverty andincome disparities,
thereby increasing thenumber of middleincome people

b. remain unchanged

4) Measures for next
generations (such as support fora. stronger support for

pregnancy, childbirth, infant care,and education)5) Measures for secure elderly
lives (with pension, medical,
and nursing care)6) Measures for energy
transition (by reducing
dependency on nuclear power plants)

7-1) Increase in tax burden(measured by tax burden in total)

7-2) Increase in fiscal deficits(an increase in new debt）

pregnancy, childbirth,
infant care, and educationb. remain unchanged

a. secure pension
systemsb. secure medical
and nursing carea. aim at zerodependency in the futureb. remain unchanged(restarting to use safe
nuclear power plants)

a. remain unchanged

b. 5 percent increasea. remain unchanged

b. an increase in
deficits (equal to 5
percent of tax burden)

6c. remain
unchangedc. 10 percent
increasec. further increasein deficits (equal to
10 percent of tax
burden)Table 3 Example of Questions Posed to the Participants
Attribute

1)

2)

3)

4)

5)

6)

7-1) or
7-2)

Candidate A

a.

a.

a.

b.

a.

b.

a.

Candidate B

a.

b.

b.

a.

c.

a.

b.

Vote for neither

4. Results(1) Overview
First, we estimate Eq.(6) assuming homogeneous preference among the participants.
Applying the conditional logit model of Eq.(5) to the survey answers revealed the results
shown on the left side of the Reference Table in Appendix 3. The resulting WTP estimateson the right side of the table are also shown in Fig. 1 (1), together with their 95% confidence
intervals.
According to Figure 1, (1) WTP estimates are significantly positive in all but one attribute,or policy categories. However, they vary significantly, depending on the policy categories
and their financing methods. In general, the policies are more highly evaluated if they arefinanced by tax increase rather than by budget deficit or bond issuance. The different
evaluation could be new direct evidence on fiscal illusion.
In Figure 1, (2) policies are arranged in descending order of the WTP estimates. This figure
clarifies different policy priorities owing to different financing methods. For example, tax
financing places the highest priority on policies for next generations, or evaluates it at leastas highly as those for older people, such as pension, medical and nursing care, and for more
equitable income distribution. However, the bond issuance financing method seems toincrease WTP estimates of the latter group of policies.
(2) Differences owing to personal characteristics
Here, we focus on two personal characteristics: age group and voting behavior. First, theparticipants are divided into three age groups: the young (18‒30), the middle-aged (31‒60),
and the old (61 and above). The estimation is conducted using age-group dummies and theirinteraction terms with other explanatory variables, resulting in WTP estimates (Figure 2).

3

We used R programs based on Aizaki et al. (2015), among others.
7

As seen in Figure 2, there are significant differences in WTP estimates among age groups.
Most are significantly positive for the middle-aged and the old, whereas none are
significantly positive for young people, except for policies for the next generation. Moreover,interestingly, these policies for the next generation are more highly valued if financed bytaxes than bonds. A plausible explanation for this may be that tax-finance enables the costs
to be shared by the middle-aged. In addition, the possible confidence of the younger people
in their health may discourage them from evaluating government’s initiatives incountermeasures against COVID-19, as demonstrated by (insignificantly) negative WTP
estimates for such policies, regardless of the financing methods.
Contrastingly, the results for the middle-aged and the old are largely similar. However,there are differences in the WTP estimates of medical and nursing care and countermeasuresagainst COVID-19 for the middle-aged are lower than that of their older counterparts, which
may reflect variations in the health status between the two age groups.
Notably, older people’s WTP for zero-nuclear-power-plant policy is estimated to besignificantly positive. This may indicate altruism toward later generations because such a
policy is unlikely to benefit them. Their altruism may be revealed in their larger WTP for
policies for the next generation than their middle-aged counterparts.
Next, we examine the WTP estimates by voting behavior. Figure 3 shows very different
evaluations among the three categories: those who “will go or have done,” “will not go,” and“not decided.” The WTP estimates of those with the negative answer are (insignificantly)
negative for almost all policy categories. This may be partly because the results reflect theirindifference to policy issues.
Those with an indeterminate attitude show their preferences in a few categories: theyprioritize the policies of the next generation, those aimed at strengthening pensions, andimproving distributions but only with budget deficits. Given their preferences, a rise inturnout may increase spending pressure and favor budget deficit financing owing to more
votes from those with an indeterminate attitude.

8

(%)

(1) Overview(%)(2) Different Priorities

Figure 1

WTP estimates

Notes: 1) ■ and lines represent point estimates and their 95% confidence intervals, respectively.
2) Bars are filled if the estimates are significant at the 5% level, but not otherwise.

9

(%)

(1) 18‒30(%)(2) 31‒60(%)(3) 61 and above

Figure 2 WTP estimates by age group

Note: Bars are filled if the estimates are significant at the 5% level, but not otherwise.

10(1) “Will go to vote or have done”(2) “Will not go”(3) “Have not decided”

Figure 3 WTP estimates by voting behavior

Note: Bars are filled if the estimates are significant at the 5% level, but not otherwise.

11

5. Conclusion
This study examines voters’ preferences for policy options using conjoint analysis.
Specifically, an online survey was conducted during the campaign period of the 49th Houseof Representatives election held in Japan in October 2021. Based on the results, we estimateddiscrete choice models and obtained WTP estimates for policy options.
The contributions of this study are summarized in the following four points. First, basedon the survey results, voters’ preferences for policy options are exemplified as their WTP.
The use of monetary values expressed as WTP enables us to compare preferences of policy
options across participants and policy categories, thereby clarifying voters’ priorities.
Second, voters’ evaluations differ significantly depending on whether the policies are to
be financed by tax increase or fiscal deficit, that is, future tax increase, as well as on personal
characteristics, such as age. These evaluation sensitivities imply possible difficulties to build
consensus in the policy-making process. Third, the WTP differences due to financing
methods are new direct indications of fiscal illusion in the election campaign period.
Fourth, this study demonstrates that voters’ preferences are not always selfish. In particular,
the elderly show their altruistic consideration for the younger generation through their highevaluation of policy options with little benefit for themselves. This may suggest that
excessive “silver democracy” could be controlled by their attitude.

12References
Aizaki, Hideo, Tomoaki Nakatani, and Kazuo Sato (2015) Stated Preference Method Using
R. Boca Raton: Chapman & Hall and RC Press.
Buchanan, James M., and Richard E. Wagner (1977) Democracy in Deficits: The Political
Legacy of Lord Keynes. New York: Academic Press.
Greene, William (2003) Econometric Analysis, 5th ed. New Jersey: Prentice Hall.
Horiuchi, Yusaku, Daniel M. Smith, and Teppei Yamamoto (2018) “Measuring Voters’Multidimensional Policy Preferences with Conjoint Analysis: Application to Japan’s
2014 Election” Political Analysis, 26:190-209.
Masaki, Miki, and Hiroshi Aramaki (2019) “Maki a Guess at the Turnout!” NHK Politics
Magazine July 19, 2019. https://www.nhk.or.jp/politics/articles/feature/19804.html (inJapanese)(Final Access February 2, 2021）.
Rao, Vithala R. (2014) Applied Conjoint Analysis. Heidelberg: Springer.

13Appendix. Estimation Results
Here we will provide estimation results of Eq. (4) using conditional logit models, andresulting WTP estimates based on Eq. (6).
Reference Table. Estimation Results
coeff. Est.

exp(coeff)

coeff.SE.

z value

WTP

conf. int.

K=T％

Const.

-0.172

0.842

0.068

-2.527 *Corona dummy

0.067

1.069

0.040

1.660

0.60

[-0.12, 1.33]

Growth dummy

0.162

1.176

0.041

4.003 **

1.47

[0.76, 2.21]

Dist. dummy

0.266

1.305

0.040

6.601 **

2.41

[1.68, 3.15]

Next Gen. dummy

0.276

1.317

0.041

6.796 **

2.49

[1.78, 3.27]

Pension dummy

0.270

1.310

0.052

5.206 **

2.44

[1.53, 3.39]

M&N care dummy

0.225

1.252

0.052

4.319 **

2.03

[1.11, 2.98]

Energy dummy

0.151

1.163

0.040

3.738 **

1.36

[0.65, 2.11]

Tax increase-0.111

0.895

0.005

-20.691 **LR test608.6 **

K=B
Const.

-0.376

0.686

0.068

-5.570 **Corona dummy

0.141

1.151

0.039

3.626 **％
2.41

[1.09, 3.85]

Growth dummy

0.115

1.122

0.039

2.945 **

1.97

[0.65, 3.41]

Dist. dummy

0.342

1.407

0.039

8.728 **

5.84

[4.36, 7.67]

Next Gen. dummy

0.221

1.248

0.039

5.625 **

3.78

[2.42, 5.35]

Pension dummy

0.328

1.389

0.051

6.491 **

5.62

[3.84, 7.72]

M&N care dummy

0.304

1.356

0.051

6.000 **

5.20

[3.44, 7.27]

Energy dummy

0.141

1.152

0.039

3.629 **

2.42

[1.12, 3.86]

Deficit increase-0.058

0.943

0.005

-11.480 **LR test注：n= 15,000, Q # = 5,000 , *=significant at 5％, **=significant at 1％.

14332.0 **