ISSN (Print) 0473-453X

Discussion Paper No. 1198

ISSN (Online) 2435-0982

Inflation Expectations and Survey Design

Junichi Kikuchi

December 2022

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

Inﬂation Expectations and Survey Design*
Junichi Kikuchi†

Abstract
We examine whether inﬂation expectations obtained by open- and closed-ended questions lead to different inﬂation expectations through a randomized controlled trial. We
ﬁnd that different questionnaires measure signiﬁcantly different inﬂation expectations, especially in the short term. We further investigate whether inﬂation expectations induce
consumers to change the intertemporal allocation of consumption via the consumption
Euler equation. Our results suggest that actual expenditures are signiﬁcantly responsive
to inﬂation expectations. The EIS of the sample in the closed-ended questionnaire washigher than that of the open-ended questionnaire.

JEL Classiﬁcation:

D84; E31

Keywords:

inﬂation expectations; measurement; forecast data
survey data; survey design* We thank INTAGE for their cooperation regarding the online household survey. We also thank Rui Ota,
Yoshiyuki Nakazono, and participants in the Japanese Economic Association Spring Meeting 2022. Kikuchi
acknowledges ﬁnancial support from JSPS KAKENHI Grant Number 22K20163.
†
Yokohama City University; Institute of Social and Economic Research, Osaka University,
m205162g@yokohama-cu.ac.jp

1 Introduction
Expectations matter. Expectations have an important role in macroeconomics. The decisions of economic agents, such as consumption or savings, depend on their expectations for the future. There is growing interest in these expectations. Central banks andresearchers collect agents’ expectations and study their formation and the relationship between expectations and behavior.
Despite its importance, there is no consensus on how to measure expectations. As wecannot observe expectations directly, we use a proxy variable for expectations. Although
there are several proxy variables for expectations, expectations measured using surveys
are often used in research. The survey design is important for investigating expectations
through questionnaires. Survey questions about expectations come in several forms, suchas choosing from options, open-ended questionnaires (percentage changes and levels),
and responses to the distribution. As expectations are known to affect the macroeconomy,
understanding how to measure them is crucial for macroeconomists and central banks.
This study investigates whether different questionnaires lead to different inﬂation expectations or not. We randomly assigned two types of questionnaires to survey inﬂation
expectations. We examine the difference in inﬂation expectations between the open- andclosed-ended questions. Our analysis focuses on inﬂation expectations and response rates.
We also investigated whether different questionnaires generated different estimates of theelasticity of intertemporal substitution(EIS).
Three main ﬁndings were obtained. First, there is a difference in inﬂation expectations between the open- and closed-ended questions. We ﬁnd that inﬂation expectations
are higher in the open-ended question than in the closed-ended question and that inﬂation expectations increase by 2% if the survey questionnaire changes from a closed-ended
question to an open-ended question. We also ﬁnd that inﬂation expectations in the openended question are more likely to show heterogeneity and that exogenous shocks strongly
inﬂuence the inﬂation expectations collected by the open-ended question. Second, we
ﬁnd that the differences between the two questionnaires are big for short-term inﬂation
expectations, while the differences become smaller for long-term inﬂation expectations.
This suggests that special attention should be paid to the impact of different questionnaires2

on short-term forecasts. Third, the EIS of the sample in the closed-ended questionnaire
was higher than that of the open-ended questionnaire. We interpret the estimated EIS as
approaching zero because the inﬂation expectations obtained by the open-ended questionnaire are subject to greater measurement errors than those obtained by the closed-ended
questionnaire.
Our study is linked to two strands of the literature. First, it is related to studies on how
to measure expectations. Several discussions have been about measuring expectations,such as wording, rounding, and how to answer. Bruine de Bruinn et al. (2012) showsthat question-wording affects responses to surveys. They compare inﬂation expectations
collected by the wordings “prices in general,“inﬂation,or “prices you pay”. Binder(2017) and Ruud et al. (2014) show that rounded inﬂation expectations relate to the uncertainty of respondents’ inﬂation expectations. Armantier et al. (2013, 2016) summarizes
the Survey of Consumer Expectations, which collects households’ inﬂation expectations
by a probability distribution. Bruine de Bruinn et al. (2017) compares survey modes, suchas face-to-face vs. web. They examined their effects on response rates, reported inﬂation
expectations, and disagreement on expectations.
Second, our study is related to studies that estimate EIS. Beginning with Hall (1978),many studies have attempted to estimate EIS. Hall (1988) concludes that the EIS is unlikely to be much above 0.1 and may well be zero, using time-series data of consumption
growth and interest rates. Follow-up studies, however, have yielded mixed results. For
example, the EIS Attanasio and Weber (1995) estimated is 0.56, using the Consumer Expenditure Survey, while Cashin and Unayama (2016) ﬁnds an EIS of 0.21, using data fromthe Japanese Family Income and Expenditure Survey. Gourinchas and Parker (2002) estimate the EIS as being between 0.7 to 2.0, using the U.S. American Consumer Expenditure
Survey, while Gary and Kumar (2009) estimate the EIS at 0.74 using data about 401(k)participation. Therefore, there is no clear consensus on the magnitude of the elasticity ofintertemporal substitution; this arises because of data limitations in relation to inﬂation
expectations, which are usually unobservable and unavailable.
The remainder of this paper is organized as follows. Section 2 describes the survey.
Section 3 shows the difference in inﬂation expectations between the two questionnaires.
Section 4 shows the difference in the EIS between the two types of questionnaires. Section3

5 summarizes the ﬁndings and concludes the paper.

2 Data2.1 Survey of inﬂation expectations
We conducted a quarterly online survey of Japanese households to collect information on
inﬂation expectations from 2015(Q4). Every quarter, approximately 30,000 households
answer questions regarding their outlook for price changes for the next one, three, and ten
years. The respondents were asked to answer the following questions:“What will the levels of CPI be over the next one-, three-, and ten-year periods giventhat the current level of CPI is 10,000? Provide price level ﬁgures over each period,
excluding the impact of consumption tax hikes on price levels.”
The question asks respondents to estimate the average CPI levels that they forecast
over the next 1-, 3-, and 10-year periods. The questionnaire directly measures households’
inﬂation expectations in the short, medium, and long terms.1 In our survey, we prepared
two types of questionnaires. Speciﬁcally, open-ended and closed-ended (multiple-choice)questionnaires are available.

2.1.1 Open-ended question
In the open-ended questionnaire, the respondents answered as in the following example:
When a respondent answers 10,080, 10,600, and 11,000 as their forecasts for price levels
over the following 1-, 3-, and 10-year periods, respectively, their forecasts for annualized
inﬂation rates over the next 1-, 3-, and 10-year periods (or the next 4, 12, and 40 quarters)
are calculated as 0.80%, 1.96%, and 0.96%, respectively.

1

The (annualized) inﬂation forecasts exclude all forecasts of inﬂation above 25 and below −5 percent.

4Years later
Forecast on price levels

1-year3-year10-year10,080 10,600

11,000↓
Annualized inﬂation rates“Spot” inﬂation rates“Forward” inﬂation rates

Years later

1-year3-year10-year1- to 3-year

3- to 10-year

Inﬂation expectations: π e

0.80%

1.96%

0.96%

2.55%

0.53%

2.1.2 Closed-ended question
In a closed-ended questionnaire, the respondents answered, as shown in Table 1. They
chose one option from the 15 options. The appendix presents 3-year and 10-year ahead
inﬂation forecast questionnaires (Table A.1). Because our closed-ended question also
surveys inﬂation expectations in terms of levels, we converted the choices into rates ofchange for our analysis.

2.2 Data about the consumption expenditure
We use panel data (SCI-personal) on consumption expenditure collected by a marketingcompany, Intage. We used the data records of day-to-day shopping information collected
on an ongoing basis from more than 50,000 consumers aged 15―79 all over Japan. The
data captures the proﬁle of these consumers in detail, including aspects such as income,education, and ﬁnancial assets. We can see who bought what, when, where, how many,
and at what prices. These data cover items that households frequently purchase, such as
food (except for fresh food, prepared food, and lunch boxes), beverages, miscellaneous
daily goods, cosmetics, pharmaceutical products, and cigarettes.2 We combine the inﬂation survey with consumption expenditure data from the same respondents and empiricallytest the theoretical relationship between inﬂation expectations and consumer spending.

2

Because our scanner data cover daily necessities, they do not cover housing, utilities, durables, clothing, andservices.

5

3 Differences in inﬂation expectations between openand closed-ended questionsFirst, we ﬁnd that inﬂation expectations are higher for open-ended questions than for
closed-ended ones. Tables 2 and 3 present the summary statistics for inﬂation expectations. It shows that the average inﬂation expectation 1-year ahead is approximately 2%
higher in the open-ended question.
Second, we ﬁnd that the differences between the two questionnaires are big for shortterm inﬂation expectations, while the differences become smaller for long-term inﬂation
expectations. In Table 2, the difference in the average 1-year ahead inﬂation forecast
between the two questionnaires is approximately 2%. In contrast, those of the 3- and10-year ahead inﬂation forecasts are approximately 1% and 0.1%, respectively. Figure
5 shows that kernel density becomes more similar as it becomes a long-term inﬂation
forecast. This suggests that the difference between the two questionnaires decreases as
the forecast horizon increases.
Third, we ﬁnd that inﬂation expectations in open-ended questions are more likely todiffer between household characteristics. It is widely known that households with several categories, such as females and young people, form higher inﬂation expectations(Ehrmann et al., 2017; Jonung, 1981; Kikuchi and Nakazono, 2021). Table 5 shows thathouseholds with certain characteristics form higher (or lower) inﬂation expectations if
they are in the open-ended question. Speciﬁcally, in the open-ended question, females
and young people have higher inﬂation expectations, while highly educated, high-income
households form lower inﬂation expectations.
Fourth, we found that the response rate is approximately 10% higher for closed-ended
questions. We also found that household characteristics explained the response rate. Table
4 lists the response rates of the survey. In the entire sample, the response rate for theclosed-ended question was approximately 50%, whereas that for the open-ended question
was approximately 35%. Table 4 also suggests that some household characteristics have
low response rates, such as females, low education, low income, and young age. Table 6
shows that the response rates for these characteristics are low and signiﬁcant.
Fifth, the inﬂation expectations collected by the open-ended questions are strongly

6

inﬂuenced by exogenous shocks. In January 2016, the Bank introduced a negative interest
rate policy. The introduction of a negative interest rate policy is an exogenous aggregate
shock that is expected to negatively impact inﬂation expectations. Table 7 shows thathousehold inﬂation expectations are lowered across the board by introducing a negativeinterest rate policy. Table 7 also shows that the inﬂation expectations collected by the
open-ended questions fall further.
Sixth, inﬂation expectations increase by 2% when the survey questionnaire changes
from a closed-ended to an open-ended question. In 2016Q2, the survey questionnaire
was standardized using two types of open-ended questions. We use this change to analyze whether inﬂation expectations change when the survey questionnaire changes from aclosed to an open-ended question. Table 8 shows that households’ inﬂation expectations
increase when the questionnaire changes from a closed to an open-ended question.

4 Differences in relationship between inﬂation expectations and spending between open- and closedended questions
4.1 A standard model of consumption
First, we present a theoretical framework to describe the relationship between inﬂation
expectations and consumption growth rate. Suppose the utility function is isoelastic. The
consumer s objective is:max E0

∞
∑

β

t=0

1−γ
−1
t ct

1−γ

,

where β is the discount factor and γ −1 is the elasticity of intertemporal substitution. We
assume that the consumer can borrow and save as much as needed at real interest rate r.
In this setting, the ﬁrst-order conditions lead to the Euler equation:
[(
Et

ct+1
ct

]

)−γ

β(1 + rt ) = 1.

7(1)

Taking the logarithm of both sides of Equation (1), we obtain
Et [∆ ln ct+1 ] = γ −1 (ln β + rt ) .

(2)

Equation (2) shows the optimal consumption path in the complete market.
Using Euler equations in real and nominal terms, we consider how consumption varies
over time, especially under ELB. Because ∆ ln ct+1 = Et ∆ ln ct+1 + εt+1 and the (linearized) Fisher equation indicates that rt = it − Et [πt+1 ], Equation (2) can be writtenas∆ ln ct+1 = γ −1 (it − Et [πt+1 ] + ln β) + εt+1 ,(3)

where it and Et [πt+1 ] denote the nominal interest rate and inﬂation expectations at time t,
respectively. Because it is almost zero under ELB, Equation (3) can be simply written as∆ ln ct+1 = −γ −1 (Et [πt+1 ] − ln β) + εt+1 .

(4)Equation (4) suggests that for consumers who do not face liquidity constraints, the growthrate of consumption depends only on inﬂation expectations and the deep parameters γ −1
and β.

4.2 Estimation results
Following Kikuchi and Nakazono (2020), the data we use allows us to directly estimate
the value of the EIS. Our empirical framework is based on the following equation.
ln(cit+4 /cit ) = α × Eti [πt→t+4 ] + Xγ + εit+4 ,where ln

( ci

t+4
cit

)

(5)

and Eti [πt→t+k ] denote the consumption expenditure growth rates ofindividual i from t to t+4 and the inﬂation forecasts of individual i over the next k quarters
at time t, respectively. A vector X includes control variables, such as time dummies andhousehold demographic variables. We focus on the parameter α in Equation (5). Whenparameter α is negative, an increase in inﬂation expectations is associated with greater
current consumption. This association follows the prediction of the consumption Euler

8equation. In our estimation, EIS(γ −1 ) is obtained by 1 − α. We show the results fromthe two types of speciﬁcations as benchmark results: (1) pooling regression (OLS) and(2) instrumental variables (IV) regression. The IV instrumental variable is 3-year aheadof inﬂation expectations.
Table 9 summarizes the estimation results of the EIS. The top panel of Table 9 presents
the results for the entire sample. This shows that the estimated EIS of the sample, which isthe subject of the open-ended questionnaire, is approximately 1.0, and that of the sample,
which is the subject of the closed-ended questionnaire, is approximately 1.4. The results
showed that the EIS of the sample in the closed-ended questionnaire was higher than thatin the open-ended questionnaire. The result that the EIS of the sample in the closed-ended
questionnaire was higher than that in the open-ended questionnaire was also found in thehigh-income (middle panel of Table 9) and highly educated groups (bottom panel of Table
9). These results suggest that inﬂation expectations collected in an open-ended questionnaire have a larger measurement error than those collected in a closed-ended questionnaire. If a variable has a measurement error, the coefﬁcients of that variable include anattenuation bias. Attenuation bias is a phenomenon in which the coefﬁcient approaches
zero when a variable has a measurement error. We interpret the estimated coefﬁcients asapproaching zero because the inﬂation expectations obtained by the open-ended questionnaire are subject to greater measurement errors than those obtained by the closed-ended
questionnaire.

5 Conclusion
We investigate whether different questionnaires lead to different inﬂation expectations.
We randomly assigned two types of questionnaires to survey inﬂation expectations. We
examine the difference in inﬂation expectations between the open- and closed-ended questions. We also investigated whether different questionnaires generated different estimatesof EIS.
Three main ﬁndings were obtained. First, there is a difference in inﬂation expectations between the open- and closed-ended questions. We ﬁnd that inﬂation expectations

9

are higher in the open-ended question than in the closed-ended question and that inﬂation expectations increase by 2% if the survey questionnaire changes from a closed-ended
question to an open-ended question. We also ﬁnd that inﬂation expectations in the openended question are more likely to show heterogeneity and that exogenous shocks strongly
inﬂuence the inﬂation expectations collected by the open-ended question. Second, we
ﬁnd that the differences between the two questionnaires are big for short-term inﬂation
expectations, while the differences become smaller for long-term inﬂation expectations.
This suggests that special attention should be paid to the impact of different questionnaires
on short-term forecasts. Third, the EIS of the sample in the closed-ended questionnaire
was higher than that of the open-ended questionnaire. We interpret the estimated EIS as
approaching zero because the inﬂation expectations obtained by the open-ended questionnaire are subject to greater measurement errors than those obtained by the closed-ended
questionnaire.

10References
Armantier, Olivier, Wändi Bruine de Bruin, Simon Potter, Giorgio Topa, Wilbert van derKlaauw, and Basit Zafar. (2013). Measuring Inﬂation Expectations. The Annual Review
of Economics, 5, 273–301.
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, and Basit Zafar. (2016). An
Overview of the Survey of Consumer Expectations. Staff Reports, 800, Federal Reserve
Bank of New York, USA.
Attanasio, Orazio P., and Guglielmo Weber. (1995). Is Consumption Growth Consistent
with Intertemporal Optimization? Evidence from the Consumer Expenditure Survey.
Journal of Political Economy, 103(6), pp.1121–1157.
Binder, Carola C. (2017). Measuring Uncertainty Based on Rounding: New Method andApplication to Inﬂation Expectations. Journal of Monetary Economics, 90(C), pp.1–12.
Bruine de Bruin, Wändi, Wilbert van der Klaauw, Giorgio Topa, Julie S. Downs, Baruch
Fischhoff, and Olivier Armantier. (2012). The Effect of Question-Wording on Consumers’ Reported Inﬂation Expectations. Journal of Economic Psychology, 33(4), 749–
757.
Bruine de Bruin, Wändi, Wilbert van der Klaauw, Maarten van Rooij, Federica Teppa, andKlaas de Vos. (2017). Measuring Expectations of Inﬂation: Effects of Survey Mode,
Wording, and Opportunities to Revise. Journal of Economic Psychology, 59, 45–58.
Cashin, David, and Takashi Unayama. (2016). Measuring Intertemporal Substitution in
Consumption: Evidence from a VAT Increase in Japan. The Review of Economics andStatistics, 98(2), 285–297.
Ehrmann, Michael, Camjan Pfajfar, and Emiliano Santoro. (2017). “Consumer’s Attitudes
and Their Inﬂation Expectation.” International Journal of Central Banking 13(1), 225–
259.
Gary, V., Engelhardt, and Anil Kumar. (2009). The Elasticity of Intertemporal Substitution: New Evidence from 401(k) Participation. Economic Letters, 103, 15–17.

11Gourinchas, Pierre-Olivier, and jonathan A. Parker. (2002). Consumption over the Life
Cycle. Econometrica, 70(1), 47–89.
Hall, Robert E. (1978). Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence. Journal of Political Economy, 86(6), 971–987.
Hall, Robert E. (1988). Intertemporal Substitution in Consumption. Journal of Political
Economy, 96(2), 339–357.
Jonung, Lars. (1981). “Perceived and Expected Rates of Inﬂation in Sweden.” American
Economic Review 71(5), 961–968.
Kikuchi, Junichi and Yoshiyuki Nakazono. (2020). “Inﬂation Expectations and Consumer
Spending: Micro-data Evidence.” ESRI Discussion Paper, No.353.
Kikuchi, Junichi and Yoshiyuki Nakazono. (2021). “The Formation of Inﬂation Expectations: Micro-data Evidence from Japan.” Journal of Money, Credit and Banking forthcoming.
Ruud, Paul A., Daniel Schunk, Joachim K. Winter. (2014). Uncertainty Causes Rounding:
An Experimental Study. Experimental Economics, 17, 391–413.

12

0

5

density
10
15

20

25

1-year ahead forecast

-5

0

5

10
Open

15

20

25
(%)

20

25
(%)

20

25
(%)

Close

0

5

density
10
15

20

25

3-year ahead forecast

-5

0

5

10
Open

15
Close

0

5

density
10
15

20

25

10-year ahead forecast

-5

0

5

10
Open

15
Close

Figure 1: Kernel density estimates of inﬂation expectations for 1-year (top panel), 3-year(middle panel), and 10-year (bottom panel) horizons. We use an Epanechnikov kernel as akernel function. The bandwidth of kernel is set to be 0.01.
13

Table 1: Questionnaire of closed-ended question (1-year ahead inﬂation forecast)
1-year ahead inﬂation expectations

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Questionnaire

Inﬂation expectations

Less than 10,050
More than 10,050 and less than 10,150
More than 10,150 and less than 10,250
More than 10,250 and less than 10,350
More than 10,350 and less than 10,450
More than 10,450 and less than 10,550
More than 10,550
More than 9,850
More than 9,750 and less than 9,850
More than 9,650 and less than 9,750
More than 9,550 and less than 9,650
More than 9,450 and less than 9,550
More than 9,350 and less than 9,450
Less than 9,350
I have no idea.

0%
1%
2%
3%
4%
5%
6%
−1%
−2%
−3%
−4%
−5%
−6%
−7%

14

Table 2: Basic statistic (%)
Open

Close

Mean Median

S.D.

Obs.

Mean

MedianS.D.

Obs.

1-year3-year10-year

3.78
2.95
1.93

1.00
1.64
0.96

5.16
3.74
2.65

14,76814,864
14,840

1.69
1.83
1.81

1.00
1.96
1.84

1.71
1.65
1.53

18,12020,27819,913Male
1-year3-year10-year

3.22
2.51
1.65

1.00
1.64
0.96

4.73
3.39
2.43

7,238
7,355
7,356

1.67
1.78
1.71

1.00
1.96
1.84

1.82
1.77
1.62

8,282
9,486
9,524

Female1-year3-year10-year

4.32
3.39
2.21

1.00
2.28
1.41

5.49
4.00
2.83

7,440
7,509
7,484

1.71
1.87
1.89

1.00
1.96
1.84

1.62
1.54
1.43

9,838
10,792
10,389Higher education
1-year3-year10-year

3.39
2.68
1.76

1.00
1.64
0.96

4.86
3.51
2.45

7,394
7,473
7,440

1.64
1.79
1.78

1.00
1.96
1.84

1.69
1.63
1.50

8,207
9,341
9,296

Lower education
1-year3-year10-year

4.11
3.18
2.10

1.00
1.64
1.14

5.39
3.91
2.79

3,156
3,199
3,209

1.75
1.88
1.80

1.00
1.96
1.84

1.73
1.68
1.58

4,422
4,868
4,655

High income
1-year3-year10-year

3.27
2.53
1.70

1.00
1.64
0.96

4.65
3.24
2.26

2,950
2,978
2,967

1.62
1.79
1.75

1.00
1.96
1.84

1.69
1.64
1.48

3,245
3,717
3,729

Low income
1-year3-year10-year

4.24
3.33
2.25

1.00
1.64
1.41

5.51
4.17
3.17

3,748
3,794
3,793

1.76
1.88
1.83

1.00
1.96
1.84

1.78
1.72
1.65

5,200
5,759
5,540

All

Note: Higher education, lower education, high income, and low income indicates fouryear college graduate or above, high school graduate or below, households’ annual income
9 million yen and above and households’ annual income below 4 million yen, respectively.
15

Table 3: Basic statistics (%)
Open

Close

Mean Median

S.D.

Obs.

Mean

Median

S.D.

Obs.

20s
1-year3-year10-year

4.25
3.58
2.37

1.00
1.64
1.41

5.58
4.36
3.48

1,928
1,971
2,019

1.88
1.94
1.87

2.00
1.96
1.84

1.83
1.80
1.64

2,386
2,745
2,759

30s
1-year3-year10-year

3.66
2.97
1.99

1.00
1.64
0.96

5.14
3.85
2.8

3,332
3,406
3,433

1.67
1.81
1.78

1.00
1.96
1.84

1.72
1.63
1.52

3,737
4,330
4,428

40s
1-year3-year10-year

3.69
2.87
1.85

1.00
1.64
0.96

5.06
3.58
2.35

4,065
4,108
4,119

1.66
1.80
1.77

1.00
1.96
1.84

1.70
1.65
1.51

4,652
5,216
5,188

50s
1-year3-year10-year

3.76
2.82
1.79

1.00
1.64
0.96

5.14
3.53
2.35

3,056
3,078
3,056

1.69
1.83
1.83

1.00
1.96
1.84

1.71
1.63
1.51

4,003
4,375
4,203

60s and over
1-year3-year10-year

2.67
2.26
1.78

1.00
1.96
1.84

3.88
2.69
1.98

5,558
5,773
5,479

2.32
2.10
1.82

1.00
1.96
1.84

3.32
2.38
1.88

5,058
5,329
5,000

16

Table 4: Response rate
Open

Close

Open CloseAll

1-year3-year10-year

36%
36%
36%

44%
49%
48%

20s

1-year3-year10-year

28%
29%
29%

35%
40%
39%

Male

1-year3-year10-year

42%
43%
43%

48%
55%
55%

30s

1-year3-year10-year

35%
36%
36%

39%
45%
45%

Female1-year3-year10-year

32%
32%
32%

41%
45%
43%

40s

1-year3-year10-year

39%
39%
39%

44%
49%
48%

Higher education

1-year3-year10-year

44%
44%
44%

49%
56%
55%

50s

1-year3-year10-year

38%
38%
38%

49%
53%
51%

Lower education

1-year3-year10-year

30%
30%
30%

42%
45%
43%

60s and over 1-year
3-year10-year

46%
48%
45%

48%
51%
48%

High income

1-year3-year10-year

44%
44%
44%

48%
54%
54%

Low income

1-year3-year10-year

30%
31%
30%

42%
46%
44%

Note: Higher education, lower education, high income, and low income indicates fouryear college graduate or above, high school graduate or below, households’ annual income 9 million yen and above and households’ annual income below 4 million yen,respectively.

17

Table 5: Inﬂation expectations and households’ characteristics
1-yearDopen
Df emale
Df emale × Dopen
Dunder29
Dunder29 × Dopen
Dhighly−educatedDhighly−educated × Dopen
Dhigh−income
Dhigh−income × Dopen

3-year10-year1.950***
0.978***
0.040(0.101)(0.074)(0.056)0.001
0.062**
0.171***(0.027)(0.024)(0.023)0.942***
0.709***
0.301***(0.092)(0.068)(0.051)0.207***
0.112***
0.048(0.040)(0.037)(0.033)0.160
0.373***
0.373***(0.141)(0.109)(0.087)−0.074*** −0.049**−0.005(0.027)(0.024)(0.023)−0.395*** −0.234*** −0.191***(0.093)(0.068)(0.051)−0.061*−0.035−0.063**(0.033)(0.030)(0.028)−0.396*** −0.350*** −0.150***(0.105)(0.076)(0.056)

Constant

1.693***(0.030)1.794***(0.027)1.716***(0.026)

Observations

32,79835,142

34,753

Note: Standard errors in parentheses are clustered at individuallevels, and ***, **, and * indicate 1%, 5%, and 10% signiﬁcance, respectively.

18

Table 6: Response rate and households’ characteristics
1-yearDopen
Df emale
Df emale × Dopen
Dunder29
Dunder29 × Dopen
Dhighly−educatedDhighly−educated × Dopen
Dhigh−income
Dhigh−income × Dopen

3-year10-year−9.106*** −14.65*** −13.85***(0.792)(0.792)(0.793)−4.817*** −7.161*** −8.440***(0.509)(0.510)(0.509)−1.888***
0.050
1.110
(0.710)(0.711)(0.711)−9.560*** −8.962*** −7.386***(0.630)(0.643)(0.641)2.318***
1.984**
1.349(0.868)(0.879)(0.880)6.308***
7.968***
8.513***(0.516)(0.517)(0.516)
4.168***
2.432***
1.626**(0.720)(0.721)(0.720)3.137***
5.132***
6.365***(0.663)(0.660)(0.659)4.142***
2.136**
0.908(0.933)(0.931)(0.931)

Constant

48.59***(0.568)54.98***(0.567)54.43***(0.566)

Observations

82,59282,59282,592

Note: Standard errors in parentheses are clustered at individuallevels, and ***, **, and * indicate 1%, 5%, and 10% signiﬁcance, respectively.

19

Table 7: Impact of negative interest rate policyi
Eti [πt→t+4 ] − Et−1
[πt−1→t+3 ] = α + β × Diopen + εi

1-year3-year10-yearDiopen−0.237*** −0.194***(0.091)(0.063)−0.058(0.047)α−0.215*** −0.239***(0.028)(0.024)−0.208***(0.023)Observations

9,151

10,303

10,123

Note: Standard errors in parentheses are clustered at individual levels, and ***, **, and * indicate 1%, 5%, and
10% signiﬁcance, respectively.

Table 8: Impact of changes in the questionnaireiEti [πt→t+4 ] − Et−1
[πt−1→t+3 ] = α + β × Diclose + εi

1-year3-year10-year

Diclose2.182***(0.109)1.098***(0.073)0.079(0.051)α−0.671*** −0.456***(0.080)(0.053)Observations

7,693

8,336

−0.191***(0.036)
8,230

Note: Standard errors in parentheses are clustered at individual levels, and ***, **, and * indicate 1%, 5%, and
10% signiﬁcance, respectively.

20

Table 9: Estimating the EISln(cit+4 /cit ) = α × Eti [πt→t+4 ] + Xγ + εit+4
Open

All

Close

OLS

IV

OLS

IV

α

−0.094(0.066)−0.088(0.067)−0.051(0.083)−0.043(0.084)−0.344*(0.180)−0.349*(0.181)−0.463*(0.265)−0.467*(0.265)

Implied EIS

1.094

1.088

1.051

1.043

1.344

1.349

1.463

1.467

Constant−0.004(0.005)−0.002(0.014)−0.006(0.006)−0.005(0.014)−0.004(0.005)0.005(0.013)−0.003(0.006)0.003(0.014)ControlTime dummy

✓

✓
✓

✓

✓
✓

✓

✓
✓

✓

✓
✓

Observations

10,390

10,39010,214

10,214

12,717

12,717

11,555

11,555OpenHigh income

Close

OLS

IV

OLS

IV

α

−0.164(0.175)-0.132(0.178)−0.069(0.204)−0.022(0.208)−0.784*(0.454)−0.763*(0.457)−0.597(0.704)−0.561(0.705)

Implied EIS

1.164

1.132

1.069

1.022

1.784

1.763

1.597

1.561

Constant

0.005(0.012)−0.006(0.036)0.001(0.012)−0.010(0.037)−0.002(0.012)−0.053(0.033)0.001(0.015)−0.041(0.035)ControlTime dummy

✓

✓
✓

✓

✓
✓

✓

✓
✓

✓

✓
✓

Observations

2,148

2,148

2,122

2,122

2,350

2,350

2,134

2,134

Open

Highly educated

Close

OLS

IV

OLS

IV

α

−0.108(0.102)−0.120(0.103)−0.137(0.124)−0.161(0.125)−0.485(0.296)−0.494*(0.297)−0.902**(0.443)−0.911**(0.444)

Implied EIS

1.108

1.12

1.137

1.161

1.485

1.494

1.902

1.911

Constant−0.006(0.008)−0.027(0.020)−0.005(0.008)−0.027(0.021)

0.004(0.008)0.009(0.019)0.009(0.010)0.011(0.021)

ControlTime dummy

✓

✓
✓

✓

✓
✓

✓

✓
✓

✓

✓
✓

Observations

5,221

5,221

5,143

5,143

5,788

5,788

5,279

5,279

Note: Standard errors in parentheses are clustered at individual levels, and ***, **, and * indicate 1%, 5%, and 10% signiﬁcance, respectively. The instrumental variable in IV is 3-year ahead inﬂation expectations. The high-income and highly
educated groups are the subsamples of consumers with more than 9 million yen a year and those with a bachelor’s degree orhigher, respectively.

21

Table A.1: Questionnaire of closed-ended question (3- and 10-year ahead inﬂation forecast)
3-year ahead inﬂation expectations
Questionnaire
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Inﬂation expectations[UP]
Less than 10,150[UP]
More than 10,150 and less than 10,450[UP]
More than 10,450 and less than 10,750[UP]
More than 10,750 and less than 11,050[UP]
More than 11,050 and less than 11,350[UP]
More than 11,350 and less than 11,650[UP]
More than 11,650[DOWN] More than 9,550[DOWN] More than 9,250 and less than 9,550[DOWN] More than 8,950 and less than 9,250[DOWN] More than 8,650 and less than 8,950[DOWN] More than 8,350 and less than 8,650[DOWN] More than 8,050 and less than 8,350[DOWN] Less than 8,050
I have no idea.

0%
1%
2%
3%
4%
5%
6%
−1%
−2%
−3%
−4%
−5%
−6%
−7%

10-year ahead inﬂation expectations
Questionnaire
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Inﬂation expectations[UP]
Less than 10,150[UP]
More than 10,150 and less than 10,450[UP]
More than 10,450 and less than 10,750[UP]
More than 10,750 and less than 11,050[UP]
More than 11,050 and less than 11,350[UP]
More than 11,350 and less than 11,650[UP]
More than 11,650[DOWN] More than 9,550[DOWN] More than 9,250 and less than 9,550[DOWN] More than 8,950 and less than 9,250[DOWN] More than 8,650 and less than 8,950[DOWN] More than 8,350 and less than 8,650[DOWN] More than 8,050 and less than 8,350[DOWN] Less than 8,050
I have no idea.
22

0%
1%
2%
3%
4%
5%
6%
−1%
−2%
−3%
−4%
−5%
−6%
−7%