Silviase/jgov_v1.4_full_ann huggingface dataset:
From the second quarter of 2001, a monitor is surveyed quarterly (March, June, September and December 1 $ ^{st} $ ) about perception for the past 12 months and expectations for the next 12 months in income, consumption, price, and debt $ ^{7} $ . The survey was implemented nine times; the last one was performed on June 1 $ ^{st} $ , 2003. Although some households are dropped after a fiscal year, most of them remain in the next year, which enables us to construct panel data.

Apart from perception for the past year and expectations for the next year, the income questions also include uncertainty about employment, pensions, or social security. The consumption questions contain concrete reasons for increases or decreases in consumption for the past year and the next year. The price questions include the effect of change in monetary policy (i.e. quantitative easing) or exogenous shocks (i.e. the attack on Iraq) on price expectation and their reasons. The debt questions ask the burden of loans out of monthly salary and the effect of deflation on debt burdens.

In addition, we have detailed information on household characteristics such as head of household age, sex, employment status (industry if employed), residential status, family size, annual income level and regions. The basic characteristics of the monitors are summarized in Table 1. The average age of the surveyed households, i.e., respondents or their spouses, is around 50. The average annual income of head of household is around 5 million yen. About 90 percent of the monitors are female.

The most notable merit of this survey is to ask respondents directly not only directions but also changes in price, income, and consumption expectations in figures. As far as we know,
all other consumer surveys in Japan ask only the direction of expectation (i.e. go up, unchanged, go down, uncertain). To obtain the price expectation, as discussed below, those studies need to rely on strong assumptions such as the normality of distribution and symmetry of thresholds to perceive change in directions. Surprisingly, the applicability of those assumptions has never been seriously examined in Japan.

### 4. Basic Facts on Price Expectations Based on Household-level Data

This section aims to estimate household-level price expectations from our unique survey. The exact wordings of the questions related to price in the “Kokumin Seikatsu Monitors” are as follows.

“During the next 12 months, do you think that prices in goods and services you frequently purchase on daily basis will go:

(1) up,

(2) remain the same,

(3) down

(4) uncertain?"

“If you answered ‘up’ or ‘down,’ how much do you think the price level will change during the past 12 months?”

“If you cannot provide an actual number, please select from among the following choices:

(1) less than 20 percent

(2) minus 10 percent to minus 20 percent

(3) minus 5 percent to minus 10 percent
(4) minus 2 percent to minus 5 percent

(5) minus 0 percent to minus 2 percent

(6) plus 0 percent to plus 2 percent

(7) plus 2 percent to plus 5 percent

(8) plus 5 percent to plus 10 percent

(9) plus 10 percent to plus 20 percent

(10) more than 20 percent

Figure 1-1 reports the estimates of average price expectation based on our survey. We have several interesting observations.

First, price expectations range from minus 0.5 percent to zero percent in 2001 and 2002. However, we see a big jump in the first quarter of 2003, followed by decline to almost zero in the second quarter. Those trends are similar when we either measure the expectation in actual figures or estimate it using the medium of multiple choices. Price expectation based on the household survey still remains below or nearly equal to zero, with the exceptions of a one-shot surge in the first quarter of 2003.

Second, current price was minus 1.5 percent to minus 2 percent until the first quarter of 2002. Although the value is still negative, the figures have gradually approached zero. The developments both in actual figures and in the medium of multiple choices are parallel, though the gap is slightly wider than that in price expectations.

Third, perception of current price is always lower than the price expectation. This might reflect that household price expectations always have an inflationary bias.
Fourth, perception of current price follows the development of the CPI well. In other words, responses capture the actual trend in price development quite well.

One might think that changes in the samples cause those trends. To address that issue, we also plot the figures from the households that responded in all nine surveys. Figure 1-2 demonstrates that this is not the case. The trends in plotted variables are very similar to those in Figure 1-1.

Next, we should address the gap in the estimates of price expectation between our survey and the C-P method.

First, we should suspect distribution of price expectations that is assumed to be normal in the C-P method. However, Figure 2 clearly shows that the distribution is not normal. We observe that the response of “unchanged” is dominant and fewer observations are in both tails. This fact implies that the normality assumption in the C-P method is unjustified.

Second, we should also investigate the C-P assumption that price expectations do not deviate from the actual price movements for a long period. The inflationary bias that we found in the averaged household price expectations strongly contradicts the assumption.

Hori and Terai (2003) reports that consumption price expectation series obtained from the C-P method basically mimics the actual CPI movements. Our findings above indicate that this C-P result property is not necessarily realistic. $ ^{8} $ .
### 5. The Determinants of Change in Price Expectation

This section examines what changes price expectations. The goal of this section is to examine whether household price expectations are revised independently of income or past price movements. Concretely, we focus on the effect of exogenous shocks such as implementation and announcement of monetary policy after 2001. As explained in the data section, our data set has a panel structure. Therefore, we are able to examine the formation of price expectations clearly after controlling heterogeneity in households.

Before running regressions to test what determines price expectations, we preview some important factors that are plausibly related with the formation of expectations.

First, price expectations naturally depend on the lagged and current actual price developments. The correlation coefficient is 0.3 between the price expectations and the lagged expectations. This implies the persistence or inertia of price expectations; once deflationary expectations are generated, we observe that those expectations last for a time. The coefficient between price expectations and actual price movements is 0.4. This indicates an adaptive behavior of households in the formation of expectations.

Second, income expectation or current income might affect price expectations. The questions related with current income and income expectation have exactly the same structure as those in the price questions explained above, including the multiple choices. Figure 3-1 describes the obtained series on current income and income expectations. As clearly observed, current income and income expectations are negative and range from minus 1 percent to minus 3 percent. We should note that there is no “jump” in the first
quarter of 2003 when a surge in price expectations is observed. In this sense, we cannot explain the hike in price expectation by income factors $ ^{9} $ .

Third, we should consider the exogenous factors that affect price expectations. Our survey asked the monitors directly about their responses to changes in monetary policy or to exogenous shocks such as the attack on Iraq by the United States and the United Kingdom. We should summarize the facts in the monetary policy first.

The Bank of Japan has performed “quantitative easing “ to increase the money supply to combat deflation since March 2001. This policy includes (1) a change in the operating target for money market operations, (2) CPI guidelines for the duration of the new procedures, (3) an increase in the current-account balance at the Bank of Japan and declines in interest rates, and (4) an increase in outright purchase of long-term government bonds $ ^{10} $ . The policy goal was revised in August to raise the balance of current accounts from around 5 trillion yen to around 6 trillion yen, and to increase the amount of government bonds purchased from the current 400 billion yen per month to 600 billion yen per month $ ^{11} $ . In September 2001, the Bank of Japan revised its goal again to maintain the current –account balance at above 6 trillion yen and reduced the official discount rate from 0.15 to 0.10. $ ^{12} $ . In December 2001, the Bank of Japan additionally increased the goal of the current account balance at around 10 to 15 trillion yen and also increased its government bond purchase to 800 billion yen per month. $ ^{13} $
After 2002, the Bank of Japan began to consider a new policy package to purchase stocks directly from the market in September 2002. Further, in October 2002, the Bank set the operating target at around 15 to 20 trillion yen, and increased its bond purchase to 1.2 trillion yen per month, accompanied the government’s policy package $ ^{14} $ . Moreover, it began to examine the possible purchase of asset-backed securities in April, 2003 $ ^{15} $ .

Our survey asked the monitors their responses to all those monetary policy shocks. Here we focused on the quantitative easing implemented since 2001. This type of monetary policy was brand new in Japan and, if we may say, a kind of regime change. The policy has been expected to contribute to alter the deflationary expectations and has been revised several times. As far as we know, there is no other survey to ask households about their responses to those policies directly.

Figure 4 summarizes household responses to the policy in the 2002 March survey. More than half of the respondents knew about the policy, and the share of those who recognized the policy gradually increased (omitted in Figure 4) $ ^{16} $ . However, out of those who knew about the policy, the share of respondents who revised their price expectations was less than 10 percent. About 70 percent answered that there was no effect on their expectations and a quarter responded that they were not sure of the effect. Further, the survey asked the reasons for the respondents who knew about but did not react to the policy. About 10 percent answered that the magnitude was too small. About a half recognized that the quantitative easing policy cannot affect the economy, and the remaining 30 to 40 percent
did not understand the mechanism of the policy effect. In addition, for those who responded that they were not sure of the effect, 60 percent did not understand the mechanism, and 30-40 percent did not know the extent of the effect.

Our survey also contains information on the respondents' answers to other types of exogenous shocks, such as terrorist attacks or the war in Iraq. Figure 5 reports the results. As regards the terrorist attack on the United States in September 2001, about 10 percent of respondents revised their expectations. About 40 percent responded they did not change their expectations and 20 percent lowered their expectations, probably due to anticipation of the future economy. On the other hand, the Iraq war made more than half of respondents revise their expectations. Naturally, this figure is much larger than the cases of monetary policy change.

Based on those previews on several candidates to explain price expectations, we employ the following specifications to test jointly whether those factors affect price expectations.

$$ \mathbf{P}^{\mathrm{e}}_{\mathrm{it}+1}=\boldsymbol{\alpha}_{0}+\boldsymbol{\alpha}_{1}*P^{e}_{i,t}+\boldsymbol{\alpha}_{2}*P_{i,t}+\boldsymbol{\alpha}_{3}*\mathbf{Y}_{\mathrm{i,t}}+\boldsymbol{\alpha}_{4}*M_{t}+\boldsymbol{\alpha}_{5}*X_{t}+\boldsymbol{\alpha}_{6}*Time+\boldsymbol{\varepsilon}_{i,t+1} $$

where $ P_{it+1}^{e} $ is a household’s price expectation for time $ t+1 $ . $ P_{it} $ is the current actual price change and $ Y_{it} $ is the current actual income change. $ M_{it} $ is a monetary policy shock at time t. As stated above, we focus on the quantitative easing implemented in 2001. $ M_{it} $ takes two forms: a dummy for those who knew each change in monetary policy in 2001 surveyed right after those events (second to fourth quarter in 2001 and first quarter in 2002) and a dummy for who revised their expectations in 2002 due to all four changes in monetary policy implemented in 2001. $ X_{it} $ refers to other exogenous shocks such as the terrorist attack in 2001 and the Iraq war in 2003. $ X_{it} $ takes a form of a dummy variable.
for respondents who revised their expectations $ ^{17} $ . Time contains dummy variables for each quarter to control macroeconomic factors. Although not reported, the squared age of head of households and logarithm of annual head of household income are included. The last is an error term.

We will estimate those regressions with two types of dependent variables. One is to perform the OLS estimation for this specification with price expectations as the dependent variables. The other is to employ the ordered probit estimation by replacing the dependent variable to a dummy variable to allocate 1 for an increase in price expectations, 0 for unchanged, and minus 1 for a decrease in price expectation, relative to the response in the previous quarter.

Table 2-1 reports the results. We notice that the coefficients on current price and lagged price expectations are positive and significant. Those on current price are around 0.3, and those on price expectation are around 0.2. In other words, price expectations have some elements of inertia of expectations and adaptive behaviors. On the contrary, the coefficients on current income are just marginally significant or insignificant and the estimated values are much smaller than those on price factors. Price factors matter for the formation of price expectations but they are not strongly correlated with current income.

Regarding monetary shocks, the dummy variable allocating 1 for those who knew about the quantitative easing policy is not significant. This result is guessed by the previews on household responses to those policies. However, they are effective for respondents who revised their expectations due to the monetary policy. The estimated coefficients are large and imply that those respondents raised their price expectations by 1.6-1.8 percent points.
On the other hand, the effects of terrorist attacks or the war in Iraq have large and significant effects on price expectations. Those shocks raised price expectations by more than one percent, which are comparable with the monetary shock effect for those who revised their expectations.

Table 2-2 reports the results on the ordered probit estimation. The dependent variable is a dummy variable to allocate 1 for an increase in price expectations, 0 for unchanged and minus 1 for a decrease in price expectation, relative to the response in the previous quarter. The explanatory variables are exactly same as those in the OLS estimation, except that we dropped the lagged independent variable.

Table 2-2 basically replicates the results in Table 2-1. The first two regressions do not include any exogenous shocks. Current price movements have still explanatory power. Note that the time dummy for the first quarter of 2003 is large and significant, which is consistent with Figure 1-1 and 1-2. This “jump” cannot be attributed to monetary shocks, since the coefficients are not significant (see third and fourth regressions). If we include the dummy variable for those who knew about the changes in monetary policy and revised their expectations, it is positive and significant. We should notice that the dummy for the first quarter of 2003 is still large and significant. Lastly, if we include the dummy for terrorist attacks and the war in Iraq, coefficients on those dummy variables are positive and significant. The 2003 first quarter dummy is still significant but the magnitude vastly decreased. This implies that the hike in the first quarter of 2003 was caused by those exogenous shocks.

In sum, what we found in this section is as follows. Current price developments and lagged price expectations contribute to form price expectations. Current income does not
have strong explanatory power. Those who knew about the quantitative easing policy did not revise their expectations, but the policy was effective for those who knew about the policy and actually revised their expectations. Other exogenous shocks such as terrorist attacks or the war in Iraq are influential on price expectations. The temporary surge of price expectations in the first quarter of 2003 was attributable to those events.

### 6. The Effect of Deflationary Expectations on Consumption

This section examines how price expectations affect household behavior. Naturally, we focus on the effect of deflationary expectations on household consumption. Deflationary expectations widen a household’s budget constraints and stimulate consumption. On the other hand, if a household anticipates that deflation will continue in the future, it will deter the purchase of luxury goods, which dampens current consumption. Moreover, if a household combines deflationary expectations with anxiety toward the future regarding business cycles or employment, deflationary expectations might discourage current consumptions. Thus, what deflationary expectations affect household consumption depends on empirical studies.

In addition to quantitative evaluation of the effect of deflationary expectations on consumption, we also pay attention to what types of goods are more affected by price expectations. Moreover, we examine the difference in the effect for households with and without any loans to address the possibility that deflationary expectations raise the real debt burden that discourages consumption further.

Figure 6 reports the results from our survey data on consumption. As clearly observed, current and expected consumption was very weak from the fourth quarter of 2001 to the
third quarter of 2002. However, we observe a recovery in both current and expected consumption; they finally reached close to zero or slightly positive in the second quarter of 2003.

In what follows, we estimate consumption functions to examine the effect of price expectation on household consumption. The basic specification is as follows.

First of all, we employ the following specification to

$$ \mathbf{C}_{\mathrm{it}}=\boldsymbol{\alpha}_{0}+\boldsymbol{\alpha}_{1}*Y^{e}{}_{i,t+1}+\boldsymbol{\alpha}_{2}*Y_{i,t}+\boldsymbol{\alpha}_{3}*\mathbf{P}^{\mathrm{e}}{}_{i,t+1}+\boldsymbol{\alpha}_{4}*D_{it}+\boldsymbol{\alpha}_{5}*Risk_{it}+\boldsymbol{\alpha}_{6}*X_{it}+\boldsymbol{\alpha}_{7}*Time+\boldsymbol{\varepsilon}_{i,t} $$

$$ \mathbf{C}^{\mathrm{e}}_{\mathrm{it}+1}=\boldsymbol{\alpha}_{0}+\boldsymbol{\alpha}_{1}*Y^{e}_{i,t+1}+\boldsymbol{\alpha}_{2}*Y_{i,t}+\boldsymbol{\alpha}_{3}*\mathbf{P}^{\mathrm{e}}_{i,t+1}+\boldsymbol{\alpha}_{4}*D_{it}+\boldsymbol{\alpha}_{5}*Risk_{it}+\boldsymbol{\alpha}_{6}*X_{it}+\boldsymbol{\alpha}_{7}*Time+\boldsymbol{\varepsilon}_{i,t+1} $$

where the dependent variable is consumption over the past year $ (C_{it}) $ or that over the next year $ (C_{it+1}^{e}) $ . Those variables are measured both in actual figures and range choices $ ^{18} $ .

The explanatory variables include income over the past year $ (Y_{it}) $ , expected income over the next year $ (Y_{it+1}^{e}) $ , and price expectation over the next year $ (P_{it+1}^{e}) $ . Moreover, they contain debt payment ratio to income or a dummy for a household with any debt $ (D_{it}) $ , risk perceptions $ (Risk_{it}) $ for being unemployed, future jobs and income, and for social security and pensions, respectively. In addition, $ X_{it} $ includes a variety of dummies to control a household's demographics such as change in family size, change in the number of workers in a household, change in tenancy status (renter to owner or vice versa), a squared age of head of household and the logarithm of head of household annual income level.
independent variables also include time dummies for each quarter from the second of 2001 to the second of 2003.

We regress those equations by OLS. Table 3-1 reports the estimation results.

First, if we have consumption over the past year as the dependent variable, the coefficients on income over the year and expected income over the next year are positive and statistically significant. Those are larger for income for the past year. The coefficients on price expectations we should focus on are also positive and significant. In other words, inflationary expectation stimulates current consumption and deflationary expectations discourage consumption. Moreover, the coefficients on price expectations are larger than those on expected income. The coefficients on household debts are not significant. On the contrary, the dummies for risk to be unemployed are negative and significant with larger coefficients.

Second, what we observed for current consumption is basically applicable to the case of expected consumption as the dependent variable. The coefficients on price expectations are always positive and significant. Those on current income and expected income are also positive and significant but the latter is larger. In other words, expected income has a larger effect on expected consumption than current income. The results on household debt and the dummies for the recently unemployed are ambiguous.

Next, to examine what types of goods are more affected by price expectation, we focus on the durables. Our survey asks the following question to respondents.

(Question)
“Do you plan to purchase more durables over the next year relative to the past year?”

(Answer)

(1) plan to buy more

(2) remain the same

(3) plan to buy less

(4) uncertain

We create a new dummy variable to allocate 1 for choice 1, 0 for choice 2 and -1 for choice 3. We replace the dependent variables to the dummy variable. We estimate the regression by the ordered probit estimation.

The left hand side of Table 3-2 reports the results. This basically replicates the results in Table 3-1. The coefficients on current income and expected income are positive and significant. Consciousness of risk to be unemployed or concerns for future income or job clearly discourages durables goods purchase. Price expectation stimulates respondents to buy durable goods, which in turn implies that deflationary expectations discourage consumers to buy durables.

Further, the right hand side of Table 3-3 confirms these findings. The dependent variable is a dummy variable to allocate 1 for those who postpone purchase of durables and 0 for those who do not. The coefficients on price expectations are negative and significant. This means that deflationary expectations deter the timing of durables goods purchases.

In sum, the empirical findings in the section demonstrate deflationary expectations discourage household consumption including durables through postponing the timing of purchase.