Silviase/jgov_v1.4_full_ann huggingface dataset:
income and expenditures for individual households as well as on the characteristics of these households and the jobs of household heads. The monthly expenditure data are compiled from a diary collected twice a month, meaning that our dataset likely is more reliable than most other datasets, which are typically based on retrospective questionnaires. $ ^{7} $

To ensure that our findings in this paper do not depend on sample selection, we employed two different samples in the empirical analysis below, that is, a "broadly-defined sample" and a "narrowly-defined sample". To construct the former, we dropped observations for households with a self-employed (or a jobless) household head since we do not have monthly income information for these households. After dropping households for which monthly income information is not available, our analysis is restricted to wage earner households, which account for roughly half of all observations in the FIES. We further confine our sample to households where the head of household is an office, or white-collar, worker. Using this broadly-defined sample, we will examine whether the seasonal expenditure pattern of public employee households changed after the abolition of the March bonus. To confirm the validity of the findings, we will also examine whether the observed changes in the seasonal pattern differ between public sector employee households (the "public sector group") and private sector employee households (the "private sector group"), using households whose head works for a large private company with more than 1,000 employees as our control group.

Although we focus on white-collar households so as to examine households of
roughly comparable attributes, occupational choice is not entirely random, and there remains some heterogeneity between the two groups (other than the timing of bonus receipts). Moreover, the two groups in the broadly-defined sample contain households that receive bonuses in months other than the regular bonus months, i.e., June (or July) and December in the case of private sector employees, and June, December, and – until FY2002 – March in the case of public sector employees, or that receive no bonuses at all. Therefore, to make the two groups homogeneous except for the timing of bonus receipts, we additionally construct the narrowly-defined sample. We do so by further confining our sample to male sole earner households and excluding households that reported no bonus receipts in the regular bonus months, i.e., June (or July $ ^{8} $ ), December, and March for public employee households until FY2002, and June (or July) and December for public and private sector employee households from FY2003 (either because they received no bonuses or failed to enter them in the diary). Moreover, we exclude households that report bonus receipts in months other than the regular bonus months. The number of observations in the narrowly-defined sample is about 40 percent of that in the broadly-defined sample.

Table 2 shows the ratio of bonus receipts to regular monthly salaries (both for all households, i.e., including those not receiving a bonus, and for those receiving a bonus) as well as the share of bonus recipients both for the broadly-defined sample (Panel (a)) and the narrowly-defined sample (Panel (b)). Looking at the figures for the broadly-defined sample, the March bonus/salary ratio for the public sector group in the pre-reform period (from July 1997 to June 2002) was 0.28 (for all households) and the
share of bonus recipients was 63 percent (the average bonus/monthly salary ratio for households receiving a bonus was 0.45). On the other hand, the ratio for the private sector group was 0.03 and the share 5 percent. Reflecting the bonus reform, the bonus/salary ratio for the public sector group in the post-reform period (from July 2003 to June 2008) falls to 0.01 months and the share of bonus recipients to 3 percent. Looking at the narrowly-defined sample (Panel (b)), we find that the abolition of the March bonus for public sector employees means that the bonus/salary ratio fell from 0.45 to zero.

Turning to the bonuses in other regular bonus months, roughly 75–85 percent of public sector employee households report that they receive a bonus in summer and in winter, while the share among private sector employee households is less than 70 percent. However, looking at the bonus/salary ratio for private sector employee households that do receive a bonus, this is more or less comparable to that for public sector employee households. When we compare the pre- and post-reform periods, the bonus/salary ratios and the bonus recipient shares appear to have decreased in all regular bonus months, probably reflecting the slowdown of Japanese economy. However, it goes without saying that the fall in bonus receipts (from the pre-reform to the post-reform period) is most remarkable for the March bonus for the public sector group. Finally, Panel (b) for the narrowly-defined sample confirms that the bonus/salary ratio and the bonus recipient share are broadly similar for the two groups except for the March bonus payments to the public sector group until FY2002.

The sample statistics of our dataset are reported in Table 3. The total number of observations from July 1997 to June 2008 is 258,328 (for 48,407 households) for the broadly-defined sample and 97,155 (for 19,285 households) for the narrowly-defined
sample. Roughly two-fifths of the total observations are for public employee households, while the remaining three-fifths are for private sector employee households. Since we exclude observations for the gradual phase-out period between July 2002 and June 2003, the total sample is split into a pre-reform sample of 123,685 observations (23,982 households) and a post-reform sample of 109,426 observations (21,389 households).

Shown in the table are the sample statistics for the observation period as a whole as well as the two sub-periods (pre-reform and post-reform), for public and private sector households together and separately, and for the broadly- and the narrowly-defined sample. The results for the sample period as a whole and for the sub-periods all paint a similar picture. That is, average household income and expenditures are somewhat larger for the public sector than for the private sector group in the broadly-defined sample, but look very similar for the two groups in the narrowly-defined sample. In addition, in each sample, the two groups also look similar in terms of their demographic characteristics such as age of the household head, number of family members, and number of workers in the household. Therefore, the sample statistics suggest that households in the public and private sector groups are broadly similar (except for the bonus payment in March before its abolition), especially when the two groups are compared using the narrowly-defined sample.

### 4. Changes in patterns of monthly expenditure after the bonus reform

In this section, using monthly observations from the FIES, we examine whether there are any changes in the pattern of public employees' monthly income and expenditure from the pre-reform period with the March bonus to the post-reform period without it. In order to statistically capture changes after the abolition of the March bonus, we run
regressions with the following specification:

$$ \begin{aligned}\ln(X_{i,t}/X_{i,t-1})=&\sum_{m=1}^{12}a_{m}\times MDummy(m)\\&+\sum_{m=1}^{12}b_{m}\times MDummy(m)\times AFTERDUMMY\\&+\beta Z_{t}+\varepsilon_{i,t}\end{aligned} $$

where $ X_{it} = Y_{it} $ or $ C_{it} $ . The dependent variable is monthly changes in the logarithm of household income ( $ Y_{it} $ ) or household expenditure ( $ C_{it} $ ). We use total consumption expenditure as well as its subcategories for $ C_{it} $ . Both variables are converted to a daily basis using the number of days in each month and deflated by the consumer price index for each category. Independent variables consist of twelve month dummies, $ ^{9} $ $ MDummy(m) $ , to capture the monthly income and expenditure patterns in the pre-reform period (July 1997 to June 2002) and interaction terms between the month dummies and a dummy variable for the post-reform period, AFTERDUMMY, which takes 1 for months from July 2003 to June 2008 and zero otherwise. If there was a change in monthly income/expenditure patterns after the abolition of the March bonus, the coefficients on the interaction terms should be significant. In addition, we include the nominal interest rate and relative price changes as control variables ( $ Z_{t} $ ), while $ \varepsilon_{i,t} $ is assumed to be a well-behaved error term. We employ OLS to obtain the coefficient estimates. $ ^{10} $

The results of the estimation are shown in Table 4. The coefficients on the monthly dummies $ (a_{m}; m=1, 2, \ldots, 12) $ correspond to the pattern of monthly
income/expenditure in the pre-reform period. The pattern of monthly income/expenditure in the post-reform period is derived as the sum of the month dummy coefficients and the interaction term coefficients $ (a_{m} + b_{m}; m = 1, 2, \ldots, 12) $ . The panels in Figure 1, which are drawn from the coefficients reported in Table 4, illustrate the household income patterns for public sector employee households. Both Figure 1.1-(a) based on the broadly-defined sample and Figure 1.1-(b) based on the narrowly-defined sample clearly illustrate that the change in the pattern of the monthly wage of the household head results mainly from the abolition of the March bonus. While we also notice a subtle smoothing of monthly wage payments from the pre- to the post-reform period, probably due to cuts in bonus amounts not only in March but also in other regular bonus months, the changes in other months look very small when compared with the striking difference in the month-on-month changes in March and April.

Staying with public sector employees, Figures 1.2-(a) and 1.2-(b) show the pattern of households' disposable income over the year. The figures indicate that households' monthly disposable income is largely determined by the wage of the household head. The results in Table 4-(a), which are calculated using the broadly-defined sample, suggest that the monthly disposable income of public sector employee households used to increase by 10 percent in March and decrease by 18 percent in April in the pre-reform period. In contrast, in the post-reform period, the pattern of monthly disposable income appears to have reversed, as the coefficients on the interaction terms more than offset the pre-reform coefficients. The smoothing in disposable income in spring comes out more clearly in the narrowly-defined sample (see Figure 1.2-(b) and Table 4-(b)). While disposable income used to increase on the
previous month by 28 percent in March and decrease by 38 percent in April in the pre-reform period, this swing more or less disappeared in the post-reform period, with disposable income actually decreasing by 13 percent in March and increasing by 3 percent in April. In other words, the abolition of the March bonus appears to have eliminated the spring income swing for public employees.

Having confirmed that there was a clear change in the pattern of monthly disposable income for public employees, we now turn to their expenditure patterns. What matters for us is whether there were any changes in the pattern of monthly expenditure from the pre-reform period to the post-reform period, and, if any, whether the changes in the monthly expenditure pattern are associated with those in income. Therefore, what we focus on is the coefficients on the interaction terms in the expenditure regressions. If the pattern of monthly household expenditure is excessively sensitive (relative to the prediction of the LC/PIH) and is affected by the pattern of monthly income, we would expect March and April expenditures to be higher in the pre-reform period than in the post-reform period (with April expenditures likely affected by the fact that the spring bonus was paid in the middle of the month, on March 15). That is, in that case, the coefficient $ (b_{3}) $ on the interaction term of the March dummy and the post-reform dummy should be significantly negative, and that $ (b_{5}) $ on the May dummy and the post-reform dummy should be significantly positive. $ ^{11} $

The results, reported in column (3) of Table 4 and illustrated in Figure 2, look generally consistent with this excess sensitivity argument. The monthly pattern of consumption expenditure in the post-reform period looks different from that in the pre-reform period, and the difference is statistically significant at the 1 percent level (as
indicated by the F-statistics for the null hypothesis that the coefficients on the interaction terms $ (b_{\mathrm{m}}\mathrm{s}) $ are all zero). In addition, the coefficient on the March interaction term is negative and statistically significant, suggesting an association between income and consumption expenditure. The positive coefficient on the May interaction term, on the other hand, is not statistically significant in the regression based on the narrowly-defined sample. However, it turns significant in the regression based on the narrowly-defined sample. Panel (b) of Figure 2 shows that in the regression based on the narrowly-defined sample, monthly household expenditure, which in the pre-reform period used to increase by 11 percent in March and decrease by 7 percent in May, in the post-reform period increases by only 3 percent in March and decreases by the same amount in May.

Although the observed response of household expenditure to the anticipated income change may at first glance appear to be inconsistent with the LC/PIH, what the hypothesis really predicts is not a smoothing of expenditure but a smoothing of consumption. Unfortunately, we cannot observe household consumption directly, since what is actually recorded in the FIES diaries is households' expenditure. Since consumption expenditure includes items of different durability, the observed association between income and expenditure may have resulted from expenditure on durable goods, for which it is reasonable to assume that the lag between expenditure and actual consumption is larger than for nondurable goods.

To examine whether this is the case, we examine expenditure patterns by subcategory. The panels in Figure 3, which are drawn based on the coefficients reported in columns (4)–(7) of Table 4, illustrate the change in the pattern of monthly expenditure on four expenditure subcategories, i.e., services, nondurables,
semi-durables, and durables, following the abolition of the March bonus. The F-tests show that the null hypothesis that the coefficients on the month dummies are the same before and after the March bonus abolition (or that the coefficients on the interaction terms are zero for all months) is rejected at the 1 percent significance level for almost all of the subcategory regressions (except the regression for durables in the narrowly-defined sample), again suggesting some deviation from the LC/PIH. However, there seem to be clear differences in the extent to which different expenditure subcategories are affected: while expenditure on services, semi-durables, and durables decreased significantly in March after the bonus reform (Figures 3.1, 3.3, and 3.4), the decrease in March in expenditure nondurables (Figure 3.2) is hardly discernible, suggesting that the pattern of nondurables expenditure was not greatly affected by the abolition of the March bonus.

To sum up, the abolition of the March bonus for public employees appears to have noticeably changed not only the pattern of monthly income but also that of monthly expenditure, especially around March. At first glance, this observed association between an anticipated change in the pattern of income and actual expenditure looks inconsistent with the LC/PIH. However, since the size of the bonus reform-driven expenditure changes is very different for expenditure subcategories of different durability, suggesting that the observed expenditure responses to the anticipated change in the timing of income flows result from a lag between expenditure and actual consumption, this leaves open the possibility that although the LC/PIH does not appear to hold for expenditure it may still hold for consumption.
### 5. Including private sector employee households as a control group

The results in the previous section show that the monthly expenditure pattern of public employee households changed in and after FY2003. Although the abolition of the March bonus is the most obvious candidate to account for the change in expenditure patterns, we have not yet excluded other possible factors that might have affected expenditure patterns. Returning to Figure 2, it can be seen that the post-reform expenditure pattern looks smoother not only in March but also in other months, most notably in July-August. This overall smoothing could suggest that factors other than the abolition of the March bonus may have been at play. To examine this issue, we use the sample of private sector employees as a control group. As already discussed in Section 3, the attributes of white-collar workers in the public sector and in large private sector firms are not very different, or even look homogeneous in the narrowly-defined sample, except for the timing of bonus receipts. Therefore, if something correlated with the abolition of the March bonus is responsible for the changes in expenditure patterns, inclusion of the control group in our regressions should alter the coefficients on the interaction terms in which we are interested.

Concretely, we extend our dataset to include the private sector group and run regressions of the following specification:

$$ \begin{aligned}\ln(X_{i,t}/X_{i,t-1_{.}})&=\sum_{m=1}^{12}a_{m}\times MDummy(m)\\&+\sum_{m=1}^{12}b_{m}\times MDummy(m)\times PUBLIC\\&\quad+\sum_{m=1}^{12}c_{m}\times MDummy(m)\times AFTER DUMMY\\&\quad+\sum_{m=1}^{12}d_{m}\times MDummy(m)\times PUBLIC\times AFTERDUMMY\\&\quad+\beta Z_{t}+\varepsilon_{i,t}\end{aligned} $$
where $ X_{i,t}=Y_{i,t}orC_{i,t} $ .^{12} Other than PUBLIC, the variables are the same as in equation (1). PUBLIC is a dummy variable for the public sector group to distinguish it from the private sector group. $ a_{m}+b_{m} $ captures the pattern of public employees' monthly income/expenditure in the pre-reform period (July 1997–June 2002), while $ a_{m}+b_{m}+c_{m}+d_{m} $ captures that in the post-reform period (July 2003–June 2008). In this new specification, we can decompose the fall (rise) in March (May) expenditure in the post-reform period into the effect of the abolition of the March bonus, i.e., $ d_{3}(d_{5}) $ , and other factors which are common to the public and private sector groups, i.e., $ c_{3}(c_{5}) $ .

The panels in Figure 4, which are based on the estimates reported in Table 5, illustrate the monthly income patterns of the private and the public sector group. The panels show that noticeable changes in the monthly income pattern took place (in spring) only for the public group. The monthly income patterns for the private sector group in the pre-reform and the post-reform period are largely indistinguishable, although the bonus amounts in summer and winter were slightly smaller in the post-reform period, while the spring income patterns (from February to May) for the public group have become very similar to those of the private group after the bonus reform. $ ^{13} $

Our main interest is, of course, to see whether a similar transformation in the patterns is observed for the expenditure variables. If the monthly expenditure pattern of the public sector group stands out from the remaining patterns only in the pre-reform period, and if the remaining patterns – those of the public sector group in the
post-reform period and of the private sector group in both periods – resemble each other, this would indicate that the change in the monthly expenditure pattern resulted from the abolition of the March bonus. This conclusion would be further supported if we find a negative/positive coefficient $ (d_{3}/d_{5}) $ on the interaction terms among the March/May dummy, the post-reform dummy, and the public sector employee dummy in the expenditure regressions.

The results of the expenditure regressions (with the control group) are shown in Figure 5 and generally support the interpretation that the change in the monthly expenditure pattern resulted from the abolition of the March bonus. The monthly expenditure patterns do not look very different from each other with the notable exception of the pre-reform pattern for the public sector group. Tests of the joint hypothesis whether the expenditure patterns in spring (or from February to May) are identical between the private and the public sector group suggest that the patterns become statistically indistinguishable in the post-reform period, while they were significantly different in the pre-reform period (see the F-tests in column (3) in Table 5-(b) for the narrowly-defined sample).

While minor changes from the pre-reform to the post-reform period can also be noticed for the private sector group, especially for June and December, similar changes in the two regular bonus months (or overall smoothing) can be observed for the public group, suggesting that these changes probably result from a general decrease in bonus payments in the post-reform period (as already reported in Section 2), i.e., a factor common to the public and the private sector group. Indeed, after the inclusion of the private group in our sample, the statistical significance of the coefficients on the interaction terms of interest (the ds) declined considerably, while the sign on the March
(May) interaction term continues to be negative (positive), which is consistent with the excessively sensitive consumption argument.

Further examination of the expenditure response for each of the four expenditure subcategories (Figure 6 and columns (4)–(7) of Table 5) sheds more light on the results obtained so far. The effects of the abolition of the March bonus on expenditure on services and nondurables look very small (columns (4) and (5)): The absolute value of the coefficients is small and most are statistically insignificant. The only exception is the significantly positive coefficient on the May interaction term ( $ d_{5} $ ) in the service regression using the narrowly-defined sample (column (4) in Table 5-(b)) suggesting that the abolition of the March bonus may have had some effect on the expenditure on services. On the other hand, the absolute values of the coefficients for the other two expenditure components, semi-durables and durables, are considerably larger (especially in the case of durables), although the negative coefficient on the March interaction term ( $ d_{3} $ ) for durables is not significant, probably due to the large errors and smaller sample size for this subcategory.

To sum up, we find that the monthly expenditure pattern of the public sector group from February to May, that is, the months in which expenditure is most likely to be affected by the abolition of the March bonus, has become very similar to that of the private group after the abolition of the March bonus, suggesting some association of expenditure and the anticipated sizable change in the timing of income. However, as seen in the examination of the public sector employee-only sample in the previous section, the sensitivity of expenditure is not uniform across expenditure subcategories: an clear reaction of expenditure to the income change is observed only for semi-durables and durables. The effect on services expenditure is ambiguous, while