Silviase/jgov_v1.4_full_ann huggingface dataset:
### 1. Introduction

The permanent-income hypothesis predicts that there should be no relation between the anticipated pattern of an individual's income and the anticipated pattern of his or her consumption: given a certain level of permanent income, an individual's consumption path is determined by the real interest rate and the discount rate, not by the time pattern of income. The real power of this standard model is that it gives the same predictions whatever the time period considered. A given set of preference parameters governs not only the pattern of consumption over individual's lifetime, but also that over the very short run, i.e., week, month or quarter. Thus it is worthwhile examining consumption smoothing over various frequencies to test the validity of the model.

The objective of our paper is to empirically examine the consumption reaction to predictable changes in income. More specifically, we use Japanese data to test recent findings by Hsieh (2002) and Browning-Collado (2001) that households react as suggested by the standard theory only when the income changes are large and well understood. Institutional features of the Japanese economy provide a good test of their bounded rationality conjecture. Japan has a well-established bonus system, under which large lump sum extra payments are paid to a majority of workers as part of their compensation. Japan's bonus ratio to total consumption is high, nearly twice as high as those of other countries under bonus systems, including Spain. Finally, there is virtually no uncertainty concerning whether or not bonuses will be paid or the payment date, and the amount is fairly predictable. Since we have already seen excess sensitivity of Japanese consumption to small policy changes (Hori, Hsieh, Murata and Shimizutani [2002], Hori and Shimizutani [2002], and Shimizutani [2002]) our examination of Japanese bonus payments (that is large and highly predictable) provides a perfect test of the Hsieh and Browning-Collado bounded rationality explanation.

To examine the relation between the anticipated path of income and the anticipated path of expenditures, we use two strategies. Our first identification strategy uses micro-data on individual household consumption and exploits the fact that there are (at least) two kinds of workers who are in a bonus-payments scheme and who are not. Since the bonus receipt is determined by the job or the firm, the seasonal pattern of the income is perfectly predictable for each individual worker. To measure the impact of the (predicted) bonus on consumption, we capture the seasonal variation in consumption between households with bonus and those without bonus. We control for the “normal” seasonal pattern of consumption with seasonal (monthly) dummies, and see whether the seasonality of consumption displays significant differences between bonus and non-bonus groups.

We implement our empirical procedure on micro-data from successive six-month panels of the HES, a nationally representative household consumption survey, from 1990 to
1999. Contrary to the Hsieh (2002) and Browning-Collado (2001) conjecture, our estimates indicate that the changes in income that originate from bonus payments undoubtedly affect the seasonal pattern of consumption expenditures (especially that of service consumption), despite the fact that the bonus payments are large and fairly predictable. Supplementary conventional Euler equation tests also suggest that Japanese consumption is “excessively sensitive” with an instantaneous marginal propensity to consume of less than 0.1.

Our second strategy focuses the seasonal pattern of aggregate consumption. If the bonus payments affect the seasonality of consumption expenditures, the recent decline in the ratio of bonus income to total compensation (in the continued stagnation) should have reduced the seasonality of consumption. We exploit this inference to confirm our excess sensitivity finding. Using monthly retail sales data from the Current Survey of Commerce and earning data from the Monthly Labor Survey, we ascertain that this inference is correct.

The paper is arranged as follows. The next section reviews the preceding literatures on the consumption response to anticipated income changes. Section 3 describes the FIES panel data that we use, the Japanese bonus system, and our empirical strategies. Section 4 reports our micro-data estimates of excess sensitivity based on the comparison of seasonality between bonus and non-bonus households. Section 5 reports the MPC from bonus payments using Euler equation estimates. Section 6 examines aggregate sales data to confirm the inferred wilting seasonality. Section 7 concludes.

### 2. Literature Review

Several studies have tackled the question of how consumption reacts to predictable changes in income. For example, in their early studies, Campbell and Mankiw (1989) and Wilcox (1989) present aggregate data evidence that consumption responds to predictable income changes. However, their test of the random walk hypothesis with aggregate data has several disadvantages such as the small number of observations, difficulty in finding variables with much predictive power for income changes, and data aggregation problems. In recent years researchers are tackling the issue using micro data on individual households. Shea (1995) presents micro data evidence that consumption of wage-earner households covered by long-term union contracts deviates greatly from the random walk prediction, regardless of the important predictable components of their wage increases. Shapiro and Slemrod (1995), Parker (1999) and Souleles (1999) each identify a feature of government policy that causes predictable income movements. All these studies found that the resulting predictable income changes caused substantial changes in consumption despite the fact that the effects of the policies on lifetime income seem negligible. One important aspect of their findings is that the observed excess sensitivity of consumption is not correlated with indicators of liquidity constraints.
Although Romer (2001) argues that the findings above are representative of what other researchers have found, more recent results by Hsieh (2002) and Browning and Collado (2001) complicate such generalizations. Hsieh found that although households overreact to (relatively small) tax refunds, the very same households do not overreact to (large and highly predictable) payments from the Alaska Permanent Fund. Browning and Collado echoed Hsieh with their finding that the patterns of consumption over the year for those who receive predictable large bonus payments are indistinguishable from the patterns of those who do not receive a bonus. To reconcile their findings with the earlier studies that report excess sensitivity of consumption, they resort to bounded rationality and infer that households react as suggested by the standard theory only when the income changes are large and well understood. When income changes are relatively small and variable from year to year, households might not smooth consumption because the benefits of making the optimal expenditure calculations in that situation are small and the costs are large.

### 3. Data Source and the Japanese Bonus System

Our micro-data observations come from a representative rolling monthly panel drawn from the Japanese population, the Family Income and Expenditure Survey (FIES) from 1990 to 1999. $ ^{1} $ The survey provides detailed information on income and expenditures for individual households as well as on the characteristics of those households. The monthly consumption data is compiled from a diary, which is collected twice a month. The survey covers approximately 8,000 households that are representative at the national level. Single households and households employed in the agriculture or fishery industries are not surveyed. The length each household stays in the panel is six months.

To improve the reliability of our estimates, we exclude the following households from our sample. First, we dropped households in which the head of household is self-employed or employed part-time since income flows for these households tend to be very irregular. $ ^{2} $ Second, we also exclude households in which the reported age of the head of household decreases or increases by more than one year during the 6-month reporting period or if the household’s tenancy status changes from owner to renter or vice-versa. Third, we excluded households in which family members other than the head of household are employed. Finally, we also exclude any households which received bonus payments in months other than the pre-scheduled “bonus months”, of March, June, July and December. After these adjustments, we end up with a sample of roughly 300 households in each six-month panel (or 1,800 households in each survey month).
These households may include children and other adults. We shall allow for variations in these in our analysis.

The power of our test comes from the existence of the institutional feature of the Japanese economy. In our sample, most of workers are paid monthly. Firms usually pay regular workers the almost same amount in each regular month of the year, but pay out more in the pre-scheduled “bonus” month. The typical schedule of the bonus payment in the private sector is once or twice a year, i.e., in winter (mid-December) or in summer (June or July) and winter. Most workers in the public sector receive a smaller third bonus payment in the spring (March). Though the timing and amount of bonus varies by job, firm or industry, the most common practice is to pay 2-3 times the monthly salary amount in the summer and winter and slightly less than double the monthly salary amount in the spring (see Table 1 for the ratio of bonus receivers by month and group). Thus the ratio of bonus to total consumption in Japan is higher than other countries including Spain, which was examined by Browning and Collado’s study.

Though it is believed that there is a performance-related aspect in Japanese bonuses, they have become institutionalized and are an integral and anticipated component of worker compensation. Thus, there is virtually no uncertainty concerning whether or not bonus will be paid or concerning the payment date of bonus, and the amount is fairly predictable. Especially, the bonuses of government workers are fixed by law as a certain multiple of each worker's regular monthly salary (see Ishikawa and Ueda [1984], Horioka [1990] and statistical descriptions in the following sections). Since we have already found excess sensitivity of Japanese consumption to small policy changes (Hori, Hsieh, Murata and Shimizutani [2002], Hori and Shimizutani [2002] and Shimizutani [2002]), our examination of Japanese bonus payments (that is large and highly predictable) would be a perfect test of the Hsieh and Browning-Collado conjecture.

In the following analysis, we focus only on the effects of winter and spring bonuses, for a few reasons. First, the shorter (six-month) panel restricts us from obtaining full-year information for each household. Therefore, the households reporting summer bonus information do not report on the winter bonus, or vice-versa. Second, the timing of the summer bonus is scattered over June and July and complicates our simple study on seasonality. Since the spring bonus is smaller than the winter bonus and is paid only for the public sector worker households, for which the bonus amount is fixed by rules and precisely predictable, we choose to focus our analysis on winter and spring bonus payments. Since the PIH model gives the same predictions whatever the time period considered, our monthly study on winter and spring bonus provides a satisfactory test. To focus on the winter and spring bonus payments, we form three panels of households (October to March, November to April, and December to May, all those panels cover both the winter and spring bonus payments) for each year between 1990 and 1999.
Pooling these panels, we end up with a total sample of slightly less than 8,000 households. These households are divided into three groups; Non-Bonus households, December-Bonus households, and December & March-Bonus households, based upon their bonus receipt entries reported in the FIES $ ^{3} $ . The summary statistics are reported in Table 2.

Figure 1-1, 1-2, and 1-3, which present histograms of the monthly difference in log household head incomes by group, reflect the payment structure we exploit in our empirical analyses below. Three histograms, that is on pooled (from November to May) data, December and January data, and March and April data, are given for each household group. In the case of the Non-Bonus group (Figure 1-1), there is no noticeable difference among three histograms with single peak at about zero mean as it is expected. But in the case of the December-Bonus group (Figure 1-2), the histogram on pooled data is accompanied by two secondary peaks (around plus and minus 1.2), reflecting the winter bonus. The pooled histogram for the December & March-Bonus group (Figure 1-3) exhibits four secondary modes reflecting the winter and spring bonus, i.e. at around plus and minus 1.3 for winter and 0.4 for spring. Figures illustrate that the seasonal income variations caused by bonus payments were sufficiently large to be immune from contaminating noises.

### 4. Empirical Test I: Browning-Collado graphical test

## 4 -a) Empirical Strategy

In Figure 2, we present the average monthly changes in log nominal income for the three groups: Non-bonus, December-bonus and December & March-bonus. It is clear from this figure that the income of bonus households displays a strong seasonal pattern while the income of non-bonus households is smooth. The December-Bonus group exhibits a strong positive swing in December and a negative swing in January, after which it converges to the same path as the Non-Bonus group. The December & March-Bonus group follows the same pattern as that of the December-Bonus group up until February; but then exhibits a smaller up and down cycle in March and April.

Our first test is to see whether consumption patterns for each of the three groups display the same patterns observed in the income patterns of Figure 2. Consumption may display seasonality without impacts from income flows. There is exogenous demand variation due to, for instance, the New Year holiday (the traditional holiday period in Japan), Christmas,
and the change of the fiscal year $ ^{4} $ (which leads to a higher demand for school and other expenses). Following Browning-Collado's methodology, we first regress the log difference of monthly real consumption on the following variables: the number of family members, a quadratic in the age of household head, the nominal interest rate, monthly dummies for the six survey months and dummy variables for each of the three groups - Non-Bonus households, December-Bonus households, and December & March-Bonus households. We then plot the monthly dummy coefficients for each of the three kinds of households. If consumers behave as predicted by the standard PIH model, we would not expect any significant difference among the monthly dummy coefficients for the three groups. Thus our starting prior was that these monthly consumption patterns would not be affected by income patterns if the Hsieh and Browning-Collado conjecture were correct, since the seasonal patterns of bonus payments are large and fairly predictable. If we find stronger December consumption for the two bonus groups and March consumption for the December & March group, it contradicts the standard model. We supplement this analysis with a conventional Euler equation excess sensitivity test to measure the degree of deviation in Section 5.

### 4 -b. Results

Figures 3 plot the coefficients on the monthly dummies with and without cross dummies for the two bonus groups for three categories of consumption goods: semi-durables, non-durables, and services, as well as on “total consumption”, that is the sum of all these three categories plus durable consumption. The first thing to notice about these plots is that there is a distinct seasonal surge in all categories of consumption in December and March regardless of the bonus payments. The observed seasonal variations were larger for semi-durables and smaller for services as expected. However, notwithstanding the conjecture by earlier studies, there seem to be consistent differences among the seasonal patterns of the three groups. We can see the differences in all of the three categories of consumption and in total consumption; the pattern is most clearly exhibited in services and total consumption (see Figure 3-3 and 3-4). The December expenditures for the two bonus groups were higher (January are lower as reaction), and the March expenditures were higher only for the December & March-Bonus group. These findings suggest “excess sensitivity” of consumption. More formal evidence is reported in Table 3, which shows that the chi-squared(6) and chi-squared(12) statistic for equality of the two or three sets of monthly dummies are all significant with all three categories and the total, suggesting statistical violation of the standard model’s smoothing prediction.

### 5. Empirical Test II: Euler equation excess sensitivity test
### 5 -a. Benchmark Euler Equation

To complement our graphical analysis and evaluate the quantitative significance of our findings, we conduct a conventional Euler equation test of the “excess sensitivity” of consumption. The basic empirical specification is the following linear regression:

$$ \ln\left(\frac{C_{h,t}}{C_{h,t-1}}\right)=\sum_{n=0}^{3}\alpha_{n}\left(\frac{Bonus_{h,t-n}}{MonthlyIncome_{h,\tau-1}}\right)+Z_{h,t}^{^{\prime}}\cdot\gamma+Month_{t}^{^{\prime}}\cdot\omega+\varepsilon_{t} $$

where h indexes households and t refers to the month $ (t=11,12,1,2,3,4) $ . The dependent variable is the log of the ratio of real consumption by household h in a given month t (after November) relative to the consumption in the previous month. The main independent variables are $ \frac{Bonus_{h,t-n}}{MonthlyIncome_{h,\tau-1}} $ , the amount of bonus received by a household relative to the household's average monthly income in the previous year. $ MonthlyIncome_{h,\tau-1} $ is calculated as the previous year's pretax income divided by 12. Since the length of the panel is six months, each household has at most five observations of the dependent variable. We allow for lags of up to three months of $ \frac{Bonus_{h}}{MonthlyIncome_{h,\tau-1}} $ , in order to address the possibility that a household does not spend the bonus income immediately. $ Z_{h,t} $ is a vector of household characteristics (a quadratic in the age of the household head, the number of family members). $ Month_{t} $ is a vector of dummy variables for each month. The coefficients of interest are $ \alpha_{n} $ s, which measure the elasticity of consumption to income variations due to the bonus. We run regressions using exactly the same dataset as that used in the graphical test in the previous section.

We estimate the specification above for three categories of consumption and total consumption. The results reported in Table 4 indicate that the coefficients on the contemporaneous bonus variable are significantly positive for all categories, supporting our finding that Japanese consumption exhibits excess sensitivity. However, the elasticity estimates are generally small, 0.1 or less $ ^{5} $ , and the positive effects are canceled out by negative coefficients on lagged terms. We cannot reject the null hypothesis that the sum of all the coefficients on bonus terms equals zero, i.e., $ \sum_{n=0}^{3}\alpha_{n}=0 $ , as reported in Table 4. All these Euler equation estimates suggest us that Japanese consumption is excessively sensitive to the anticipated large income variation of the bonus system, contrary to the Hsieh and Browning-Collado conjecture. However, the degree of violation is relatively small and corrected over a few months.
### 5 -b. Comparison with unanticipated small income changes

Given the observed overreaction to anticipated large income changes, it is interesting to examine the reaction of these same households to small income changes. We have already documented the excess sensitivity of Japanese consumers' to anticipated small policy changes (Hori, Hsieh, Murata and Shimizutani [2002], Shimizutani [2002] $ ^{6} $ ). Here we present the reaction (of the very same households as those analyzed in the previous sections) to unanticipated small income changes.

The unanticipated small income change that we use here is the year-end tax adjustment refund to each household. The tax refund is entered as a part of non-current income in the FIES, and we can roughly estimate the refund amount for December by deducting gifts from the non-current income $ ^{7} $ . As can be confirmed in the summary statistics (Table 2), the adjustment amount is relatively small in comparison with the bonus payments studied above. In addition, the year-end tax refund is generally perceived as an unpredictable windfall. $ ^{8} $

To compare the effects of large anticipated and small unanticipated income changes, we estimate the following specification that includes the year-end tax adjustment as an additional independent variable:

$$ \ln\left(\frac{C_{h,t}}{C_{h,t-1}}\right)=\sum_{n=0}^{3}\alpha_{n}\left(\frac{Bonus_{h,t-n}}{MonthlyIncome_{h,\mathfrak{t}-1}}\right)+\sum_{n=0}^{3}\beta_{n}\left(\frac{Y.E.A d j u s t m e n t_{h,t-n}}{MonthlyIncome_{h,\mathfrak{t}-1}}\right)+Z_{h,t}^{^{\prime}}\cdot\gamma+M o n t h_{t}^{^{\prime}}\cdot\omega+\varepsilon_{t} $$

where $ \frac{Y.E.Adjustment_{h,t-n}}{MonthlyIncome_{h,\tau-1}} $ is the value of the year-end tax adjustment received by household h relative to the household's average monthly income in the previous year.

The dependent variables are again the log of the ratio of consumption (total and three sub-categories) by household h in a given month t relative to the consumption in the previous month. The results are reported in Table 5. Reflecting the orthogonality between bonus and the year-end adjustment, our extension does not affect the coefficients on the bonus terms; that is, they are all significantly positive on the contemporaneous term, and cancel out over the following months. What's more interesting for us here is the coefficients on the year-end adjustment terms. The standard theory suggests that consumption reacts to an income shock.