Silviase/jgov_v1.4_full_ann huggingface dataset:
## 一 般消費者等

一般の消費者、消費者グループ、農産物直売所や道の駅等への委託販売のほか、子等親族に有償で販売した場合をいう。

## その他

J A 等、販売業者（卸・小売）、外食事業者及び一般消費者等に有償で販売した以外の主食用の米穀をいい、地代、作業賃料等に係る現物支払、物々交換等を含む。

## 無償讓渡量

農家が贈答等、無償で譲り渡した主食用の米穀の量をいう。

## 13 利用上の注意

(1) 本調査は調査方法等の見直しにより、平成30年6月分まで月次調査で実施し、その後は年次調査に移行した。

このため、本書への掲載に当たっては、平成29年度（平成29年4月分から平成30年3月分）に加え、平成30年4月分から同年6月分までの結果についても併せて掲載した。

(2) 本調査は標本調査であることから、平成28年度末在庫量と平成29年度初在庫量は一致しない。

(3) 統計数値については、表示単位未満を四捨五入したため、計と内訳が一致しない場合がある。

(4) 供給量、消費量、販売量、在庫量等の数量は玄米換算した数値である。

(5) 表中に使用した記号は、次のとおりである。

「 0 」、「 0.0 」、「 0.00 」: 単位に満たないもの又は増減がないもの（例：0.4kg→0kg）

「-」: 事実のないもの

「…」: 事実不詳又は調査を欠くもの

「△」：負数又は減少したもの

「nc」：計算不能

(6) この統計表に掲載された数値を他に転載する場合は、「生産者の米穀在庫等調査結果」（農林水産省）による旨を記載してください。

(7) 公表した数値の正誤情報は、ホームページでお知らせする。

## 14 ホームページ掲載案内

本統計の累年データは、農林水産省ホームページ「統計情報」の分野別分類「作付面積・生産量、被害、家畜の頭数など」、品目別分類「米（消費）」の「生産者の米穀在庫等調査」で御覧いただけます。

【 http://www.naff.go.jp/j/tokei/kouhyou/kone_zai.html#r】

## 15 お問合せ先

農林水産省 大臣官房統計部 経営・構造統計課 分析班

電話：（代表）03-3502-8111（内線3635）

（直通）03-6744-2042

FAX: 03-5511-8772
# The Effect of Inheritance Receipt on Individual Labor Supply: Evidence from Japanese Microdata

Takeshi Niizeki and Masahiro Hori

July 2018

Economic and Social Research Institute

Cabinet Office

Tokyo, Japan

The views expressed in “ESRI Discussion Papers” are those of the authors and not those of the Economic and Social Research Institute, the Cabinet Office, or the Government of Japan. (Contact us: https://form.cao.go.jp/esri/en_opinion-0002.html)
# The Effect of Inheritance Receipt on Individual Labor Supply: Evidence from Japanese Microdata $ ^{\dagger} $

Takeshi Niizeki $ ^{‡} $

Ehime University

Economic and Social Research Institute, Cabinet Office

3 Bunkyo-cho, Matsuyama City, Ehime 790-8577, Japan

Tel: +81-89-927-9247

Masahiro Hori

Economic and Social Research Institute, Cabinet Office

1-6-1 Nagata-cho, Chiyoda-ku, Tokyo 100-8914, Japan

Tel: +81-3-5253-2111

July, 2018

## Abstract

This paper examines the effects of wealth on individual labor supply by considering inheritance receipts as an exogenous change in household wealth. Using Japanese microdata consisting of individuals aged 26–51, we find that (i) while men’s probability of working does not respond to inheritance receipt, women’s probability of working decreases; and (ii) in the case of most respondents the receipt of an inheritance seems to be unanticipated. We also test the unitary household model using information on respondents’ spouses. The results indicate that who received an inheritance influences the labor supply decision of each household member, meaning that we find no support for the unitary model.

Keywords: Wealth effects, individual labor supply, inheritance receipt, unitary model

JEL Classification: D13, D64, J22
## 1 Introduction

Understanding the effects of wealth on individual labor supply can provide meaningful insights for both researchers and policymakers. In an academic context, while many macroeconomic models assume that leisure is a normal good, some studies, especially those analyzing the effects of news shocks on macroeconomic variables (see, e.g., Beaudry and Portier 2014), rely on the formulation of household preferences proposed by Greenwood, Hercowitz, and Huffman (1988) in which the effect of wealth on individual labor supply is zero. $ ^{1} $ To make simulation exercises using macroeconomic models more reliable, it is important to empirically examine to what extent changes in wealth influence individual labor supply. In addition, if wealth has an impact on individual labor supply, this might also provide important insights on the link between wealth and consumption. Several recent studies examining the effect of wealth on household consumption find a much smaller marginal propensity to consume (MPC) out of wealth than predicted by the standard life-cycle/permanent income hypothesis (LC/PIH). $ ^{2} $ As highlighted by Cheng and French (2000), this may be due to a strong positive effect of wealth on leisure. That is, people consume an increase in wealth eventually, but mostly in the form of increased leisure, not consumption.

From policymakers’ point of view, it is also important to understand to what extent an exogenous change in wealth reduces people’s incentive to work. For example, one important policy issue has been whether an expansion of welfare programs to mitigate inequality depresses recipients’ work incentives. While a substantial amount of empirical evidence on the effects of welfare programs on individual labor supply has been accumulated for the United States (see Moffitt 2002 for a comprehensive survey), evidence for Japan is still limited.

Against this background, the current paper examines the effects of wealth on individual labor supply using panel microdata for Japan. To identify the wealth effects on individual labor supply, the simplest approach is to regress individuals' employment status or hours worked on non-labor income using cross-section data. As highlighted by Keane (2011), however, one of the drawbacks of this approach is the endogeneity problem arising from the possible correlation between non-labor income and unobserved preferences for work. For instance, those who prefer working to enjoy leisure likely accumulate more wealth, which in turn means that they likely will receive more non-labor income (asset returns). In this case, the resulting positive correlation between the error term and non-labor income creates an upward bias in the estimation of wealth effects. For example, regressing men's
hours worked on various types of non-labor income and a number of demographic variables using cross-sectional data for the United States, Pencavel (1986) suggests that an additional 10,000 dollars in asset income are associated with an increase in annual hours worked of 46 hours. However, this result seems rather counterintuitive and a possible explanation is the failure to control for unobserved preferences.

One way to overcome the endogeneity problem arising from ignoring preferences is to adopt a fixed effects approach using panel data. However, there may be other omitted variables potentially giving rise to endogeneity. To deal with such endogeneity issues, researchers often exploit situations or events that can be regarded as akin to randomized controlled experiments. In the case of research on the effect of wealth on individual labor supply, most studies following this approach focus on one of the following three types of natural experiment.

The first type of natural experiment employed is to focus on the effects of winning the lottery (Picchio, Suetens, and van Ours 2018, Cesarini et al. 2017, Arvey, Harpaz, and Liao 2004, Imbens, Rubin, and Sacerdote 2001, Lindh and Ohlsson 1996). Since winning the lottery is a random event (once the number of lottery tickets purchased is controlled for), it provides researchers with an ideal opportunity to identify the effect of an exogenous increase in wealth on individual labor supply.

The second type of experiment focuses on exogenous changes in taxes and the social security system such as changes in social benefits for recipients around a certain age (Bargain and Doorley 2011, Lemieux and Milligan 2008), changes in social security benefits after retirement (Coile and Gruber 2007, Chan and Stevens 2004, Krueger and Pischke 1992), changes in the normal retirement age (Hanel and Riphahn 2012, Mastrobuoni 2009), and changes in the tax system (Blundell, Duncan, and Meghir 1998, Eissa and Liebman 1996). Since changes in taxes and the social security system are independent of individuals' decision making, they also enable us to identify the effect of exogenous changes in wealth on individual labor supply.

The third type of experiment uses the incidence of inheritance receipt (Sugano and Matsuyama 2017, Doorley and Pestel 2016, Elinder, Erixson, and Ohlsson 2012, Brown, Coile, and Weisbenner 2010, Joulfaian and Wilhelm 1994, Holtz-Eakin, Joulfaian, and Rosen 1993). Compared to the previous two experiments, the disadvantage of this approach is that the probability of inheritance receipt and the inheritance amount may not be completely exogenous to individuals. For example, decedents may give a larger share to lazy children when dividing up their inheritance. Since lazy people are more likely to be out of the labor force, ignoring the preference for work gives rise to a downward bias in estimates of the link between wealth and individual labor supply. $ ^{3} $ This kind of bias, however, can be overcome by using panel data, provided that individual preferences are constant over time.
## 2 Data

The data employed in the current analysis are taken from the second wave of the “Family and Lifestyle Survey” (FLS hereafter) conducted in 2012 by our research group. To create the sample, we utilized the pool of approximately 220,000 consumer testers across Japan who were preregistered by INTAGE Inc., one of the largest research firms in Japan. More precisely, we first randomly drew 4,525 individuals from the pool in such a way that the distribution of individuals in terms of sex, residential area (10 groups), and age group (6 groups) for the first wave of our survey conducted in 2011 resembles that in the Population Census for Japan. We then tracked participants in the first wave to create the sample for the second wave of our survey conducted in 2012, which forms the basis for the current analysis. The response rate for the second wave is 86.2% (3,144 individuals). $ ^{4} $ Note that we only employ the second wave of the FLS to conduct our analysis. However, since the second wave contains some recall-based questions such as the past employment status, we treat it as a panel-structured dataset.

The FLS collects three important pieces of information that we need to conduct our analysis: (i) the year parents died, $ ^{5} $ (ii) the inheritance amount received, and (iii) the employment status before and after the parental death. Note that the FLS asks these questions not only with regard to respondents but their spouse as well, so that there are up to four observations (for each of the four parents) for each respondent. The FLS also collects information on respondents' and their spouses' demographic characteristics such as their age, sex, and number of children.

To conduct our analysis, we confine the sample based on the following criteria. First, individuals born before 1956 are dropped, since the age profiles of the employment status of these older cohorts seem to suffer from serious measurement error. To illustrate this, Figure 1 compares the employment status age profiles obtained from the FLS (our dataset) and the Labor Force Survey conducted by the Ministry of Health, Labour and Welfare (official statistics). As can be seen, both among male and female individuals, the employment rate for cohorts born before 1956 (the first four cohorts) tends to be lower than in the official statistics. A possible reason is that the question about individuals' employment status is on a recall basis and that older respondents find it difficult to correctly recall their employment status a long time ago. Second, we only include observations for which all of the following three variables are available: (i) the year that a parent died, (ii) the inheritance amount received, and (iii) the employment status of the respondent or spouse over a 9-year window centered at the year of parental death. Third, the sample is confined to observations for which information on the respondent's/spouse's characteristics (age, sex, number of children aged 12 or below, and health
status) at the time of the death of the parent, not the time of the survey (2012), is available. Fourth, the sample is limited to individuals who lost only one of their own parents in a 9-year window, since otherwise it would be difficult to determine the death of which parent (and hence which inheritance) caused the individual's change in labor supply. $ ^{6} $ The final sample consists of 158 men and 205 women that lost at least one of their own parents.

Table 1 provides descriptive statistics of the sample we employ to conduct our analysis. The average age of individuals in our sample at the time of the survey in 2012 was about 49 years for both sexes. However, what we are really interested in in our investigation is individuals' age at the time their parent died, which in our sample on average is about 38 years for men and 37 years for women. This may seem much younger than one might expect, but note that our sample consists only of those that did lose a parent, while in the general population many in the age group we focus on still have all their parents. Next, a majority of respondents (including spouses) in our sample report that the amount they inherited when their parent passed away was zero, with only 41% of men and 32% of women reporting a non-zero (positive) amount. This likely reflects that in many cases the other parent was still alive. The average inheritance amount (including those whose inheritance amount was zero) converted into 2010 prices using the Consumer Price Index is 4.30 million yen for men and 2.41 million yen for women (approximately 43,000 and 24,100 U.S. dollars, respectively). Note that since more than half of respondents (including their spouses) reported a zero inheritance amount, the median is zero for both sexes.

## 3 Empirical strategy and results

### 3.1 Benchmark case

In our benchmark estimation, we compare changes in the employment status of those who received an inheritance with those who did not after controlling as much as possible for other factors. Normalizing the year of parental death to t = 0, the benchmark estimation equation is:

$$ E m p_{i t}=\beta_{0}+\beta_{1}P O S T_{t}+\beta_{2}[P O S T_{t}\times I n h e r_{i0}]+\pmb{\beta}_{3}^{\prime}\pmb{X}_{i t}+\alpha_{i}+\mu_{t}+\varepsilon_{i t}, $$

where $ Emp_{it} $ is an employment dummy that equals one if individual i is employed and zero otherwise, $ POST_{t} $ is a dummy that equals one if $ 0 \leq t \leq 4 $ and zero if $ -4 \leq t \leq -1 $ , $ Inheri_{i0} $ is a dummy that equals one if individual i received an inheritance and zero otherwise, and $ X_{it} $ is a vector of control variables consisting of the number of children aged 12 or below and an illness dummy that equals one if individual i had a major illness in year t impeding normal daily life and zero otherwise.
had expected to inherit something but then discovered they did not. In this case, not receiving an inheritance represents an unexpected negative shock to their wealth, increasing the likelihood that they worked. $ ^{8} $ Another possible explanation is that some of these women did not work before the death of their parent in order to provide home care to the parent. In this case, the death of their parent enabled them to rejoin the labor market.

Columns (6) and (8) also show that women who received an inheritance were significantly less likely to work following the death of their parent than before, with the probability being around 10 percentage points lower than that of women that did not receive an inheritance, which is consistent with the idea that wealth has a negative effect on labor supply. Thus, the results in column (6) suggest that the combined effect is that the likelihood that women whose parent died and who did receive an inheritance were 4.70 percentage points less likely to work after the death of their parent than before.

So far, we have only considered whether individuals received an inheritance or not and have not exploited information on the inheritance amount. Therefore, we next replace the key explanatory variable with the inheritance amount (including zero) and examine whether those who received a larger inheritance were more likely to stop working. To do so, we estimate the following equation:

$$ \begin{aligned}Emp_{it}=\beta_{0}+\beta_{1}POST_{t}&+\beta_{2}[POST_{t}\times Amount_{i0}]\\&+\beta_{3}[POST_{t}\times Amount_{i0}^{2}]\\&+\beta_{4}[POST_{t}\times Amount_{i0}\times Morethan_{i0}]\\&+\beta_{5}[POST_{t}\times Amount_{i0}^{2}\times Morethan_{i0}]\\&+\boldsymbol{\beta}^{\prime}_{6}\boldsymbol{X}_{it}+\alpha_{i}+\mu_{t}+\varepsilon_{it},\\ \end{aligned} $$

where $ Amount_{i0} $ is the inheritance amount (measured in 100 million yen in 2010 prices). In addition, we interact the square of $ Amount_{i0} $ with $ POST_{t} $ to allow for possible non-linear effects. $ Morethan_{i0} $ is a dummy variable that equals one if the amount inherited was larger than expected, and zero if the amount was either as expected or smaller than expected. This variable enables us to examine whether those who received a larger than expected inheritance were more likely to stop working than those who did not. All other settings are identical to those in the estimation of Equation (1).

Columns (1) to (4) in Table 3 show the estimation results obtained using the specification including only $ POST_{t} $ and $ POST_{t} \times Amount_{i0} $ as key explanatory variables. We find that in all specifications none of the coefficients are significant, including in columns (2) and (4) for women,
$$ (d=-4,-3,-2,0,1,2,3,4) $$

where $ \mathbf{1}(\cdot) $ is an indicator variable that equals one if the expression inside of the parentheses occurs at time t and zero otherwise. Note that the sample is always confined to two periods (t = -1 and t = d) in estimating Equation (3). In other words, we run a regression for each d and obtain the eight estimates for $ \beta_{2} $ . All other settings are identical to those in the estimation of Equation (1).

Figure 2 shows our estimates for $ \beta_{2} $ in Equation (3) – that is, the estimated additional effects on the labor supply response of receiving an inheritance compared to the response of not receiving an inheritance – over a 9-year window, with 90% confidence intervals. For example, in Figure 2(b), the estimate for three years after the parent’s death (about -0.16), means that the probability of women who received an inheritance working decreased by about 16 percentage points more than that of women who did not receive an inheritance. For men, receipt of an inheritance in all years (except in t = -4) does not have a statistically significant impact on their labor supply. In contrast, women’s probability of working begins to decline additionally in response to the inheritance receipt at t = 0 and the peak of decline occurs at t = 3. This implies there is some time lag for women who received an inheritance to change their labor supply behavior. More importantly, changes in the probability of women to work from t = -1 to t = -4, -3, -2 do not significantly differ between those that subsequently received an inheritance and those that did not, rejecting the hypothesis that they changed their labor supply before their parent’s death in anticipation of receiving an inheritance. This result may not be surprising since the average age of individuals in our sample at the time of their parent’s death is about 38 for men and 37 for women, which is much younger than the age of individuals in the surveys used in previous studies. $ ^{9} $ This means that the death of their parent is probably an unanticipated event for most individuals in our sample.

In summary, while men’s labor supply is not affected by inheritance receipt, women tend to decrease their labor supply with some time lag. Given that the mean and median of women’s inheritances in our sample are only about 7.60 and 3.58 million yen (about 76,000 and 35,800 U.S. dollars), respectively, the decision to leave the labor market seems irrational in light of the rigidity of Japan’s labor market, which makes it difficult for people to return to work once they have left. One possible explanation for women’s labor supply response therefore is that at least some of the women were non-regular workers, since the income elasticity of labor supply of non-regular workers is usually higher than that of regular workers. Unfortunately, the FLS does not allow us to distinguish between regular and non-regular workers, so that we cannot examine this issue.

### 3.3 Unitary model
did not change their employment status despite receiving a large inheritance. In addition, we did not find any evidence that inheritors had anticipated their inheritance receipts a few years before the death of their parent, implying that the decline in women’s labor supply after receiving an inheritance is caused simply by the unanticipated positive wealth shock.

Taking advantage of the fact that our dataset also provides information on respondents' spouse, we further tested the unitary model by comparing the impact of inheritance receipt on the inheritor's and the inheritor's spouse's labor supply response. We found that no significant decline in the probability that women worked could be observed when their husband received an inheritance, so that we found no support for the unitary household model.
## References

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[3] Bargain, O. and Doorley, K. (2011) “Caught in the Trap? Welfare’s Disincentive and the Labor Supply of Single Men,” Journal of Public Economics, Vol. 95, pp. 1096–1110.

[4] Beaudry, P. and Portier, F. (2014) “News-Driven Business Cycles: Insights and Challenges,” Journal of Economic Literature, Vol. 52, No. 4, pp. 993–1074.

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[8] Chan, S., and Stevens, H. A. (2004) “Do Changes in Pension Incentives Affect Retirement? A Longitudinal Study of Subjective Retirement Expectations,” Journal of Public Economics, Vol. 88, Issues. 7–8, pp. 1307–1333.

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[10] Christelis, D., Georgarakos, D., and Jappelli, T. (2015) “Wealth Shocks, Unemployment Shocks and Consumption in the Wake of the Great Recession,” Journal of Monetary Economics, Vol. 72, pp. 21–41.

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[13] Doorley, K. and Pestel, N. (2016) “Labour Supply after Inheritances and the Role of Expectations,” IZA DP No. 9822.

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