ISSN (Print) 0473-453X

Discussion Paper No. 1073

ISSN (Online) 2435-0982

THE IMPACT OF BEQUEST MOTIVESON RETIREMENT BEHAVIOR
IN JAPAN:
A THEORETICAL AND EMPIRICAL ANALYSISCharles Yuji Horioka
Emin Gahramanov
Aziz Hayat
Xueli Tang

January 2020

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

The Impact of Bequest Motives on Retirement Behavior in Japan:
A Theoretical and Empirical Analysis
Charles Yuji Horioka*
Research Institute for Economics and Business Administration, Kobe University, Japan;
National Bureau of Economic Research, United States of America; Asian Growth ResearchInstitute, Japan; and Institute of Social and Economic Research, Osaka University, Japan
Emin Gahramanov
American University of Sharjah, United Arab Emirates
Aziz Hayat
Deakin University, Australia
Xueli Tang
Deakin University, Australia
January 2020
Abstract: In this paper, we conduct a theoretical and empirical analysis of the impact ofbequest motives on the work and retirement behavior of households in Japan using micro datafrom the Preference Parameters Study of Osaka University. Our empirical findings are
consistent with our theoretical model and show that respondents with an altruistic or
strategic/exchange bequest motive work more at the intensive margin than those without any
bequest motive but that respondents with a strategic or exchange bequest motive work less at
the extensive margin (i.e., retire earlier) than those without any bequest motive. Our findings
for the strategic or exchange motive suggest that respondents with such a motive tend to work
harder than others before they retire so that they can earn more, leave a larger bequest to theirchildren, and elicit more care from them but that they tend to retire earlier than others so thatthey can start receiving care for themselves and their spouses from their children sooner. A
policy implication of our findings is that the exchange of bequests for the care of parents bychildren may be very sensitive to the inheritance tax framework.
JEL classification numbers: D15, D64, J14, J22, and J26
Key words: Altruistic bequest motive, bequest motives, exchange bequest motive, inheritances,
Japan, labor supply, retirement, strategic bequest motive, working hours*Corresponding author: Charles Yuji Horioka. Address: Research Institute for Economics andBusiness Administration, Kobe University, 2-1, Rokkodai-cho, Nada-ku, Kobe, Hyogo 6578501, JAPAN. E-mail: horioka@rieb.kobe-u.ac.jp

1. Introduction
Parents and children are connected in various ways, and one of the most important ways inwhich they are connected is through intergenerational transfers (i.e., bequests and inter vivos
transfers) from parents to children. The desire to leave bequests and other intergenerationaltransfers to one’s children is likely to affect the economic behavior of parents in many ways.
In other words, it is quite possible that parents planning to leave a bequest to their children will
behave very differently from those not planning to leave a bequest to their children. For
example, it is quite possible that parents planning to leave a bequest to their children will savemore than those not planning to leave a bequest to their children because they need to save not
only to finance their own retirement needs but also to leave a bequest to their children. Indeed,
many previous studies have examined the impact of bequest motives on saving and wealthaccumulation behavior, and most of them have found that parents planning to leave a bequest
to their children do, in fact, save more than those not planning to leave a bequest to theirchildren (see, for example, Horioka et al. (1996), Horioka et al. (2002), and Niimi and Horioka(2018); see Hurd (1990) for a comprehensive survey).
By the same token, it is quite possible that parents planning to leave a bequest to their children
will work more at the intensive margin (i.e., work more hours per day and/or more days peryear) and/or at the extensive margin (i.e., work longer and retire later) than those not planningto leave a bequest to their children so that they can increase their lifetime incomes and thence
the amount that they can bequeath to their children. Moreover, work-related outcomes at boththe intensive and extensive margins may differ by the nature of bequest motives (for example,
by whether they are motivated by altruistic or strategic/exchange considerations). Surprisingly,
however, no research has been done on the bequest-work relationship of parents thatdifferentiates between those with different bequest motives. This paper intends to fill this gap
in the literature.
The impact of bequest motives on the work-related outcomes of parents may be especiallypronounced in the case of Japan where bequest motives are relatively strong. As Table 2 shows,34.0 percent of respondents have a strong bequest motive, 47.3 percent have a weak bequest
motive, and only 18.7 percent have no bequest motive at all.1 Moreover, the social norm inJapan has traditionally been for children (especially the eldest son) to provide care to elderly
parents, and until a public long-term care insurance program was introduced in 2000, theelderly in Japan had to rely on their children to provide care or to pay the full cost of hiring
professional care workers. Furthermore, even today, the financial burden of elderly care falls
largely upon the elderly themselves because the public long-term care insurance system has a
co-payment of 10 percent or more and also has strict eligibility requirements, as a result of
which only care services that are concomitant with one’s care needs are covered by insurance.
Thus, it seems likely that a substantial proportion of Japanese has an interest in inducing theirchildren to provide care during old age and in using bequests for this purpose (see Horioka, etal. (2018) for corroboration of this point).
In this paper, we conduct a theoretical and empirical analysis of the impact of bequest motives
on the work and planned retirement decisions of households in Japan. We first do a theoreticalanalysis of the impact of altruistic and exchange bequest motives on work-related outcomes at
1

However, Horioka (2014) finds that bequest motives are even stronger in India and the United States than inJapan although they are of roughly comparable strength in China and Japan. Thus, if we find bequest motives tohave a significant impact on work-related outcomes in Japan, their impact is likely to be even greater in India andthe US, where bequest motives are even stronger..
1

the intensive and extensive margins. We then test our theoretical model’s predictions
empirically using micro data from the Preference Parameters Study (Kurashi no Konomi to
Manzokudo ni tsuite no Chousa) of Osaka University. Consistent with our theoretical model’s
predictions, we find that respondents with an altruistic or strategic/exchange bequest motive
work more (empirically measured by individual’s working hours per week) at the intensive
margin than those without any bequest motive but that respondents with a strategic or exchangebequest motive work less at the extensive margin (i.e., retire earlier, empirically measured byplanned/desired retirement age) than those without any bequest motive. Our findings for the
strategic or exchange bequest motive are entirely plausible because respondents with such a
motive may want to work harder than others before they retire so that they can earn more, leavea larger bequest to their children, and elicit more care from them but that they may want toretire earlier than others so that they can start receiving care from their children sooner.
Moreover, our findings suggest that the altruistic bequest-work relationship in Japan is driven
by relatively young respondents (those aged less than 40 years), which suggests that altruistic
respondents decide their work behavior at a relatively young age. Interestingly, the strategic or
exchange bequest-work relationship is driven primarily by the married male sample. A possible
explanation for this finding is that married males have a greater demand for care from theirchildren because they as well as their wives are potential care recipients.
We employ a battery of robustness checks to show that our empirical findings concerning thebequest-work relationship are highly robust, remaining significant and consistent with thepredictions of our theoretical model even when (i) we use a dummy variable for full-time workin lieu of the number of hours worked per week as an alternative measure of the intensive
margin, (ii) we include a large number of control variables relating to individual- andhousehold-specific factors to ensure that the bequest-work relationship is free from theendogeneity bias arising from omitted variable(s), (iii) we ensure that our results are free fromreverse relationship bias, and (iv) we add a number of proxies for wealth to eliminate thepossibility that bequest motives are merely acting as a proxy for wealth, as we discuss in moredetail in section 3.
We make an original contribution to the literature in at least four respects. First, it is one of thefirst papers to conduct a theoretical and empirical analysis of the impact of bequest motives on
the work and retirement behavior of parents at both the intensive and extensive margins. Many
studies have analyzed the impact of time and monetary transfers from parents on the recipients’(children’s) work behavior (see, for example, Holtz-Eakin et al. (1993), Joulfaian and Wilhelm(1994), Wolff (2006), Dustman et al. (2009), Gong (2009), Brown et al. (2010), Dimova and
Wolff (2011), Elinder et al. (2012), Blau and Goodstein (2016), and Doorley and Pestel (2016)
for studies for other countries and Sugano and Matsuyama (2017) and Niizeki and Hori (2019)
for studies for Japan), and most of these studies find that the receipt of bequests and inter vivos
transfers reduces the work behavior (the workforce participation, the number of hours worked,
and the retirement age) of recipients (the so-called “Carnegie conjecture”). However, we havenot been able to find any papers that analyze the impact of bequest motives on the work
behavior of bequest givers (parents). The only related paper of which we are aware is Brown
et al. (2015), which finds that Croatian retirees are more likely to opt for a larger but deferredstream of pension benefits if they have a stronger bequest motive. To the extent that those whochoose to defer are more likely to continue working, this result implies that bequest motives
have an impact on retirement behavior. Second, to the best of our knowledge, this paper is thefirst to conduct an analysis of the impact of bequest motives on work and retirement behavior
for the case of Japan. Third, this paper uses micro data from the Preference Parameters Study,2which reports an exhaustive list of bequest motives along with respondent’s detailed attributes,
such as wage, family income, full-time vs part-time, number of hours worked per week, andplanned retirement age, pension, etc. Fourth, this paper distinguishes between different bequest
motives (e.g., altruistic, strategic/exchange motives, etc.), as discussed in more detail later.
Our findings have important policy implications for policymakers in Japan. Since individual
work behavior can be altered by changing inheritance taxes, it is very important forpolicymakers to realize that the bequest-work relationship exists but that it varies by bequest
motive in Japan. In the case of a strategic or exchange bequest motive, which affects parents’work behavior as well as retirement decision, inheritance tax policy should be set taking
account both the increased work effort at the intensive margin as well as the induced retirement
effect of this motive. In the case of the altruistic bequest motive, by contrast, there does notseem to be any need to worry about the induced retirement effect, meaning that lowering
inheritance taxes will unambiguously increase labor supply by encouraging individuals to leave
bequests.
The remainder of this paper is organized as follows: section 2 presents the theoretical model ofthe impact of bequest motives on work and retirement behavior, section 3 provides empiricalevidence by using micro data from the Preference Parameters Study of Osaka University to test
the predictions of our theoretical model about the impact of bequest motives on work behavior(e.g., employment status, working hours, and planned retirement age), and section 4 is aconcluding section.
2. The Theoretical ModelIn this section, we present a theoretical model that shows the impact of bequest motives onwork and retirement behavior. In subsection 2.1, we present the basic setup of the model; in
subsection 2.2, we consider the case of altruistic bequest motives; in subsection 2.3, weconsider the case of strategic or exchange bequest motives; and in subsection 2.4, wesummarize our findings.
2.1. Basic Setup
Dynamic optimization models resulting in closed-form solutions to endogenous consumption,saving and labor supply are, to our knowledge, rare. They are often used in quantitative financeand related economics literature to investigate decision-making under uncertainty. For example,
Rogers (2013, p. 110) augments a standard infinite-horizon Merton problem with the intensive
margin of labor supply and numerically simulates the solutions. Similarly, Rogers (2013, p.
99) presents a Merton-type model with endogenous retirement and presents an explicit solution
to the critical value of wealth that would trigger retirement. Farhi and Panageas (2007)
endogenize risky investment with endogenous retirement choice only. This allows the authors
to focus on closed-form solutions. Our model abstracts from risky investment and focuses on
closed-form solutions pertinent to both margins of labor supply in the context of parentoffspring transfers. The dynamic quantitative-theoretical literature with labor supply is large.
The interested reader might refer, for instance, to Bagchi’s (2015) study that numericallysimulates the effect of the U.S. Social Security system on different margins of labor supply inan environment with mortality and labor income risk and also cites many studies that look at
dynamic pension reforms and labor supply distortions.
3Our model features a standard bounded optimal control framework in which we focus on
closed-form solutions by explicitly taking into account the time constraint on leisure. Most
standard theoretical studies with closed-form solutions consider an interior solution withrespect to labor supply (e.g., Bütler 2001) for ease of exposition, but we follow the approachdeveloped in Gahramanov and Tang (2016a; 2016b) for deriving the optimal age of retirement
and hours worked. In addition, under various assumptions, we are able to provide analytic
solutions for the optimal inheritance level.
Our model is set in continuous time, and time itself is denoted by . To derive closed-form
solutions, we attempt to keep the environment as simple as possible. The main decision-maker(the “agent” or “parent”) enters the workforce at birth (0) and exits the model by age
0. The time endowment is normalized to unity. The retirement age () must be chosen
optimally. For each unit of labor endogenously devoted to market work at date , exogenously
determined efficiency units () are supplied to production. The wage per labor efficiency
unit is0. All wage income not consumed flows into the individual’s financial asset
account, which grows at rate . The main decision-maker starts the life cycle with agiven amount of bequest received from her own parent (0), and she finishes the life cyclewith some assets(determined endogenously) that she will bequeath to her offspring at time.
Suppose that culture and social norms help to shape the care level a person might devote to herparent (and possibly to others, such as other family members). The overall amount of carerequires a sacrifice of time and is a strictly increasing function of the bequest received (seesubsection 2.2 for more discussion of this.)
Remark 1. From here on in, we assume that the main decision-maker starts her life with no0), and provides no care to her own parents. This assumption is innocuous
assets (and the resulting care-to-own-parents will bebecause at the start of the model,
exogenously given by assumption and will be mainly driven by the decisions of the parents ofthe main decision-maker. Setting these values to zero allows us to state our forthcoming
solutions in a more compact way and to focus exclusively on the interaction between the main
decision-making agent and her children.
The agent enjoys (derives utility from) private consumption () and personal leisure ().
Note that the agent’s hours of work (1) are endogenous since
is a choice variable.
In what follows, we consider two separate cases—the case of an altruistic bequest motive andthe case of a selfishly motivated strategic or exchange bequest motive.
2.2. Case 1: Altruistic Bequest Motives
When modeling the case of altruistic bequest motives, we assume that the bequest left by theparent increases her utility because it increases the present value of resources available to herchild and thus by implication the child’s ultimate consumption. By contrast, Wilhelm (1996),
Kopczuk (2010), and especially Laitner and Ohlsson (2001) have in mind Barro-type recursive
altruism models in which the parent cares about the consumption and therefore the well-beingof her children, grandchildren, and more distant descendants. These models assume that theinheritance provided by the parent directly influences the consumption available to the child(see eq. 1 on p. 208 in Laitner and Ohlsson, 2001). Laitner and Ohlsson (2001, p. 210) and4

Kopczuk (2010, p. 6) differentiate our formulation from the altruism model and refer to it as
the “egoistic model” or the “joy-of-giving model,” and indeed the two formulations have very
different implications for public policy. However, since we are not concerned about Ricardianequivalence or tax considerations, we can presume that this fine distinction in the parent’s
motivations is not important for our purposes and that our Case 1 corresponds in broad terms
to the “altruistic bequest motive” setting. Wilhelm (2010, pp. 880-881) makes a similarargument (see also Arrondel and Masson, 2006, and Laferrere and Wolff, 2006).
The objective in our altruism model is to maximize
ln

ln
ln Ψ

where

,

,

are positive constants, and(1),

is nonnegative.

Remark 2. Let function Ψ summarize the present value of economic resources available tothe child over the latter’s lifetime as seen from the perspective of the decision-making parent.
We assume that the parent believes that if her offspring is given a larger bequest, this will
increase the present value of resources available to the latter; that is,
0.2
Observe from (1) that a function of the terminal stockis added to the integral, and this“scrap value function” has the standard economic interpretation (e.g., Léonard and Van Long,
1992, pp. 226-229). In other words, the parent attaches some positive value to what she leaves
behind at time
because she has an altruistic bequest motive.
The optimization problem is subject to the dynamic budget equation, control constraints, andthe endpoint conditions given in (2)-(5):
1
0
0

1,
0,
free.

,

(2)
(3)
(4)
(5)

Equation (4) is consistent with Remark 1. Note that the chosen utility function allows us toignore the additional control constraint on. Further, given (5), the solution to the problem
can be obtained by using a transversality condition for a free endpoint with scrap value thatwould essentially equate the marginal benefit of an increase in the terminal asset level to theassociated marginal cost over the entire time interval. For ease of exposition, however, we
proceed with the two-step procedure outlined in the remark below when deriving the solution.
Remark 3. Here we adapt the two-step solution strategy as follows: (i) solve the optimizationorproblem treating
as fixed (i.e.,
is arbitrarily fixed at some amount of2

In principle, it is possible that a larger bequest would discourage, say, work effort and ultimately leave the child
financially worse off (or no better off), but we assume that the parent rules out such a possibility when making adecision.
5“bequest given”), and then (ii) solve for the optimal value ofgiven that consumption and3labor supply are chosen optimally for every possible
value.
In the first step, we thus define the Hamiltonian function
ln

ln
1

where

(6)

,

is a dynamic multiplier. Optimal controls must satisfy the following conditions:
1

,
,

(7)
(8)

and
⇔

max

,

max

(9)

,

ln

ln

1

0 such that if the

A necessary condition is that there exists a dynamic multiplier
Lagrangian of the Hamiltonian
ln

.

ln

1
1 ,

(10)

then (11)-(14) hold:
0,

(11)
0,

1

1

0.

0,

(12)
(13)
(14)

We focus our attention on standard labor supply behavior. Let there be some internal point in
time
∈ 0,
(to be determined) on or after which the agent stops working, and hence
1. Thus,
1 for

∈ 0,

1 for

∈

3

,

,

(15)

.

(16)

Furthermore, since the solution to such dynamic problems can still easily become cumbersome, we will assume
that the discount rate and the interest rate are equal in order to facilitate the analysis.
6

0, then

The complementarity condition implies that if
following system of equations:

1, and we have the

1
for

∈ 0,

(17)

.

If, on the other hand,0, then1, and we have the following system of equations:(18), . Hence, the optimal solution can be found by joining together the solutions offor ∈(17)-(18). Note that the function
is defined over the entire planning interval, and from(17) and (18) we see that it obeys the same law of motion. Since the function is continuous, we
obtain
for
where

∈ 0,

,

(19)

is a constant to be determined.

From (11), we obtain/
Now, note that if

0, then.

(20)

1. Hence, (12) leads to
1/.

1. Substituting this into (21) (and recalling thatin terms ofas

Recall thatthe constant≡), we can express

.

/

(21)

(22)

Thus,
for

∈ 0,

.

(23)

Substituting (23) into (20), we obtain from (18)
,
for

∈

,

(24)

.

Using (5) for an arbitrarily fixed terminal stock value

7, we derive the solution to (24) as

1
for

∈

,

,

(25)

.

Evaluating (25) at, we obtain
≡Λ
1

.

(26)

Next, substituting (23) into (11) and (12) and considering the
0 case (recall that), we solve for the optimal consumption and leisure paths as functions of
:
,

(27)
,

for

∈ 0,

(28)

.

Remark 4. Note from (28) that for the agent to retire before exiting the model, it is necessarythat the labor productivity profile,, decline sufficiently rapidly after some point in time.
Substituting (27) and (28) into (17), we obtain
1
for

∈ 0,

,

(29)

. Using (4), the solution to (29) is
1
(30)
,

for

∈ 0,

. Expression (30) implies that
≡Λ
1

(31)

.
Hence, for a given bequest amount,is the solution to the following equation:
Λ

Λ

8

.

(32)

Remark 5. It is clear from (32) that even a simple dynamic model can easily lead to acumbersome solution, and it might be impossible to derive a closed-form solution. To obtain a
tractable, closed-form solution, we introduce additional simplifying assumptions. First, we
assume that the interest rate
0 (an assumption that is quite reasonable in the case of Japan).
Also, we assume that1
1/ .
Consequently, recalling (22), we obtain
lim Λ

(33)

,

→

2

lim Λ

2

.

2

→

(34)

Thus, setting (33) equal to (34), we can solve for the optimal retirement age for a given bequest
amount. Under the assumption of both roots being real, a positive root takes the form
√ /

(35)

,

where
≡

2

2

(36)

.

Remark 6. It is clear from (36) that an exogenous increase in the amount of the bequest given
would raise the age of retirement. However, the next task is to find the optimal bequest
amount. For that purpose, we need to specify the form of the Ψ function.
For the sake of simplicity, let us assume that the parent believes that a one-unit increase in thebequest given increases the lifetime well-being of her offspring by
0 units, where canbe sufficiently small. Let
.

Ψ

(37)

0, using (22), (27)-(28), (35), and (37), let us rewrite (1) as

Recalling that

Γ

Γ,

(38)

where
Γ ≡

ln
(39)

ln
ln
Γ ≡

,

ln

ln 1

9

.

(40)

The optimal bequest amountis the one that solves
Γ

Γ

(41)

0.

) is

Under the assumption of real roots, the optimal bequest amount (

(42)

,
where
≡

2

.

(43)
) as follows:

Substituting (42) into (35), we obtain the optimal retirement age (
1

2

.

(44)

where
≡2

2

2

Analogously, we can find the optimal leisure profile (supply () during the working life as follows:

.

(45)

), and ultimately the optimal labor

2

≡1

.

(46)

The optimal consumption profile takes the form
2

(47)

.

Notice that.

(48)

is strictly less thanis strictly greater than .
The term, whileTherefore, (48) is strictly positive in sign, indicating that the more the parent cares for her
child’s financial well-being, the larger the bequest she intends to leave. Similarly,

10

4

6

2

2

2

4

2

.

(49)

2

The denominator of (49) is negative since up to the age of retirement,. The numerator
is negative since the term 42exceeds the term 4
62
2
by a positive amount 42
2.
Thus, an increase in the strength of the altruistic bequest motive increases the number ofworking hours.
Finally,.

(50)

Since (49) is positive, so is (50), implying that an increase in the strength of the altruistic
bequest motive delays retirement. Thus, we conclude with
Remark 7. An increase in the strength of the altruistic bequest motive will cause parents to not
only work more hours per week but also to work longer and retire later, as shown by equations(49) and (50).
2.3. Case 2: Strategic or Exchange Bequest Motives
In this subsection, we assume that parents leave a bequest to elicit care and/or attention fromtheir children. This is the so-called strategic or exchange bequest motive discussed by Laitnerand Ohlsson (2001, p. 211) and Bernheim, Shleifer, and Summers (1985). Some questions arise
immediately. Suppose a child took good care of her elderly parents by sacrificing time andresources. How can he/she be sure that her parents will reward him or her properly and will notrenege on their implicit or explicit promise? By contrast, even if parents gave the promised
reward to their child, the latter might still fail to carry out her duties as promised. After all, if
intra-household gifts and exchanges are based on purely selfish motives to begin with, selfish
individuals might consider breaking their promises whenever they felt like it.
Real life is more complex, however. Even if it is in an individual’s self-interest to break an
agreement, often a society develops social customs and rules to minimize such deviant behavior,and such social customs might be easier to enforce between members of one family (who tend
to be bound by intra-household trust and affection) than between total strangers. Moreover,another way to ensure that both parents and children hold up their end of the bargain is for themto draw up and sign a legally enforceable contract (or at least an implicit or verbal contract).
To proceed with our technical analysis simply, we need to specify a quid pro quo bequest/carefunction. Note that care to parents can take many forms. We assume that care takes the formof a time sacrifice on the part of children (e.g., when they spend time interacting with, andentertaining, their parents or running errands for them). Certainly, it is not necessary to assume
that parents and children are expected to always spend time together as nothing prevents an
11

arrangement whereby, for example, a child paints her parent’s fence while the latter is at workor on vacation elsewhere, but to simplify the analysis, we assume in our model that care always
takes the form of spending time with parents. Fundamentally, even though spending time withparents entails various opportunity costs, the reward is a bequest.
Remark 8. Let us introduce the “care function”,, , whereis the vector offunctions, and assume that the care function is known and shaped by social customs andtraditions. In line with the mathematical theory of optimal processes, let functionbecontinuously differentiable in all of its arguments, none of which is a derivative. Assume that
,
,
0
,
,
1 and that
0 . Hence, we assume that a ceteris paribus
increase in the bequest amount
her parent.

increases the amount of care time the child spends withNote that time might enter function in the sense that, before some age, the expected carefrom one’s child might be minimal since the parent is presumably healthy and busy at work
but that it might increase rapidly with time as the parent ages and children mature. Vector
might include, among other things, the child’s bargaining power and outside opportunities (thatis, a child with better outside options would need to be promised a larger bequest to exert thesame amount of care effort).
For any given bequest amount, the parent expects her child to spend,,
fraction oftime with the parent. For example, consider a parent who promises to bequeath$10,000. Suppose that, at a certain point in time, the parent enjoys nine hours of non-sleep
time as leisure, while social customs require that, in this case, the child spend one hour withthe parent (i.e.,,,
1/9 . Thus, the parent enjoys eight hours of leisure alone(away from the child) and one hour with the child. If the promised bequest amount increases
to $20,000, the child would promise to spend, say, an hour and a half with the parent(,,
1/6) at time . In this case, the parent enjoys seven and a half hours of leisurealone, and an hour and a half with the child.
Let the lifetime utility function of the main decision-maker now be
ln
ln 1
ln
,

,

,

,

(1ʹ)
.

Remark 9. We assume that the parent derives utility not only from leisure spent alone but also
from leisure spent with her child. Note from (1ʹ) that when the parent leaves a larger bequest
to her child (is greater), she ends up buying more joint time with the child, and thus, bydefinition, spends less time alone. There is a trade-off between leisure enjoyed privately andleisure enjoyed jointly with the child. Note, moreover, that the parent does not derive any utility
directly from the amount of her bequest or the consumption of her child because she is notaltruistic. The parent’s bequest increases her utility only by increasing the amount of time she
can spend with her child.
Let us for clarity of exposition denote terminal capital stockas
two separate assumptions about the care function, the first one being
12. We now consider,Assumption 1. Care is given by,, whereis positive yet small.

Under Assumption 1, we consider a truly simplistic case, where the care level is simply
proportional to the amount of the assets bequeathed to the child. This greatly facilitates theanalysis, yet leads (as will be seen shortly) to one-sided results. Following the same steps as insubsection 2.2, we can re-state the analogue of (12) as the first-order necessary condition for
leisure:0.

(12ʹ)

Hence, the analogues of (22) and (28) are
≡

/

,

(22ʹ)

and
,
for

∈ 0,

(28ʹ)

, respectively. We can thus rewrite (31) as≡Λ
1(31ʹʹ).
Taking the limit of (31ʹʹ) as → 0, and equating the resulting expression with the analogue ofis replaced with, we solve for the retirement age as follows:(33) (where
/

(35ʹ)

,

where
≡

2

2

.

(36ʹ)

Thus, under Assumption 1, the optimal bequest amount can be computed as in Case 1, this time
rewriting (1ʹ) as (and recalling that
0
Δ

Δ ,

where

13

(38ʹ)

Δ
≡

ln
ln

1

ln
Δ ≡

,
,

(39ʹ)

,

,

,

ln
ln 1
ln

,
,

,

,

(40ʹ)
.

The optimal bequest amount is the amount that solves
≡

Δ

Δ

(41ʹ)

0.

Unfortunately, even under Assumption 1, it is practically impossible to obtainfrom (41ʹ)
as an explicit function of the exogenous parameters. However, let (41ʹ) implicitly define theoptimal bequest amount as a function of exogenous parameters. Consequently,
/
/

(51)

We verify that the right-hand side of (51) can be strictly positive around a range of points
might increase the optimal bequest amount.
satisfying (41ʹ), implying that an increase in
Using this fact and expression (35ʹ) (where we replacewith), we can compute thecomparative statics as follows:

(50ʹ)
,
where
≡

2

2

.

(52)

Even when (51) is positive, the sign of (50ʹ) is ambiguous. The same ambiguity is certainly
observed when considering the number of hours worked during the working phase of life,
which can be expressed as
14

≡1

(46ʹ)

1

Remark 10. Under Assumption 1, both the retirement age and hours worked move in the same
direction in response to the rise in the strength of the exchange motive (see (46ʹ) and (50ʹ)).
Intuitively, in the case of the quid pro quo strategic or exchange bequest motive, the decisionmaking parent wants to extract as much care as possible from her child and for that reason she
wants to leave as large a bequest as possible, which follows from equation (51). Thisencourages the parent to maximize lifetime income, which in turn requires the parent to supply
more labor and to retire later. However, in order to be able to afford to leave a larger bequest,
the parent might want to reduce private consumption, which can be compensated for byincreasing the amount of leisure. Interestingly, equation (46ʹ) implies that if the strategic or
exchange bequest motive induces the parent to increase her labor supply at the intensive margin,
it will also induce her to retire later, and conversely. Thus, both the retirement age and numberof hours worked move strictly in the same direction under Assumption 1.
However, in reality, younger parents tend to have less need for care and attention from theirchildren. Earlier in life, people are healthier and/or they find it harder to distract their children,
who are at the early stages of their studies and career. More importantly, when parents arepreoccupied with their work duties, they feel less lonely and less vulnerable. However, when
they age and approach retirement age (and especially when they are less preoccupied with theirformal work duties), their need for attention might increase. We thus propose an alternative
specification for the care function, as given by the following assumption.
Assumption 2. Care is given by
,
where

and

,

(53)

,

1

are exogenous parameters.

Thus, under the second assumption, the care function takes a logistic form (which isdifferentiable) and again rises with the amount of bequest left,. However, notice that during
younger working ages (whenis small), the level of care is low. As the agent ages andthus approaches retirement (→ 1), the care level demanded from the child can rise rapidly.
When care is given by (53), we can try to derive the analogue of (12ʹ), which now will becomemuch more complicated.
0,
where

≡

1

,

1
15

(54)

(12ʹʹ)

≡1

(55)

.

1

≡ 1. Next, we obtain

We can see that, in Assumption 1, essentially
≡
2

4
2

2

2
2

.

(22ʹʹ)In what follows, it is important to solve (12ʹʹ) for leisurewhen
0 so that dynamic
budget constraints can be used to pin down the optimal retirement age for a given terminal
bequest level. Unfortunately, no closed-form solution exists in this case, which makes it
extremely difficult to analytically infer the effect of a quid pro quo strategic or exchangebequest motive on the optimal retirement age and intensive labor supply. However, we haveconducted a number of computations using various techniques as well as programmed
simulations in GPOPS II (Patterson and Rao, 2014). Some interesting numerical results areprovided in Table 1.
We observe from the last column of Table 1 that parents with a stronger quid pro quo strategic
or exchange bequest motive bequeath more. The second and third columns show that the
optimal retirement age and hours worked move in opposite directions. Hence, we conclude
with the following
Remark 11. Under Assumption 2, it is possible that the stronger the quid pro quo strategic or
exchange bequest motive, the larger the number of working hours and the earlier the retirementage, as shown by Table 1.
2.4. Summary
To summarize, our theoretical model has shown that different types of bequest motives havedifferent impacts on the work behavior of households. Households with a stronger altruistic
bequest motive unambiguously work more hours and retire later than households with a weaker
bequest motive, but the impact of a strategic or exchange bequest motive on work behavior istheoretically ambiguous. Households with a stronger strategic or exchange bequest motive may
work more or fewer hours and retire earlier or later than households with a weaker strategic or
exchange bequest motive.
It is entirely possible that some parents would expect much more care specifically during theretirement stage, while in general some parents would seek greater attention when they are lesspreoccupied with their current jobs. The flexibility of (53) allows us to generate various shapes
for the care function. Under different parameterisations, the impact of a strategic or exchangebequest motive on the timing of retirement can still be ambiguous because, on the one hand,the parent wants to work longer to increase her lifetime income and the amount of her bequest
in order to elicit more care from children, while on the other hand, she might want to retireearlier so she can start receiving care from her children sooner. Thus, when a strong strategic
or exchange bequest motive is present, bequest motives have a complex impact on various

16margins of work behavior. A careful empirical analysis is needed to shed light on theseinteractions, and this is precisely what we do in section 3.
3. Empirical Analysis
In this section, we present the results of our empirical analysis of the impact of bequest motives
on the retirement behavior of households in Japan using micro data from the Preference
Parameters Study of Osaka University. More specifically, in subsection 3.1, we derive testable
hypotheses for a Japanese individual from our theoretical analysis; in subsection 3.2, we
explain our data source and sample selection criteria; in subsection 3.3, we explain ourestimation model and variable definitions; in subsection 3.4, we conduct a univariate analysis
of individual work behavior under different bequest motives; and in subsection 3.5, we present
and interpret our estimation results.
3.1. Hypothesis Development
In this subsection, we derive testable hypotheses from our theoretical analysis in section 2. Our
theoretical model predicts that a parent with a stronger altruistic bequest motive will leave alarger bequest to her children and thus work more at both the intensive margin (see Remark 7
on page 11). Thus, the testable hypothesis regarding the altruistic bequest motive is as follows:
H1: The stronger an individual’s altruistic bequest motive, the larger the bequest she will leaveto her children and the more she will work at both the intensive and extensive margins.
By contrast, our theoretical model reveals that an individual with a strategic or exchangebequest motive confronts a dilemma. On the one hand, she wants to work more in order to beable to earn more, to leave a larger bequest to her children, and to elicit more care from them,but on the other hand, she wants to work less so that she can spend more time with (and receive
more care from) her children. As a result, the net impact of this type of bequest motive on theamount of work at the intensive margin ( see Remark 11 on page 16) is ambiguous. However,since the social norm in Japan is to work hard, a Japanese individual may work more at theintensive margin (for example, work more hours per week) in order to earn more, to leave alarger bequest to her children, and to elicit more care from them, but retire earlier in order tobe able to start receiving care from her children sooner. Thus, the testable hypothesis regarding
the strategic or exchange bequest motive is as follows:
H2: An individual with a strategic or exchange bequest motive will work more at the intensive
margin but work less at the extensive margin (i.e., retire earlier).
Hypothesis H1 is framed in terms of a continuous variable measuring the strength of thealtruistic bequest motive, and H2 is framed in terms of a variable measuring how much value
the parent places on spending time with her children, but as discussed in subsection 3.2 below,
we only have discrete information on whether or not respondents have each type of bequest
motive. Therefore, we test these hypotheses by analyzing how the work behavior of a
respondent with an altruistic or strategic/exchange bequest motive compares with that of a
respondent with no bequest motive whatsoever.

173.2. Data Source and Sample Selection Criteria
In this subsection, we discuss the data source we use for our analysis and our sample selection
criteria. We use micro data from the 2012 wave the Preference Parameters Study (Kurashi no
Konomi to Manzokudo ni tsuite no Chousa) of Osaka University, a panel survey that was
conducted in Japan and three other countries by the 21st Century Center of Excellence (COE)
Program “Behavioral Macrodynamics Based on Surveys and Experiments” and the Global
COE Project “Human Behavior and Socioeconomic Dynamics” of Osaka University. The
survey was conducted annually during the 2003-13 period, but we chose to use data from the2012 wave because the question about bequest motives was not asked in every year and 2012
was the most recent year for which this question was asked. The survey collects data on anationwide random sample of both sexes, and the 2012 survey had 4588 respondents.
The micro data from the 2012 wave is perfectly suited for our purposes because it collects
detailed information on bequest motives, working hours, employment status (full-time vs. parttime), planned retirement age, and all of the other variables that we need for our analysis. The
complete survey instrument (questionnaire form) for the survey that we used for this analysis
can be found at the following website:
https://www.iser.osaka-.ac.jp/survey_data/doc/japan/questionnaire/english/2012QuestionnaireJAPAN.pdf
Since the data source we used is a panel survey, it would have been preferable to do a panel
analysis with fixed effects to control for individual heterogeneity, but unfortunately, we were
not able to do so because some questions such as the ones pertaining to bequest motives were
not asked in every wave. Fortunately, however, the survey we used collects information on amultitude of individual and household attributes, so we were able to control for such
heterogeneity by including a large number of individual- and household-related covariates.
The sample selection criteria we used are as follows:(1) We dropped all observations for which there were missing values for at least one of thevariables used in the estimations.
(2) We dropped all observations for which respondents are not currently working.
(3) We dropped all observations for which respondents have no children because we wereinterested in examining whether respondents’ intention of leaving bequests to their children
has any impact on their work behavior.
(4) Since the value of the wage rate (WAGE) was unreasonably high or low in some cases dueto the reported number of hours worked being unreasonably high or low, we dropped allobservations that were in the top 1% or the bottom 1% of the distribution of WAGE.
3.3. Estimation Model and Variable Definitions
In this subsection, we describe the estimation model and the variables we use from the survey
questions to test the hypotheses regarding the impact of bequest motives on individuals’ work
behavior that we derived and discussed in the subsection 3.1. The question number inparentheses for each variable shows the survey question we used to construct that variable.
18

The estimation model for an individual i’s work behavior is as follows:
,

(56)

where
is the dependent variable that represents work-related outcomes for the intensive andextensive margins for individual i as defined below:
Log(HRSPERWEEK) = the natural logarithm of the number of hours the respondent is working
per week (a measure of the intensive margin, survey question B9), andLog(RETAGE) = the natural logarithm of the age at which the respondent plans to retire (ameasure of the extensive margin, survey question B12).
HRSPERWEEK pertains to the intensive margin (i.e., how much the respondent works during
a given period of time, given that he or she works) whereas RETAGE pertains to the extensive
margin (i.e., how long the respondent plans to work before retiring completely). We estimate
a separate equation for each of these two dependent variables4. More precisely, we estimate the
HRSPERWEEK and RETAGE equations using ordinary least squares.
In addition, we use the probability of working full-time as an alternate measure of the intensive
margin in our robustness checks to be presented later:
FULLTIME = 1 if the respondent is working full-time and 0 if the respondent is working parttime (survey question B13b)
The explanatory variables pertaining to bequest motives in the estimation model above
which are of most interest for our purposes, are as follows:,

BEQMOTALT= 1 if the respondent is planning to leave a bequest to his or her
child(ren) under any circumstances and 0 otherwise (survey question A31)
= 1 if the respondent is planning to leave a bequest to his or her
BEQMOTCARE
child(ren) only if his or her child(ren) provide care (including nursing care) during old age and0 otherwise (survey question A31)
BEQMOTFIN= 1 if the respondent is planning to leave a bequest to his or her
child(ren) only if his or her child(ren) provide financial assistance during old age and 0
otherwise (survey question A31)

4

It is quite possible that the two work-related variables—number of hours worked per week and planned
retirement age—are seemingly contemporaneously correlated. For example, an individual who plans to retireearlier may choose to work for more hours per week. This can make the error terms of the two work-related
dependent variables (Log(RETAGE) and Log(HRSPERWEEK)) contemporaneously correlated. These equations
can be estimated jointly using the Seemingly Unrelated Regression (SUR) method. However, the joint (SUR)
estimates and the single equation (ordinary least squares or OLS) estimates are identical when the right-hand side
variables are the same. In our case, the right-hand side variables are the same in the two equations, and hence weestimate each equation separately.
19

BEQMOTBUS= 1 if the respondent is planning to leave a bequest to his or her
child(ren) only if his or her children carry on the family business and 0 otherwise (survey
question A31)
BEQMOTWEAK= 1 if the respondent does not plan to make special efforts to leavea bequest to his or her child(ren) but will leave whatever is leftover and 0 otherwise (survey
question A31)
We regard BEQMOTALT as an altruistic bequest motive because the respondent does not
impose any preconditions for leaving a bequest, and we regard BEQMOTCARE,
BEQMOTFIN, and BEQMOTBUS as strategic or exchange bequest motives because therespondent imposes preconditions for leaving a bequest in all three cases. The default
categories are respondents who do not plan to leave a bequest to their children under any
circumstances and respondents who want to leave a bequest to their children but will not
because they do not have the financial capacity to do so. Since we benchmark on individuals
with no bequest motive5, the ′ measure the impact of each type of bequest motive on theindividual’s work behavior. For instance, the sign and significance ofand
can shed
light on the impact of altruistic and strategic or exchange bequest motives on work behavior asstated in H1 and H2 above, respectively.
To control for the impact of other individual- and household-specific factors on the three workrelated outcomes, we include the following variables in vector x following, for example, Brown
et. al (2015), Farhi et. at (2007), and Honig (1998), among others:
Log(WAGE) = the natural logarithm of the respondent’s wage rate (hourly wage) (survey
questions B9 and B18)
In the data source we used, respondents have a choice between writing down his or her monthly
salary or his or her hourly wage. For respondents who wrote down their hourly wage, we used
this information as is, but for respondents who wrote down their monthly salary, we converted
their monthly salary to an hourly wage by dividing their monthly salary by the number of hours
worked per month. Since respondents are asked to report the number of hours they work per
week, we converted it to the number of hours they work per month by multiplying it by 52,
then dividing by 12 (or by multiplying by 4.33333).
Since the work decisions of respondents will be affected by the earned income of otherhousehold members, we also include the respondent’s household earned income excluding the
respondent’s own earned income:Log(OTHERINC) = the natural logarithm of non-respondent earned income, which was
calculated as the respondent’s household earned income excluding the respondent’s own
earned income (survey questions B19 and B36)

5

“No bequest motive” includes the following three out of eight responses to the bequest motive question in thesurvey: “the repondent does not plan to leave a bequest to his or her child(ren) under any circumstances because
doing so may reduce their will to work,” “the respondent does not plan to leave a bequest to his or her child(ren)under any circumstances because he or she wants to use his or her wealth himself or herself,” and “the respondent
wants to leave a bequest to his or her chid(ren) but he or she won’t because he or she does not have the financial
capacity to do so.”20

BEQREC = 1 if the respondent has received a bequest (including real and financial assets) witha total value of 5,000,000 yen or more from his or her parents or parents-in-law in the past and0 otherwise (survey question A32)
BEQEXP = 1 if the respondent expects to receive a bequest (including real and financial assets)with a total value of 5,000,000 yen or more from his or her parents or parents-in-law in the
future and 0 otherwise (survey question A33)
We include wealth-related variables such as WAGE, OTHERINC, BEQREC, and BEQEXP toeliminate the possibility that bequest motives are merely acting as a proxy for wealth, and webelieve that BEQREC and BEQEXP are especially suitable for this purpose because they arelargely exogenous, being the decision of the respondent’s parents.
Furthermore, we include the following personal and work-related attributes of the respondent
to eliminate the possibility of omitted variable(s) (endogeniety) bias that can bias the bequestwork relationship due to the model’s errors ( ) being correlated with bequest motives6:
MALE = 1 if the respondent is male and 0 if the respondent is female (survey question B1)
MARRIED = 1 if the respondent is married or cohabiting with a partner and 0 if the respondentis never married, divorced, widowed, or separated and in the process of getting divorced(survey question B2)
Log(AGE) = the natural logarithm of the respondent’s current age (survey question B4)HEALTH = the respondent’s health status on a scale of 1 to 5 (with 5 being the highest) (survey
question B51)
WORRY = the extent to which the respondent is worried about his or her life after age 65(future life in the case of respondents who are 65 or older) on a scale of 1 to 5 (with 5 being
the highest) (survey question A1)
WORK = the extent to which the respondent feels that “work is something to live for” on ascale of 1 to 5 (with 5 being the highest) (survey question A1)
WORKSAT = the extent to which the respondent is satisfied with work on a scale of 1 to 5
(with 5 being the highest) (survey question B18)SALWKR = 1 if the respondent is a salaried worker and 0 if the respondent is self-employed
or a family worker (survey question B13a)
PENSION = the proportion of the living expenses after the retirement of the respondent andhis or her spouse (if any) that the respondent expects to be able to cover using public pension
benefits (in percent) (survey question B42)
NUMCHILDREN = the number of children the respondent has (survey question B15)

6
For example, omitting MALE may cause
to be correlated with bequest motives (main contributor to household wealth in Japan.

21) since males are theGAMBLE = 1 if the respondent gambles at least several times a year and 0 otherwise (included
as a proxy for the degree of risk aversion) (survey question B57)
We believe that our estimates are free from reverse relationship (endogeneity) bias—a bias
arising from the fact that the respondent works hard simply because he/she enjoys working,that he/she ends up being able to accumulate more wealth than he/she can use himself/herself
because he/she works harder, and that this makes it easier for him//her to leave a bequest-because a reverse relationship is more likely to be observed for older workers (who are more
likely to have accumulated a significant amount of wealth) whereas our results are driven byyounger workers (as we show later). Moreover, we include WORK and WORKSAT (both ofwhich are presumably fundamental or exogenous variables) to eliminate the possibility ofreverse relationship bias. Note, finally, that, even if including WORK and WORKSAT is not
sufficient to eliminate reverse relationship bias, the survey we used lists five types of bequest
motives (BEQMOTALT, BEQMOTCARE, BEQMOTFIN, BEQMOTBUS, and
BEQMOTWEAK), and respondents who accumulate more wealth than they can use
themselves because they enjoy working will presumably be more likely to have a weak(unintended) bequest motive (BEQMOTWEAK) rather than an altruistic bequest motive(BEQMOTALT) or a strategic or exchange bequest motive for care (BEQMOTCARE). For allof these reasons, reverse relationship bias is unlikely to be applicable in the case of our main
variables of interest.7
3.4. Univariate Analysis
In this subsection, we conduct a univariate analysis of the variables relating to work behavior
and bequest motives. As can be seen from Table 2, the mean values of the three work-related
outcomes are as follows: 59.4% of the sample works full-time, the average number of hours
worked per week is 41.3, and the average planned retirement age is 64.7 years. The averageplanned retirement age is reasonable because, in Japan, the mandatory retirement age (and theage at which workers can start receiving public pension benefits) are in the process of being
raised from 60 to 65.
As for bequest motives, 29.4% of the sample has an altruistic bequest motive, 3.0% of thesample has a strategic or exchange bequest motive pertaining to providing care to parents, 0.8%of the sample has a strategic or exchange bequest motive pertaining to providing financial
assistance to parents, 0.8% of the sample has a strategic or exchange bequest motive pertaining
to carrying on the family business, 47.3% of the sample has a weak bequest motive, and 18.7%of the sample has no bequest motive at all.
Among the strategic or exchange bequest motives, we confine our discussion to the motive
pertaining to providing care to parents because this is the motive that is closest in spirit to ourtheoretical model and because the shares of the other strategic or exchange bequest motives are
7

Moreover, respondents who worked for many hours per week and accumulated considerable wealth as a result
may or may not choose to leave a bequest. For example, Andrew Carnegie strongly opposed leaving inheritances
to one's children even though he worked hard and became one of the world's wealthiest men because he felt that
it would weaken their will to work and to contribute to society (see Carnegie, 1962; this motive corresponds tothe first response in footnote 5). Indeed, he set an example by giving away all of his massive wealth to charitablecauses and leaving nothing to his daughter, and there are many other wealthy individuals who behave similarly.
Thus, we believe that bequest decisions arise from deep parameters that are exogenous and that whether or not
one has a bequest motive is independent of one’s work effort or wealth level.
22less than 1% of the sample. Moreover, the weak bequest motive is not related to H1 and H2 so
we do not discuss the results for this motive either although we include all bequest motives inthe estimation model so we can estimate the partial effects
andof the bequest motives
in which we are interested, i.e., BEQMOTALT
and BEQMOTCARE.
Before turning to our regression analysis, we present the results of our univariate analysis of
the bequest-work relationship (as hypothesized in H1 and H2 ) in Table 3 with the averagevalues of the two work-related outcomes being broken down by bequest motive. We can see
from this table that the outcome variables differ substantially by bequest motive in systematicways. For example, respondents with an altruistic bequest motive (those who plan to leave abequest to their children under any circumstances) show higher values of both outcome
variables than other respondents: i.e., they work more hours per week and plan to retire later.
By contrast, respondents with a strategic or exchange bequest motive for care (those who plan
to leave a bequest to their children only if they provide care (including nursing care) during oldage) work more hours per week but plan to retire earlier than other respondents.
Our theoretical model showed that those with an altruistic bequest motive work more and retire
later than others but that those with a strategic or exchange bequest motive tend to work more
but retire earlier than others. Thus, our preliminary findings based on univariate analysis are
fully consistent with H1 and H2 regarding the bequest-work relationship. However, we needto see whether these findings hold even after we control for the impact of individual- andhousehold-specific factors on the two work-related outcomes using regression analysis, which
is what we do in the next subsection.
3.5. Estimation Results and Empirical Findings
In this subsection, we present and discuss the estimation results of our econometric model inequation (56) for the work behavior of individuals in Japan with emphasis on the impact of thebequest motives of interest,
thereon. More specifically, we present and discuss theestimation results for the two (dependent) variables—one for work at the intensive margin, i.e.,
the number of hours worked per week and the other for work at the extensive margin, i.e., theplanned retirement age. Our interest in individual- and household-specific factors (islimited to controlling for their impact on individuals' work behavior.
3.5.1. The bequest-work relationshipWe present the estimation results for the bequest-work relationship in Tables 4-5. Table 4shows the results for the number of hours worked per week, while Table 5 shows the results
for the planned retirement age, both estimated using ordinary least squares.
We show estimation results for the full sample, for the married sample, for the male sample,
and for the married male sample for all ages and for those aged 40 or older because work
behavior tends to differ by marital status, gender, and age and because this may help us to findthe subsample, if any, that drives the bequest-work relationship in the full-sample. As discussed
earlier, we are interested primarily in the altruistic bequest motive and the strategic or exchangebequest motive for care, and we present these results under “bequest motives of interest” inTables 4-5.
23

We find thatis positive and statistically significant at the 10% levels for the full sample(see the column marked “Both sexes, all ages”) in log(HRSPERWEEK) regression, as shownin Table 4. Thus, as in the case of our univariate analysis, the number of working hours per
week of respondents with an altruistic bequest motive (BEQMOTALT) is significantly higher
than that of respondents without any bequest motive. However, we do not find similar support
for respondents’ planned retirement age as
is statistically insignificant in thelog(RETAGE) regression, as shown in Table 5. The fact that more significant results are
obtained for all ages than for the 40-plus sample in the log(HRSPERWEEK) regression
suggests that the significant altruistic bequest-work relationship for the full sample appears tobe driven by respondents who are less than 40 years old, which in turn suggests that altruistic
respondents modify their work behavior at a relatively early age. Thus, we find partial supportfor H1 (i.e., an altruistic bequest-work relationship) in the case of Japan.
Our empirical results pertaining to H2 are consistent with theoretical predictions as well aswith the univariate analysis discussed in subsection 3.4 for both work-related outcomes. We
find that, which measures the strength of the strategic or exchange bequest-work
relationship, is positive and statistically significant at the 5% level for the full sample (see thecolumn marked “Both sexes, all ages”), as shown in Table 4, and negative and statisticallysignificant at the 5% level in the log(RETAGE) regression, as shown in Table 5. These results
imply that the number of hours worked per week of respondents who plan to leave a bequest
only if their children provide care (including nursing care) during old age (BEQMOTCARE)
is significantly higher but that their planned retirement age is significantly lower than that ofrespondents without any bequest motive. These results provide strong support for H2.
Looking at the results for various subsamples, the strategic or exchange bequest-work
relationship is stronger for the male sample than for both sexes in the log(HRSPERWEEK)
regressions (in fact,
is statistically significant at the 1% level in the male sample of allages). This suggests that the strategic or exchange bequest motive affects the number of hours
worked per week of male respondents more than that of female respondents and that male
respondents are the ones driving the results for the full sample.
Moreover, the strategic or exchange bequest-work relationship is stronger for the married malesample than for the full male sample in the log(RETAGE) regression. This suggests that thestrategic or exchange bequest motive affects the planned retirement age of married males morethan it affects that of unmarried males, which suggests that it is married males who are driving
the results for the full sample (our unreported results for female respondents provide further
support for this claim). A possible explanation for this finding is that married males have agreater demand for care from their children because they as well as their wives are potential
care recipients8.
Our interpretation of the strategic or exchange bequest-work relationship is that respondents
with a strategic or exchange bequest motive tend to work more intensively than others before
they retire so that they can earn more, leave a larger bequest to their children, and elicit morecare from them after they retire but that they tend to retire earlier than others so that they canstart receiving care from their children sooner.
8

Our unreported results indicate that the strategic or exchange bequest-work relationship is supported for
respondents aged less than 50 years old. In other words, the bequest-work relationship is driven by relatively
young married couples in general and young married males in particular. This makes sense since planning forbequests and retirement is an issue for young working couples with children.
24Comparing our results for the altruistic and strategic/exchange bequest motives,
is morethan twice as large as
in almost all cases, as can be seen from Tables 4 and 5, implyingthat the strategic or exchange bequest motive (whereby parents leave a bequest to their children
in exchange for receiving care) has a much greater impact on their employment status andworking hours than the altruistic bequest motive (whereby parents give a unilateral transfer totheir children without receiving anything in return).
3.5.2. The impact of other factors on work behavior
In this subsection, we discuss our findings relating to the other factors that can affect the various
work-related outcomes considered in the estimation model. We included the sixteen control
variables discussed in subsection 3.2, plus the natural logarithm of wage squared to account forpossible non-linearity in the impact of wages. We provide explanations of the factors that are
relevant and important in the Japanese context.
3.5.2.1. Wages and other income
The net effect of the respondent’s wage rate (WAGE) on the number of hours worked per week
is positive. More specifically, the marginal effect of an increase in the wage rate is
2 , whereis the wage rate, which equals 1.097 2
0.081
0.935 for the fullsample in the log(HRSPERWEEK) regression (see the column marked “Both sexes, all ages”
in Table 5). The effect seems to be intuitively reasonable as it implies that a one percentage
point increase in the wage rate increases the number of hours worked per week by less than
one percentage point.
By contrast, the respondent’s wage rate has a consistently negative and statistically significant
impact on the planned retirement age, as shown in Table 6, presumably because leisure is aluxury good, the demand for which increases (causing a decline in labor supply) as income
increases. More specifically, the marginal effect of an increase in the wage rate is 0.161
2
0.01
0.141 for the full sample in the log(RETAGE) regression (see the column
marked “Both sexes, all ages” in Table 6).
As expected, an addition to non-respondent earned income (OTHERINC) induces respondents
to retire earlier, again presumably reflecting the fact that leisure is a luxury good.
3.5.2.2. Bequest receipts and bequest expectations
Bequest receipts (BEQREC) and bequest expectations (BEQEXP), both of which are a measureof nonwage income, should have qualitatively similar impacts as non-respondent earned
income (OTHERINC) on individual work behavior, but the impact of BEQREC is neverstatistically significant, while BEQEXP has a negative and statistically significant impact in
the log(RETAGE) regression. The latter finding implies that respondents expecting to receive
bequests plan to retire earlier than respondents without such expectations, as expected.

25

3.5.2.3. Gender, age, and marital status
The impact of gender (MALE) is significantly positive as expected, reflecting the social normin Japan that males are expected to work more than females both at the intensive and extensive
margins.
As for the impact of marital status (MARRIED), being married shortens working time
significantly at both the intensive and extensive margins in the full sample but does not have asignificant impact on working time in the male sample. Our finding for the male sample mayarise because the desire of married males to spend time with their wives and children, which
would tend to reduce their working time, is offset by the social norm in Japan that wives beara disproportionate share of the burden of housework and childrearing, which would enablemarried males to increase their working time.
The respondent’s age (AGE) has a negative and statistically significant impact on the numberof hours worked per week but has a positive and statistically significant impact on the planned
retirement age. The former finding is plausible because mental and/or physical fatigue
presumably increases with age, reducing how much the respondent can work at the intensive
margin. The latter finding suggests that respondents postpone retirement as they get older,perhaps because they gradually realize that they do not have enough resources to finance theirliving expenses during retirement.
3.5.2.4. Work importance, work satisfaction, and occupation typeThe importance of work (WORK) generally has a positive and statistically significant impact
on the number of hours worked per week and on the planned retirement age, meaning that
respondents for whom work is more important work more and work longer, which is as one
might expect.
As expected, work satisfaction (WORKSAT) has a positive and statistically significant impact
on the extensive margin (i.e., the planned retirement age), meaning that respondents who aresatisfied with work, work longer but this is not the case at the intensive margin.
As for the impact of occupation type (SALWKR), salaried workers plan to retire earlier than
the self-employed. This result is as one might expect because salaried workers face a mandatory
retirement age, whereas the self-employed do not, and because the pension benefits of salaried
workers are higher than those of the self-employed in Japan.
3.5.2.5. Public pension benefits
The generosity of public pension benefits (PENSION) has a negative and statisticallysignificant impact on the number of hours worked per week and on the planned retirement age(Honig (1998) reports similar results for a sample of 590 white married women in the UnitedStates). This is evidence of the induced retirement effect identified by Feldstein (1974).
3.5.2.6. Number of children
As for the impact of the number of children (NUMCHILDREN), it does not have a significant
impact on either work-related outcome.

26

3.5.2.7. Risk preference, health status, and worry about retirement
As for the impact of the degree of risk aversion (GAMBLE), risk-loving respondents who liketo gamble do not differ significantly from other respondents for the number of hours worked
per week or for their planned retirement age in the case of both sexes. Farhi and Panageas(2007) find that individuals who wish to retire earlier are less risk-averse and invest more in
the stock market, but our finding that there is not a statistically significant association between
the degree of risk aversion and the timing of retirement implies that Farhi and Panageas’s(2007) finding does not apply in the case of Japan. However, this result might be due to theweak proxy we use for risk aversion.
The health status (HEALTH) of males delays their planned retirement age, which is in linewith the findings of Brown et al. (2015), who report that Croatian retirees in good health are
more likely to opt for a deferred retirement package.
Finally, worry about life after 65 (WORRY) does not have a statistically significant impact oneither work-related outcome.
3.6. Robustness Checks
In this section, we discuss the large number of robustness checks that we conducted for our
empirical analysis. First, we used the probability of working full-time as an alternative measureof the intensive margin. The model is estimated using the probit method. The results for themarginal effects are shown in Table 6, and as can be seen from this table, the results are
generally very similar to those for the number of hours worked per week, especially for thebequest motive-related variables that are of the most interest to us. Even though working fulltime is a weak proxy for work at the intensive margin because it is not a continuous variable,
it shows that individuals with an altruistic or strategic/exchange bequest motive work morethan individuals with no bequest motive at all, as we found when we used the number of hours
worked per week.
We also conducted a battery of other robustness checks, but our main empirical results of thebequest-work relationship remained unchanged and significant. For example, we restricted oursample to households with at least one child since bequest allocation is a parent-child issue.
We also added a long list of individual- and household-specific controls to eliminate theendogeneity bias arising from omitted variable(s). Moreover, our results are free from reverse
relationship bias, as discussed earlier. We also eliminated the possibility that bequest motives
are merely acting as a proxy for wealth by including a large number of wealth-related variables
such as WAGE, WAGE , OTHERINC, BEQREC, and BEQEXP.
4．Conclusion and Policy Implications
In this paper, we conducted a theoretical and empirical analysis of the impact of bequest
motives on the work and retirement behavior of households in Japan using micro data from thePreference Parameters Study of Osaka University to shed light on whether or not households
planning to leave bequests work more or work longer than those not planning to leave bequests.
Our empirical findings are consistent with our theoretical model and show that respondents
with an altruistic or strategic/exchange bequest motive work more at the intensive margin than27

those without any bequest motive but that respondents with a strategic or exchange bequest
motive work less at the extensive margin (i.e., retire earlier) than those without any bequest
motive. Our findings for the strategic or exchange bequest motive are entirely plausible because
respondents with such a motive may want to work harder than others before they retire so thatthey can earn more, leave a larger bequest to their children, and elicit more care from them butthat they may want to retire earlier than others so that they can start receiving care forthemselves and their spouses from their children sooner. Moreover, the altruistic bequest-work
relationship in Japan is driven by relatively young respondents (those aged less than 40 years),
which suggests that altruistic respondents decide their work behavior at a relatively young age.
Interestingly, the strategic or exchange bequest-work relationship is driven primarily by themarried male sample. A possible explanation for this finding is that married males have agreater demand for care from their children because they as well as their wives are potential
care recipients.
We employ a battery of robustness checks to show that our empirical findings concerning thebequest-work relationship are highly robust, remaining significant and consistent with thepredictions of our theoretical model even when (i) we use a dummy variable for full-time workin lieu of the number of hours worked per week as a measure of the intensive margin, (ii) we
include a large number of control variables relating to individual- and household-specificfactors to address the endogeneity bias arising from omitted variable(s), (iii) we ensure that thebequest-work relationship is free from reverse relationship bias, and (iv) we add a number ofproxies for wealth to eliminate the possibility that bequest motives are merely acting as a proxyfor wealth.
Our findings have important implications for policymakers in Japan. Since individual work
behavior can be altered by changing inheritance taxes, it is very important for policymakers torealize that the bequest-work relationship exists but that it varies by bequest motive in Japan.
In the case of a strategic or exchange bequest motive, which affects parents’ work behavior aswell as retirement decision, inheritance tax policy should be set taking account both theincreased work effort at the intensive margin as well as the induced retirement effect of thismotive. On one hand, a lower inheritance tax will encourage parents to work more before
retirement so they can leave a larger bequest, and this will contribute to higher economic
growth. However, a lower inheritance tax may also lead some parents to retire earlier thanotherwise so that they can start receiving care sooner, meaning that labor supply may notincrease, on balance, as a result of a reduction in the inheritance tax. In the case of the altruistic
bequest motive, by contrast, there does not seem to be any need to worry about the induced
retirement effect, meaning that lowering inheritance taxes will unambiguously increase work
efforts by encouraging individuals to leave bequests. Since the rapid ageing of Japan’s
population is projected to produce severe shortages of workers in the coming years, reforming
inheritance taxes and other government policies relating to bequests may be an effective wayof encouraging people to work more, if implemented carefully.
Acknowledgements
The empirical work undertaken in this paper utilizes micro data from the Preference Parameters
Study of Osaka University’s 21st Century Center of Excellence (COE) Program “Behavioral
Macrodynamics Based on Surveys and Experiments” and its Global COE Project “Human
Behavior and Socioeconomic Dynamics.” We acknowledge the program/project’s
contributors─Yoshiro Tsutsui, Fumio Ohtake, and Shinsuke Ikeda. We are also grateful toYoung Jun Chun, Shoshana Grossbard, Nobuaki Hamaguchi, Tetsushi Homma, Shinichiro
28

Iwata, Young Lee, Colin McKenzie, Oleksandr Movshuk, Jan Ondrich, Steven Stern, Midori
Wakabayashi, other participants at the Annual Meeting of the Society of Economics of theHousehold, the Family Economics Workshop in Kyoto, the Kobe University-Nanyang
Technological University-Hanyang University Joint Symposium in Economics, and seminars
at ADA University (Azerbaijan), the American University of Sharjah, the Bank of France andl’Ecole des Hautes Etudes en Sciences Sociales, Monash University, Toyama University, theUniversity of Western Australia, and especially Clémence Berson, Soungman Kang, Yoko
Niimi, and Keunkwan Ryu for their valuable comments and discussions. This work was
supported by a grant to Hayat from the faculty research scheme (FRGS), Department of
Finance, Deakin University (2018-19) and JSPS (Japan Society for the Promotion of Science)
KAKENHI Grant Numbers 15H01950, 18H00870, and 15H05728 and a project grant from the
Asian Growth Research Institute to Horioka.

29

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32

Table 1
Numerical results for the case of strategic or exchange bequest motives
These results correspond to the following parameters of the model. The wage rate ( ) is 1, the age of death (25) is 80, the weight on personal consumption ( ) is 0.10, the weight on personal leisure ( ) is 0.20, and theandare equal to 0.20, and 5.00, respectively.
care function parameters

Strength of exchange
motive ( )Age ofretirement

Average number of hours worked
per week

Optimalbequest

0.40
0.50
0.60
0.70
0.80
0.90

60.55
60.10
59.53
59.30
58.93
58.65

40.66
40.77
41.24
41.42
41.84
42.20

5.02
5.33
5.56
5.73
5.88
6.00

33

Table 2
Summary statistics for the variables used in the estimation model.
This table shows summary statistics for Japanese households based on micro data from the 2012 wave of the Preference Parameters
Study (Kurashi no Konomi to Manzokudo nit suite no Chousa) of Osaka University. We used the natural logarithm (log( )) of allcontinuous variables in the estimation model. Variables and relevant considerations are discussed in section 3.

Variable

Mean

Std. dev.

MedianMinimum

Maximum

No. of obs.

105
4.654
90
4.500
1

1574
1574
1574
1574
1574

1
1
1
1
1
1

1574
1574
1574
1574
1574
1574

6527.473
8.784
24.2

1574
1574
1574

Dependent variables
HRSPERWEEK
log(HRSPERWEEK)RETAGElog(RETAGE)FULLTIME
BEQMOTALTBEQMOTCARE
BEQMOTFIN
BEQMOTBUS
BEQMOTWEAK
BEQMOTNONEWAGE
log(WAGE)
OTHERINC

41.34715.151
40
1
3.632
0.480
3.689
0
64.694
5.402
65
35
4.166
0.084
4.174
3.555
0.594
0.491
1
0
Explanatory variables pertaining to bequest motives
0.294
0.456
0
0
0.030
0.172
0
0
0.008
0.087
0
0
0.008
0.091
0
0
0.473
0.499
0
0
0.187
0.390
0
0
Other explanatory variables
1521.143
856.469
1296.154
346.154
7.196
0.501
7.167
5.847
10.045
6.628
13.5
0

log(OTHERINC+1）

2.053

1.004

2.674

0

3.227

1574

BEQRECBEQEXP
MALE
MARRIED
AGE
log(AGE)HEALTHWORRY
WORK
WORKSATSALWKRPENSION
NUMCHILDRENGAMBLE

0.341
0.267
0.571
0.922
51.230
3.917
3.475
3.494
3.576
3.283
0.838
48.221
2.165
0.431

0.474
0.443
0.495
0.267
9.852
0.199
0.917
1.068
0.858
0.944
0.369
24.424
0.431
0.495

0
0
1
1
51
3.932
3
4
4
3
1
55
2
0

0
0
0
0
26
3.258
1
1
1
1
0
5
1
0

1
1
1
1
79
4.369
5
5
5
5
1
95
5
1

1574
1574
1574
1574
1574
1574
1574
1574
1574
1574
1574
1574
1574
1574

Table 3
Distribution of work-related outcomes by bequest motive.
This table shows the mean, standard deviation, and the number of observations of the work-related outcomes for each bequest motive. The fullsample consists of 1574 observations. We classify BEQMOTALT as an altruistic bequest motive, and BEQMOTCARE, BEQMOTFIN and
BEQMOTBUS as strategic or exchange bequest motives as explained in subsection 3.2. FULLTIME is a dummy variable that takes a value of one
for respondents who work full-time and a value of zero for respondents who work part-time, HRSPERWEEK is the number of hours the respondentworks per week, and RETAGE is the respondent’s planned retirement age. See the notes to Table 2 and subsection 3.4 for further details.
FullsampleBEQMOTALTBEQMOTCARE

BEQMOTFIN

BEQMOTBUS

BEQMOTWEAK

BEQMOTNONEHRSPERWEEK
Mean

41.3

44.0

42.9

39.4

41.8

39.9

40.6

Std. dev.
# of obs.

15.2
1574

14.5
463

14.5
48

11.1
12
RETAGE

19.4
13

14.6
744

16.9
294

Mean

64.7

64.8

64.3

63.3

68.5

64.6

64.7

Std. dev.
# of obs.

5.4
1574

5.5
463

5.3
48

5.8
12

8.5
13

5.5
744

4.9
294

Table 4
The bequest-work relationship for the number of hours worked per week
The dependent variable is the natural logarithm of the respondent’s number of hours worked per week. The bequest motives of interest are the altruistic
bequest motive (BEQMOTALT) and the strategic or exchange bequest motive for care (BEQMOTCARE), and the table shows the impact of thesevariables after controlling for the effect of other bequest motives and explanatory variables on the planned retirement age. The model described insubsection 3.2 is estimated by ordinary least squares and the standard errors, within brackets, are robust to heteroscedasticity. The p-values for thesignificance of the coefficients are expressed as *p < 0.1; ** p < 0.05 and ***p < 0. The model’s estimates are shown in the eight columns 2—9 andvary due to variations in the sample, which are based on various combinations of gender, marital status, and/or age. For example, the second column
shows the estimates for the full sample, while the third shows the estimates for individuals of both sexes aged 40 years or above.

Dependent variable: log(HRSPERWEEK)

Explanatory variable

Both sexes,
all ages

Both sexes,age>=40

Both sexes,
married, allages

Both sexes,
married,age>=40

Males,
all ages

Males,
age>=40

Marriedmales, allages

Marriedmales,
age>=40

Bequest motives of interest
BEQMOTALT

0.053

*

0.039

0.048

0.034

0.009

0.021

0.010

0.021

BEQMOTCARE(0.031)0.121**(0.052)(0.034)0.099*(0.056)(0.031)(0.035)***0.141
0.121**(0.053)(0.057)
Other bequest motives(0.027)
0.096***(0.035)(0.029)0.110***(0.037)(0.027)0.102***(0.037)(0.030)0.117***(0.039)BEQMOTFIN-0.063-0.102-0.111-0.170-0.240**-0.240*-0.239**-0.242*BEQMOTBUS(0.105)0.040(0.173)(0.117)0.044(0.169)(0.121)
0.027(0.175)(0.137)0.031(0.171)(0.120)-0.210(0.246)(0.131)-0.177(0.240)(0.119)-0.208(0.247)(0.130)-0.175(0.240)

BEQMOTWEAK

0.028

0.023

0.022

0.020

-0.016-0.008-0.011-0.003(0.030)(0.033)(0.027)(0.029)(0.028)(0.030)1.097*

0.719

1.034*

0.681

0.432

0.504

0.559

0.649

(0.597)log(WAGE)
log WAGE
log(OTHERINC)
BEQRECBEQEXP
MALE
MARRIEDlog(AGE)HEALTH
WORRY(0.030)(0.032)Other explanatory variables(0.590)(0.604)(0.598)(0.641)(0.665)(0.675)(0.704)**-0.055-0.076*-0.052-0.036-0.041-0.045-0.051(0.041)-0.009(0.010)-0.012(0.024)0.017(0.022)(0.040)-0.004(0.011)-0.005(0.024)-0.010(0.023)(0.041)-0.012(0.011)-0.015(0.025)0.011(0.024)(0.041)-0.008(0.012)-0.007(0.025)-0.015(0.024)(0.044)0.005(0.010)0.009(0.020)0.004(0.020)(0.045)0.010(0.011)
0.009(0.021)0.001(0.022)(0.046)0.002(0.010)0.011(0.021)
0.002(0.021)(0.048)0.007(0.011)0.011(0.022)0.0005(0.022)0.530***

0.520***

0.536***

0.526***(0.029)(0.031)(0.031)(0.033)******-0.0090.002(0.042)(0.045)(0.044)(0.046)-0.285***-0.570***-0.270***-0.542***-0.448***-0.672***-0.449***-0.676***(0.065)0.003(0.012)-0.002(0.011)(0.086)0.011(0.013)-0.009(0.011)(0.067)0.0003(0.013)-0.011(0.012)(0.088)0.009(0.014)-0.018(0.011)(0.054)0.009(0.011)
0.011(0.009)(0.079)0.008(0.013)0.008(0.010)(0.055)0.010(0.011)0.010(0.009)(0.080)0.009(0.013)0.007(0.010)-0.081-0.161-0.156

WORK

0.025*

0.028**

0.021

0.024*

0.017

0.018

0.020*

0.022*

WORKSAT(0.013)-0.019(0.013)(0.014)-0.020(0.014)(0.013)-0.014(0.013)(0.014)-0.015(0.014)(0.011)
0.005(0.012)(0.012)0.011(0.013)(0.012)0.002(0.012)(0.013)0.009(0.014)SALWKR

0.058

0.057

0.053

0.054

0.007***-0.0050.010-0.002(0.036)(0.040)(0.037)(0.040)(0.032)(0.034)(0.033)(0.035)

***

**

***

**

-0.001-0.001*****-0.001**PENSION-0.001-0.001-0.001-0.001-0.001(0.0005)(0.001)(0.001)(0.001)(0.0004)(0.0005)(0.0004)(0.0005)

NUMCHILDREN-0.009-0.015-0.001-0.004

0.015

0.010

0.018

0.014

GAMBLE(0.015)-0.009(0.021)(0.017)-0.013(0.022)(0.016)-0.003(0.021)(0.018)-0.009(0.023)(0.012)0.001(0.018)(0.013)0.004(0.019)(0.012)0.001(0.018)(0.013)0.004(0.020)Constant

0.916

3.439

0.909

3.287

4.265*

4.901**

3.781

4.366*(2.209)(2.174)(2.251)(2.233)(2.369)(2.483)(2.502)(2.640)Adjusted R

0.283

0.283

0.292

0.290

0.161

0.177

0.163

0.179

# of observations

1,574

1,369

1,452

1,263

899

792

868

763

2

37

Table 5
The bequest-work relationship for the planned retirement age
The dependent variable is the natural logarithm of the respondent’s planned retirement age. The bequest motives of interest are the altruistic bequest
motive (BEQMOTALT) and the strategic or exchange bequest motive for care (BEQMOTCARE), and the table shows the impact of these variables
after controlling for the effect of other bequest motives and explanatory variables on the planned retirement age. The model described in subsection 3.2
is estimated by ordinary least squares and the standard errors, within brackets, are robust to heteroscedasticity. The p-values for the significance of thecoefficients are expressed as *p < 0.1; ** p < 0.05 and ***p < 0. The model’s estimates are shown in the eight columns 2—9 and vary due to variationsin the sample, which are based on various combinations of gender, marital status, and/or age. For example, the second column shows the estimates forthe full sample, while the third shows the estimates for individuals of both sexes aged 40 years or above.

Dependent variable: log(RETAGE)
Bothsexes,
married,age>=40

Males,
age>=40

Marriedmales, allages

Marriedmales,
age>=40-0.005(0.005)

Bequest motives of interest-0.007-0.006-0.008(0.005)(0.006)(0.006)0.006(0.007)-0.002(0.007)0.003(0.007)-0.005(0.007)-0.022**-0.022**-0.026**-0.027**-0.017-0.019-0.023**-0.026**(0.010)(0.010)(0.010)(0.011)(0.011)(0.012)(0.011)(0.011)Bothsexes,
age>=40

BEQMOTALTBEQMOTCARE

Explanatory variable

Bothsexes,
married,all ages

Males,
all agesBothsexes, allages

Other bequest motives
BEQMOTFIN-0.044**-0.018-0.050**-0.020-0.026-0.015-0.028-0.016BEQMOTBUS(0.021)
0.012(0.025)(0.012)0.006(0.024)(0.024)0.011(0.025)(0.013)0.006(0.024)(0.021)
0.037(0.035)(0.016)0.028(0.034)(0.022)0.035(0.035)(0.016)0.027(0.034)BEQMOTWEAK-0.009*-0.013***-0.009*-0.013**-0.001-0.006-0.002-0.007(0.005)(0.006)(0.006)(0.006)(0.006)-0.319***(0.109)-0.284***(0.108)-0.366***(0.107)-0.338***(0.106)log(WAGE)-0.161**(0.079)(0.005)(0.005)(0.005)
Other explanatory variables-0.153*-0.180**-0.169**(0.078)(0.082)(0.083)log WAGE

0.010*

0.010*

0.012**

0.011*

0.020***

0.018**

0.024***

0.022***(0.005)(0.005)(0.006)(0.006)(0.007)(0.007)(0.007)(0.007)log(OTHERINC)-0.004**-0.003*-0.001-0.002

0.002

0.002

0.002

0.002

BEQREC(0.002)0.002(0.004)(0.002)0.003(0.004)(0.002)0.004(0.004)(0.002)0.005(0.004)(0.002)-0.003(0.005)(0.002)-0.002(0.005)(0.002)-0.002(0.005)(0.002)-0.0002(0.005)BEQEXP-0.013***-0.012***-0.014***-0.013***-0.009*-0.007-0.010**-0.008(0.004)(0.005)(0.004)(0.005)(0.005)(0.005)(0.005)(0.005)

***

***

***

***

-0.006-0.004(0.015)(0.016)***0.140***

0.113***

0.140***

MALE
MARRIEDlog(AGE)

0.049

0.046

(0.004)(0.004)******-0.030-0.022(0.007)(0.007)

***

***

0.119

0.163

0.052

(0.004)

0.121

***

0.049

(0.004)

0.159

***

0.111

(0.012)(0.013)(0.012)(0.014)(0.013)(0.016)(0.014)(0.016)HEALTH

0.003

0.003

0.003

0.004*

0.004*

0.005*

0.005**

0.005**

WORRY(0.002)-0.0001(0.002)-0.002(0.002)0.0005(0.002)-0.001(0.002)-0.0002(0.003)-0.002(0.003)-0.0002(0.003)-0.00238

WORK
WORKSAT(0.002)(0.002)(0.002)(0.002)(0.002)(0.002)(0.002)(0.002)0.010***

0.010***

0.010***

0.010***

0.006**

0.007**

0.005*

0.005*(0.003)(0.003)(0.003)(0.003)(0.003)(0.003)(0.003)(0.003)

**

**

*

*

0.003

0.004

*

0.003

0.005*

0.004

0.004

0.004

0.004

(0.002)(0.002)(0.002)(0.002)(0.003)(0.003)(0.003)(0.003)

***

***

***

***

***

***

***

-0.075***SALWKR-0.067PENSION(0.005)-0.0003***(0.0001)(0.005)-0.0003***(0.0001)(0.006)-0.0003***(0.0001)(0.006)-0.0003***(0.0001)(0.007)-0.0002(0.0001)(0.007)-0.0002*(0.0001)(0.007)-0.0002(0.0001)(0.007)-0.0002*(0.0001)

NUMCHILDREN

0.001

0.00050.001-0.0005

0.003

0.001

0.002

-0.001GAMBLE(0.003)-0.0003(0.004)(0.003)-0.001(0.004)(0.003)-0.001(0.004)(0.003)-0.001(0.004)(0.003)-0.004(0.004)(0.004)-0.006(0.004)(0.003)-0.002(0.004)(0.003)-0.004(0.004)

Constant

4.339***

4.131***

4.362***

4.182***

5.003***

4.764***

5.172***

4.971***(0.299)(0.295)(0.311)(0.314)(0.415)(0.417)(0.405)(0.410)Adjusted R

0.316

0.366

0.323

0.373

0.305

0.344

0.319

0.364

# of observations

1,574

1,369

1,452

1,263

899

792

868

763

2

-0.067-0.06839-0.069-0.070-0.073-0.071

Table 6
The bequest-work relationship for employment status (full-time vs. part-time)
The dependent variable is an indicator variable for whether or not the respondent works full-time. The bequest motives of interest are the altruistic
bequest motive (BEQMOTALT) and the strategic or exchange bequest motive for care (BEQMOTCARE), and the table shows the impact of thesevariables after controlling for the effect of other bequest motives and explanatory variables on the planned retirement age. The model described insubsection 3.2 is estimated by the probit method, the coefficients and the p-values are for (average) marginal effects, and the standard errors, withinbrackets, are robust to heteroscedasticity. The p-values for the significance of the coefficients are expressed as *p < 0.1; ** p < 0.05 and ***p < 0. The
model’s estimates are shown in the eight columns 2—9 and vary due to variations in the sample, which are based on various combinations of gender,
marital status, and/or age. For example, the second column shows the estimates for the full sample, while the third shows the estimates for individualsof both sexes aged 40 years or above.

Dependent variable: FULLTIME (full-time dummy)
Explanatory
variableBothsexes, allages

Both sexes,age>=40

Both sexes,
married, allages

Both sexes,
married,age>=40

Males,
all ages

Males,
age>=40

Marriedmales, allages

Marriedmales,
age>=40

Bequest motives of interest
BEQMOTALTBEQMOTCARE

BEQMOTFIN
BEQMOTBUS
BEQMOTWEAK

**

0.021

0.079*

0.013

0.060*

0.021

0.061*

0.024(0.039)(0.046)(0.035)(0.041)(0.035)(0.040)

0.076

***

*

***

0.126*

0.082(0.044)(0.042)

*

0.078

0.146

**

(0.074)(0.088)(0.050)(0.071)(0.048)(0.069)-0.224(0.159)0.134(0.184)-0.310**(0.154)0.102(0.185)(0.073)(0.089)Other bequest motives-0.375**-0.488***(0.149)(0.111)0.134
0.104(0.189)(0.190)-0.385**(0.167)-0.062(0.118)-0.527***(0.164)-0.071(0.124)-0.369**(0.176)-0.053(0.113)-0.511***(0.179)-0.056(0.116)0.033-0.0080.039-0.0030.022-0.001

0.035

0.015

(0.038)(0.041)(0.040)(0.044)(0.036)(0.041)(0.036)(0.041)

0.141

0.133

0.131

0.128

Other explanatory variables
log(WAGE)
log WAGE
log(OTHERINC)
BEQRECBEQEXP
MALE
MARRIED

1.112(1.157)-0.054(0.079)-0.018(0.015)0.002(0.031)1.088(1.195)-0.052(0.081)-0.019(0.016)0.023(0.033)1.14(1.358)-0.055(0.093)-0.021(0.016)0.009(0.033)1.152(1.386)-0.056(0.095)-0.026(0.017)0.036(0.034)0.436(0.979)-0.019(0.066)0.012(0.013)0.002(0.029)0.557(1.065)-0.027(0.072)0.011(0.014)0.033(0.030)0.314(0.993)-0.011(0.067)0.013(0.013)-0.001(0.029)0.400(1.055)-0.017(0.071)0.013(0.014)0.033(0.03)

0.072**

0.049

0.063*

0.033

0.062**

0.064*

0.058**

0.057*(0.032)(0.035)(0.034)(0.036)(0.029)(0.033)(0.029)(0.033)

***

***

***

***

0.166*

0.228**(0.088)(0.099)***-0.881***-0.559***-0.859***

0.351

0.337

(0.030)(0.033)-0.142***-0.142**(0.053)(0.058)

***

***

0.377

(0.031)

***

0.369

(0.034)***log(AGE)-0.483HEALTH(0.086)0.006(0.016)(0.121)0.001(0.017)(0.092)-0.002(0.017)(0.131)-0.007(0.018)(0.099)0.021(0.015)(0.132)0.013(0.018)(0.098)0.017(0.015)(0.131)0.009(0.018)WORRY

0.0003-0.013-0.013-0.029*

0.017

0.006

0.011

-0.001-0.780-0.496-0.82540-0.590(0.014)-0.008(0.018)-0.023(0.017)(0.015)-0.013(0.019)-0.004(0.018)(0.015)-0.019(0.019)-0.019(0.018)(0.016)-0.024(0.021)-0.003(0.019)(0.014)-0.013(0.018)-0.001(0.017)(0.015)-0.014(0.020)0.011(0.019)(0.014)-0.018(0.018)-0.003(0.017)(0.015)-0.020(0.020)0.010(0.019)SALWKR

0.251***

0.237***

0.253***

0.232***

0.345***

0.300***

0.353***

0.305***PENSION(0.048)0.0001(0.001)(0.050)0.0001(0.001)(0.052)-0.0002(0.001)(0.053)0.000(0.001)(0.061)-0.0004(0.001)(0.062)0.0002(0.001)(0.062)-0.001(0.001)(0.064)-0.0001(0.001)NUMCHILDREN

0.045**

0.051**

0.041*

0.048*

0.043*

0.047*

0.037

0.038

(0.021)(0.024)(0.023)(0.026)(0.023)(0.027)(0.023)(0.026)

*

0.055

*

*

**

0.025

0.029

0.035

0.041

(0.029)(0.03)(0.030)(0.032)(0.027)(0.03)(0.027)(0.03)

Correctly
predicted (%)

77.26

76.77

77.9

70.99

82.31

82.2

81.44

70.99

McFadden R2

0.27

0.27

0.29

0.15

0.28

0.29

0.31

0.15

# of observations

1,574

1,369

1,452

1,263

899

792

868

763

WORK
WORKSATGAMBLE

0.047

0.057

0.065

41