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Time preferences and career investments

01 Aug 2015-Labour Economics (ELSEVIER SCIENCE BV)-Vol. 35, pp 77-92

Abstract: This paper examines the role of time preferences in career investments. We focus on the effects of patience on two types of career investments: work effort and on-the-job search. Whereas the former increases the probability of obtaining a promotion, the latter affects the chance of receiving an outside job offer. We propose a theoretical career model which allows for these two distinct career paths. To test the theoretical predictions, we make use of the DNB Household Survey. This large Dutch longitudinal survey contains detailed information on individual time preferences, on-the-job search behaviour and indicators of work effort. The results show that on-the-job search and work effort increase with patience. The relation between patience and job mobility is more ambiguous. These findings may be hard to reconcile with standard on-the-job search models but can be rationalized by models in which work effort and on-the-job search are substitutes.
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University of Groningen
Time preferences and career investments
van Huizen, Thomas; Alessie, Rob
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Labour Economics
DOI:
10.1016/j.labeco.2015.03.017
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Time preferences and career investments
Thomas van Huizen
a,
, Rob Alessie
b
a
Utrecht University, PO 80125, Utrecht 3508 TC , Netherlands
b
University of Groningen, Netherlands
HIGHLIGHTS
We examine how time preferences affect career investments and mobility.
Workers can invest in work effort and on-the-job search.
Patience is positively related to work and search effort.
The relation between patience and job mobility is ambiguous.
abstractarticle info
Article history:
Received 6 May 2013
Received in revised form 20 March 2015
Accepted 28 March 2015
Available online 7 April 2015
Keywords:
Time preferences
Job search
Work effort
Job mobility
This paper examines the role of time preferences in career investments. We focus on the effects of patience on
two types of career investments: work effort and on-the-job search. Whereas the former increases the probability
of obtaining a promotion, the latter affects the chance of receiving an outside job offer. We propose a theoretical
career model which allows for these two distinct career paths. To test the theoretical predictions, we make use of
the DNB Household Survey. This large Dutch longitudinal survey contains detailed information on individual time
preferences, on-the-job search behaviour and indicators of work effort. The results show that on-the-job search
and work effort increase with patience. The relation between patience and job mobility is more ambiguous. These
ndings may be hard to reconcile with standard on-the-job search models but can be rationalized by models in
which work effort and on-the-job search are substitutes.
© 2015 Elsevier B.V. All rights reserved.
1. Introduction
Climbing up the wage ladderlike any other laddertakes time and
effort. There are two distinct career paths one can follow to reach a
higher position: through (internal) promotions or (external) job mobil-
ity. First, the worker can stay within the rm and exert high effort on the
job in an attempt to obtain a promotion. Second, an employee can
search on the job for vacancies in order to increase the chances of re-
ceiving an outside offer. Since on-the-job search and work effort involve
immediate costs and delayed rewards, they can be considered as invest-
ment activities. It can be expected that the extent to which workers are
willing to make such career investments depends on how they value
future rewards compared to immediate costs. Hence, individual time
preferences are likely to be important for this intertemporal decision-
making process. This paper therefore examines theoretically and empir-
ically how time preferences are related to career investments and there-
by shape the individuals career path.
Recent literature in economics demonstrates that time preferences
predict important social and economic outcomes. Using a large Swedish
sample, Golsteyn et al. (2014) show that a high discount rate measured
at age 13 years is negatively associated with educational attainment, la-
bour supply and income later in life. Cadena and Keys (forthcoming)
also demonstrate that impatience is negatively related to school perfor-
mance and thereby depresses lifetime income: the earnin gs ga p
between impatien t and patient ind ividuals is ov er $75.000 by the
time they reach middle age. Both studies emp hasise the role of time
preferences in the development of human capital. Other papers (e.g.,
Fouarge et al., 201 4) assess to wh at extent economic preferences of
recent graduates predict thei r occupa tional choice. These previous
studies focus on mechanisms before entering the labour market (i.e.,
educational and occupational choice). We explore whether time prefer-
ences affect labour market outcomes through an effect on c areer
investmentsthat is, after ent ering the labour market. This channel
could indeed be important, given that ample empirical research shows
that internal and external job mobility are important sources of wage
growth (e.g., Borjas, 1981; Topel and Ward, 1992; McCue, 1996; Light
and McGarry, 1998; Le Grand and Tahlin, 2002; Blau and DeVaro,
2007; Kosteas, 2009).
A limited number of studies have examined the role of time prefer-
ences in (post-entry) labour market behaviour. Paserman (2008) and
DellaVigna and Paserman (2005) examine the relation between time
Labour Economics 35 (2015) 7792
Corresponding author.
E-mail address: T.M.vanHuizen@uu.nl (T. van Huizen).
http://dx.doi.org/10.1016/j.labeco.2015.03.017
0927-5371/© 2015 Elsevier B.V. All rights reserved.
Contents lists available at ScienceDirect
Labour Economics
journal homepage: www.elsevier.com/locate/labeco

preferences and job search behaviour of unemployed job seekers. Their
ndings indicate that impatient individuals search less intensively and
are less likely to exit unemployment. These results are consistent with
the predictions derived from the hyperbolic discounting model.
Halima and Halima (2009) and Van Huizen and Plantenga (2014) repli-
cate these ndings for France and the Netherlands, respectively. Where-
as these studies examine the behaviour of unemployed job seekers, the
work of Drago (2006) is more related to our study as he also focuses on
career investments of workers. Dragos theoretical model predicts that
impatience is positively related to on-the-job search effort and job mo-
bility. A potential limitation is that the model implicitly assumes that
on-the-job search is a leisure acti vity and may therefore overlook
some central dimensions of job search, a typical investment activity.
However, his empirical ndings conrm that more impatient job
seekers are more likely to move to other (outside) jobs.
1
This study contributes to this literature in several ways. First, we
discuss an alternative, simple model of on-the-job search and work
effort with endogenous career investments. Although promotions and
job mobility are typically studied in isolation, recent literature stresses
that on-the-job search may pl ay an important role in the wage for-
mation of workers staying in the rm (e. g., Cahuc et al., 2006;
Postel-Vinay and Turon, 2010; Moen and Rosen, 2013). We follow this
literature and argue that on-the-job search and work effort are substi-
tutes, leading to career paths that are mutually exclusive: when a work-
er accepts an outside job offer, he forgoes promotion opportunities in
the current rm (and vice versa). When these interactions between in-
side and outside mobility are taken into account, we can de rive new
predictions on how time preferences are related to career investments
and mobility. The model shows that patience increases work and search
effort (at least within a certain range of the discount rate), but that the
relation with mobility is ambiguous.
Second, making use of the DNB Household Survey (DHS), a large
Dutch panel study, we assess empirically how time preferences are re-
lated to work effort, on-the-job search activities and job mobility. To
our knowledge, this is the rst study to analyse empirically the relation
between time preferences and on-the-job search behaviour. In general,
studies on on-the-job search examine job-job transitions and ignore the
search process. A nal contribution is methodological: whereas most
studies rely on (a combination of) rather noisy behavioural proxies for
time preferences,
2
we construct a measure for time preferences using
items from the Consideration of Future Consequences (CFC) Scale, a
psych ological construct that measures an individuals orientation
towards the future. We argue that this measure is more precise than
those derived from behavioural proxi es. Moreover, we compare the
estimation results using the CFC scale with those using an indicator
based on behavioural proxies: it appears that the results depend crucial-
ly on how heterogeneity in time preferences is captured.
Overall, our ndings show that more patient workers exert more
work effort in the current job and search more intensively for outside
positions. The results on job mobility are in general ambiguous, al-
though there is some weak evidence that, in line with previous studies,
impatient workers move more frequently from one job to another. The
result that patience is positively related to on-the-job search intensity
but not (or negatively) associated with job mobility may be hard to rec-
oncile with standard on-the-job search that focus exclusively on exter-
nal mobility. These ndings can, however, be explained by models in
which work effort and on-the-job search are substitutes in determining
career progress.
This paper is structured as follows. In the next section, we present
the model and derive theoretical predictions on the relation between
time preferences and career investments and job mobili ty. In Sectio n 3,
we present the data on time preferences, work effort, search intensity
and mobility. Subsequently, we discuss our empirical ndings. The
nal section concludes.
2. Theoretical framework
2.1. A career model
On-the-job search and work effort may be seen as substitutes since
both activities increase the chances of improving the workers future
labour market position. However, inte rnal and external mobility are
generally examined in isolation. Focusing exclusively on either internal
or external mobility, the relation between time preferences and on-the-
job search and work effort may seem obvious. Following basic on-the-
job search or promotion models, one can easily show that the marginal
gains from search or work effort in crease with patien cegiven that
these gains materialize in the future. These models therefore predict
that more patient workers invest more in bo th career activities and
are more likely to move to another job (within and outside the current
rm).
However, if search and work effort are considered jointly in a theo-
retical model, this may lead to different predictions. Drago (2006)
shows that more patient workers invest more in effort, but less in on-
the-job search: Dragos model therefore predicts a negative relation
between patience and job mobility, for which he nds empirical sup-
port. Clearly, this nding is inconsistent with the prediction derived
from a standard on-the-job search model. Nevertheless, the assump-
tions of the model ar e rather strict: the total level of career effort
(i.e., search plus work effort) is exogenous and job search involves im-
mediate net benets and delayed costs in terms of foregone promotions.
Hence, workers allocate thei r total time between a leisure activity
(on-the-job search) and an investment activity (work effort, or collab-
oration). More impatient workers therefore engage more in the former
and less in the latter activity. We propose an alternative career model
where the total level of on-the-job search in tensity and work effort
is end ogenous and both activities are modelled as investments
(i.e., generating immediate costs and delayed rewards).
2.2. The optimization problem
The structure of our model is in the spirit of Moen and Rosen (2013),
who developed a model where on-the-job search and work effort are
substitutes. In their 2-period model, the wage in the second period de-
pends on whether the worker found another job (during on-the-job
search in period 1) and, if the workers stays within the rm, on his effort
exerted in period 1. One of the central premises of the model is that
workers receive deferred compensation for effort, which may negative-
ly affect on-the-job search. We also use a 2-period model but focus on
the supply side aspects of job search and do not examine general equi-
librium issues. In contrast to Moen and Rosen (2013), we allow for a
discount rate betwe en the two periods and we do not make the
assumption that all outside job offers are accepted.
Workers can climb the career ladder though promotions (internal
mobility) and by moving to another job (external mobility). In period
1, workers decide on the allocation of time and energy to work effort
(e 0) and on-the-job search (s 0). Work effort may be interpreted
as the amount of effort which is in addition to the minimal acceptable
work effort: it represents extra-role behaviour, such as working over-
time hours, accepting temporary impositions without protest, assisting
co-workers and building good relationships with supervisors. On-the-
job search effort consists of all kinds of screening (e.g., searching for
1
Although it is not the focus of their study, Cadena and Keys (2014) also provide evi-
dence that impatient individu als switch more frequently between jobs. Like Drago
(2006), the results of Cadena and Keys (2014) are based on the NLSY.
2
For instance, Drago (2006) and DellaVigna and Paserman (2005) use behavioural out-
comes, such as smoking, alcohol consumption and having a life insurance, to construct a
measure of impatience. However, these proxies are rather noisy measures. In fact, in both
studies, the Cronbachs alpha is below conventional norms. The results of Cadena and Keys
(2014) are based on a single item (i.e., the interviewers assessment whether the respon-
dent acts impatient or restless), which is likely to capture various individual characteristics
other than time preferences.
78 T. van Huizen, R. Alessie / Labour Economics 35 (2015) 7792

vacancies in newspapers and on the internet) and application activities
(writing application letters, preparing for and attending job interviews).
Both career activities involve immediate costs according to the increas-
ing convex cost functions c
1
(s)andc
2
(e), with c
1
(0) = c
2
(0) = 0.
By investing in work effort, the agent increases the probability of
receiving a promotion through probability μe (0 μe 1), where μ is a
constant (μ N 0). A promotion leads to a wage increase of w
p
w,
according to the de terministic function Φ(w) (Φ '(w)N 0), whi ch
continuously describes the promotion wage in w;
w½:bydenition,
promotion offers are higher than the current wage. Similarly, increasing
the level of on-the-job search intensity positively affects the probability
of receiving an outside offer λs(0 λs 1), with constant λ (λ N 0). The
wage offer x is drawn from a known distribution F(x), whic h is the
cumulative distribution function with a lower and upper bound
w; w½.
Assuming that workers aim to maximize expected utility, the worker
chooses on-the-job search intensity and work effort to solve:
max
s;e; w
w c
1
sðÞ c
2
eðÞ
þ δ w þ μew
p
w

þ λs
w
^
w
x w þ μew
p
w

dF xðÞ
no
ð1Þ
In period 1, the worker receives wage w and makes career invest-
ments c
1
(s)andc
2
(e). The payoffs in period 2 will be discounted accord-
ing to the discount factor δ (0 b δ 1). If the worker decides to stay
within the rm, he receives his current wage or, depending on the effort
level exerted in period 1, obtains a promotion. The term multiplied by λs
represents the potential gains if the worker receives an outside offer.
The worker accepts the job offer when the offer is higher than the cutoff
point ŵ (reservation wage). From Eq. (1) we can derive the three rst
order conditions:
c
1
0
sðÞ¼δλ
w
^
w
x w þ μew
p
w

dF xðÞ ð2Þ
c
2
0
eðÞ¼δμ 1λs 1F
^
wðÞðÞðÞw
p
w

ð3Þ
w
¼ w þ μew
p
w

ð4Þ
Eq. (2) shows that the marginal costs of on-the-job search are equal
to the marginal benets. Given the convexity of the cost functions, mar-
ginal costs and therefore the level of on-the-job search increase with the
size of the marginal benets. A higher probability of nding an accept-
able offer increases search intensity, whereas the payoffs from staying
negatively affect on-the-job search. Similarly, the right-hand side of
Eq. (3) represents the marginal benets of work effort, which decline
with the probability of leaving the rm λs 1Fw
ðÞðÞ. Finally, Eq. (4)
describes the reservation wage ŵ, indicating the wage offer at which
the worker is indifferent between staying and moving.
Given that the right-hand side of Eq. (3) is positive and that we as-
sume convexity of the cost functions and c
2
'
(0) = 0, the optimal level
of effort is positive (e N 0). Likewise, on-the-job search effort is positive,
as we can show that Eq. (2) can be rewritten as
c
1
0
sðÞ¼δλ 1F
^
wðÞðÞEx w þ μew
p
w

x N
^
w

N 0 ð5Þ
which implies that workers will always exert a positive amount of on-
the-job search effort (s N 0). Hence, we can rule out corner solutions.
The central question here is how time preferences are related to
career investments. Using the rst order conditions and a pplying
implicit differentiation (see Appendix A), we can derive how on-the-
job search and work effort are related to the discount factor δ:
c
1
00
sðÞs
0
¼ λ
w
^
w
x w þ μew
p
w

dF xðÞδλμe
0
1F
^
wðÞðÞw
p
w

ð6Þ
c
2
00
eðÞe
0
¼ μ w
p
w

1λs 1F
^
wðÞðÞþλδ f
^
wðÞμe
0
w
p
w

δλs
0
1F
^
wðÞðÞ

ð7Þ
where s
0
¼
ds
dδ
, e
0
¼
de
dδ
.Eq.(6) implies that c
1
''
(s)s' N 0, that is, search effort
increases with δ if e' b 0. Moreover, one can derive that, when e' N 0,
search effort is positively related with δ if:
δ b
Ex
^
wj x N
^
wðÞ
μe
0
w
p
wðÞ
ð8Þ
Basically, patience is positively related to on-the-job search when
the payoffs from and the probability of receiving a promotion are rela-
tively small: in that case, the future costs from quitting (in terms of for-
gone promotions) do not outweigh the future gains from outside job
mobility. Furthermore, one can clearly see that this condition is more
likely to hold at low patience levels. As the model does not rule out
the possibility of a negative relation between patience and on-the-job
search, there may exist a hump-shaped relation between δ and this ca-
reer investment. However, given 0 b δ 1, search intensity increases in
the entire range of δ when the expected future payoffs from external
mobility are relatively large (E(x ŵ| x N ŵ) N μe'(w
p
w)).
Next, we can use Eq. (7) to show that patience increases the level of
work effort if:
λs 1F
^
wðÞðÞþδλ s
0
1F
^
wðÞðÞμ w
p
w

f
^
wðÞe
0

b 1 ð9Þ
We reach similar conclusions for work effort as for search intensity,
since e' N 0whens' b 0: the two career investments are substitutes.
Moreover, Eq. (9) implies that when s' N 0, work effort increases with
patience if:
δ b
1λs 1F
^
wðÞðÞþλf
^
wðÞEx
^
wj x N
^
w½þc
1
00
sðÞs
0
1F
^
wðÞðÞ
1
λs
0
1F
^
wðÞðÞ
ð10Þ
Eq. (10) indicates there may be an inverse U-shaped relation
between patience and work effort. The potential negative association
between δ and the two investment activities can be ex plained by a
crowding out effect of one investment activity in favour of another. By
moving to another job one forgoes the opportunity to climb the ladder
within the current rm. Similarly, the worker may be inclined to reject
a decent outside offer anticipating a future inside offer. However, an
interesting result is that the model shows it is not possible that both
work and search effort decrease with patience. Indeed, e' b 0 implies
s' N 0ands' b 0 implies e' N 0.
The nal issue concerns job mobility. In a standard on-the-job search
model, patience is positively related to search intensi ty and the quit
rate. Drago (2006), on the other hand, predicts a negative relation be-
tween patience and job mobility. In the model presented here, external
job mobility occurs if the worker receives a wage that is higher than his
reservation wage ŵ. Hence, job mobility (i.e., the quit rate) is given by:
q ¼ λs 1F
^
wðÞðÞ ð11Þ
Eq. (9) shows that the quit rate in this career model is closely related
to the quit rate dened in standard on-the -job search models
(e.g., Burdett, 1978). However, in our model, the probability of rejecting
an offer is given by F(ŵ) rather than F(w). This is why search models
lead to unambiguou s predictions on the relation between patience
and job mobility, as patience only affects the job arrival rate λs through
more intensive job search effort. However, our model predicts that both
work and search increase with patience (at least for sufciently low δ).
Since the reservation wage increases with the level of work effort, the
model in dicates two opposing effects on the quit rate. A higher level
of search effort results in a positive effect on the job arrival rate, whereas
an increase in the level of work effort generates a negative effect on the
79T. van Huizen, R. Alessie / Labour Economics 35 (2015) 7792

job acceptance rate (1 F(ŵ)). How patience affects the quit rate de-
pends on the relative size of these two effects. Interesting ly, DellaVig na
and Paserman (2005) arrive to similar conclusions on the relation be-
tween time preferences and the exit rate out of unemployment. Hence,
the model does not lead to unambiguous predictions on job mobility.
2.3. Discussion
In the model presented above, we made several assumptions. How-
ever, one may argue that there are plausible alternative assumptions, for
instance, concerning the costs functions. Here we consider several alter-
native model specications and potential extensions.
First, although the assumption of convex costs functions is standard in
on-the-job search models,
3
it is interesting to consider the case of non-
separable cost functions. We could model the costs as c(i), a convex func-
tion of total career investments i = s + e. Similarly, period utility may be a
function of w and g(l), an increasing concave functio n of leisur e l = T
s e (with exogenous total available time T). Under such alternative as-
sumptions, the two investments are perfect substitutes in terms of costs
in period 1. Given that search (work) effort decreases the gains from
work (search) effort, workers have no incentive to invest in both activities
and will invest in the activity that generates the highest expected payoffs.
However, it is clear that, when search and work are perfect substitutes,
the model also predicts that more patient individuals invest more in
their career (see the online appendix for derivations).
Second, the probability of receiving a promotion may be modelled as
stochastic so there exists a probability μeλs that the worker receives
both a promotion and an outside job offer. When the worker obtains
an outside offer x, he evaluates this offer against w or w
p
. In that case,
the probability that the outside wage will be compared with the current
wage rather than the promotion wage is a decreasing function of the in-
dividuals work effort. Similarly, the likelihood that a promotion offer is
rejected (w
p
b x) increases with on-the-job search intensity. In line with
our central model, this implies that the marginal gains from work
(search) effort decline with the intensity of search (work). Such a
model leads to qualitatively similar predictions: work effort e increases
with δ if s decreases with δ and s increases with δ if e decreases with δ.
Moreover, it can be shown that both s and e increase with δ when δ is
sufciently low (see the online appendix for derivations).
Third, the model assumes that rms are not able to make counter
offers once an ou tside offer is received. Following on-the-job search
models that allow for wage renegotiation s (Postel -Vinay and Robin,
2002; Dey and Flinn, 2005; Cahuc et al., 2006), workers reject the out-
side offer if its value is below the counter off er made by the current
employer. On-t he-job search may in that way lead to wage growth
(promotions) within the current rm. However, as these counteroffers
depend on the productivity of the worker, they are likely to be positively
related to work effort. Allowing for wage renegotiations introduces
additional gains from both search and work effort. It is therefore not
obvious how this affects the results.
Finally, the model captures the role of time preferences in a rather
basic way. A potential extension could be to allow for present-biased
time preferences, which seem to be consistent with a s ubsta ntial
amount of experimental and el d evidence (DellaVigna, 2009;
Frederick et al., 2002). In order to allow for time-inconsistency,
(quasi-)hyperbolic discounting models have been proposed as an alter-
native for the standard exponential model (Laibson, 1997). This may be
relevant as one of the most important predictions of hyperbolic
disco unting models is that individuals have a tendency to postpone
investment activities (ODonoghue and Rabin, 1999). Moreover, job
search behaviour of unemployed job seekers seems to be consistent
with this model (DellaVigna and Paserman, 2005; Halima and Halima,
2009; Van Huizen and Plantenga, 2014). Drago (2006) proposes a theo-
retical model of search and work effort that allows for hyperbolic
discounting. The hypothesis that distinguishes between exponential
and hyperbolic discounting is based on sophistication (the extent to
which individuals are aware of their tendency to procrastinate): this
has an effect on search behaviour of hyperbolic discounters but should
have no effect under exponential discounting. However, sophistication
is hard to measure. Moreover, the predictions depend on rather strict
assumptions on the timing and size of the payoffs of the different career
paths. It is therefore difcult to distinguish empirically between expo-
nential a nd hyperbolic discounting in career models. We therefore
focus on the role of time preferences in general in decisions on work
effort, search and mobility.
3. Data
3.1. Sample
To examine the relati ons between time preferences and career
investments, we make use of the DNB Household Survey (DHS). This
Dutch longitudinal survey has been collected annually by CentERdata
since 1993. Around 2500 households participate in the panel each
year. All household members aged 16 or older complete the question-
naire online.
4
The analyses are based on the panel waves 19962013. As the ques-
tions about time preferences were not asked in 19931995, we exclude
the rst waves of the DHS. We select male employees aged 2360 and
exclude workers who were non-employed in the previous year. The
rationale is that workers who just (re)entered the labour market may
have rather distinctive job search behaviour, as they may for instance
accept a job that they perceive as temporary. In addition, many ques-
tions refer to the period prior to the interview (e.g., the number job
applications during the past 2 months). During this period, the entrants
could have been unemployed and in that case their answers may not
reect on-the-job search effort. Due to panel attrition and refreshment,
we make use of an unbalanced panel, consisting of almost 7000 obser-
vations (over 2000 individuals).
3.2. Time preferences
We construct an indicator for time preferences using eleven items
from the Consideration of Future Consequences (CFC) Scale (Strathman
et al., 1994).
5
This psychological construct aims to capture the individ-
uals orientation towards the future. Respondents use a 7-point scale
to indicate to what extent they agree with each of the eleven statements
(see Table 1). Th e answers to these statements indicate how much
value the individual puts on the present compared to the future. Inter-
estingly, empirical work has shown that the CFC items are signicantly
correlated with conventional time preference measures (Borghans and
Golsteyn, 2006; Daly et al., 2009) and predict eld behaviour (Van
Huizen and Plantenga, 2014; Fouarge et al., 2014).
6
Between 1996 and 2009, the DHS included the CFC items in every
wave, except for the 2008 wave. From wave 2010 onwards, the ques-
tions are asked only to the respondents who did not provide the infor-
mation in one of the previous waves (including new panel members).
3
See, for instance, Chrisensen et al. (2005). Moen and Rosen (2013) assume a convex
cost function of search effort, but a linear cost function of work effort. Moreover, Dragos
model uses a U-shaped cost function of search effort. Given the assumption that total costs
of effort (s + e) is exogenous in his model, such a cost function is similarto two convex and
separable cost functions.
4
It is not necessary that households have a PC or internet: when a PC is absent, access is
provided through a special box which enables household members to ll in the survey via
the television.
5
The original CFC Scale consists of twelve rather than eleven statements. However, this
twelfth item is missing in the waves 19962003 and is therefore not included in th e
analysis.
6
Van Huizen and Plantenga (2014) demonstrate that the items are associated to job
search behaviour of the unemployed. Fouarge et al. (2014) show that CFC02 is related to
occupational choice of recent graduates.
80 T. van Huizen, R. Alessie / Labour Economics 35 (2015) 7792

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References
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David Laibson1Institutions (1)
Abstract: Hyperbolic discount functions induce dynamically inconsistent preferences, implying a motive for consumers to constrain their own future choices. This paper analyzes the decisions of a hyperbolic consumer who has access to an imperfect commitment technology: an illiquid asset whose sale must be initiated one period before the sale proceeds are received. The model predicts that consumption tracks income, and the model explains why consumers have asset-specific marginal propensities to consume. The model suggests that financial innovation may have caused the ongoing decline in U. S. savings rates, since financial innovation in- creases liquidity, eliminating commitment opportunities. Finally, the model implies that financial market innovation may reduce welfare by providing “too much” liquidity.

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