Parenthood&Wages MarianneSimonsen AarhusUniversity May2010 - - PowerPoint PPT Presentation

Parenthood
&
Wages


Marianne
Simonsen
 Aarhus
University
 May
2010


Outline


• Research
ques@on

• Rubin’s
causal
model

• Parameters
of
interest

• Iden@fica@on
via
ignorability
assump@ons

• Es@ma@ng
the
effects
of
parenthood
on
wages


Research
ques@ons


• 1. Does
parenthood
cause
lower
(or
higher)


wages?


• 2. Do
the
effects
vary
with
gender
of
parent?

• 3. Do
the
effects
vary
with
age
of
the
youngest


child?


Causality


Determining
causality
essen@al
if
we
want
to
 answer
policy
relevant
ques@ons
like


• 1. Do
employment
policies
work
in
the
sense
that


they
cause
lower
unemployment?


• 2. Does
the
tes@ng
of
math
skills
for
10
year
olds


increase
(that
is
cause!)
learning?


• 3. Do
lower
prices
increase
(cause)
demand
for
a


product?


• 4. Does
being
a
parent
affect
career
outcomes?


Associa@onal
inference


• Emil,
2
years
old:
"When
I
get
chewing
gum
I


will
become
three
years
old".
"When
I
get
my
 jacket
on,
it
will
become
cold
outside“


• Even
though
one
variable,
x,
has
a
significant


associated
coefficient
in
a
linear
regression
of
 y
on
x
it
does
not
necessarily
mean
that
x
 causes
y


Effects
of
Parenthood
on
Wages


Mo@va@on
and
context


• Most
individuals
become
parents
at
some
point
in
their
life


(87%
of
49‐year
old
women
are
mothers
in
2005)


• An
average
woman
gives
birth
to
1.8
children
(median
2)

• The
average
woman
takes
9
months
of
parental
leave,
the


average
man
22
days


• Important
for
most
(men
and
women)
to
know
how
their


choices
affect
career
outcomes
(e.g.
wages)


• Note
that
if
one
accumulates
less
in
terms
of
wages,


pension
contribu@ons
will
bare
smaller
too!


• Surprisingly
licle
interest
in
the
literature
(and
in
society?)


in
the
effects
for
men


(Some)
Addi@onal
Danish
Literature


• Simonsen,
M.
and
L.
Skipper
(2010):
The
Family
Gap
in


Wages.
What
Wombmates
Reveal.
Working
paper


• Simonsen,
M.
and
L.
Skipper
(2008):
An
Empirical


Assessment
of
Effects
of
Parenthood
on
Wages.
 Advances in Econometrics


• Simonsen,
M.
and
L.
Skipper
(2006):
The
Costs
of


Motherhood:
An
Analysis
Using
Matching
Es@mators.
 Journal of Applied Econometrics


• H.
Skyt
Nielsen,
M.
Simonsen,
and
M.
Verner
(2004):


Does
the
Gap
in
Family
Friendly
Policies
Drive
the
 Family
Gap?
Scandinavian Journal of Economics


Household
Decision
Making


• Mom
&
Dad
decides
to
have
Most
Wished‐for
Child

• Most
Wished‐for
Child
arrives;
mom
&
dad
must


decide
how
much
leave
to
take,
how
to
distribute
leave
 among
them,
secle
prac@cali@es
aker
they
return
to
 the
labor
market
 Poten@ally
important
factors:


• Needs
of
Most
Wished‐for
Child

• U@lity
from
being
at
home
with
Most
Wished‐for
Child

• Access
to
and
compensa@on
during
leave

• Wage
costs
associated
with
choices

• Job
flexibility

• Price
and
access
to
child
care


Wage
differences,

 parents
and
non‐parents


• Parents
invest
differently
in
household


produc@on
and
the
labor
market
that
non‐ parents
(e.g.
leave)


• Parents
may
have
other
preferences
for


working
condi@ons
than
non‐parents
(e.g.
 choice
of
sector,

sektorvalg,
over@me)


• Parents
bargaining
posi@on
may
be
different


(e.g.
because
of
lower
mobility)


• Discrimina@on
(maybe
sta@s@cal)


Wage
differences
likely
to
reflect
 individuals’
(costly)
choices


Evalua@on:
The
Ideal
Counterfactual


Individual
i
as
non‐parent
 Wage
w1
 Wage
w0
 Effect:
w1‐w0
 Individual
i
as
parent


Example:
Marianne
&
Emil


• May
1,
2007:
Deadline,
applica@on
for
associate


professorship
at
School
of
Economics
and
 Management,
AU


• September
18,
2007:
Emil
arrives
(leave
August


2007
–
February
2008)


• November
2007:
Declared
qualified
for
and

• ffered
posi@on.
Nego@a@on
of
star@ng
@me
for


posi@on.


• April
1,
2008:
Associate
professor


What
was
the
(wage)
cost
of
Emil?


• We
want
to
know
w1‐w0

• But
what
was
my
counterfactual
wage,
w0?

• Assump@on:
Take‐up
of
posi@on
in the absence of Emil



December
1,
2007


• Cost
of
Emil:
Roughly
DKK
3,000
for
four
months.
Or


about
3
%
of
my
yearly
wage
income
prior
to
 parenthood


• Note
that
we
had
to
make
an
assump@on
in
order
to


es@mate
the
costs
of
Emil



In
prac@ce:
Compare
individuals
with
same
observable
 characteris@cs
except
for
parenthood
status


Individual
j,
non‐parent
 Wage
w1
 Wage
w0
 Es@mated
average
effect
for
group
of
parents,
ATET
 Individual
i,
parent


Data
and
selec@on
criteria


• Registerbased
data
maintained
by
Sta@s@cs
DK

• Hourly
wage
informa@on
for
all
employed


individuals
(firms>9
employees)
in
2006


• Defini@on
of
parenthood:
Child
under
the
age
of


18
living
at
home


• Long
list
of
observable
characteris@cs

• Exclude
re@rees,
individuals
enrolled
in


educa@on,
self‐employed,
non‐insured
and
 individuals
employed
less
than
200
hours
per
 year


Relevant
observable
characteris@cs?


Affect
both
parenthood
and
wages:


• (Flexible
specifica@on
of)
age

• Type
and
length
of
educa@on

• Geographic
loca@on

• Own
number
of
siblings

• Own
parents’
level
of
educa@on


Es@ma@on
of
P(D=1),
selected
res.

Women
 Men
 Marg.
effect
 Std.
error
 Marg.
effect
 Std.
error
 Age
25‐29
 0.293
 0.003
 0.196
 0.004
 Age
30‐34
 0.511
 0.002
 0.482
 0.003
 Age
35‐39
 0.569
 0.002
 0.589
 0.003
 Age
40‐42
 0.465
 0.001
 0.566
 0.002
 High
school
 ‐0.209
 0.006
 ‐0.099
 0.006
 Voca@onal
degree
 ‐0.113
 0.009
 0.005
 0.010
 Short
further
 ‐0.224
 0.010
 0.008
 0.010
 Med.
length
further
 ‐0.220
 0.009
 0.037
 0.011
 Long
further
 ‐0.115
 0.010
 0.052
 0.011
 Number
of
siblings
 0.024
 0.001
 0.017
 0.001
 Note:
Probit
es@ma@on,
N
(women)=372,377,
share
(mothers)=0.66,
N(men)=336,633,
 share(fathers)=0.49.
Bold
significant
at
5
%
level.


Main
findings
I


Women
 Men
 ATET
 Std.
err
 ATET
 Std.
err.
 Outcome: Log normal hours Popula@on
 ‐0.046
 0.002
 0.045
 0.002
 One
child
vs.
no
children
 ‐0.044
 0.003
 0.025
 0.002
 Two
children
vs.
no
children
 ‐0.042
 0.002
 0.051
 0.002
 More
than
two
vs.
no
 ‐0.069
 0.004
 0.066
 0.004
 Outcome: Log actual hours Popula@on
 ‐0.021
 0.002
 0.055
 0.002
 One
child
vs.
no
children
 ‐0.005
 0.003
 0.039
 0.002
 Two
children
vs.
no
children
 ‐0.027
 0.003
 0.058
 0.002
 More
than
two
vs.
no
 ‐0.059
 0.004
 0.070
 0.004
 Note:
Nearest
neighbor
matching.
N
(women)=372,377,
share
(mothers)=0.66,
 N(men)=336,633,
share(fathers)=0.49.
Bold
significant
at
the
5%
level.



Main
findings
II


Women
 Men
 ATET
 Std.
err.
 ATET
 Std.
err.
 Outcome: Log normal hours Child
aged
0‐2
vs.
no
children
 ‐0.053
 0.003
 0.076
 0.002
 Child
aged
3‐6
vs.
child
aged
0‐2
 0.036
 0.002
 0.017
 0.003
 Child
aged
7‐9
vs.
child
aged
3‐6
 0.008
 0.002
 0.000
 0.003
 Child
aged
10‐14
vs.
child
aged
7‐9
 ‐0.002
 0.002
 ‐0.001
 0.004
 Outcome: Log actual hours Child
aged
0‐2
vs.
no
children
 ‐0.008
 0.002
 0.094
 0.002
 Child
aged
3‐6
vs.
child
aged
0‐2
 0.008
 0.003
 0.009
 0.002
 Child
aged
7‐9
vs.
child
aged
3‐6
 ‐0.001
 0.003
 ‐0.003
 0.002
 Child
aged
10‐14
vs.
child
aged
7‐9
 ‐0.006
 0.004
 ‐0.005
 0.004
 Note:
Nearest
neighbor
matching.
N
(women)=372,377,
share
(mothers)=0.66,
 N(men)=336,633,
share(fathers)=0.49.
Bold
significant
at
the
5%
level.



What
to
take
away
from
this
exercise?


• Child
penalty
for
women,
child
premium
for


men
(some
indica@on
that
household
income
 is
unchanged)


• The
hours
measure
macers!

• Larger
impacts
if
one
has
more
kids

• Larger
impacts
if
one
has
young
kids