2500+ words Essay

Spousal labor supply

SESS 0042

2nd December 2019

2

Men’s falling, women’s rising LFP

Labor force participation rate

0

10

20

30

40

50

60

70

80

90

100

1850 1860 1870 1880 1900 1910 1920 1940 1950 1960 1970 1980 1990

%

Total Men Women

3

Allocation of Weekly Hours to Various Activities, By Gender and Marital Status

40.2

32.9

16.7

22.2

14.3

12

34.9

23.5

77.6

76.9

78.7

79.4

22.4

24.2

22

23.8

13.5

22

15.7

19.1

0 24 48 72 96 120 144 168

Married Men

Unmarried Men

Married Women

Unmarried Women

Market Work Household Work

Personal Care Passive Leisure Other

4

Labor Force Participation Rates over the Life Cycle in 2005

30

40

50

60

70

80

90

100

15 25 35 45 55 65

Age

L a

b o

r fo

rc e

p a

rt ic

ip a

ti o

n r

a te

Male

Female

5

Hours of Work over the Life Cycle, 2005

500

1,000

1,500

2,000

2,500

15 25 35 45 55 65

Age

A n

n u

a l

h o

u rs

o f

w o

rk

Male

Female

6

Women & employment: what we know

 Huge increase in formal employment over the last century  Particularly among married women  (Singles had been working for some time

already)  Big gains in educational attainment  Sectoral shift from (light) industry to

services (white-collar jobs)

7

Our research questions

 Why have women changed their ways?  How do they make choices between

fertility and labor market participation?  How are the lifecycle decisions made

and how have they changed?  Career choices, parity choices etc.  Birth timing, marriage timing

8

What was the actual historical experience?

 The “engines-of-liberation” story  Wave of gadgets comes around with electricity  The gadgets liberate women from house work  Women’s LFP increases

 But: see Table 6 and Figures 1+3 in Ramey (2008)

9

10

11

12

Composition of employment of single women

Proportions employed as: Single women, aged 20-24

186 0

187 0

188 0

190 0

191 0

192 0

193 0

LFP

Non-metro area

32.4 6

26.9 4

31.3 9

39.9 1

49.7 6

51.0 1

53.4 8

Metro area 55.0

3 56.6

2 57.0

9 64.1

3 73.0

6 79.9

8 79.1

4

Professional, clerical and

sales

Non-metro area

15.5 0

18.2 5

21.7 6

35.4 0

48.8 9

63.5 8

60.0 2

Metro area 7.06 5.71 12.1

9 28.4

9 40.0

0 62.2

1 65.9

4

Craftswomen and operatives

Non-metro area

24.4 4

23.7 6

25.4 0

22.9 6

16.6 5

13.4 3

15.1 0

Metro area 37.6

2 37.9

2 44.1

4 37.1

8 36.9

1 25.5

4 19.1

9

Service workers

Non-metro area

54.4 1

52.2 6

45.0 8

34.6 8

23.5 5

14.6 8

16.4 1

Metro area 54.1

2 51.5

9 40.5

2 32.1

6 20.5

2 9.65

12.3 0

Other Non-metro

area 5.65 5.72 7.75 6.95

10.9 2

8.31 8.48

Metro area 1.21 4.78 3.16 2.17 2.57 2.60 2.58

13

What was the actual historical experience?

 The “engines-of-liberation” story  Wave of gadgets comes around with electricity  The gadgets liberate women from house work  Women’s LFP increases

 But: see Table 6 and Figures 1+3 in Ramey (2008)  Men and women are specializing less than before  Total hrs per person have not changed much  Decline in overall hrs per household corresponds to

the decline in the size of households  The timing issue

14

Graphical representation?

Household goods

Market goods 1. Specialization is less necessary (men and women have become more “interchangeable”)

2. Individual LFP becomes less predictable

3. Overall quantity of consumption has gone up

15

In what sense was this a liberation?

 Liberation from  Dirt (intensity of work)  Drudgery  Domestic servitude  Sharp specialization along gender lines

 Alternative explanation?  A pull story: emergence of office jobs leads to

 A decline in the relative supply of domestic servants  A response in the form of a market for household

gadgets  Effect of WW2

 Blame it on the rising relative wages of women

16

Why have women changed their ways?

Proportions employed as: Single US women, aged 20-24

186 0

187 0

188 0

190 0

191 0

192 0

193 0

LFP

Non-metro area

32.4 6

26.9 4

31.3 9

39.9 1

49.7 6

51.0 1

53.4 8

Metro area 55.0

3 56.6

2 57.0

9 64.1

3 73.0

6 79.9

8 79.1

4

Professional, clerical and

sales

Non-metro area

15.5 0

18.2 5

21.7 6

35.4 0

48.8 9

63.5 8

60.0 2

Metro area 7.06 5.71 12.1

9 28.4

9 40.0

0 62.2

1 65.9

4

Craftswomen and operatives

Non-metro area

24.4 4

23.7 6

25.4 0

22.9 6

16.6 5

13.4 3

15.1 0

Metro area 37.6

2 37.9

2 44.1

4 37.1

8 36.9

1 25.5

4 19.1

9

Service workers

Non-metro area

54.4 1

52.2 6

45.0 8

34.6 8

23.5 5

14.6 8

16.4 1

Metro area 54.1

2 51.5

9 40.5

2 32.1

6 20.5

2 9.65

12.3 0

Other Non-metro

area 5.65 5.72 7.75 6.95

10.9 2

8.31 8.48

Metro area 1.21 4.78 3.16 2.17 2.57 2.60 2.58

17

Sectoral change  Techno change makes brawn

more productive  It is easier to satisfy demand

for brawny stuff  Relative price of brawny stuff

declines  Some reallocation of resources

to brainy stuff: sectoral shift in employment

 Demand for brawn on lab market declines

 Relative wages of brawn go down

 Crucial assumption: brawny stuff and brainy stuff are complements in consumption

Brainy stuff

Brawny stuff

18

Note, however:

 Initial growth in women’s employment did not mean women got careers:  Mostly, they just had (less-skilled) jobs  Career jobs were available to life-time

single women (teaching)  Marriage bar in place (first informal, then

formal)  Attachment to labor market was very weak

19Source: YouGov

20

Lifecycle decisions  Children are a major disruption in a

career  Most women (and their male partners)

want children at some point  It is an issue that affects the dynamic

decision-making (i.e. across time)  What career to choose  What kind of human capital to accumulate  When exactly to go ahead with the family  How many years to stay away

21

Career and children

 Lifetime career employment required better control of timing of fertility

 This did not arrive until 1960s: Enovid

 “the Pill” is a most effective contraceptive

 It puts the contraceptive decision entirely in the woman’s hands

22

Bailey (2007) & Stange (2010)

23

24

25

Occupational crowding  Better timing is great but is only part of the

cost  Fertility still determines human capital

accumulation  Leaving job depreciates human capital  Leaving job means missing promotions

 Women are still more likely to choose careers with slower HC depreciation:  Teaching, child care etc.  NOT finance, NOT IT, NOT anything cutting-edge

26

Data on occupational crowding

27

Salient features of male LFP

 It is generally higher than women’s  But it has come down in the last

century  Greater variance among men in wages  Shift from market place to home

28

Labor force participation rate

29

Careful with statistics!

 Longevity can account for some of the decline

 Longer education for another portion  Finally, there is the growing similarity

between men and women

30

Average hours worked/week, 1900- 2005

30

35

40

45

50

55

60

1900 1920 1940 1960 1980 2000 2020

Year

W e

e k

ly h

o u

rs

31

Male labor and marriage

 Earning potential matters on the marriage market

 Improved labor market conditions will make men more attractive as partners

 This will increase marriage rate overall

32

Proportion Never Married/Single by Age 45 – 54; by Census Year (Birth

Decade)

33

Mean OCCSCORE of White Men by

Age

34

Mean OCCSCORE of Black Men by

Age

35

Table 11 - Effect of Explanatory Variables on Imputed Probability of Marriage

  White Black

  Men Women Men Women

Sex ratio 5.4 -0.9 12.6 2.6

Trait 8.5 6.4 7.5 6.9

Variance in number of breadwinners 1.2 0.9 -1.3 -1.0

Variance in number of children -0.5 -0.3 0.9 -1.6

All partner search variables 14.5 3.1 17.2 2.5

Single women's LFP -6.0 -10.4 0.9 -7.0

Married women's LFP 0.9 0.3 0.6 -2.1

Men's LFP 1.2 3.7 1.6 4.2

Own OCCSCORE 20.8   25.7  

Average men's job quality 11.0 9.3

All labor market variables 16.9 2.2 26.1 1.6

All marriage market variables 30.9 5.5 41.4 4.1

Note: The reported values are percentage point changes in the probability of being ever married by each race-sex groups median age (25 for white men, 22 for white women, 23 for black men, 20 for black women) as each variable is varied between its 10th and 90th percentile.

36

Early 20th century

 Labor market factors pushed for marriage as much as search factors  Men were getting good stable jobs  This was the heyday of stable mfg jobs  Women clearly responded by accepting

more marriage proposals  Apart from the long term trend, there is

also response to cyclical conditions

37

How have things changed?

 Mfg jobs have decreased in importance  Weakening of the unions  Career launch takes longer  Growing inequality among men  Outcome:

 Average vs variance again  Stabler marriages at the upper end of

income distribution

38

Marriage and unemployment

 Marital stability increases with income  Income is still frequently man’s significant

contribution to relationship gains  Unemployment significantly reduces

those gains  Particularly his end of the bargain

 Jalovaara (2003) study on unemployment and divorce risk: Finland

39

Jalovaara (2003)

 Link census information on couples to divorce papers

 Covers period 1990 – 1993  This was a time of severe recession in Finland  We get plenty of variation of economic

outcomes  Measure risk of divorce per marriage-year

40

41

42

 Clearly, unemployment increases chances of divorce

 The effect is stronger for men than for women  Men and/or women do not adjust well to male

unemployment  Education gradient shows there may be a long-term

problem on the horizon: marriage only for the rich?

43

Determinants of the Male- Female Wage Ratio

 The wage gap is VERY persistent

44

Wage distribution by gender (earnings ratios of full-time workers)

67   

 Notes: Updated version of Figure 7‐2 from Blau, Ferber, and Winkler (2014); for additional information on references, see p. 148.  Workers aged  16 and over from 1979 onward, and 14 and over prior to 1979. 

55 60 65 70 75 80 85 1 9 5 5

1 9 6 0

1 9 6 5

1 9 7 0

1 9 7 5

1 9 8 0

1 9 8 5

1 9 9 0

1 9 9 5

2 0 0 0

2 0 0 5

2 0 1 0

E a r n i n g s  R a t i o  ( P e r c e n t )

Year

Figure 1:  Gender Earnings Ratios of Full‐Time Workers  1955‐2014Weekly

Annual (Full Year)

45

Determinants of the Male- Female Wage Ratio

 The wage gap is VERY persistent  Men and women differ in their labor market histories  Human capital is more profitable the longer the payoff

period  Occupation crowding has segregated women into

particular occupations where the return to education is lower

 Women are better off if they enter occupations in which their skills do not deteriorate during the years they spend in the household sector

46 Source: The Economist

47 Source: The Economist

48

49

73   

T a b l e  4 :   D e c o m p o s i t i o n  o f  G e n d e r  W a g e  G a p ,  1 9 8 0  a n d  2 0 1 0  ( P S I D )

1 9 8 0 2 0 1 0 E f f e c t  o f  G e n d e r  G a p  i n  

E x p l a n a t o r y  V a r i a b l e s E f f e c t  o f  G e n d e r  G a p  i n  

E x p l a n a t o r y  V a r i a b l e s

V a r i a b l e s L o g  P o i n t s

P e r c e n t  o f   G e n d e r  G a p  

E x p l a i n e d L o g  P o i n t s

P e r c e n t  o f   G e n d e r  G a p  

E x p l a i n e d

A .  H u m a n  C a p i t a l  S p e c i f i c a t i o n

E d u c a t i o n   V a r i a b l e s 0 . 0 1 2 9 2 . 7 % ‐ 0 . 0 1 8 5 ‐ 7 . 9 % E x p e r i e n c e  V a r i a b l e s 0 . 1 1 4 1 2 3 . 9 % 0 . 0 3 7 0 1 5 . 9 %

R e g i o n   V a r i a b l e s 0 . 0 0 1 9 0 . 4 % 0 . 0 0 0 3 0 . 1 %

R a c e   V a r i a b l e s 0 . 0 0 7 6 1 . 6 % 0 . 0 1 5 3 6 . 6 %

T o t a l   E x p l a i n e d 0 . 1 3 6 5 2 8 . 6 % 0 . 0 3 4 2 1 4 . 8 %

T o t a l   U n e x p l a i n e d  G a p 0 . 3 4 0 5 7 1 . 4 % 0 . 1 9 7 2 8 5 . 2 %

T o t a l   P a y   G a p 0 . 4 7 7 0 1 0 0 . 0 % 0 . 2 3 1 4 1 0 0 . 0 %

B .   F u l l  S p e c i f i c a t i o n

E d u c a t i o n   V a r i a b l e s 0 . 0 1 2 3 2 . 6 % ‐ 0 . 0 1 3 7 ‐ 5 . 9 % E x p e r i e n c e  V a r i a b l e s 0 . 1 0 0 5 2 1 . 1 % 0 . 0 3 2 5 1 4 . 1 %

R e g i o n   V a r i a b l e s 0 . 0 0 0 1 0 . 0 % 0 . 0 0 0 8 0 . 3 %

R a c e   V a r i a b l e s 0 . 0 0 6 7 1 . 4 % 0 . 0 0 9 9 4 . 3 %

U n i o n i z a t i o n 0 . 0 2 9 8 6 . 2 % ‐ 0 . 0 0 3 0 ‐ 1 . 3 % I n d u s t r y  V a r i a b l e s 0 . 0 4 5 7 9 . 6 % 0 . 0 4 0 7 1 7 . 6 %

O c c u p a t i o n   V a r i a b l e s 0 . 0 5 0 9 1 0 . 7 % 0 . 0 7 6 2 3 2 . 9 %

T o t a l   E x p l a i n e d 0 . 2 4 5 9 5 1 . 5 % 0 . 1 4 3 4 6 2 . 0 %

T o t a l   U n e x p l a i n e d  G a p 0 . 2 3 1 2 4 8 . 5 % 0 . 0 8 8 0 3 8 . 0 %

T o t a l   P a y   G a p 0 . 4 7 7 0 1 0 0 . 0 % 0 . 2 3 1 4 1 0 0 . 0 %

N o t e s :   S a m p l e  i n c l u d e s  f u l l   t i m e  n o n f a r m   w a g e  a n d  s a l a r y   w o r k e r s   a g e   2 5 ‐ 6 4   w i t h   a t   l e a s t   2 6 w e e k s  o f   e m p l o y m e n t .    E n t r i e s  a r e   t h e  m a l e ‐ f e m a l e   d i f f e r e n t i a l   i n   t h e   i n d i c a t e d   v a r i a b l e s m u l t i p l i e d  b y  t h e  c u r r e n t   y e a r  m a l e   l o g   w a g e  c o e f f i c i e n t s   f o r  t h e   c o r r e s p o n d i n g  v a r i a b l e s .    

T h e   t o t a l  u n e x p l a i n e d  g a p   i s   t h e   m e a n   f e m a l e  r e s i d u a l   f r o m   t h e  m a l e   l o g  w a g e   e q u a t i o n .

50

Discrimination – hard to pin down

 Selection among women  Who works and who does not  What kind of women go to work  When and how many children they have  Long-term investment in human capital

 Forms of discrimination:  Glass-ceiling  Different hiring standards  Statistical discrimination

51

Goldin (1997) on blind auditions

 Orchestras need musicians  For long, they were predominantly male  By 1970s, some start adopting blind

auditions  Selection committees do not see gender

of applicants – that should eliminate bias

52

Goldin (1997) on blind auditions

53

54

55

56

Conclusions  Women and men are much samer than they used to

be but still different  Unlike men, whose labor supply is boring, women

face a more complicated decision  Lot has changed over the past century  More will change in the future  It is difficult to disentangle discrimination from

other stuff going on in the market  Considering all this, some differences between men

and women may persist, others may change continually

The rest

 If there is time

57

What came of it all

 Changes in women’s lives over 20th century:  More LFP  Higher wages  Better careers  Convergence in housework  Higher quality of children  Improvements in health

 Are women happier?

Stevenson & Wolfers (2009)

 Happiness research  Beware – it has many critics!

 Q: Taken all together, how would you say things are these days, would you say that you are very happy, pretty happy or not too happy?  Same question over 30 years  Asked of men and women of all walks of life  Separate questions about specific areas of

life

What is going on?

 Change in reference?  Women compare with men  Women compare over more domains  Expectations rose faster than reality

Conclusion  Careful what you wish for (you may get it)  The less you expect, the less disappointed

you will be  Always look on the bright side of life  More seriously:

 Reported happiness is not a direct index of quality of life

 Most women, even if reporting less happiness, would not want to go back to the life of 1970