Capturing gender disparities: some stylized facts and...

Capturing gender disparities: some stylized facts and suggestions from Europe

Third UNDP Conference on Measuring Human Progress

Session 2: „Capturing gender disparities“

Christina Boll

Hamburgisches WeltWirtschaftsInstitut (HWWI)

New York – 10 March, 2014

Aim of indicators

• Greater attention and awareness of gender issues in human development

• Boost political action

Requirements

• Indicators should be simple to communicate, transparent, suitable for

cross-country and cross-time comparison, …


2

Indicators capturing gender disparities

1. Inequality does not necessarily imply a welfare loss

– Selection as a major challenge on the labor market

– Well-being: income ≠ consumption

– But: women‘s relative earnings are crucial for female empowerment

2. Adopting the life course perspective adds valuable information

– ‚Shadow price of children‘:lifetime earnings matter

– Women‘s personal resources impact on their intra-household bargaining power

3. Some (components of) indicators are of region-specific importance

– Different factors drive well-being and empowerment of women in different regions of the world


3

Some suggestions drawn from stylized facts from Europe

INEQUALITY = WELFARE LOSS?

ADDRESSING THE LABOR MARKET


4


5

Gender gaps: Reflecting institutional impediments or gendered preferences?

0

5

10

15

20

25

30

35

pe

rce

nta

ge

po

ints

< 6 years from 6 to 11 years 12 years or over

Gap in employment rates of women and men aged 25 to 54, by age of youngest child, 2012

Sources: Eurostat (2014); HWWI.

Note: child has to be in full social and economic dependence from other household member/-s (parents/ adults).


6

3.1

17.51.1

3.3

19.60.8

17.60.7

17.4

19.61.5

21.1

9.80.0

35.28.3

9.2

29.42.0

4.4

17.52.0

1.10.6

10.33.0

4.20.9

21.12.0

13.85.3

2.11.7

0.7

6.40.5

3.81.4

23.43.2

0 10 20 30 40 50 60

DK femalesDK males

DE femalesDE males

FR femalesFR males

IT femalesIT males

NL femalesNL males

AT femalesAT males

PL femalesPL males

FI femalesFI males

SE femalesSE males

UK femalesUK males

NO femalesNO males

CH femalesCH males

Looking after children or incapacitated adults Other family or personal responsabilities

Inactive population aged 25 to 64 by sex and main reason why no job search, 2011


%

1/3 of German inactive women: Family tasks =main reason why no job search


7

Impediments to full-time work of mothers, particularly with small children

0

10

20

30

40

50

60

70

80

90

100

A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C

DK DE ES FR IT NL AT PL FI SE UK NO

%

1-29 h min. 30 h

Formal childcare by children’s age and weekly hours as share over the

population of each age group in 2011


Notes: A: <3 years; B: 3 years - compulsory school age; C: compulsory school age - 12 years.


8

4.1

2.3

7.3

2.4

6.3

2.8

1.1

1.7

0.9

5.1

1.5

2.4

1.3

3.8

1.9

6.4

2.5

7.8

3.7

4.9

1.5

9.0

2.3

0

1

2

3

4

5

6

7

8

9

10

F M F M F M F M F M F M F M F M F M F M F M F M

DK DE FR IT NL AT PL FI SE UK NO CH

%

Involuntarily part-time employed aged 15 to 74 as a percentage of labour force, 2011


Welfare implications are more easily drawn from reported preferences

In terms of working hours, the female labor force is more likely to be rationed.


9

Women‘s relative earnings: relevant for women‘s empowerment

0

5

10

15

20

25

Gender pay gap in unadjusted form, 2012


%

Note: France: Figure refers to 2011

4 driving factors: Occupational segregation, low representation in leadership, restricted working hours, interrupted careers

ADOPTING THE LIFE COURSE

PERSPECTIVE ADDS VALUABLE

INFORMATION


10


11

“Having children is a lifelong undertaking.”

Siv Gustafsson, Swedish economist, 2003


12

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0

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15000

20000

25000

30000

35000

40000

Att

ain

ed e

ducation /

age a

t la

bour

mark

et

entr

y

hig

h /

27

mediu

m /

22

lo

w /

19

Age at first birth

28 years 32 years 36 years

The ‚shadow price of children‘ over the life course: The case of West German women

Loss in gross wages (€) referring to a 6-years withdrawal from full-time employment up to age

45, by education and age at first birth

13 Hamburgisches WeltWirtschaftsInstitut (HWWI)

Aggregate loss in gross earnings up to age 45: West German women

80.411,15

26.115,09 26.115,0933.381,93

40.681,67

27.901,42

60.268,4349.443,96

72.806,90

76.926,56

66.688,48

0,00

25.000,00

50.000,00

75.000,00

100.000,00

125.000,00

150.000,00

175.000,00

200.000,00

225.000,00

3 years (0/3) 6 years (3/3) 3 years (1/2) 6 years (1/5)

Accumulated loss in gross earnings from age 30 to 45*, by withdrawal pattern (years OLF/part-time)- medium educated West German woman, birth of first child at age 30 -

Earnings loss during OLF time (€)Earings loss during part-time (€)Earnings loss af ter reentry in full-time (€)

€

*Difference in total earnings compared to a continuously full-time employed woman of same education and age.

Sources: Own calculations based on German Socio-Economic Panel (SOEP) 1984-2005, see Boll (2009; 2011)

Sources: - Boll, Christina (2011): Mind the gap – German motherhood risks in figures and game theory issues, International Economics and Economic Policy 2011 (4), 8, 363-

382. - Boll, Christina (2011): Lohneinbußen von Frauen durch geburtsbedingte Erwerbsunterbrechungen. Der Schattenpreis von Kindern und dessen mögliche Auswirkungen

auf weibliche Spezialisierungsentscheidungen im Haushaltszusammenhang, Eine quantitative Analyse auf Basis von SOEP-Daten, Monografische Dissertationsschrift, Reihe "Sozialökonomische Schriften" (Hrsg.: Prof. Dr. B. Rürup und Prof. Dr. W. Sesselmeier), Verlag Peter Lang, Frankfurt am Main et al.


14

Factors governing intra-household bargaining position of partners

• Fertility decisions • Gender does not matter per se

Pavetic/Stein 2011, Thomson/Hoem 1998, Bauer/Kneip 2013

• Personal resources • education

Germany: Bauer /Jacob 2010, Italy: Rosina/Testa 2009

• earnings Hener 2010

• Demand/supply ratio on the marriage market Bauer/Kneip 2013

• To whom child related public transfer payments are assigned Hener 2010

• Public grants to single parents Greenwood et al. 2003, McElroy 1990

• Likewise: Personal and assigned public resources govern decisions upon within-household work division and income distribution

• Employment decisions impact on the bargaining position of partners over the life cycle

• Anticipation of asymmetric specialization risks in t+1 prevents women from specialization in t

Iyigun/Walsh 2007, Steurer 2008, Boll 2011

Source: Beblo, Miriam, Christina Boll (2013): Couples – uniform groups with common interests? (Review of international empirical evidence, at present in German language only)

Research financially supported by:


15

Intra-household work division: Gender gap in unpaid work

Own multivariate

analyses show:

Fathers‘childcare time

is positively

associated to father

friendly parental

leave schemes

(high wage

replacement rates,

exclusive father

weeks).

Boll, Christina, Julian S. Leppin and Nora Reich (2014): Paternal childcare and parental leave policies: evidence from industrialized countries. Review of Economics of the Household 12 (1), 129-158.

Research financially supported by

36

77

5360

167

6964 65

0

20

40

60

80

100

120

140

160

180

min

ute

s p

er day

Gender gap in household tasks at the turn of the millennium- dual earner couples, both partners full-time employed, youngest child in hh <5 years old -

Sources: Multinational Time Use Study (2010); calculations HWWI.

Norwegen (2000)

Niederlande (2000)

Kanada (1998)

Italien(2002)

Ver. Königr. (2000)

Finnland(1999)

Deutschland (2001)

Schweden (2001)

.

Norway(2000)

Netherlands (2000)

Canada (1998)

Italy (2002)

UK(2000)

Finland(1999)

Germany(2001/02)

Sweden (2001)

46

77

53

42

6471 69

64

0

20

40

60

80

100

120

140

160

180

Schweden NorwegenNiederlande Kanada Italien Ver. Königr. Finnland Deutschland

min

ute

s p

er

da

y

Gender gap in childcare time at the turn of the millenium - dual earner couples, both partners full-time employed, youngest child in hh <5 years old -

Sources: Multinational Time Use Study (2010); calculations HWWI.

Sweden (2001)

Norway(2000)

Netherlands(2000)

Canada(1998)

Italy(2002)

UK(2000)

Finland(1999)

Germany(2001/02)

COMPONENTS OF INDICATORS

SHOULD VARY BY REGION


16


17

Educational attainment in the Baltic Sea Region: Women outperform men…

0

2

4

6

8

10

12

14

16

18

F M F M F M F M F M F M F M F M F M

DK DE EE LV LT PL FI SE NO

Early leavers from education and training by gender, 2013


0

50

100

150

200

250

DK DE EE LV LT PL FI SE NO

Women per 100 men graduating from ISCED levels 5-6 in 2011


Source:

Biermann, Ulrike, Christina Boll, Nora Reich, Silvia Stiller (2013): Economic Perspectives, Qualification and Labour Market Integration of Women in the Baltic Sea Region,

Baltic Sea Academy - Max Hogeforster (Hrsg.), Norderstedt, Germany.


18

…but women are more prone to overeducation: Employment biography matters

+ unemployment experience

+ Out of labour force (OLF) experience

+ weekly working hours 16-25

+ marginal employment (weekly working hours <16)

+ Re-entry into employment

- Employment experience

+ (-) Increasing (decreasing) the risk of overeducation (across models and educational levels)

West Germans > East Germans, except UE experience

Sources:

• Boll, Christina, Julian S. Leppin (forthcoming): From quantitative to qualitative aspects of work: Overeducation and Earnings in Germany, Baltic Sea Academy Series. • Boll, Christina, Julian S. Leppin (2014): Overeducation among graduates: An overlooked facet of the gender pay gap? Evidence from East and West Germany, HWWI

Research Paper No. 147; SOEPpaper No. 627.

Research financially supported by:


19

Prevalence of overeducation among the medium educated

0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010

According to both measures

Realized matches

Self-assessed

Sources: SOEP v28, 1992-2011, HWWI.

0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010


Men, medium education, West Germany Men, medium education, East Germany

Women, medium education, West Germany Women, medium education, East Germany

0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010


0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010


Self-assessed overeducation West&East: Declining trend, but more frequent among women during the last decade.

RM overeducation: Increasing trend among women, women recently approaching (East) and outperforming men‘s level (West), respectively.

2011=14%

2011=8% 2011=12%

2011=10%


20

Men, high education, West Germany Men, high education, East Germany

Women, high education, West Germany Women, high education, East Germany

0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010

According to both measures

Realized matches

Self-assessed


0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010


0%

10%

20%

30%

40%

50%

60%

1992 1995 1998 2001 2004 2007 2010


0%

10%

20%

30%

40%

50%

60%

70%

1992 1995 1998 2001 2004 2007 2010


Prevalence of overeducation among the highly educated

RM overeducation: Women outperformed (West) and almost reached (East) men‘s level,respectively.

2011=36%

2011=30%

2011=38%

2011=41%

Self-assessed overeducation W&E: Women outperform men.


21

Earnings effects of overeducation: Returns to attained education

Ordinary Least Squares Model

Random Effects Model with Mundlak

Correction

2009–2010 1992–2011

Model Category 1 2

West German Female Graduates

RE 9.90 9.64

OE 2.62 5.38

UE -6.40 -6.76

R² (%) 44.27 33.75

West German Male Graduates

RE 10.04 6.89

OE 3.46 4.60

UE n.s. -3.18

R² (%) 37.32 32.49

East German Female Graduates

RE 9.50 7.07

OE 3.23 3.90

UE n.s. -5.33

R² (%) 39.12 41.44

East German Male Graduates

RE 9.85 5.32

OE n.s. 3.12

UE n.s. -4.06

R² (%) 53.34 31.2

How to read these figures? Example (West German women): One year of required education yields a wage premium of 9.90%, whereas one year of excess education yields only 2.62%. Overeducation entails severe wage losses! (≠ human capital theory)

But, on the other hand, returns are above zero! (≠ assignment theory)

Parliamen-

tary represen-

tation

Representation in economic leadership

Earnings

Bodily integrity

Reproductive health

Unwanted births

Life expectancy

Education

Leisure time

LFP rate Job match

quality

(Overeducation, job satistfaction)


22

• All components refer to women and have to be converted into figures relative to men (if applying to both genders)

• bold: empowerment • italic: well-being universal components region-specific supplements for both genders region-specific supplements applying to women only

Suggestions referring to universal and region-specific components

Thank you very much for your attention.

[email protected]

Publications for download:

http://www.hwwi.org/en/research-areas/labour-economics-economics-of-education-family-economics/publications.html


23
















Benefits of fathers’ childcare time

• children’s well-being

Bonke and Greve 2012; Carlson and McLanahan 2004; Palkovitz 2002

• gain in social competences and work-life balance for fathers

Hook 2006

• higher fertility

Buber 2003; de Laat and Sevilla-Sanz 2011; Duvander and Andersson 2006; Lappegård

2010; Oláh 2003

• increased marital stability and satisfaction

Greenstein 1995; McHale and Crouter 1992; Oláh 2001; Sanchez and Gager 2000;

Sigle-Rushton 2010; Wengler et al. 2008

• Higher female employment rates and earnings

Boll 2011; Light and Ureta 1995; Mincer and Polachek 1974


24

Childcare time of fathers


25

Childcare time of fathers 1971-2005 in 8 countries

0

10

20

30

40

50

60

70

min

ute

s

Fathers' average minutes of childcare on the survey day

Sources: MTUS (Gershuny and Fisher 2010); own calculations and illustration.

Boll, Christina, Julian S. Leppin and Nora Reich (2014): Paternal childcare and parental leave policies: evidence from industrialized countries. Review of Economics of the Household 12 (1), 129-158.


26

Women‘s representation in leading positions

Source: Holst/Kirsch (2014): Managerinnen-Barometer, DIW-Wochenbericht

3/2014, graph 2, p. 28.

Women in leading positions* in Europe‘s biggest listed enterprises, 2013 (percentages)

*referring to boards of directors (monistic corporate governance systems) and supervisory boards (dualistic systems), respectively


27

Part-time is a specialty of women‘s employment in Western Europe

0

10

20

30

40

50

60

70

%

Females Males

Percentage of part-time employed aged 15 to 64 by sex in 2012


Note: For Germany and Polang, figures refer to 2011 since 2012 is not available


28

0

5

10

15

20

25

30

35

40

EU (27) DK DE EE LV LT PL FI SE NO

Share of adult population aged 25 to 64 participating in education and training, 2012

Females Males


Life-long learning varies across Baltic Sea Region countries


29

Gender pay gaps translate into (even more wide) pension gaps

Source: OECD (ed.): Pensions at a Glance 2013. OECD and G20 Indicators


30

Causal factors of overeducation: Models

Capturing gender disparities: some stylized facts and...

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