POLICY BRIEF I MEN, MALE ROLES AND GENDER EQUALITY...

POLICY BRIEF I

Authors:Leonor RodriguesVanessa CunhaKarin Wall

MEN, MALE ROLES AND GENDER EQUALITY

Publication dra�ed as part of the Project Men’s Roles in a Gender Equality Perspective, undertaken in a partnership between the Commission for Equality in Labour and Employment (CITE) and the Institute of Social Sciences of the University of Lisbon (ICS-ULisboa). This project was funded by the Financial Mechanism of the European Economic Area, EEA Grants, Programme Area PT07 – Mainstreaming of Gender Equality and Work-Life Balance, with the Commission for Citizenship and Gender Equality (CIG) as the progamme operator.

Funded by the Financial Mechanismof the European Economic Area 2009-2014

Title

POLICY BRIEF I - MEN, MALE ROLES AND GENDER EQUALITY

Authors

Leonor RodriguesVanessa CunhaKarin Wall

Translation

Richard Wall

Editors

Institute of Social Sciences of the University of Lisbon

Av. Prof. Aníbal Be�encourt 91600-189 LisboaPortugal

Tel: 217804700www.ics.ulisboa.pt

Design and Composition

Francisco [email protected]

ISBN 978-972-8399-83-2

Place and Date of PublicationLisbon, September 2017

Commission for Equality in Labour and Employment

Rua Américo Durão, n.º 12-A – 1.º e 2.º andares,Olaias, 1900-064 LisboaPortugal

Tel: 215954000www.cite.gov.pt

POLICY BRIEF I – Men, Male Roles and Gender Equality

1. LABOUR MARKET

a. Activity / Employment / Unemployment rates

b. Full-time employment / Number of working hours

c. Business Sector

2. ECONOMIC SITUATION

a. Income: Average Basic Monthly Income and Average Monthly Earnings

b. At-Risk-of-Poverty rate before and a�er social transfers; At Risk of Poverty or Social Exclusion

3. FAMILY

a. A�itudes towards division of household work

Time spent on household / care tasks

Conjugal division of unpaid work

b. Co-residence (Censos 2011)

4. EDUCATION

a. Population distribution by a�ainment level, by sex

b. Population distribution by educational field, by sex

c. Early dropout from education and training (Early leavers)

d. NEETs

5. PORTUGAL IN THE EUROPEAN CONTEXT

INDEX

POLICY BRIEF I

Current Situation 2011/2014

MEN, MALE ROLES AND GENDER EQUALITY


This Policy Brief summarises the present situation regarding gender equality in Por-tugal in fundamental areas of men’s and women’s lives such as the labour market, the economic situation, family and education.

Focusing in particular on the condition of men, this report seeks to offer a picture which is as up to date as possible of the situation in each of these areas, based on a secondary analysis of key indicators, taking sex and age group into account. The gen-der disparity has also been calculated for each indicator.

The report also contains a short comparative analysis of a more restricted range of gender equality indicators, with a view to ascertaining Portugal’s relative position vis-à-vis the other members of the European Union.

Policy Brief I was prepared as part of the project entitled ‘The Role of Men in Gender Equality’ undertaken jointly by ICS-ULisboa and CITE and funded by the EEA Grants Programme and by the Commi�ee on Citizenship and Gender Equality (Comissão para a Cidadania e Igualdade de Género).

INTRODUCTION

Analysis of the three key indicators relating to the situation of men in the labour market in 2014 shows, first of all, that there is strong participation in the labour market (over 90%) for the age groups between 25 and 44 years, in contrast to the situation of older and younger men, for whom the incidence of activity is much lower, either because they have retired (in the former case), or because they are still in education or training, in the la�er case (Figure 1).

The employment rate in 2014 reflects roughly the same reality: men in the more active-age groups, from 35 to 44 years, are be�er placed in the labour market. There is a residual presence in the la-bour market of younger men, from 15 to 24 years: only 22.9% were effectively working; and the unemployment rate is not only more than double in the context of the total population, but is also high-er than the employment rate for this age group. These data not only show the ageing of the Portuguese working population, but also the vulnerability of the younger population

Activity rate represents the number of active workers for every 100 persons aged 15 and over. Active workers are available man-power, and the active-age population includes workers who are employed or unemployed

Employment rate represents the number of employed workers for every 100 persons aged 15 and over.

Unemployment rate represents the number of unemployed per-sons for every 100 active-age persons. (metadata INE)

1. LABOUR MARKET

Figure 1 - Active-age population, employed and unemployed, total and by sex and age group (2014, %)

Source: INE, Labour Force Survey (Inquérito ao Emprego) (data made available in May 2015)

The analysis of gender equality in the labour market takes into account a set of tradi-tional indicators which describe labour participation of men and women: activity, em-ployment and unemployment rates; full-time (versus part-time) employment and num-ber of hours worked; and business sectors.


TOTAL(15+)

55,8% 46,1%21,9%22,9%

15-24years

74,3%77,5%

25-34years

77,5%84,2%

35-44years

34,8%48,4%

45+years

EMPL

OYM

ENT

14,3%13,5%35,4%34,2% 16,5%14,5% 12,7%10,6% 10,6%11,4%

UNEM

PLOY

MEN

T

64,5% 53,8%33,8%34,8% 89,0%90,6% 88,8%94,2% 39,0%54,6%

ACTI

VITY

WomenMen

5

TOTAL(15+)

35h 32h

80,0%82,7%

33h36h

85,2%88,5%

15-24years

33h35h

73,0%82,1%

25-34years

34h38h

89,6%93,9%

35-44years

34h37h

92,0%95,5%

45+years

FULL

-TIM

EEM

PLOY

MEN

T

NUM

BER

OFEF

FECT

IVE

WEE

KLY

WOR

KING

HOU

RS

TOTAL(15+)

NUM

BER

OF E

FFEC

TIVE

WEE

KLY

WOR

KING

HOU

RS

FULL

-TIM

E

NUM

BER

OF E

FFEC

TIVE

WEE

KLY

WO

RKIN

G HO

URS

PART

-TIM

E

36h39h

14h 15h

Figure 2 - Absolute disparity between men and women in activity employment and unemployment rates, total and by age group (2014, percentage points)

Comparison of the above with the situation of women in 2014 shows the persistence of gender inequality in labour market participation, with higher levels of activity and employment (10.7 and 9.7 percentage points more, respectively) and lower unemployment levels (0.8 percentage points lower) for men (Figure 2). There is an exception, however, for unemployment in the older age group, in which men account for almost 0.8 percentage points more than women. Although gender inequality persists in the labour market, it declines the younger the active-age population.

Figure 3 - Percentage of full-time employment and number of effective weekly working hours, total and by sex and age group (2014, %/hours)

*Gender disparity calculation based on the absolute difference between the activity / employment / unemployment rates of men and women

Source: INE, Labour Force Survey (Inquérito ao Emprego (data made available in May 2015)

Analysis of full/part-time employment and the number of week-ly working hours is equally important for assessing men’s and women’s participation in the labour market. As is well known, full-time employment is dominant in Portugal, for both men and women. However, the incidence of full-time employment varies by age group, and it is precisely at the time when family life is being established - between the ages of 25 and 44 – that both most work full-time: 95.5% of men and 92.0% of women aged 35 to 44 were working full-time in 2014 (Figure 3). For older and younger workers, even though full-time work is still the predom-inant type, the percentage is considerably lower, mainly among younger female workers (73.0%). These figures point to more or less intensive pa�erns of work at the beginning and end of work-ing lives.

As far as the average number of weekly working hours is con-cerned, the pa�ern in 2014 was similar to the full /part-time em-ployment pa�ern: longer weekly hours, averaging 37 or 38 hours, are worked by men aged 25 to 44. It should be clarified here that this indicator includes part-time working hours, so that lower working hours are found where part-time work is more preva-lent, among younger and older workers and women. If average working hours only for those working full-time are separated out, the weekly working hours increase by 3 hours for both men and women.

1%

1,6%

5,4%

15,6%

10,7%

15-24

25-34

35-44

45+

TOTAL

50 10 15 20

UNEM

PLOY

MEN

TRA

TE

1%

3,2%

6,7%

13,6%

9,7%

EMPL

OYM

ENT

RATE

15-24

25-34

35-44

45+

TOTAL

1,2%

2%

2,1%

0,8%

0,8%

15-24

25-34

35-44

45+

TOTAL

ACTI

VITY

RATE

Source: INE, Labour Force Survey (Inquérito ao Emprego) (data made available in May 2015) WomenMen

6

Disparity M-W: more activity/employment – menDisparity M-W: more unemployment – women


Figure 4 - Disparity between men and women in the percentage in full-time employment and in the number of effective weekly working hours, total (full and part-time) and by age group (2014, percentage points/hours)

The incidence of full-time employment and the number of week-ly working hours of paid work also vary according to sex, with men having higher values both in terms of the percentage em-ployed full-time (3 percentage points more), as in the number of weekly hours of paid work (3 hours more) (Figure 4). This gap var-ies, however, according to age, and the difference between full-time employed men and women declines with increasing age.

For number of hours spent at work, the age group with the wid-est gap is the 25 to 44 years group (4 percentage points) and the narrowest is in the youngest age group (2 percentage points). When looking at the gap in the number of weekly hours spent by workers in full/part-time employment, men work more full-time hours (3 hours more) and fewer part-time hours (1 hour less).

9,1%

4,3%

3,5%

2,7%

3%

15-24

25-34

35-44

45+

TOTAL

10 3 5 10FU

LL-T

IME

EMPL

OYM

ENT

2 4 6 7 98

2%

4%

3%

3%

3%NUM

BER

OF E

FFEC

TIVE

WEE

KLY

WOR

KING

HOU

RS 15-24

25-34

35-44

45+

TOTAL

3%

1%

TOTAL (15+)FULL-TIME

TOTAL (15+)PART-TIME

Figure 5 - Active-age population by business sector, by sex (2011, %)

7,1%

19,9%

1,0%17,3%

15,0%6,1%

4,6%2,4%2,4%

0,6%3,3%

2,6%7,9%

3,4%2,7%

1,1%1,1%

0%1,3%

14,5%1,5%

7,5%1,2%

2,2%0,5%

4,3%3,5%

5,0%13,2%

13,9%1,1%

2,9%

0,7%

0,6%

5,8%0%

0%15,3%

AGRICULTURE, FORESTRY AND FISHERIES

MINING AND QUARRIES

INDUSTRY

ELECTRICITY/GAS/STEAM/AIR CONDITIONING SUPPLY

WATER SUPPLY

CONSTRUCTION

WHOLESALE AND RETAIL TRADE

TRANSPORT AND STORAGE

HOTELS AND RESTAURANTS

INFORMATION AND COMMUNICATION

FINANCE AND INSURANCE

REAL ESTATE

PROFESSIONAL, SCIENTIFIC AND TECHNOLOGICAL

ADMINISTRATIVE AND SUPPORT SERVICES

PUBLIC ADMINISTRATION AND DEFENCE

EDUCATION

HUMAN HEALTH AND SOCIAL SERVICES

ARTS, ENTERTAINMENT AND LEISURE

OTHER ACTIVITIES AND SUPPORT SERVICES

According to the Labour Force Survey (EU-LFS), in 2011 most of the employed men in Portugal worked in industry, construction and commerce, followed by public administration, agriculture and fisheries and transport/storage (Figure 5). Women worked mostly in industry, commerce, health, social services and educa-tion, followed by the hotel and restaurant trades. While industry and commerce are sectors which account for a significant and identical percentage of male and female labour, in other sectors there is a clear gender gap. This means there are physically more demanding sectors of activity in which labour is essentially male – construction, but even more so mining and quarrying and the supply of water, electricity, etc. – and other sectors where wom-en predominate, namely those associated with care and teach-ing – health, social services and education.

Narrowing the analysis to sectors where women usually pre-dominate, it can be seen that in 2011 men still accounted for only 22% of those employed in education, 44.9% in administrative work and support services and only 17.4% in human health and social services (Figure 6). The numbers of men and women from different age groups in those sectors suggest, except for the youngest groups, a trend towards a slight increase in the number of men and therefore some narrowing of the gender gap in edu-cation and administrative work and support services. Thus while for the older age group the percentage of men in those sectors in 2011 was 20.8% and 40.9% respectively, for the 25 to 34 age group it was 24.3% and 48.6%.

Source: Eurostat, EU-LFS 2011, data consulted on 21 July 2015 WomenMen

7

Disparity M-W: greater among men than women Disparity M-W: greater among women than men

Gender disparity calculation based on the absolute difference between the percentage of men and women employed full-time and between the number of average effective weekly

working hours for men and women Source: INE, Labour Force Survey (Inquérito ao Emprego) (data made available in May2015)

8

Figure 6 - Proportion of men and women in the education, administrative work and support services and health and welfare sectors, total and by age group (2011, %)

2. ECONOMIC SITUATIONGender equality in the economic sphere is determined by analysing two types of indicators: 1) income indicators, like average monthly earnings (AME), average basic monthly income (ABMI) and additional income; and 2) indicators relating to the risk-of-poverty, such as the at-risk-of-poverty rate (before and a�er social transfers) and the risk of poverty or social exclusion rate (see Definitions boxes).

Basic monthly income (ABMI) Gross amount (before any deduc-tions) in cash and/or kind, paid on a regular basis and guaranteed to the worker for the period in question and corresponding to normal working hours (metadata – GEE/ME).

Monthly earnings (AME) Gross amount (before any deductions) in cash and/or kind, paid monthly on a regular basis for hours of work carried out, as well as payment for qualifying hours of work not ac-tually worked. Includes, in addition to basic remuneration, additio-nal income – i.e. all regular premiums and allowances (continuous service bonuses, and bonuses or allowances for the nature of the job, lunch, housing, transport, seniority, productivity, performance, shi�s, flexible hours, dangerous, difficult or dirty work, etc.), as well as payment for overtime and additional hours (metadata – GEE/ME).

15-24*

25-34

35-44

45+

TOTAL

0 50 100

EDUC

ATIO

NAD

MIN

ISTR

ATIV

EAN

D SU

PPOR

T SE

RVIC

ES

25-34

35-44

45+

TOTAL

HUM

AN H

EALT

HAN

D SO

CIAL

SER

VICE

S 15-24*

25-34

35-44

45+

TOTAL

WomenMen

Analysis of income from work according to age group shows that for men it tends to increase with age (Figure 7). In 2012, ABMI for younger men was 625 euros and for older men 1280 euros, in other words more than double. AME, which includes additional income, follows the same trend, ranging from 753 euros to 1478 euros.

For women, not only does the gender pay gap with men persist, both in overall terms and by age group, for all three indicators, but the highest level of salary occurs between the ages of 35 and 44 and not for those aged 45 and over, as occurs with men. It is in the 35 to 44 years age group that women have the highest ABMI, highest additional income and consequently greater AME. This means that the gender pay gap widens with age, with men earning on average 474 euros more than women, taking AME into account.

* low reliability data Source: Eurostat, EU-LFS 2011, data consulted on 21 July 2015


9

Figure 7 - Average basic monthly income (ABMI), additional income and average monthly earnings (AME)*, total and by sex and age group (2012, euros)

* Data from 2013. 1 Source: Department of Strategy and Economic Research/Ministry of Economy, data supplied on 2 September 2014 2 Source: Department of Strategy and Economic Research/Ministry of Economy, consulted at www.INE.pt and last updated on 15 December 20143 Authors’ calculations based on previous data

Figure 8 - Absolute (€) and relative (%) gender disparity in average basic monthly income (ABMI), additional income and average monthly earnings (AME), total and by age group (2012, euros/%)

Source: Authors’ own calculations based on ABMI and AME data from Department of Strategy and Economic Research (until 2009) and the Department of Strategy and Economic Research / Ministry of Economy (from 2010) – (Staff Establishment Plan), consulted at Pordata on 3 February 2015, last updated 5 May 2014

The value of the gender pay gap for average monthly earnings can be broken down, in absolute terms, as the sum of the average difference between men and women in ABMI and the amount of additional income received. Analysis of this breakdown by age group produces the conclusion that, in general, the higher the age the greater the difference in average monthly earnings of men and women, and that the gap is the outcome mainly of the differences in basic salary, and also of those in additional income from bonus-es, allowances, etc. (Figure 8). Thus the base salary of men aged between 25 and 34 was 61 euros higher and the amount of bonus-es and allowances 42 euros higher than women in the same age group; men aged 65 and over earn 471 euros and 73 euros more, respectively, than women aged 65 and over. Analysis of the same indicators in relative terms – i.e. what is the difference between men’s and women’s earnings expressed as a percentage, shows that for all age groups, the largest gap between men and women is in additional income earned, with its being particularly marked in the 45 to 64 and over 65 age groups, with men earning some 40% more than women in bonuses, allowances and overtime.

TOTAL(18+)

814,5€915€572€625€

18-24years

761,9€823,3€

25-34years

879,4€1.055,8€

35-44years

874,4€1.279,9€

45+years

178,8€ 143,6€94,2€110,1€ 125,8€167€ 160,8€214,3€ 129,7€198,4€

ADDI

TION

AL IN

COM

E3

1.093,8€ 958,1€666,2€753,1€ 887,7€990,3€ 1.040,2€1.270,1€ 1.004,1€1.478,3€

AME

(201

3)2

ABM

I1

0

100

200

300

400

500

600

5.00

10.00

15.00

20.00

45.00

35.00

25.00

40.00

30.00

18-24

93.18 103.81

243.9

432.04

545

25-34 35-44 45-64 65+

DA_RMMB (€) DA_Rend Suplem (€) DA_GMM (€)

DR_RMMB (%) DR_Rend Suplem (%) DR_GMM (%)

WomenMen


10

Figure 9 - Percentage of the population at risk of poverty (before and a�er social transfers) and at risk of poverty or social exclusion, total and by sex and age group (2012, %)

In 2012, 45.6% of men (aged 18 and over) were at risk of monetary poverty before social transfers (Figure 9). The risk was greater amongst working-age males, increasing very significantly a�er 50 years of age, reaching its highest value of 87.8% of elderly males. For women, the poverty risk, before taking social transfers into account, was slightly higher than for men (2.5 points), but only because of its high incidence in the 50 to 64 age group, compared with men (61.7% and 53.3%, respectively). The gender pay gap in this specific age group can be explained, at least in part, by the fact there are more economically active-age men than women, benefiting from income from work.

Taking social transfers into account, some 19% of the adult popu-lation was at risk of poverty in 2012. The risk is clearly greater for younger adults and lesser for the elderly (65 and over), in so far as the la�er are the major beneficiaries of social transfers.

On the other hand, if the at risk of poverty or social exclusion indi-cator (AROPE), which, alongside monetary poverty, measures low work intensity in the household and severe material deprivation, the situation deteriorates for both men and women, with approx-imately a quarter of the adult population affected. The AROPE pa�ern by age group is very similar to the previous indicator, with higher incidence among young adults (over 31%), and less for the elderly.

At-risk-of-poverty rate is the proportion of individuals with income equivalent below the poverty threshold, which is 60% of average national income by adult equivalent (metadata – Eu-rostat). Risk rate is here analysed on the basis of calculations that refer to: 1. Before any social transfers: includes income from work and other private income, excluding old age and survivor’s pensions; 2. A�er social transfers: includes income from work and other private income, old age and survivor’s pensions and other social transfers (family, education, housing, sickness/disability, unemployment, social exclusion). (metadata – INE)

At risk of poverty or social exclusion (AROPE) rate is the pro-portion of individuals who are at risk of poverty OR living with severe material deprivation* OR in households with low work intensity**.

* Severe material deprivation rate is the proportion of the pop-ulation unable financially to meet certain expenses or purchase certain goods (at least 4 of 9 items defined at the European level).

** Very low per capita work intensity is the proportion of in-dividuals under 60 which, in the income period in question, lived in households in which adults aged 18 to 59 (excluding students) worked on average for less than 20% of the time of potential work (metadata – INE).

Further information on these indicators can be found in Wall et al. (2015).

TOTAL(18+)

24,6% 25,9%

45,6% 48,1%

18,6%18,8%

31,2%31,5%

37,0%41,3%

24,8%24,4%

18-24years

23,7%24,0%

30,9%32,3%

17,3%17,7%

25-49years

23,7%24,4%

61,7%53,3%

18,0%17,2%

50-64years

24,0%19,7%

86,5%87,8%

15,2%13,7%

65+years

AT R

ISK

OF P

OVER

TYOR

SOC

IAL

EXCL

USIO

NAT

-RIS

K-OF

-POV

ERTY

BEF

ORE

SOCI

AL T

RANS

FERS

AT-R

ISK-

OF-P

OVER

TYAF

TER

SOCI

AL T

RANS

FERS

Source: EU-SILC 2012/3, consulted at INE and Eurostat, on 30 June 2015 WomenMen


Figure 10 - Absolute disparity of at-risk-of-poverty rate before and a�er social transfers and of at risk of poverty or social exclusion, total and by age group (2012, percentage points)

Source: INE, Labour Force Survey 2012/2013; Authors’ own calculations (|H-M|) using Eurostat data, last updated 7 July 2015

Of all the indicators describing the economic situation of men and women, the at-risk-of-poverty rate a�er social transfers shows the least gender gap, drawing a�ention to the importance of State contributions in a�enuating poverty among women and the elderly (Figure 10): in the 50 to 64 age group, for example, the gen-der gap was 8.4 percentage points before social transfers and 1.5 percentage points a�er. Nevertheless, a�er the age of 50 men are still slightly be�er protected than women (0.8 points for the 50 to 64 age group 1.5 points for 65 and over), undoubtedly because

of their higher social security contributions throughout their ca-reers, which in general are longer and based on higher incomes.

Analysis of disparities using the AROPE indicator shows high dis-parities in the over 50s age groups. Bearing in mind the lower dis-parity described above for the poverty risk, this is likely to be due to greater inequality between men and women in terms of lower work intensity and material deprivation.

Determination of gender equality in this area is based on the analysis of: 1) ISSP 2012 indicators (see glossary box) relating to practices and a�itudes, like the number of hours expended in non-paid work (household tasks and care), the conjugal division of household tasks and a�itudes towards the division of unpaid work; and the 2011 Census indicator relating to type of household.

3. FAMILYEven though men increasingly take part in family life, family is still a locus of persistent gender inequalities. There are inequalities in the time devoted to household chores and the care of children and other family members, in the type of household tasks carried out by men and women, and also in the mode of residence (who one lives with) over the life course.

0,4%

0,4%

0,8%

1,5%

0,2%

18-24

25-49

50-64

65+

TOTAL

2.0 3.0 4.0 5.0 6.01.00 7.0 8.0 9.0AT

RIS

K OF

POV

ERTY

AFTE

R SO

CIAL

TRA

NSFE

RS

4,3%

1,4%

1,3%

8,4%

2,5%AT R

ISK

OF P

OVER

TYBE

FORE

SOC

IAL

TRAN

SFER

S

18-24

25-49

50-64

65+

TOTAL

0,3%

0,3%

6,6%

4,3%

1,3%AT R

ISK

OF P

OVER

TYOR

SOC

IAL

EXCL

USIO

N 18-24

25-49

50-64

65+

TOTAL

11

Greater At-risk-of-poverty/social exclusion for men Greater At-risk-of-poverty/social exclusion for women

Disparity M-W


As has been observed above, while the economic situation and men’s and women’s position in the labour market are key elements in determining the level of gender equality in society, unpaid work, i.e. that which takes place in the family home or domestic space, is no less significant.

The number of weekly hours expended in unpaid work indicator shows the level of gender inequality in the performance of house-hold tasks and care of family members (Figure 11). In 2014, men carried out on average 13 hours of unpaid work per week, while women did 30 hours. It is interesting to see that the number of hours performed by men tends to diminish with age, being at its highest, 20 hours, from ages 30 to 44 and lowest, over the age of 65. However, in the youngest age group the number of weekly hours is also 8, by virtue of the fact that many of these men are not married nor do they have children, and are still living with their parents. For women, by contrast, the number of hours of unpaid work increases with age, reaching its highest for the 45 to 64 age group (35 hours).

Analysis in isolation of the average number of weekly hours ex-pended on household tasks and care of family members confirms the tendency for the general indicator: men between the ages of 30 and 44 are those who most undertake those two types of un-paid work. Among these, however, on average seven hours more are spent on care than on household tasks. This means that taking care of the children is the catalyst for male participation in fami-ly life. In effect, in the 45 to 64 years age group, in which there is less occasion to care for small children, men’s weekly hours are significantly lower. Among women of that age group, however, the burden remains high, because they provide care to grandchildren and/or elderly parents.

Figure 11 - Number of hours spent on unpaid work, by sex and age (2014, hours)

Source: ISSP, 2012

The ISSP - International Social Survey Programme is an interna-tional network of comparative and longitudinal studies which con-ducts annual surveys.

The 2012 edition (ISSP-2012) launched the Family and changing gender roles model, which was applied in Portugal in 2014. The sur-vey was administered to a representative sample of the population resident in continental Portugal aged 18 and over (N=1001).

More information on the ISSP and ISSP-2012 results for other coun-tries can be consulted at h�p://issp.ics.ul.pt/ and h�p://www.issp.org/.

Gender inequality is at its highest for those aged 45 to 64 and low-est for those aged 30 to 44, 23 and 12 hours respectively (Figure 12).

As a result of men taking a greater part in caring, gender dispar-ity is higher for time devoted to household tasks (men spend 13 hours less on these than women do) than for care (7 hours less than women). It is important to underline that this situation aris-es on account of the lower disparity values for the 30 to 44 age group, in which care of children predominates (only 4 hours less than women) and for those aged 65 and over, for whom assistance to parents and spouses is more evident (1 hour less than women).

TOTAL(18+)

13h 30h

9h 17h

21h8h

23h8h

17h5h

13h6h

18-29years

32h20h

21h17h

17h10h

30-44years

35h12h

20h8h

24h8h

45-64years

26h8h

5h4h

24h

65+years

NUM

BER

OF W

EEKL

Y HO

URS

UNPA

ID W

ORK

(SUM

OF

TOTA

LS)

NUM

BER

OF W

EEKL

YHO

URS

FAM

ILY C

ARE

NUM

BER

OF

WEE

KLY

HOUR

S HO

USEH

OLD

TASK

S

7h

WomenMen

12


13

Figure 12 – Disparity between men and women in number of weekly hours spent on unpaid work, total, by type of work and age group (2014, hours)

Source: ISSP, 2012

Figure 13 - Conjugal division of household tasks - ‘Who does what in household tasks?’, by type of household task and age group (2014, %)

Source: ISSP, 2012

8%

8%

16%

17%

13%

18-29

30-44

45-64

65+

TOTAL

25.00NU

MBE

R OF

WEE

KLY

HOUR

S SP

ENT I

NHO

USEH

OLD

TASK

S 20.015.010.05.0

12%

4%

1%

12%

7%NUM

BER

OF W

EEKL

YHO

URS

SPEN

T IN

FAM

ILYCA

RE TA

SKS

18-29

30-44

45-64

65+

TOTAL

15%

12%

23%

17%

18%NUM

BER

OF W

EEKL

YHO

URS

SPEN

T IN

UNPA

IDW

ORK

18-29

30-44

45-64

65+

TOTAL

TOTAL(18+)

18-29years

30-44years

45-64years

65+years

WHO

DOE

S TH

E LA

UNDR

Y?W

HO C

OOKS

?W

HO C

ARES

FOR

THE

SIC

K?W

HO D

OES

REPA

IRS?

8,9%

12,2%

78,9%

10,7%

10,7%

78,7%

9,6%

6,6%

83,8%

9,8%5,7%

84,5%

9,9%

8,2%

81,9%

6,1%

37,8% 56,1%

2,5%

47,3% 50,2%

3,6%

53,2% 43,2%

6,1%

44,8% 49,1%

4%

48,6% 47,4%

5,4%

10,9%

83,7%

1,6%

5,4%

93,1%

1,3%

5%

93,7%

3,5%

5,3%

91,2%

2,2%

5,7%

92,1%

12%

26,1%

62%

7,5%

24%

68,5%

4,5%

15,1%

80,5%

7,3%

16,3%

76,4%

6,6%

18,9%

74,6%

Mulheres

Both

Homens

WomenMen

13

Disparity M-W: more hours spent by menDisparity M-W: more hours spent by women


The conjugal division of unpaid work is an indicator which gives an account of the way couples divide household tasks and care of children and/or other family members amongst themselves. Each task may be shared by the couple or performed by one of the spouses, and for this reason the way these tasks are divided as a whole (together with the number of hours spent) is also important for an understanding of gender equality in family life.

A preliminary reading of ISSP 2012 data on the conjugal division of four specific tasks – doing repairs, cooking, doing the laundry and caring for the sick – shows that inequalities associated with tradi-tional gender roles persist (Figure 13): repairs are assigned to the male, given that this task is always or usually performed by men in 82% of couples; doing the laundry is the task with the great-est disparity between men and women, as it is overwhelmingly women who perform it (in 92% of couples). Moreover, this is the least shared task, as only 6% of couples share it. With other tasks there is more sharing: 47% of couples share the care of the sick; and 19% of couples share the preparation of meals. Nevertheless,

when there is no sharing, it is the woman who carries out the task: in only 4% of couples do men always or usually care for the sick; and only in 7% of couples do men prepare meals on their own.

Analysis by age group reveals a trend towards greater participa-tion by men in unpaid work, either by sharing tasks as a couple, or doing them individually. Younger couples have a be�er balanced division of household tasks. It is among couples in the 45 to 64 year age group that gender inequality is greatest and not in old-er couples, probably due to a life-cycle effect, whereby men are called upon to make a greater contribution to household tasks when women start having difficulty in carrying them out.

Cooking is the aspect of domestic life in which men are increas-ingly making a mark, either by sharing or doing it all themselves. In effect, over half of young couples divide this task and in 12% of couples it is the man who always or usually cooks, double the per-centage for all couples as a whole.

Figure 14 – Disparity between men and women in the conjugal division of household tasks, by type of task and age group (2014, percentage points)

Source: ISSP, 2012

Analysis of the disparity shows the strong genderification of household work (Figure 14). Of the four selected tasks, repairs continue to be the main task assigned to men in all age groups. The other tasks are those for which the burden of performing them falls on women, although doing the laundry is the most feminized task of all, occupying a position equivalent to repairs for men. Cooking is the task for which the disparity is clearly diminishing, from 76% for the 45 to 64 age group to 50% in the 18 to 29 age group. Finally, looking a�er the sick is the task in which gender disparity is the lowest (6%), regardless of age. Caring is thus the area of greatest conjugal sharing and the one in which men participate the most.

70,0%

68,0%

74,3%

74,6%

72%

18-29

30-44

45-64

65+

TOTAL

20 30 40 50 60100 70 80 90 100

WHO

DOE

S RE

PAIR

S?

50%

61%

69,1%

76%

68%

WHO

COO

KS?

18-29

30-44

45-64

65+

TOTAL

31,7%

6,1%

6,1%

6,1%

6,1%

78,3%

91,5%

92,4%

87,6%

89,9%

WHO

CAR

ES F

ORTH

E SI

CK?

18-29

30-44

45-64

65+

TOTAL

WHO

DOE

STH

E LA

UNDR

Y?

18-29

30-44

45-64

65+

TOTAL

14

Disparity M-W: task predominantly carried out by menDisparity M-W: task predominantly carried out by women


A�itudes towards the conjugal division of unpaid work show that there is ample recognition not only of the desirability of gender equality in family life, but also of the need for changes in male behaviour with a view to achieving that ideal (Figure 15). Men and women agree that tasks should be divided equally, and that men should take a greater part than they currently do in household

tasks and care of children. Despite the consensus on the three in-dicators, it diminishes with age and is always lower among men. It is interesting to compare these results with the previous ones, in that they show there is a disconnect between the idea of equality in terms of values and couples’ practices which are far from being egalitarian.

Figure 15 - A�itudes towards the conjugal division of unpaid work, total and by sex and age group (2014, % agree totally/agree)

Source: ISSP, 2012

TOTAL(18+)

74,0% 81,4%

72,4% 85,4%

91,7%73,5%

91,0%82,0%

87,2%71,6%

97,4%71,9%

18-29years

87,7%82,1%

91,9%71,3%

92,0%77,2%

30-44years

79,6%68,9%

83,4%78,4%

92,5%77,3%

45-64years

72,5%64,4%

80,9%64,8%

87,1%64%

65+years

IN A

COU

PLE

THE

MAN

AND

THE

WOM

AN S

HOUL

D DI

VIDE

HOUS

EHOL

D TA

SKS

EQUA

LLY

MEN

SHO

ULD

LOOK

AFT

ER T

HE C

HILD

REN

MOR

E TH

AN T

HEY

DO C

URRE

NTLY

MEN

SHO

ULD

TAKE

AGR

EATE

R PA

RT IN

HOU

SEHO

LDTA

SKS

THAN

THE

Y DO

CUR

RENT

LY

WomenMen

Figure 16 – Disparity between men and women in a�itudes towards the conjugal division of unpaid work, total and by age group (2014, percentage points)

9%

5,6%

10,7%

8,1%

7,4%

18-29

30-44

45-64

65+

TOTAL

10.0 15.0 20.0 25.0 30.05.00

IN A

COU

PLE

THE

MAN

AND

THE

WOM

AN S

HOUL

D DI

VIDE

HOUS

EHOL

D TA

SKS

EQUA

LLY

MEN

SHO

ULD

LOOK

AFTE

R TH

E CH

ILDR

EN M

ORE

THAN

THE

Y DO

CUR

RENT

LY

MEN

SHO

ULD

TAKE

A G

REAT

ER P

ART

IN H

OUSE

HOLD

TAS

KSTH

AN T

HEY

DO C

URRE

NTLY

15,6%

20,5%

16,1%

5%

13%

18-29

30-44

45-64

65+

TOTAL

25,5%

14,8%

15,2%

23,1%

18,2%

18-29

30-44

45-64

65+

TOTAL

15

Source: ISSP, 2012

more favourable a�itude among men than women more favourable a�itude among women than men

Disparity M-W


Analysis of the disparity shows that women in all age groups generally have a more favourable a�itude to gender equality (Figure 16). The indicator which reflects the idea of equality in household work, however, is that in which the disparity is the least, because men tend to be in agreement with it. Indicators reflecting changes in behaviour, namely those aiming at greater male participation in childcare and household tasks, show larger disparities, or in other words a greater distance between men’s and women’s a�itudes. For childcare, the distance is greatest in the 30 to 44 age group (21%), in other words at the point in the life-cycle when the children require the most care. For tasks in general, it is among younger individuals (26%) and the more elderly (23%) where the gender gap is the most marked.

Figure 17 - Co-residence: resident population (20+ years) by type of household, by sex and age group (2011, %)

Source: Census, 2011; Delgado, A. and Wall, K. (eds). 2014. Famílias nos Censos 2011. Diversidade e Mudança, Lisboa, INE/ICS.

65+years

20-29years

30-39years

50-64years

WO

MEN

MEN

1%

52%

19%

14%

7%7%

3%

54%

10%

17%

5%

11%

1%

63%

10%

12%

8%6%

1%

43%

29%

15%

8% 4%1%

58%

14%

13%

12% 2%

2%

45%

18%

15%

10%

10%

2%

51%

14%

18%

5%10%

1%

61%

9%

13%

5%11%

2%

31%

32%

16%

10%

9%

3%

36%

18%

8%

7%

28%

TOTAL(20+)

In 2011, 71% of the resident male population over 19 years of age was living in households made up of couples (see methodology box), most of them with children (52% of all households) (Figure 17). The remaining male population was living in complex family households (14%), monoparental households (7%) and persons alone (7%). Just 1% lived in other types of household, made up of two or more related or unrelated persons, but in which there was no conjugal or parental family nucleus. This pa�ern of co-resi-dence is not constant throughout life, as is reflected in the differ-ences between age groups: men from 30 to 49 years of age in 2011 were those most living as a couple with children (63%), whereas living alone or just with a spouse was more frequent among men aged 65 and over (12% and 58%, respectively). This is a stage in life when adult children no longer live with their parents and where widowhood is increasingly found.

Household is the sociological concept that describes the group of people who live in the same house, the residence criterion being based on the sharing of lodging and resources. A household may consist of one person alone, several unrelated persons or several persons having blood or marriage ties.

A detailed description of the codification underlying this study of households in the Census can be consulted in Delgado and Wall (2014, Chapter 2 - Annex – Methodological Notes, pp. 61-63).

Although these pa�erns of co-residence are similar for women, the data show that men always live more in couple households and less in other types of household than women. On the other hand, inequality in the mode of co-residence increases with age: in the 20 to 29 age group male and female pa�erns are relatively similar; between 30 and 49 gender difference begins to make itself felt, with more women living in monoparental households as a result of changes to living arrangements which occur a�er the separation of couples with children (Delgado and Wall, 2014); in the 50 to 64 and 65 and over groups gender difference accentuates, largely as a result of the greater incidence of female widowhood . In effect, among the elderly population, it is women who most live alone (28%), in complex families (18%) and other types of household (3%), representing different ways of living a�er being widowed.

16

Living Alone

Monoparental families

Other Households

Couple without children

Couple with children

Complex Families


17

3.8

0.9

2.7

22.474,6%

1.6

20-29

30-49

50-64

65+

TOTAL

COUP

LE W

ITHO

UTCH

ILDR

EN0 252015105

3.6

2.3

6.9

11.9

7.1

COUP

LE W

ITH

CHIL

DREN

20-29

30-49

50-64

65+

TOTAL

1.1

5.0

5.5

5.9

3.3

1.2

1.2

1.0

4.3

1.6

0.0

2.3

2.4

16.9

3.6

MON

OPAR

ENTA

LFA

MIL

IES

20-29

30-49

50-64

65+

TOTAL

LIVI

NG A

LONE

20-29

30-49

50-64

65+

TOTAL

COM

PLEX

FAM

ILIE

S 20-29

30-49

50-64

65+

TOTAL

Figure 18 – Disparity between men and women in co-residence: resident population (20+ years) by type of household, total and by age group (2011, percentage points)

Source: Authors’ own calculation based on Censos 2011; Delgado, Ana and Wall, Karin (eds). 2014. Famílias nos Censos 2011. Diversidade e Mudança, Lisboa, INE/ICS.

Analysis of gender disparity shows even more clearly the differ-ences in pa�erns of co-residence. It is important to highlight the crucial role of men’s and women’s calendars in establishing a fami-ly and throughout family life, as reflected in their greater presence in any given family type by age group (Figure 18). A clear example of this is the gender disparity in monoparental families, where there are more men than women only in the youngest age group. This is due to the fact that men start out later on the conjugal life, o�en still living with their families of origin when in this age group, either with their parents (couple with children), or with only one of them (monoparental family).

The same can be said of gender disparity in households of per-sons living alone. The prevalence of men in the 30 to 49 age group reflects, on the one hand, that delay in entering into conjugal life (where there is residential independence) and, on the other, the impact of divorce. In effect, a�er the dissolution of a marriage it is generally women who keep custody of the children, and then form a monoparental family (as is shown by the prevalence of this type of family from the age of 30 onwards), while men go on to live alone (Delgado and Wall, 2014).

Among the male population, living in a couple household is the predominant form, although between 20 and 29 years of age this reflects the fact of living in the parents’ home rather than estab-lishing their own family. Living in a couple household without chil-dren shows a different pa�ern, very much tied to the age differ-ence frequently found in couples (men tend to be older): this type is found most in women from ages 20 to 29 and men from age 30 to 49, reflecting their different ages when they start living as a couple; and it prevails again in the 50 to 64 age range for women and the 65 and over group for men, corresponding to the stage of life when couples live alone again a�er their adult children leave home.

It is also important to emphasize that gender disparity is at its highest among the elderly population, reflecting not only dif-ferent male and female calendars, but also women’s higher life expectancy (and consequently the greater incidence of female widowhood), which explains their strong presence in households of person living alone and in complex families, while men continue living in couple households.

Disparity M-W: more men than women Disparity M-W: more women than men


Analysis of educational a�ainment levels of the Portuguese (aged 15 and over) shows the low overall levels of educational a�ainment, a legacy of the delayed democratization of the education system in Portugal (Figure 19): almost 60% of men have at most the ba-sic cycle of school education; 24% secondary education; and 17% higher education. As is clearly evident, analysis by age group sho-ws the progress made in the education system and the successive increases in the period of compulsory schooling (on how the edu-cation system has changed see Almeida and Vieira, 2006). In ef-fect, 72% of men aged 45 and over – who went to school when the

compulsory schooling period was 4 years (the former fourth class) or 6 years (the former 2nd year of preparatory schooling) – have basic education; the remainder are equally distributed throughout secondary and higher education. Among those under 45 – who had 9 years of compulsory schooling – there is an observable increase in secondary and higher education levels, the former much more rapid than the la�er, although basic levels of a�ainment are still prevalent in this segment of the population (except for younger persons, many of whom are still studying).

Analysis of gender inequality in education is here carried out using the traditional indicator relating to education of the Portuguese pop-ulation, but also using indicators which reflect two contrasting situations: 1) that of the population with higher levels of schooling, based on a distribution analysis by area of higher education; 2) that of those who are younger and more vulnerable in terms of qualifications, that of early leavers from the education system and that of young people who neither in work nor in education (NEET) (see definitions box below).

4. EDUCATIONEducation is known to be the area of social life in which gender inequality has for some years been reversed, i.e., it is men who are at a disadvantage in educational a�ainment indicators.

Figure 19 - Population distribution by level of educational a�ainment, total and by sex and age group (2014, %)

Source: INE, Labour Force Survey

TOTAL(15+)

23,5% 25,4%

57,0% 43,4%

2,4%2,3%

48,1%45,4%

28,5%43,7%

--

15-24years

33,3%34,1%

25,8%41,9%

25-34years

27,4%25,9%

37,4%51,5%

0,7%1,2%

35-44years

15,5%13,8%

59,2%68,9%

5,1%3,0%

45+years

SECO

NDAR

Y SC

HOOL

ING

17,2% 28,8%22,5%9,2% 40,7%23,7% 34,6%21,4% 19,3%13,1%

HIGH

ER E

DUCA

TION

BASI

C SC

HOOL

ING

NONE --

WomenMen

18


Comparison of a�ainment levels of men and women highlights the higher educational qualifications of women. Those having secon-dary and higher education (54%) is already higher than those who have only a�ained the basic level of education; and the growth of higher education among women is much more significant than among men, to the extent that it already at 41% among women

aged 25 to 34. Comparison within this age group are particularly interesting, in that the numbers of men and women having secon-dary education is similar (about one-third), but very different for those having secondary and higher education: 42 and 24% respec-tively for men; 26 and 41% for women.

Figure 20 - Disparity between men and women in population distribution by level of education a�ained, total and by age group (2014, percentage points)

*Only the 2nd and 3rd cycles of basic education were taken into account, 1st cycle data not available **Data on 2nd cycle of basic education, secondary education and higher education for 65 and over were not taken into account for women because they were not available

Source: INE, Labour Force Survey, data consulted on 28 July 2015

0.0

0.0

0.5

2.2

0.1

15-24

25-34

35-44

45+

TOTAL

NONE

0 181614102 4 6 8 12

15.2

16.1

9.6

14.2

13.5

BASI

C SC

HOOL

ING

2.7

0.8

1.5

1.7

1.9

17.0

13.1

6.2

11.6

SECO

NDAR

Y SC

HOOL

ING

HIGH

ER E

DUCA

TION

13.3

15-24*

25-34

35-44

45+**

TOTAL

15-24

25-34

35-44

45+**

TOTAL

15-24

25-34

35-44

45+**

TOTAL

Analysis of the gender gap highlights the differences between men’s and women’s educational trajectories (Figure 20). Men have a stronger presence in basic education, with an increasing gap: 9.6% in the oldest age group, to 16.1% in the 25 to 34 age group. In contrast, there is a greater presence of women in higher educa-tion – increasing the gap from 6.2 to 17.0% -, and also in secondary education, although here the gap has tended to diminish, to the

extent that in the 25 to 34 age group men predominate (due to the prevalence of women in higher education). Finally the population not having even the basic level of education is very residual, and non-existent among those under 35. The gaps in the two older age groups reveal a transition from an education system under the Estado Novo, which penalized women, to democratization and the consequent feminization of education.

Figure 21 - Student distribution by educational a�ainment level (ISCED 5-6), by educational area and sex (2012, %)

2,4%

8,9%

7,7%

7,8%

28,1%

8,3%

34,9%

1,8%

0,1%

8,6%

10,1%

23%

5,2%

34,0%

6,4%

10,7%

1,9%

0,1%

EDUCATION AND TRAINING

HUMANITIES AND THE ARTS

HEALTH AND WELLBEING

SERVICES

SOCIAL SCIENCE, MANAGEMENT AND LAW

SCIENCE, MATHEMATICS AND IT

ENGINEERING, CONSTRUCTION AND MANUFACTURING

AGRICULTURE AND VETERINARY SCIENCE

UNKNOWNSource: Eurostat, data consulted on 5 August 2015

19

Disparity M-W: education level where men predominate Disparity M-W: education level where women predominate


When analysing the distribution of men and women in higher ed-ucation (ISCED levels 5-6) by major educational areas, men are strongly concentrated in two areas, engineering and construction (35%) and social sciences, management and law (28%) (Figure 21). Well below these come the arts and humanities (9%) and science, mathematics and IT (8%). All other educational areas are residual. Distribution is more widespread among women, although social sciences, management and law are the main educational areas (34%). Next come health and well-being (23%) and lower down, engineering and construction (11%) arts and humanities (10%). Re-maining areas vary between 2 and 6%.

Analysis of gender disparity clarifies that despite the greater presence of men than women in three major educational areas – engineering and construction; science, mathematics and IT; servic-es (which include personal, transport, security and environmental protection services) – it is only in the first of these that they ef-fectively stand out, with 24.2 percentage points more (Figure 22). Women, with greater presence in the remaining 6 educational ar-eas, stand out above all in health and well-being (15.2 pp), but also in the social sciences, management and law (5.9 pp) and education and training (3.8 pp). We may thus state that there are essentially two particularly genderified educational areas: engineering and construction for men; and health and well-being for women.

Figure 22 –Disparity between men and women in student distribution by educational level (ISCED 5-6), by educational area (2012, percentage points)

0 5 10 15 2520 30

1,9%

2,6%

24,2%

6,2%

1,1%

15,2%

5,9%

0,2%

0,1%

Disparity M-W: field in which men predominate

Disparity M-W: field in which women predominate

EDUCATIONAND TRAINING

HUMANITIESAND THE ARTS

HEALTH AND WELLBEING

SERVICES

SOCIAL SCIENCE, MANAGEMENT AND LAW

SCIENCE, MATHEMATICS AND IT

ENGINEERING, CONSTRUCTION AND

MANUFACTURING

AGRICULTURE AND VETERINARY SCIENCE

UNKNOWN

Figure 23 - NEETs and early leavers from education and training, total and by sex and age group (2013, %)


13,9%14,2%

NEETEARLY LEAVERS FROM

EDUCATION AND TRAINING

14,1%20,7%

TOTA

L(1

5-24

yea

rs)

WomenMen

Figure 24 - Disparity between men and women in NEET rates and early dropout from education and training, total (2013)


Source: Eurostat, data consulted on 5 August 2015

Rate of early dropout from education and training (early leavers) is the percentage of the population aged 18 to 24 that le� off study-ing without completing secondary education (metadata – INE).

NEETs are young people (generally aged between 15 and 24) who are not employed, studying or in training.

More information on these indicators can be consulted in Rowland et al. (2015) and Torres and Lima (2014)

0 2 51 3 4 6 7

NEET

EARLY LEAVERS FROMEDUCATION AND TRAINING

0,3

6,6

Disparity M-W: high numbers of NEET and early dropout among men

Disparity M-W: higher levels of NEET and early dropout among women

Moving on to the more socially vulnerable segments of the youth population – either because they have dropped out without com-pleting secondary education, or because they are not in the edu-cation system, the labour market nor training (NEET), 2013 results show that young males are at a greater disadvantage, particularly as far as early dropout is concerned: 21% of boys, as compared to 14% of girls, failed to complete secondary education (Figure 23). The gender gap here is accordingly 6.6 percentage points and pe-nalizes young males.

The scenario is less unequal, however, if young NEETs are taken into account. Here there is an equal number of each sex. Between the ages of 15 and 24, some 14% of boys and girls are neither stud-ying, working nor in training. The gender gap here is clearly resid-ual (Figure 24).

Comparison of these two indicators is of great interest, in that it reveals that although boys are at the outset more vulnerable in social terms, in the light of their less successful educational tra-jectories – with early dropout and lower numbers entering higher education, their failure is less penalized in the labour market than that of girls. In effect, although girls are more successful at school, this fact does not seem to influence NEET status i.e. it is of no ben-efit to them when they are entering the labour market.

20


1,1

0,1

Disparity M-W: greater risk of poverty among men

Disparity M-W: greater risk of poverty among women

3.0

2.5

2.0

1.5

1.0

0.5

0.0

POLA

ND

SLOV

ENIA

PORT

UGAL

IREL

AND

ROM

ANIA

LUXE

MBO

URG

NETH

ERLA

NDS

DENM

ARK

HUNG

ARY

MAL

TA

BELG

IUM

LATV

IA

UNIT

ED K

INGD

OM

SPAI

N

FINL

AND

EU28

FRAN

CE

GREE

CE

CROA

TIA

NORW

AY

AUST

RIA

CZEC

H RE

PUBL

IC

SLOV

AKIA

ITAL

Y

GERM

ANY

LITH

UANI

A

CYPR

US

BULG

ARIA

SWED

EN

ESTO

NIA

11,66,7

Gender disparity: higher activity rate among men

Gender disparity: higher activity rate among women

30.0

20.0

10.0

0.0

FINL

AND

SWED

EN

LITH

UANI

A

DENM

ARK

LATV

IA

PORT

UGAL

SLOV

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Despite the existing gender disparities observed and discussed here for Portugal as far as labour market and the economic situation are concerned, comparative analysis shows that in the context of the European Union the value for Portugal is low (6.7 percentage points) in the gender gap for the activity rate (Figure 25). It is thus in 6th place in the ranking of countries with less inequality in the activity rates for men and women, alongside the Nordic and Baltic countries. This reflects the high rate of these women’s participation in the labour market.

5. PORTUGAL IN THE EUROPEAN CONTEXTFigure 25 - Disparity between men and women in Activity rate, EU28 (2014, percentage points)

Source: Eurostat

Figure 26 - Disparity between men and women in at-risk-of-poverty rate a�er social transfers, EU28 (2012, percentage points)

Source : EU-SILC 2013, Eurostat.

As far as gender disparity in the at-risk- of-poverty rate is concerned, Portugal occupies the 2nd place in the ranking of countries along-side Slovakia and behind Poland, 3 countries in which the disparity tends towards zero (Figure 26). Two interesting aspects in connection with this indicator are worth highlighting here. First, unlike the gender disparity in the activity rate, where the prevalence of men is com-mon to all countries, gender disparity in the at-risk-of-poverty rate is not always in the same direction. While in the majority of countries the risk of poverty is greater for women, there are four countries where men are more affected: Spain, Denmark, Hungry and, very re-sidually, Portugal. Secondly, it is important to recognize the particular economic vulnerability of women in many developed countries, whether in contexts where they work shorter hours or even in contexts where they work the same number of hours as men. In the same way, countries with low levels of at-risk-of-poverty rate gender disparity also have different labour market models amongst themselves.

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Disparity M-W: higher activity rate among men Disparity M-W: higher activity rate among women


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Disparity M-W: higher dropout rates among men

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Disparity M-W: greater number of hours performed men

Disparity M-W: greater number of hours performed by women

Household Tasks

Childcare

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In the context of family life and in particular as far as the way men and women divide unpaid work is concerned, disparities in Portugal are higher for men and lower for women in terms of hours spent on household tasks and childcare, while in Portugal the value of the disparity is the same for both types of tasks (7 hours), while in Europe as a whole the disparity in the participation of men and women is higher for childcare (10 hours) than it is in participation in household chores (5 hours) (Figure 27).

In clear contrast to the gender inequality present in the labour market, the economic situation and the division of unpaid work, in edu-cation in 2011 Portugal was in the worst position for gender disparity in terms of early dropout from education and training, with 10.2 percentage points to the disadvantage of boys (Figure 28). This is a value far off the 3.3 percentage points of the EU28 average and even further from the be�er positioned countries, in which gender disparity is residual, like Germany, Croatia, the Czech Republic and Slovakia. It should be added that, regardless of the actual value of the indicator, the sense of disparity is the same in all countries except Bulgaria, where the early dropout rate is higher for girls, probably due to an early transition to maternity (Wall, Cunha, Rodrigues and Correia, 2015).

Figure 27 - Disparity between men and women in the number of hours spent on household tasks and childcare, UE27 (2012, hours)

Figure 28 - Disparity between men and women in early dropout rate from education and training (Early leavers), EU28 (2011, percentage points)

Source: EQLS, 2012 - Eurofound

Source: Eurostat

This leads to the possibility that, as we saw above for Portugal, social transfers may play a key role in other countries as well as in redu-cing the economic vulnerability of women – caused by their shorter or more intermi�ent working hours and their income levels which tend to be lower – thus mitigating gender disparities related to the poverty risk.

REFERENCESAlmeida, Ana and Vieira, Maria Manuel (2006). A Escola em Portu-gal, Lisboa, Imprensa de Ciências Sociais.

Delgado, A. and Wall, K. (eds). 2014. Famílias nos Censos 2011. Di-versidade e Mudança, Lisboa, INE/ICS. Available at http://www.observatoriofamilias.ics.ul.pt/images/INE/familiascensos2011.pdf

Rowland, Jussara et al., 2015. Nem emprego, nem em educação ou formação: jovens NEEF em Portugal numa perspetiva compara-da – Policy Brief 2014. OPJ/ICS-ULisboa

Torres, Sónia and Lima, Francisco. 2014. «Dinâmica e caracter-ização dos jovens não empregados que não estão em educação ou formação (NEEF) em Portugal». Estatísticas do Emprego – 3º trimestre de 2014: 35-47. Available at http://www.igfse.pt/upload/docs/2015/NEEFestudoINE.pdf

Wall, Karin et al. 2015. Impactos da Crise nas Crianças Portugue-sas. Indicadores, Políticas, Representações, Lisboa, Imprensa de Ciências Sociais.

Wall, Karin, Cunha, Vanessa, Rodrigues, Leonor and Correia, Rita (2015). «Famílias em Portugal e na Europa». In João Ferrão and Ana Delicado (coord.). Portugal Social em Mudança. Portugal no Con-texto Europeu em Anos de Crise: 2015, Lisboa, Instituto de Ciên-cias Sociais da Universidade de Lisboa: 31-45.


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