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1、GENDER DIMENSION OF LABOUR MARKET TRANSITIONS Implications for activation and skills development policies of the EU neighbouring countries GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|02 The contents of the report are the sole responsibility of the ETF and do not necessarily reflect the views of th

2、e EU institutions.European Training Foundation,2024 Reproduction is authorised,provided the source is acknowledged.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|03 PREFACE This study focuses on the gender dimension of labour market transitions and its implications for policy-making in the areas of a

3、ctive labour market policies,career guidance,and skills development.The European Training Foundation(ETF)initiated this research to map how activation and skills development policies are gaining importance in the neighbouring countries of the European Union as key components of post-COVID-19 recover

4、y,in green and digital transitions and strategies to address emerging socio-economic risks and uncertainties,and significant security threats worldwide.The report provides an overview of the key trends in labour market participation among women,education outcomes,and gender-responsive policies and p

5、rogrammes.It sheds light on exemplary policies,national initiatives or donor programmes to enhance gender equality in labour market transitions and to address root causes of inequalities.The ETF contributes to the development of human capital by providing advice and support to its partner countries

6、and to the EU institutions on the reform of education,training and employment policies and systems.This contributes to the social well-being,stability and prosperity in the countries surrounding the European Union.We hope this report will provide a good basis for decision-making to promote gender eq

7、uality in the EU neighbouring countries(hereinafter ETF Partner Countries),inspire reforms and gender-sensitive programmes,as well as to inform EU external support activities.In order to meet the objectives,the research team implemented a multidisciplinary methodological framework that combined quan

8、titative and qualitative research methods.The analysis was conducted primarily via desk research and was supported by a survey among several ETF Partner Countries to identify good practices.This thematic report was drafted by Nicola Duell with the contribution of Martina Lubyova,Marius Haulica and A

9、rmen Cekic,as part of the ETF project Active labour market policies and skills development studies in the ETF partner countries.ETFs Donatella Di Vozzo,Iwona Ganko,Eva Jansova,Outi Krkkinen and Cristina Mereuta contributed to the definition of the research methodology,information collection,and revi

10、ewed the report.Anna Dorangricchia,Project Manager Gender Equality from the Social and Civil Affairs Division of the Secretariat of the Union for the Mediterranean,peer reviewed the report and provided valuable suggestions.The ETF shared the preliminary findings and conclusions with the representati

11、ves of the EU neighbouring countries as well as regional,European and international organisations during the policy learning event on gender and inclusive Active Labour Market Policies,held in Barcelona,Spain(November 2023).The ETF experts and research team would like to thank all the stakeholders i

12、n the countries covered by this study and other European or international researchers who shared information and reflections.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|04 CONTENTS PREFACE 3 CONTENTS 4 EXECUTIVE SUMMARY 6 1.INTRODUCTION 12 2.MAIN TRENDS IN THE GENDER DIMENSION OF LABOUR MARKET TRA

13、NSITIONS IN ETF COUNTRIES 14 2.1 Main labour market features and trends by gender 14 2.2 The position of women in the labour market 16 2.3 Gender aspects in skills development and skills mismatch 22 2.4 Effects of COVID-19,recovery and multiple crises on the employment of women 26 2.5 Employment opp

14、ortunities for women in the twin transition 27 2.6 Conclusions 30 3.CHALLENGES FOR WOMEN TO ACCESS THE LABOUR MARKET AND ROOT CAUSES OF GENDER INEQUALITIES 31 3.1 Gender stereotypes and social norms 31 3.2 Inequalities in access to training,finance and capital 34 3.3 Care responsibilities 34 3.4 Con

15、clusions 36 4.ACTIVE LABOUR MARKET POLICIES TO PROMOTE THE EMPLOYMENT OF WOMEN 37 4.1 Overview of priorities and strategies gender mainstreaming and targeted activities 37 4.2 Employment incentives and direct job creation programmes 44 4.3 Programmes to promote female entrepreneurs 46 4.4 Programmes

16、 that target women in rural areas 49 4.5 Measures to support the green transition 50 4.6 Childcare support to promote the employment of women 51 4.7 ALMPs to mitigate the labour market effects of COVID-19 54 4.8 Programmes for vulnerable female migrants 55 4.9 Conditions for successful implementatio

17、n 56 5.CAREER GUIDANCE,UPSKILLING AND RESKILLING 61 5.1 Overview 61 5.2 Examples of gender-sensitive and gender-transformative career guidance 62 5.3 Participation in training measures 63 5.4 Upskilling and reskilling measures for developing digital skills 65 GENDER DIMENSION OF LABOUR MARKET TRANSI

18、TIONS|05 5.5 Conditions for successful implementation of training measures 66 6.CONCLUSIONS AND RECOMMENDATIONS 68 6.1 Issues and challenges 68 6.2 Enabling Factors 69 6.2 The way ahead 70 ANNEX:ADDITIONAL STATISTICS AND INFORMATION 72 GLOSSARY OF GENDER EQUALITY TERMS 88 ACRONYMS 89 REFERENCES 91 G

19、ENDER DIMENSION OF LABOUR MARKET TRANSITIONS|06 Executive Summary Objective of the report In this report there is a review of the gender dimension in labour market transitions,an overview of main causes for gender inequalities in ETF Partner Countries(PCs),and an examination of what strategies,polic

20、ies and activities ETF partner countries have been undertaking mainly in the area of active labour market policies,including upskilling,reskilling and career guidance.Active Labour Market Policies(ALMPs)and skills development policies are gaining importance in Europe and beyond as key components of

21、post-COVID-19 recovery,green and digital transitions and emerging socio-economic risks and uncertainties in the context of Russias aggression against Ukraine.This report looks at the gender sensitiveness,gender-responsiveness and the gender-transformative approaches1 of ALMPs and career guidance,nat

22、ional initiatives and donor programmes to enhance gender equality in labour market transitions and to address the root causes of the inequalities.The report focuses on the participation of women in the labour markets and characteristics of female employment,and it is based on reviewing available lit

23、erature and data.The work was underpinned by a survey of active labour market programmes,the monitoring and evaluation practices as well as initiatives to make the access and delivery of(re)training measures more flexible,involving mainly Public Employment Services of several ETF PCs2.Gender dimensi

24、on of labour market transition in ETF Partner Countries In most ETF PCs,the activity rate and employment rate of men is higher than those of women.The activity gap is highest in most Southern and Eastern Mediterranean countries,as well as in Trkiye and Kosovo*.Activity gaps are comparatively low(and

25、 below EU-27 average)in Israel,Moldova,Kazakhstan,and Ukraine.The female activity rates have been decreasing in some of the countries and increasing in others.Those countries with very high gender employment gaps are also characterised by very low employment rates of women(mainly in Southern and Eas

26、tern Mediterranean countries).This points to a double challenge for policymakers;namely to increase employment rates while reducing the gender employment gap.Conversely,those countries with the smallest employment gender gaps are also those with the highest female employment rate(mainly Central Asia

27、n countries,a few Eastern Partnership countries and Israel).In some countries,employment rates are low for both men and women.Several Western Balkan countries and Eastern Partnership countries fall into this category.In addition to the level of activity,the quality of female employment and thus thei

28、r working conditions and pay are highly relevant.Women are at higher risk than men to be in vulnerable employment.In particular,contributing family members,who are not receiving an own income and social protection,are typically women.Their share of the total employment is significant in a number of

29、countries.In contrast to helping family members,own-account workers are more often men than women in all ETF PCs.Nevertheless,the share of female own account workers among all female employed is sizeable in several ETF PCs.In Central Asia,the agricultural sector is the main employer in rural areas,a

30、nd women make up more than half of this workforce.In addition,informal employment renders women particularly vulnerable.Women are poorly represented among entrepreneurs and as owners/leaders/managers of medium-sized and large companies.1 See Glossary of gender equality terms at the end of the report

31、.2 Countries include:for Central Asia:Kazakhstan,Kyrgyzstan,Tajikistan,Uzbekistan;for Eastern Partnership:Armenia,Georgia,Moldova,Ukraine;for Western Balkans and Trkiye:Albania,Bosnia and Herzegovina,Kosovo,Montenegro,Serbia,Trkiye;for Southern an Eastern Mediterranean Egypt,Jordan,Morocco and Tunis

32、ia.*This designation is without prejudice to positions on status,and is in line with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo declaration of independence.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|07 The gender pay gap is generally high.One reason in all ETF PCs is that women tend to be

33、more often employed in occupations and sectors where pay is relatively lower for a given level of education and skills.Another reason is that they are not well represented in managerial positions.In most ETF PCs,the enrolment rate of women in secondary and tertiary education is well above that of me

34、n.In all ETF PCs,there are issues of gender segregation in the graduation levels according to fields of studies.One exception is the ICT sector,where the differences are less visible,in particular in the Southern and Eastern Mediterranean region.This is in contrast to the EU,where gender disparities

35、 among ICT graduates are much larger.Another general issue across ETF PCs is the significantly lower participation of girls in technical study fields within vocational education and training as compared to boys,and in particular in the technical study fields(as in EU countries).Gender segregation in

36、 vocational education and training(VET)tends to be higher than for tertiary education.In most ETF PCs,women have greater difficulties than men in accessing the labour market,despite the fact that they are often better educated.That said,having a high education level in general increases the probabil

37、ity of women finding employment.The reason for the difficulties is that women continue to face discrimination in the labour market,in addition to skills mismatch issues.The gender unemployment gap tends to be larger in those countries where unemployment rates are at a high level for both men and wom

38、en.The high unemployment rates for women may discourage some women to search for a job.In contrast,in Central Asian countries and some Eastern Partnership countries,and Israel,the unemployment rate of women is comparatively low,ranging between 2%and 10%,and is close to or even below that of men.Youn

39、g people not in employment,education and training(NEET)represent a major challenge in many ETF PCs.A closer look at the NEET shows that young men tend to be more often unemployed,while young women are more often inactive(and thus not looking for work and/or not being available for work).Gender stere

40、otypes and caring duties can explain this pattern.Migration affects the labour market position of women.Often female migrants have lower participation rates,due to the different motivations for migration of women(even more so in the past e.g.for family reunification),or due to gender stereotypes and

41、 social norms.Another issue is overqualification,difficulties in getting qualifications recognised and certified,which applies to both male and female migrants.For women,overqualification is also more often a problem within their home country labour markets.Female refugees are particularly vulnerabl

42、e.Evidence indicates that women refugees encounter significant obstacles if they wish to enter the host country labour market(for example,female refugees from Syria in Egypt and Jordan).The integration of female refugees from Ukraine in EU countries(e.g.Germany)shows better results,but lacks behind

43、the integration rates of male refugees in the long run.Another issue related to migration is the potentially lower activity rates of women whose men have migrated.Women have tended to be more adversely affected by recent multifaceted crises,such as the COVID-19 crisis.At the same time,they are at ri

44、sk of benefitting less,compared to men,from employment opportunities created by the digital and green transitions.Challenges for women to access the labour market and root causes of gender inequalities A critical driving force for gender inequalities are gender stereotypes and social norms.They have

45、 a great impact on the female labour market participation rate,the guidance and choice of VET and tertiary education study fields,gender distribution of unpaid care work.They also influence mens beliefs and attitudes.Social norms also influence employers behaviours in their recruitment choices,they

46、generate and foster prejudices on womens abilities and competences,and influence employers human resource management approaches to career progression.There are large differences in the strictness of social norms,the patriarchal models and breadwinner perceptions GENDER DIMENSION OF LABOUR MARKET TRA

47、NSITIONS|08 between urban and rural areas,with rural areas having stricter social patriarchal norms.The perceptions also depend on education levels,with more conservative views on female and male roles among the lower educated.Perceptions differ between regions and between countries within a given r

48、egion,as progress in politics and the legal and institutional frameworks happens at a different pace.For example,access to affordable and quality childcare plays a significant role in womens participation in the labour market and there are major differences between PCs in that regard.A lack of affor

49、dable and quality childcare arrangements are important reasons for women for not being active in the labour market or for not being able to fully exploit employment options and to progress in careers.An associated obstacle that women face to fully participate in the labour market and in the economy

50、via entrepreneurial activities is the more limited access to resources compared to men,mainly consisting of:limited access to land and to financial capital,weaker empowerment of women to make loan decisions and less well-developed financial literacy,and limited access to informal networks.Priorities

51、 for employment policies to improve the labour market transition for women Overall,PCs policies prioritise reducing gender inequalities.Several ETF PCs developed comprehensive strategies to promote gender equality and have introduced employment services targeted at women or at specific groups of wom

52、en.Comprehensive approaches include also the needs profiling of both unemployed and inactive women and reaching out to inactive women,and targeting services and ALMPs accordingly.One limitation however is that budgets for ALMPs as a percentage of GDP in PCs are relatively low(e.g.as compared to the

53、EU MS).Getting support from international donors therefore plays an important role in a number of PCs,which allows for developing and testing new approaches,but may also adversely affect long-term sustainability of the adopted measures and activities.In most PCs for which data are available,more wom

54、en than men tend to be registered with the PES and more women than men tend to participate in ALMPs in many cases.A number of PCs have ALMPs and job-search services to assist women with specific employment barriers,in addition to ALMPs that are equally available to men and women.Active labour market

55、 policies to improve the labour market transition of women and to reduce gender inequalities In most PCs for which data are available,women tend to participate in ALMPs and use job search services.However,there are significant differences in the share of female participants in different types of ALM

56、Ps.The main target groups among women in mainstream ALMPs or in female-dedicated ALMPs are women with caring responsibilities(in particular for employment incentives),single parents,women returning to the labour market after a child-rearing break,and women in rural areas(with a focus on job search s

57、ervices and start-up incentives).Female university graduates are among the target groups;however,the focus remains on the other groups.In a number of PCs,employment incentive programmes include women or specific groups of women among target groups.There is some evidence from other countries that mai

58、nstream employment incentive programmes may have a higher employment impact on women as compared to men.However,this would need to be confirmed by evidence from a greater number of countries in order to draw definite conclusions.Nearly half of the countries that responded to the ETF survey paid spec

59、ific attention to women in start-up programmes which include dedicated programmes,mainly for women in rural areas and for single mothers.Despite the progress made,women may still be far less represented among participants in entrepreneurship measures.In addition to ALMPs organised by PES,a variety o

60、f other actors are implementing programmes to promote female entrepreneurship.Measures involve a wide range of activities:increasing the share of women with bank accounts,entrepreneurship training and GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|09 mentoring,as well as granting financial support or

61、 supporting cooperatives.Evaluation evidence on the impact of entrepreneurship support is scarce and the little available evidence points to the existence of multiple barriers for women to become entrepreneurs and to grow their businesses.Social norms and behaviour add to other,institutional or stru

62、ctural barriers.Given the multiple employment barriers women face in rural areas,several PCs have targeted programmes to promote labour market activity and improve the quality of employment in rural areas.While that is highly relevant,little evidence has been documented on whether the adopted approa

63、ches have been effective so far.Given the persisting large differences in female employment rates and job quality between urban areas and rural/remote areas,there may be a need to scale up initiatives and measures that show good results.Comprehensive strategies that also consider issues such as chil

64、dcare availability,transportation,access to training opportunities,local economic development and mitigating gender stereotypes are essential to address gender inequalities,particularly in rural areas,and requires close cooperation among various actors on the ground.Among the policies to reduce gend

65、er inequalities int the labour market,the expansion of childcare facilities in quantity,increase in quality,the implementation of voucher systems,and awareness-raising activities have played a role in the PCs.There are only a few cases where the impact of these activities was assessed.However,the li

66、nk between the availability of childcare and employment for women varies significantly across countries,as underlying social norms play a significant role.In addition to the link between the availability of childcare and take up of employment or provision of employment,the quality of childcare and t

67、ransforming social norms and gender stereotypes are decisive.As a result,gender-responsive strategies need to be supplemented by gender-transforming approaches.Therefore,activities to increase fathers involvement in childcare through changing laws and conditions for taking paternal leave have starte

68、d to be implemented in an increasing number of countries.Programmes for female migrants,in particular refugees(including women displaced from Ukraine and Syria)have been implemented in EU countries,Trkiye,Jordan and Egypt.Important approaches have included training in language skills,which are impor

69、tant for both men and women.Approaches in all countries have included gender-responsive activities related to childcare.In addition,in Trkiye,female Syrian refugees have received gender-responsive protection support,as well as training in digital and financial skills.Most PCs have implemented gender

70、-sensitive and gender-responsive approaches to mitigate the impacts of COVID-19.Nevertheless,women may have benefited less from support to mitigate the impact of COVID-19,given that they have often been in a more fragile situation,with precarious employment conditions,stressful working conditions an

71、d greater difficulties in combining work and family lives.The research shows that the effects of measures and initiatives are enhanced when a variety of actors are involved,including several Ministries and agencies,NGOs and the private sector.Implementing comprehensive strategies is challenging,but

72、it is likely to increase impact in the long-term.However,the strictness of social norms and entrenched gender stereotypes limit the success of ALMPs,in particular those directed at more conservative target groups in rural areas.Experience across countries shows that increasing female participation i

73、n the labour force rates takes decades.Inequalities are being reduced in many countries over time,and the implementation of ALMPs,the improved availability of childcare,have certainly contributed.However,inequalities and gender segregation persist.Awareness-raising activities and gender-transformati

74、ve measures are needed to change social norms.It is essential that the activities of PES are closely monitored using sex-disaggregated data and by mirroring them with the findings on gender inequalities observed in the labour market.To achieve greater effectiveness of ALMPs to increase gender equali

75、ty in the labour market,PES should review their approaches accordingly and raise awareness among counsellors,target measures and/or introduce affirmative actions,as necessary.There is also a need to assess the effect of specific GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|10 ALMPs on women,to avoi

76、d policies and activities that are gender-blind and gender discrimination when accessing ALMPs.Career guidance,upskilling and reskilling measures to reduce gender inequalities Several PCs have implemented gender-transformative measures in vocational career guidance.Some countries have implemented me

77、asures to encourage women to take up training in male-dominated professions.Examples from several ETF partner countries include initiatives in particular to break gender stereotypes early on.The initiatives are transformative in the sense that they seek to raise and strengthen the interest of girls

78、and young women in STEM,in particular in technology,engineering and ICT.Strategies and initiatives encompass gender-responsive elements so that they do not only target girls and young women but also their social environment and parents,teachers and school curricula.Specific programmes have been targ

79、eted at women with caring responsibilities.This approach is gender-responsive and gender sensitive in addressing barriers for women to access training and in targeting support towards women with caring responsibilities.Examples also show the interest in implementing packages of measures,including co

80、unselling,mentoring,internships in addition to the training measures.Support for the development of digital skills of girls and women is key for their employability.Therefore,examples from PCs show that it is relevant to enhance digital skills,such as in the area of e-commerce,artificial intelligenc

81、e and smart technologies to strengthen womens potential to be more successful in their economic activities.This is particularly relevant for women in rural and remote areas as digital technologies also help to overcome challenges related to remoteness.In addition,examples from ETF partner countries

82、show the relevance of including other actors,such as IT parks and large employers,in training and hiring women as IT professionals.Some PCs have been successful in enhancing the participation of women in training measures.Examples suggest that the actions of positive discrimination and other gender-

83、transformative measures,such as dedicated scholarships,have the potential to be successful in attracting women towards study fields traditionally not associated with women.Successful training measures benefit from activities that support the education to work transition through internship programmes

84、,dialogue with employers and awareness-raising activities.Evaluations conducted around the world show the positive impact of training measures on women.Looking at the EU experience,an evaluation that has been carried out for the Austrian programme to support women to take up VET training in technica

85、l occupations,shows positive results.Escudora et al.(2017)have conducted metadata analysis of the evaluation results of active labour market programmes in Latin American countries.They find that training programmes are(slightly)more effective than other types of ALMPs,in particular relative to direc

86、t job creation programmes.In terms of targeting,they find that ALMPs in the region seem to work better for women than for men and also for youth compared to prime-age workers.In particular,the impact of training programmes appears overall higher among women than men.We can also conclude that overcom

87、ing gender stereotypes and changing social norms is essential to pursue gender sensitive and gender-transformative measures.This needs to start at a young age and needs to be pursued during the whole education system.Measures include,for example,gender-sensitive revisions of textbooks.Moreover,compr

88、ehensive approaches need to be taken with a view to reducing the levels of leaving school early and reducing the number of young NEETs,as underlying reasons for inequalities are strongly linked to traditions and norms.To move forward Several areas still require public employment services and other e

89、mployment and training stakeholders attention,such as the following:1.improving the information base by including a gender dimension in the reporting and monitoring of PES activities,stocktaking of activities of other stakeholders,conducting studies and evaluations;GENDER DIMENSION OF LABOUR MARKET

90、TRANSITIONS|11 2.designing comprehensive approaches by considering the multitude of employment barriers women face,including access to affordable quality childcare,taking actions to change male attitudes and perceptions,conducting awareness raising activities,linking training measures to workplace a

91、ctivities,internship and placement;3.working in partnership,to address multiple facets of gender inequalities and consolidate cooperation among public,private and civil society organisations to address stereotypes in education,access to employment,insufficient gender sensitivity of social protection

92、 measures or business practices;4.balancing gender-mainstreaming,namely integrating the gender perspective into the policy cycle(from design to evaluation),and dedicated gender-sensitive and gender transformative approaches in programming and policy development.It is recommendable to implement a gen

93、der-mainstreaming approach for PES activities,including funding,monitoring and evaluation of services and programmes.But it is also important to address deep inequalities and employment gaps through,for example,gender-sensitive career guidance and introducing transformative measures to attract women

94、 to male-dominated professions and men to female-dominated professions;5.investing in removing barriers to womens economic empowerment by leveraging effective measures and thus increasing budgets for PES services and ALMPs.6.Gender-responsive budgeting:integrating gender perspectives into performanc

95、e-based and programme-based budgeting;tracking financial allocations to promote womens rights and gender equality;applying standard gender budgeting tools such as gender aware policy and budget appraisal,gender disaggregated public expenditure and revenue incidence analysis,and gender responsive ben

96、eficiary needs assessments.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|12 1.Introduction Reducing gender inequalities and promoting the economic empowerment of women raises social justice questions.It corresponds to Sustainable Development Goal(SDG)5 Achieve gender equality and empower all women a

97、nd girls3 and SDG 8 on Decent Work an Economic Development.Other SDGs are relevant when it comes to eliminating discrimination in institutional frameworks,wages policies and social protection(Kring,2017).Drawing on the EU Gender Equality Strategy 2020-2025,which calls for a gender-equal Europe,the n

98、ew EU Gender Action Plan for 20212025(GAP III)has been adopted4.It aims to accelerate progress on empowering women and girls and to safeguard gains made on gender equality since the adoption of the Beijing Declaration5.For many ETF PCs,of importance is also the Ministerial Declaration of the Union o

99、f the Mediterranean(UfM)in Charge of Employment and Labour,adopted in 20226 as well as the one on Strengthening the role of Women in Society7.It contains a variety of policies and strategies to support the economic empowerment of women.Reducing gender inequalities,promoting female employment and imp

100、roving labour market transition benefits women,societies and the economy.The economic gain of reducing gender inequalities in the EU was assessed by EIGE(EIGE 2017).The econometric model used showed that by encouraging more women to participate in the labour market and increasing their attainment in

101、 STEM(Science,Technology,Engineering and Mathematics)would increase the GDP per capita and employment of women.In a scenario where all gender equality measures were implemented and fertility rates increased,the GDP would increase by up to nearly 10%by 2050 with an additional 10.5 million jobs in the

102、 EU.Comparable data for ETF PCs is only available for the Western Balkans.Using the same methodology(Sura et al.2021),a study conducted for the Regional Cooperation Council has shown that reducing gender inequalities could lead to an increase in GDP per capita by 1.5%by 2035,if Western Balkan PCs un

103、dertake rapid and intensified action,compared to the continuation of the current situation,to reduce the gender gap in participation rates.The study also suggested that implementing measures that only lead to closing the gender pay gap would raise the GDP per capita by 0.04%-0.13%by 2035 compared to

104、 the absence of such measures.Using a different methodology,a study conducted for UN Women showed the positive economic impact of reducing gender inequalities in Morocco(Bargain and LO BUE 2021;DEFP et al.2022).The present report provides a review of the gender dimension in labour market transitions

105、.The report focuses on the women dimension,and looks in particular at labour market barriers,inequalities,causes of inequalities and policy responses from a womens perspective.The report also looks into the implications for policy-making in the area of activation,upskilling,reskilling and career gui

106、dance.Active Labour Market Policies(ALMPs)aim to improve the employability of specific target groups,such as the unemployed,young graduates,laid-off workers or people with obsolete skills,through the provision of different services and measures(for example training,employment and entrepreneurship in

107、centives or subsidised employment).Such interventions can further contribute to better matching skills supply to the demand.Activation and skills development policies are gaining importance in Europe and beyond as key components of post-COVID-19 recovery,green and digital transitions and emerging so

108、cio-economic risks and uncertainties in the context of Russias aggression against Ukraine.This report looks at the gender sensitiveness and the gender-transformative approaches8 of ALMPs and career guidance,national initiatives and donor programmes to enhance gender equality in 3 https:/sdgs.un.org/

109、goals/goal5 4 https:/www.eeas.europa.eu/eeas/gender-action-plan-iii-towards-gender-equal-world_en 5 The Beijing Declaration and the Platform for Action was adopted at the 1995 Fourth World Conference on Women in Beijing by 189 countries.It is an agenda for womens empowerment and is considered the ke

110、y global policy document on gender equality.6 https:/ec.europa.eu/commission/presscorner/detail/en/ip_22_3087 7 https:/ufmsecretariat.org/wp-content/uploads/2022/10/5th_UfM_Declaration_StrengtheningRoleWomenSociety_Final-_EN.pdf 8 See Glossary of gender equality terms at the end of the report GENDER

111、 DIMENSION OF LABOUR MARKET TRANSITIONS|13 labour market transitions and the assumptions behind them.It reflects on the effectiveness of selected measures.It identifies innovative good practices in re/activation,up/reskilling and career guidance and counselling for enhancing gender equality in the l

112、abour market in general and for the green and digital transitions in particular.This report is based on reviewing the available literature and data.Work on this report was underpinned by a survey on active labour market programmes conducted(mainly)among Public Employment Services in ETF Partner Coun

113、tries.The survey is referenced as“ETF Survey”throughout the report.The results of the survey are used in chapters 4 and 5 of this report.Criteria for selecting good practices presented in the report included the adoption by PCs of the measures to increase women employment and reduce gender inequalit

114、ies.Examples have been collected from 18 ETF PCs(Table 3)and show the high divergence in labour participation and employment rates between and within each of these regions,and show distinct features in other issues of quality of employment and skills.Also,the selection encompasses a varying type of

115、economic context(with some countries still characterised by a large share of employment in the agricultural sector).Whenever available,the report discusses practices that had been evaluated;however,comprehensive evaluations of ALMPs and similar programmes are rare.Therefore,also practices which prov

116、ide a potential for reducing gender inequalities have been selected.The presented practices also include evidence on innovative approaches.In addition,whenever evidence is available,the limitations of the success or the absence of concrete activities is discussed.However,an in-depth assessment of th

117、e gender-sensitivity and gender-transformative potential of policies was not possible within the scope of this report.The report is structured as follows:Chapter 2 show the main trends and patterns in the gender inequalities in the labour market,labour market transitions and skills development.The c

118、hapter provides also specific insights on the employment of women in the field of ICT and into the effects of the COVID-19 pandemic and female employment.Chapter 3 outlines the roots and causes of gender inequalities and identifies key challenges for women for a smooth labour market transition.Chapt

119、er 4 reviews key activation policies to promote female employment in selected PCs.Chapter 5 provides an overview of career guidance,upskilling and reskilling measures to improve womens employability and reduce gender inequalities in selected ETF partner countries.Lessons from the implementation of e

120、mployment services,ALMPs,career guidance and skilling measures for women from EU countries and other parts of the world(in particular middle-income economies as this is relevant for the ETF PCs)are included.Chapter 6 draws general conclusions and presents recommendations for further policy actions.G

121、ENDER DIMENSION OF LABOUR MARKET TRANSITIONS|14 2.Main trends in the gender dimension of labour market transitions in ETF countries 2.1 Main labour market features and trends by gender Women have in general lower activity rates9 and employment rates as compared to men.The activity(and employment)gap

122、 measures the difference in percentage points between the male activity rate(and employment rate)and the female activity rate(Figure 1).Activity gaps are range between 36.4 and 51.7 percentage points in SEMED countries(except Israel),Trkiye and Kosovo.Activity gaps are comparatively low(and below EU

123、 27 average)in Israel,Moldova,Kazakhstan and Ukraine.The reversed employment gap in Uzbekistan(with more women being employed than men,is difficult to explain,and may be related to statistical issues and the high emigration of men).The same patterns can be observed for the gender employment gap(Figu

124、re 1).Figure 1:Activity and employment gaps in 2021,in percentage points Source:ETF collected datasets/KIESE,Eurostat for EU 27 Note:for DZ 2019,EG 2020,KG 2020,ME 2020,UZ 2020,no female employment rate data available for Algeria Gaps are calculated at the difference between male and female rates Th

125、e levels of female activity rate in 2021 vary greatly across the regions,as well as within regions(see Figure 2).On average,activity rates and employment rates of women aged 15+in each of the four ETF regions are below the EU 27 average,although single countries in each of the regions show female ac

126、tivity rates and employment rates above the EU-27 average.There are large differences in activity and employment rates also among countries within a region.The disparities between in the level of female activity rates are highest in the SEMED region,as female activity rates are comparatively high in

127、 Israel,while they are fairly low in the remaining countries.9 Female activity rate or labour force participation rates is the share of women aged 15+being in employment or being unemployed(and thus being searching and available for employment),according to the ILO definition.UZILMDKZUAEU27AZMEALRST

128、MTJGEAMMKBAKGEGXKTRTNJODZMAPS-40.0-30.0-20.0-10.00.010.020.030.040.050.060.0Activity gapEmployment rate gap GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|15 Figure 2:Activity rate of women and employment rate of women(15+)in 2021 Source:ETF collected datasets/KIESE,Eurostat for EU 27 Note:for DZ 201

129、9,EG 2020,KG 2020,ME 2020,UZ 2020,no female employment rate data available for Algeria The female activity rates have been decreasing in some of the countries(for the overview of trends,see Annex 1 Figure A1 Panel A-D,using ILOSTAT estimates data).Over the past decade,the activity rates of women hav

130、e been significantly falling(although with some variations)among Central Asian countries in Turkmenistan and Kyrgyzstan,among Eastern Partnership countries in Georgia,Moldova and Ukraine,while they have been increasing in other countries in this region.The activity rates of women have remained compa

131、ratively stable in most SEMED countries,except in Egypt,where there is a decline and in Israel and Lebanon,where a sizeable rise can be observed.The activity rates of women have been on the rise in the Western Balkans and in Trkiye.The development of female employment rates has shown the following r

132、egional patterns10:Over the period of 2015 and 2021(except in 2020 during the pandemic),the employment rate of women has been increasing in the Western Balkans11.Female employment rates have been rather stable(with only small increases or decreases)in many of the some of the Central Asian countries(

133、Kazakhstan,Turkmenistan,Uzbekistan),Eastern Partnership countries(Armenia,Azerbaijan,Georgia,Ukraine),Trkiye,as well as Southern an Eastern(SEMED)countries(Algeria,Israel,Jordan,Libya,Lebanon,Syria,Tunisia,West Bank and Gaza).Over the same period the female employment rate has been declining in Mold

134、ova,the Kyrgyz Republic,Egypt and Morocco.Countries with very high gender employment gaps also show very low employment rates of women(Figure 3,based on ILOSTAT estimates).This finding applies to a number of SEMED countries.This points to a double challenge for policymakers that are to increase empl

135、oyment rates and to reduce gender employment gap.Conversely,those countries with the smallest employment gender 10 World Bank Database,ILO Modelled Estimates and Projections database(ILOEST)11 Excluding Kosovo for which comparable ILO estimates are not available.Central AsiaUZKZKGTMTJEastern Partner

136、ship CountriesAZUAAMGEMDSouthern and Eastern ILEGTNMADZPSJOWestern Balkan and TrkiyeALRSMEMKBATRXKEU2701020304050607080Female Activity RateFemale Employment Rate GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|16 employment gaps are also those with the highest female employment rate(mainly Central Asi

137、an countries and a few Eastern Partnership countries and Israel).In a number of countries,the employment rates of women(aged 15+)are below 45%and gender gaps are around 20 percentage points or below.This points to general low employment rates of both men and women.Several Western Balkan countries an

138、d Eastern Partnership countries fall into this category.In general,there is a big divide between female employment rates in urban and rural areas.Figure 3:Female employment rate(15+)and employment gender gaps in ETF countries in 2021 Source:Authors compilation from World Bank databases using wbopend

139、ata Stata module(Joao Pedro Azevedo,2011.WBOPENDATA:Stata module to access World Bank databases,Statistical Software Components S457234,Boston College Department of Economics,revised 02 Jul 2020).Note:ILO modelled estimates,without Uzbekistan and Turkmenistan.To compare,in the EU,in 2021,48%of women

140、 aged 15+were employed(and 63.4%of women aged 15-6412).The gender employment gap was 10.8 percentage points(pp),which had only slightly decreased in the last 10 years(-1.9 percentage points)13.2.2 The position of women in the labour market Part-time employment As in other regions of the world,includ

141、ing the EU,on average in ETF PCs women typically work more often part-time,compared to men.Part-time employment is associated with positive and negative effects for womens employment and career progression.The main reasons for women working part-time are related to care responsibilities which they s

142、till take on far more often than men(see section 3).In addition to work-life balance aspects,a higher share of part-time work can also be associated 12 Eurostat,LFSI_EMP_A_custom_6714591 last update:20/06/2023.13 In 2021,the gender employment gap was highest in Romania(20 percentage points)and lowes

143、t in Lithuania(near 2 percentage points).https:/commission.europa.eu/strategy-and-policy/policies/justice-and-fundamental-rights/gender-equality/women-labour-market-work-life-balance/womens-situation-labour-market_en GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|17 with more difficult access to qual

144、ity jobs.A major concern of part-time employment is that it usually offers less good career prospectives and social protection rights,such as unemployment benefits and a pension.Full-time employment is generally regarded as empowering women economically(Suta et al.2021).The incidence of part-time em

145、ployment is high in many SEMED countries(with the highest share in Morocco among all ETF countries with 46.3%of employed women working part-time in 2021 and Israel(46.2%in 2020),Algeria(36.2%)and Tunisia(28.6%).It is also comparatively high in some Central Asian countries(Kyrgyz Republic with 41.9%)

146、and Tajikistan(37.5%)14.The Western Balkan economies take a middle-field position.Women are on average less likely to work part-time than in the EU,but remain more likely than their male counterparts in the region(Suta et al.2021).The incidence of part-time employment is lowest in Montenegro(8.5%),M

147、oldova(10.1%),Egypt(11.1%),Kazakhstan(11.9%)and Jordan(15.2%)(see Figure A2 in Annex 1),as well as in Kosovo15(Suta et al.2021).Quality of employment The quality of female employment is significant.Remuneration and career progression are important aspects of the quality of employment,labour market s

148、ecurity and social protection,and working conditions(the OECD quality of job indicator,for example,is built on earnings quality,labour market security,and the quality of the working environment)16.Vulnerable employment and informal employment Vulnerable employment is made up of contributing family m

149、embers and own-account workers17.Contributing family members do not receive their own remuneration and they have generally no independent social protection scheme.This type of employment is regarded as vulnerable employment(Kring 2017).The share of contributing family members is linked to the econom

150、ic structure,productivity and the economic model of a country.Women are more likely than men to be contributing family members.Globally,14.9 per cent of women are contributing family workers compared to 5.5 per cent of men(ILO,2017).In 2019,in the ETF PCs,two contrasting realities were present(see F

151、igure A3 in Annex 1):The share of women employed as contributing family workers as well as the gender gap were very large in Azerbaijan,where 42.5%of women worked as contributing family members as compared to 24.0%of men(gender gap of 18.5 percentage points)and Morocco(34.8%and a gap of 25.9 pp).The

152、 share of employed women working as contributing family members ranged between 20%and 30%in Albania,Georgia,Trkiye,Egypt and Tajikistan.In Trkiye and Egypt,the gender gaps are very large,as only few men are contributing family workers.The share of women working as contributing family members was bel

153、ow 5%in Moldova,Turkmenistan,Montenegro,Tunisia,Algeria,Armenia,Lebanon,Ukraine,Kazakhstan,Jordan,Israel(in descending order).In contrast to helping family members,own-account workers are more often men than women in all ETF PCs(see Figure A4 in Annex 1).The share of employed women working as own ac

154、count workers can be regarded as comparatively high,ranging between 20 and 42%across Central Asia,Eastern Partnership countries and a few SEMED countries(Tajikistan,Armenia,Algeria,Kazakhstan,Libya,Georgia and Azerbaijan in descending order).In Central Asia,the agricultural sector is the main employ

155、er in rural areas.Female share of agricultural employment is above 50%in Kyrgyzstan,Tajikistan and Uzbekistan.14 Note that there are no data for Uzbekistan and Turkmenistan.15 This designation is without prejudice to positions on status,and is in line with UNSCR 1244/1999 and the ICJ Opinion on the

156、Kosovo declaration of independence.16 https:/www.oecd.org/statistics/job-quality.htm 17 https:/ilostat.ilo.org/paid-employment-vs-vulnerable-employment/GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|18 In addition,informal employment may lead to vulnerability18.Informal employment is generally more w

157、idespread among men than women.In Central and Eastern Europe,28.1%of men and 23%of employed women are working informally19.Specific issues are linked to certain groups of vulnerable women,in particular coming from ethnic minorities and in rural areas.This is the case for example in the Western Balka

158、ns(Suta et al.2021).Informal employment is more widespread in some countries of Central Asia.For example,in Uzbekistan,60%of the employed work informally.About 61%of women and 73%of men in the private sector lack social security coverage20.Globally,lower shares of women in informal employment are of

159、ten found in countries with lower participation rates of women in the labour market.In the SEMED region,a large share of employed women work in the public sector,which is more likely to offer formal employment contracts and better access to social protection(see occupational and sectoral segregation

160、 above).Informal employment among women is more widespread in countries with a large rural economy,such as in Egypt and Morocco(OECD/ILO/CAWTAR,2020).The analysis of regional data shows that,outside the agricultural sector,most women in informal employment in the SEMED region work in the personal se

161、rvice sector and hospitality,while men occupy informal jobs in construction(UfM,2022).Gender pay gap Globally,women earned from labour income on average about 52%of what men earn in 2019(ILO 2023).The gender wage gap was larger in Central Asia than the global average:working women earn about 60%of w

162、hat men earn in Tajikistan,61%in Uzbekistan,75%in the Kyrgyz Republic,and 78%in Kazakhstan21.In Tajikistan,it is estimated that earned income for women is 4.5 times lower than the estimated male earned income(World Bank 2021).This gap in earnings results from gaps in the employment rate,average hour

163、s worked as well as wages per hour.For the Western Balkan countries,the average pay gap is 16%on average(Suta et al.2021)22.Similarly,in the SEMED countries,men earn on average 16%higher wages than women(UfM,202223).These gender pay gaps are above the EU average,as womens gross hourly earnings were

164、on average 12.7%below those of men in the EU24.The ILO has also aggregated the data on the median gender wage gap(hourly wages)for some of the Eastern Partnership countries:the median gender wage gap was 23.5%in Armenia and 20.8%in Ukraine,while for comparison on average of high-income countries exa

165、mined by the ILO report,the wage gap was 15.7%(ILO 2018).Differences in hourly earnings can be explained by(i)differences in the average characteristics of male and female employees(such as the segregation of employment by sector and occupation,qualification level,part-time employment and job roles)

166、and(ii)differences in the financial returns for the same characteristics,which would result from gender-based wage discrimination.Women tend to be more often employed in occupations and sectors that pay less well for a given level of education and skills.Occupational segregation and segregation acro

167、ss sectors is an issue in all ETF partner countries.This has been shown for example for SEMED region by the OECD(2020)and for the Western Balkan by Suta et al.(2021).Another reason is that women are less often taking up leadership and management roles(vertical segregation)25.The OECD report found th

168、at three-quarters of the gender wage gap between similarly skilled women and men reflects pay differences within firms,including disparities in tasks and responsibilities.One-quarter of the gap reflects the concentration of 18 There may be overlaps with the definition of vulnerable employment.19 htt

169、ps:/www.ilo.org/budapest/WCMS_628487/lang-en/index.htm 20 https:/www.ilo.org/moscow/projects/WCMS_826842/lang-en/index.htm 21 https:/blogs.worldbank.org/europeandcentralasia/faster-growth-central-asia-must-confront-biased-perceptions-about-value-womens 22 Suta et al.(2021),use mean nominal monthly e

170、arnings of employees by sex and occupation from ILO data and compute the percentage difference between male and female earnings by occupation 23 Referring to ILO data 24 https:/ec.europa.eu/eurostat/statistics-explained/index.php?title=Gender_pay_gap_statistics 25 OECD defines horizontal segregation

171、 as the concentration of women and men in different labour market sectors and occupations.Women tend to be overrepresented in relatively low-wage fields.And vertical segregation as the concentration of men and women in different job levels.Men tend to be overrepresented in management and leadership

172、roles.https:/www.oecd.org/stories/gender/gender-equality-and-work GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|19 women in low-wage industries(sectoral segregation)(OECD 2021b).A comparable analysis by ETF PCs regions is not available,but there is evidence of occupational and sectoral segregation a

173、s well as of vertical segregation in the PCs(see more on women in management positions below)Entrepreneurship Self-employment which includes both own-account workers26 as well as micro-enterprises when self-employed are employing a small number of workers,or cooperatives may be an important option f

174、or men and women to become employed.This is the case in several countries across the different regions covered by ETF engagement:In 2019,self-employment is the dominant form of employment for women and/or men in Azerbaijan(72.8%of female employment and 63.2%for male employment),Morocco(57.1%and 45.9

175、%),Albania(52.1 and 56.8%),and Georgia(46.3%and 52.5%)(ILOSTAT,retrieved from World Bank Database).In contrast,in other PCs,only between 1%and 16%of women are self-employed(Lebanon,Tunisia,Montenegro,Ukraine,Israel,Syrian Arab Republic,Jordan,Kosovo,West Bank and Gaza in descending order).In these c

176、ountries,the share of self-employed men is considerably higher than that of women.Moreover,women may encounter more often barriers to becoming self-employed.One way of indicating gender inequalities in leadership is to look at the share of firms with female top managers.Only a minority of firms has

177、women in top management,with the highest shares in the Kyrgyz Republic(33%)and Kazakhstan(26%).When looking at other Central Asian countries,it is striking that despite the high female employment rate in Uzbekistan,only 12%of companies state that they have women as a top manager.Moreover,in most Wes

178、tern Balkan countries and Eastern Partnership countries,the share of firms with a female top manager ranges between 10 and 15%.In SEMED countries,the share of firms with female top managers is below 10%(Figure A5 in Annex 1).Unemployment and labour market transition In most ETF PCs,women have greate

179、r difficulties than men to access the labour market.The gender unemployment gap tends to be larger in those countries where unemployment rates are at a high level for both men and women(with the exception of Georgia and North Macedonia).In the SEMED region,women face very high barriers to access the

180、 labour market.The high unemployment rates for women may discourage some women to even search for a job.High inactivity rates and high unemployment rates of women taken together explain the low employment rate and the high gender employment gap(Figure 4 based on data collected by ETF and Figure A6 i

181、n Annex 1 for the ILO estimates).Figure 4:Unemployment rates by gender,2021 Source:ETF collected datasets/KIESE,Eurostat for EU 27 Note:for DZ 2019,EG 2020,KG 2020,ME 2020,UZ 2020,no female employment rate data available for Algeria 26 Here there is an overlap with vulnerable employment MDTMUZILKGKZ

182、EGTJAZEU27UAALRSMKTRAMMAGEMEBADZTNXKJOPS05101520253035404550Unemployment rate femaleUnemployment rate male GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|20 A much more difficult labour market transition for women,as compared with men,is visible for women with both intermediate and with advanced educ

183、ation(Figures A8 and A9 in Annex 1).Moreover,the school-to-work transition for young girls is significantly more difficult in this region(and in part of the Western Balkan region),as indicated by high youth unemployment rates among females and the large unemployment gender gap(Figure A6).Gender gaps

184、 in unemployment are also present in many Eastern Partnership and Western Balkan economies.(Figure 4).Strikingly in some of the Western Balkan countries,the unemployment rate of women with basic education is high(ranging between 16%and 41%)(Figure A7 in Annex 1).In Albania,the data show that more th

185、an half of unemployed female and male jobseekers have completed only primary or lower secondary education.The number of unemployed women jobseekers increases with age,while the data show the opposite for men(Suta et al.2021).Evidence for Western Balkan economies shows that Roma women have a higher u

186、nemployment risk than Roma men(Suta et al.2021).Multiple employment barriers increase the risk of Roma women being unemployed.In addition to ethnicity,factors such as being older or living in rural areas add to labour discrimination against women,e.g.in the Western Balkans(Suta et al.2021,OECD 2021)

187、.In contrast,in the Central Asian countries and a few Eastern Partnership countries and Israel,the unemployment rate of women is comparably low,ranging between 2%and 10%and is near the rate for men,or even below.Migration There are gender patterns in labour force participation and access to the labo

188、ur market of migrants.Often women have lower participation rates,due to the different motivations for migration of women(even more so in the past,e.g.in the context of family reunification),or due to gender stereotypes and social norms.When comparing the difference between employment rates between n

189、on-EU citizens and nationals by gender in the EU in 2022,it appears that the gap is much larger for women than for men,indicating a significantly lower presence of non-EU migrant women in the labour market as compared to male migrants27.Another issue is overqualification,difficulties in getting qual

190、ifications recognised and certified,which applies to both men and women.For women,overqualification is also a problem in their home country labour markets.Migration patterns are highly complex,as underlying motivations for migration vary.In the following sections,a few aspects of migration are highl

191、ighted(although not all aspects are covered).Spotlight on women displaced from Ukraine Since February 2022,due to the war of Russian aggression against Ukraine,there was a large influx of persons displaced from Ukraine,consisting mainly of women and children.Until 4 April 2023,5 million refugees fro

192、m Ukraine had registered for temporary protection or similar national protection schemes in Europe28,of whom 1.6 million registered in Poland and nearly 1 million in Germany.The vast majority of the refugees are women and children.The EU PES Network carried out surveys among PES about registration,e

193、mployment and ALMPs for displaced Ukrainian citizens and residents.The results of the fourth survey carried out in February 2023 show on an aggregated level that the number of persons registered in PES amounts to more than 353 000 registrations in the 28 PES that answered this question in the survey

194、.More than 50%of these registrations were reported from Germany.The data reported by 25 PES indicate that more than 1 300 000 people displaced from Ukraine were in employment in these countries in February 2023.Jobs are found mostly in sectors 27 https:/ec.europa.eu/eurostat/statistics-explained/ind

195、ex.php?title=File:Figure_10_migrant_integration_labour_market_indicators.png 28 Ukraine Refugee Situation(unhcr.org);The figure on Refugees from Ukraine registered for Temporary Protection or similar national protection schemes in Europe may include multiple registrations of the same individual in t

196、wo or more EU+countries;registrations that remain incomplete for various reasons;or registrations of refugees who have moved onward,including beyond Europe.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|21 with labour shortages and these vary across countries.Sectors such as construction,hospitality,

197、and the wholesale and retail trade are mentioned29.The German research institute IAB carried out a survey among registered displaced persons from Ukraine in Germany in Autumn 202230.The results show that six months after immigration,the employment rate for men(24%)is significantly higher than for wo

198、men(16%).For women,it is also significant whether small children have access to childcare services.Spotlight on female refugees in the area of the Southern and Eastern Mediterranean Women and girls account for almost half of the refugees globally(UNHCR,2019).Recent increases in refugee flows have be

199、en driven by conflicts in and around the SEMED region,including in Syria.The refugee crisis of people migrating from Syria to the EU(in particular to Germany)has been largely dominated by men.Women have been more often fleeing to neighbouring countries.The United Nations High Commissioner for Refuge

200、es(UNHCR)reports that Lebanon continues to host the largest number of refugees relative to its national population,followed by Jordan and Trkiye.Egypt also hosts a large number of refugees,coming mostly from Syria and South Sudan.The evidence indicates that women refugees encounter many obstacles wh

201、en trying to enter the host country labour market.For example,in Jordan women have obtained only 4%of the work permits issued to Syrian refugees,and many women are working informally(OECD/ILO/CAWTAR 2022).Obstacles to work are linked to social norms,childcare responsibilities and the lack of transpo

202、rtation.Spotlight on female migrants leaving the Western Balkans Emigration from the Western Balkan(and from Trkiye)towards EU countries,mainly Germany,Austria,Switzerland,Italy,and other countries has been high for decades.However,the profile of migrants,and in particular of female migrants,has cha

203、nged over time.Recently,young people and young adults who are looking for employment or enrolling in higher education have been emigrating increasingly.For all Western Balkan countries,the share of women in the stock of migrants in OECD countries is about the same as that of men,with a slightly lowe

204、r share for Kosovo.The OECD data of 2015/16 show a gender-specific pattern common to migrants from most Western Balkan countries(except Albania):men are more likely to have middle-level education while women are more likely to either be low-or highly educated(OECD 2022).In Albania,the emigration of

205、high-skilled persons was a key feature of migration patterns in the late 1990s and 2000s.Overqualification is a common issue for migrants.In 2015/16,the over-qualification rate for female migrants was lower than that of men,but still high for female migrants from North Macedonia,Albania and Kosovo.O

206、ver-qualification rates for migrants from Western Balkans are high compared to the overall foreign-born population in OECD countries(OECD 2022).A few studies have looked at the impact of emigration on the situation of women in the Western Balkans.Key findings of the literature review by Atoyan et al

207、.(2016 and 2017)show that remittances affect negatively on employment and participation rates of those receiving the remittances,in particular among women.Reasons for this may be higher reservation wages as well increased difficulties to combine work and family lives.Spotlight on Central Asia:effect

208、s of migration on women in Tajikistan One in four Tajik households have migrant members,mainly residing in the Russian Federation.Migration has become an important choice for men to get employment.The number of female migrants has been increasing since the 20082009,but their share among migrants rem

209、ains low.29 https:/ec.europa.eu/social/main.jsp?langId=en&catId=89&furtherNews=yes&newsId=10526 30 Presseinformation des IAB,des BiB,des BAMF und des SOEP vom 15.12.2022,https:/iab.de/presseinfo/ukrainische-gefluechtete-bringen-gute-voraussetzungen-fuer-die-teilhabe-in-deutschland-mit/GENDER DIMENSI

210、ON OF LABOUR MARKET TRANSITIONS|22 Gender stereotypes play a role for this migration pattern because maintenance of the family is almost exclusively the responsibility of males.Hence,households prefer to send men abroad to seek paid employment(World Bank 2021a).Migrant women also have a bad reputati

211、on and face stigmatisation,as they face criticism about leaving their families behind.The high gender disparity of migrant workers in Tajikistan is in contrast to its neighbouring country Kyrgyzstan,a country in which leaving the country for working abroad has been an important feature as well.Here,

212、the share of women among migrants is considerably higher than in Tajikistan.It is evaluated that roughly half of migrants from Kyrgyzstan are women(IMO 2021 and ILO31).The wives of migrant workers often encounter the additional burden of household responsibilities typically assumed by their husbands

213、(such as financial management,household maintenance,and farm labour).Kan(2018)uncovers some evidence that the emigration of men leads to greater unpaid family work.In Tajikistan,around a quarter of the women left behind are not in contact with their husbands and are dependent on other family members

214、.Wives of migrant workers may have less time for income generating activities outside the home(World Bank 2021a).Low activity rates of women may also be linked to remittances as an income source.The negative effect of the emigration of men and labour force participation of women have also been found

215、 in other parts of the world(e.g.El Salvador,Nepal)(Kan,2018).2.3 Gender aspects in skills development and skills mismatch Participation in education Women tend to be better educated than men in many countries.In 9 out of 14 ETF partner countries for which data on net enrolment rates in secondary ed

216、ucation is available,the enrolment rates of girls are slightly higher than those for boys,as is the case for the EU(Figure A10 in Annex 1).The rate of enrolment varies quite significantly across PCs.Among the 14 examined countries,the female and male net enrolment rates were lowest in Jordan and hig

217、hest in Uzbekistan(and slightly below the EU average,see Figure A10 in Annex 1).For young people and young adults,it can be seen that girls tend to stay longer at school than boys(including primary,secondary and tertiary education)in the majority of PCs for which data from the World Bank Data base a

218、re available,and this holds also true for most of the SEMED countries(Algeria,Libya,Jordan,Tunisia,West bank and Gaza)32.In most ETF PCs,the gross enrolment rate of women in tertiary education is well above that of men33.For example in Tunisia,the share of female graduates is 66%,even higher than in

219、 some OECD countries(OECD 2020).In all ETF PCs,there are issues of gender segregation in the graduation levels by field of studies(Table A2 in Annex 1).Women in general pursue more often tertiary studies in social sciences,humanities,health and welfare,while they are significantly absent from engine

220、ering.In the area of ICT,the differences are less marked,and there is a more balanced composition of students,in particular in the SEMED region(see also below section digital skills).Women are over-represented among tertiary graduates in natural sciences in most countries worldwide,including in the

221、ETF PCs(Table A2,Annex 1).It is worth noting that girls in Jordan outperform their national and regional counterparts in terms of mathematical,reading and scientific literacy.In addition,girls in Morocco perform better than boys in science tests(OECD 2020).Also,in the area of engineering,gender segr

222、egation is less marked in some countries and regions than in others.With 34%to 57%of science,technology,engineering and mathematics(STEM)graduates in MENA countries are women,the region outperforms the OECD average(31%).For example,in 2023,more than 57%of Tunisian engineer are women.In the Western B

223、alkans,young women account for a larger share of students and graduates in higher education institutions in science,technology,engineering,and mathematics(STEM)subjects than in 31 https:/www.ilo.org/moscow/projects/WCMS_750545/lang-en/index.htm 32 World Bank Database(latest available year,mostly 201

224、8 and 2019)(SE.SCH.LIFE.FE,SE.SCH.LIFE.MA)33 World Bank Database(SE.TER.ENRR.FE,SE.TER.ENRR.MA)GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|23 many EU economies(including in engineering and computer sciences).Nevertheless,computer sciences and engineering remain more typical choices for young men(R

225、CC 2020).Another general issue across ETF PCs is the much lower participation of girls in technical vocational education and training(TVET)as compared to boys.Gender segregation in vocational education and training(VET)tends to be higher than for tertiary education.A particularly high gender segrega

226、tion by study field within the VET system is likely to be an issue in many ETF PCs,as is the case for example in the area of the South and Eastern Mediterranean(UNICEF,2020;ADB 2019),as well as in the EU(for example,in Germany).NEETs and early school leavers Despite a tendency for young women to be

227、better educated than young men,young women are at a higher risk of being early school leavers and not in employment,education and training(NEETs)(Figure 5).A closer look at the NEETs shows that young men tend to be more often in unemployment,while young women are more often inactive.Figure 5:NEET ra

228、te by gender(15-24 years old),2021 or earliest available year Source:Data collected by ETF KIESE,compilation by the author Gender stereotypes and caring duties can explain this gender pattern(see also Chapter 3 below).ETF data show that a high rate of NEETs is often related to lower educational atta

229、inment,gender,and lower employability as a result of skill gaps and socioeconomic background(ETF 2022).Specific issues exists also for some groups of girls in some countries,such as those coming from disadvantaged ethnic minorities(e.g.the Roma population in the Western Balkans,(Suta et al.2021,Powe

230、ll et al.2021).School-to-work transition and youth joblessness The transition from school to work is often a lengthy and difficult pathway for young people,with many unemployment periods and phases of employment in jobs for which they are overqualified and/or which are precarious.In addition,some yo

231、ung people do not search for work.One indicator for joblessness is the NEET rate.Young people not in employment,education or training can be inactive(and not in education)or unemployed.The NEET rates for both men and women are higher in all ETF PCs for which data are available as compared to the EU(

232、11%).Another finding is that on average in the EU,there is no difference in the NEET rate between men and women.There is a significantly higher share of women NEETs than men in most ETF partner countries(except for Tunisia,Serbia and Montenegro).The female NEET rate was highest in Tajikistan(47%),fo

233、llowed by Jordan,Egypt,Tunisia and Morocco(around 40%each).High inactivity rates of young women are linked to gender 05101520253035404550NEETRateFemaleNEETRateMale GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|24 stereotypes and gender roles.Young women will choose more than young men to be inactive

234、 after leaving education.The youth unemployment rate is generally higher than the unemployment rate of adults.High youth unemployment has been a major concern in ETF partner countries,in particular in SEMED and in the Western Balkans(Figure A14 in Annex 1).Youth unemployment rates for women are sign

235、ificantly higher for young women than for young men in a range of SEMED,including in Egypt,Jordan and Syria.In Tunisia,youth unemployment rates are very high for both men and women at 36.1%and 39.9%respectively in 2021 and Morocco(26.3%and 24.5%,respectively).High youth unemployment rates for women,

236、above 20%,are also recorded in several Western Balkan economies and Trkiye,and Eastern partnership countries(Armenia,Georgia,and Ukraine),and comparatively low in Central Asia.Labour force participation by educational attainment Labour force participation of women varies largely by educational attai

237、nment and the gender gap is large in particular for those with basic education.According to data from the World Bank database,there is a significantly larger share of men of working age with basic education participating in the labour market compared to women.The largest gender gap in the labour for

238、ce of working age population with basic education,is in the SEMED region(ranging between 55 and 64pp,except for Israel where the gap is significantly smaller)(see Figure A11 in Annex 1).The gender gap is large also in some countries in other regions,as in Trkiye(39.4 pp)and North Macedonia(33.2 pp).

239、This indicates that lowly-educated women in these countries are mostly inactive.Women of working age with intermediate education participate more often in the labour market as compared to women with basic education.Gender gaps however remain significant in many countries(see Figure A12 in Annex 1).G

240、ender gaps are less marked among the labour force with advanced education(Figure A13 in Annex 1).Thus,in a range of countries,women of working age with advanced education participate nearly as much as men or even slightly more in the labour force in a several of countries,mainly in the Western Balka

241、n region(Montenegro,North Macedonia,Serbia,and Israel),and the gap was relatively small,ranging between 10 and 20 pp in several countries mainly of Eastern Partnership countries and Trkiye and Western Balkan region(Armenia,Georgia,Moldova,Kosovo,Tunisia,Trkiye).The gender gap was comparatively high

242、in Central Asian countries and highest in the SEMED countries in a context of a very high gender gap in labour force participation(except in Tunisia).But even in the SEMED region,women with advanced education participate significantly more often in the labour market than those low-and intermediate-e

243、ducated.Nevertheless,underutilisation of human capital remains a major concern and labour market transition of well-educated women is a major challenge.The higher enrolment rate of women in tertiary education,as compared to men,and increasing educational level of women is in strong contrast with the

244、 comparatively low and stagnant labour force participation of women in SEMED(Assaad et al.,2018).Participation in adult training Lifelong learning is crucial to maintain and increase employability of workers and make them fit for organisational and technological changes.Unfortunately,only few compar

245、able data for the participation in adult training are available.A joint Eurofound-ETF survey in 2022 conducted in EU countries and among 10 ETF PCs on Living,Working and COVID-19 sheds light on countries capacities to offer training possibilities to adults.In ETF PCs,33%of women and 24%of men had ac

246、cess to education and training opportunities over the previous 12 months,as compared to 65%and 64%of women and men in the EU-27.On average,women in the 10 ETF partner countries participated more often than men in job-related and non-job-related training(with non-job-related training showing the high

247、est gender gap in favour of women)(Eurofound-ETF 2022).GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|25 Available data for 15 ETF partner countries show that participation in lifelong learning lags behind the EU average(with the exception of Israel where the share of men participating in lifelong le

248、arning is larger than on average in the EU)(Figure 6).On average in the EU-27,as well as in Armenia,Bosnia and Herzegovina,Georgia,Moldova,Montenegro,North Macedonia,Serbia,Tunisia,more women than men participate in lifelong learning,while the reverse is true for the remaining 7 countries.Figure 6:P

249、articipation in lifelong learning(LLL),by gender Source:ETF collected datasets/KIESE,Eurostat for EU 27,compilation by the author Digital skills Digital skills at different proficiency levels are necessary to succeed professionally across various sectors.Thus,the economic empowerment of women increa

250、singly depends on their digital skills.One indicator of the digital gender divide is access to the internet.The use of the internet is important for accessing online education,as well as for e-banking,e-commerce and other economic activities.This is in particular relevant for remote rural areas.In a

251、ddition to the internet access,it is crucial that women have the necessary skills to use the internet for learning and business purposes.According to the International Telecommunication Union ITU,of the estimated 2.7 billion people who are currently unconnected worldwide,the majority are women and g

252、irls.Globally,in 2022,62%of men are using the Internet,compared with 57%of women.Between 2013 and 2019,the internet gender gap was shrinking in the CIS34 countries and Europe.However,in the Arab States,the gender gap was growing because most new internet users since 2013 were men35.Not only are the

253、digital infrastructure and access to devices factors that contribute to the digital gender divide,but they also contribute skills to use the internet and devices in a professional way.Digital skills are becoming more important to perform an increasing number of jobs.This requires digital skills at d

254、ifferent proficiency levels,ranging from basic digital skills to high skills proficiency levels needed by IT professionals.Systematic and comparable information on the digital skills gap between men and women is not available for all ETF PCs,with the exception of Western Balkans countries36.Some stu

255、dies provide insights into specific countries and regions.For example,the ETF studies on new forms of employment and platform work in Eastern Partnership and Western Balkans countries shed light on employment patterns and digital skills use at workplace37.In the whole SEMED and other Arab States,the

256、 digital divide is larger for the low-educated and those living in rural areas.One explanation is that ICT is often accessed outside home,where safety concerns and social norms act as barriers for womens and girls access to these technologies(UNICEF 2020).34 Commonwealth of Independent States 35 htt

257、ps:/www.itu.int/en/mediacentre/backgrounders/Pages/bridging-the-gender-divide.aspx 36 https:/ec.europa.eu/eurostat/databrowser/view/ISOC_SK_DSKL_I21_custom_2753855/default/table?lang=en 37 The future of work New forms of employment in the Eastern Partnership countries:Platform work|ETF(europa.eu);Em

258、bracing the digital age|ETF(europa.eu)2021 EU272021 AM2021 AZ2020 IL2020 TR2020 XK2021 RS2020 BA2021 TN2020 ME2020 MK2021 GE2021 MD2017 JO2019 AL2021 UA0.02.04.06.08.010.012.014.0LLLRateFemaleLLLRateMale GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|26 A study in Uzbekistan by UNDO(2022)shows that w

259、omens digital skills lag behind those of their male counterparts by nearly 24%;with a basic digital skills gap of 23%,standard digital skills gap of 21%,advanced digital skills gap of 26%).The gender gap was even greater for programming skills:only about 20%of men and 10%of women indicated programmi

260、ng experience.To compare,at the EU and OECD level,there is evidence that young women(aged 16-24)have less well-developed programming skills than young men.In 2021,in the EU,8.5%of young women indicated that they wrote code in a programming language as compared to 17.6%young men.In Trkiye,3.1%of youn

261、g women and 7.5%of young men had programming experience(data for other ETF partner countries are not shown)(OECD Going Digital Toolkit)38.A persistent gender divide in graduation from studies in information and technology can also be observed.ICT professions are well paid and have a potential to red

262、uce gender wage gap and to bring women into a growing occupation.On average of 19 ETF PCs for which data on the share of women among graduates of tertiary education are available data shows that they are underrepresented among ICT graduates as their share was 37.6%in 2018.This share was however larg

263、er than the average share of female graduates in engineering(31,9%)(see Table A2).There were large differences between countries,the share of female ICT graduates ranging from 17.5%in Ukraine and 17.8%in Uzbekistan to 55.6%in Tunisia and 57.3%in Syria.From a regional perspective,the share of female

264、ICT graduates is highest in the SEMED region,followed by the Western Balkans and Trkiye region,Central Asia and Eastern Partnership countries.To compare with the EU,a higher share of women in the ETF PCs are graduating from tertiary level ICT studies.In the EU,according to a study by the European In

265、stitute for Gender Equality(EIGE),the share of women among ICT professionals(highly qualified specialists,technicians,ICT service professions)in the European Union was only 17%in 2016.In addition,the share of women was even lower in ICT professions than in the engineering and science sector as a who

266、le(25%)(EIGE 2018).Stoet and Geary(2018)show that in many countries,girls outperform boys in their numeracy and reading-writing skills.On the other hand,boys are relatively better in math and science,so boys and girls would make their choice based on their comparative advantage in skills.Gender diff

267、erences in skills and vocational choices are also likely to be the result of stereotypes in education.Also,the role of stereotypes and traditional family models in Europe should not be underestimated,as women are moving towards jobs that are often less well paid.2.4 Effects of COVID-19,recovery and

268、multiple crises on the employment of women Globally,the employment of women has been negatively affected by the COVID-19 pandemic in several ways.First,the pandemic has affected the quality of employment in the health care sector,a sector with a predominance of females in the workforce.Working condi

269、tions deteriorated,stress increased and the risk of infections was higher for these workers(WHO and ILO 2022).Globally,COVID-19 disproportionally affected workers at the low end of the pay scale in the health care sector and thus affected women(WHO and ILO 2022).Also in the ETF PCs,the health care s

270、ector is feminised.Second,in a number of countries women were more likely than men to lose their employment,because they worked in less well protected jobs.In the absence of job protection schemes in many ETF partner countries,female employment rates have been declining in 2020.The World Bank Databa

271、se39 indicates the sharpest decrease in female employment rates in 2020 was in most Western Balkan economies,Trkiye and SEMED countries.The decline in female employment rates was 38 https:/goingdigital.oecd.org/indicator/54 39 ILO modelled estimates;population 15+.Note that ETF is updating its own d

272、atabase at the time of writing.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|27 smaller in Central Asia.Employment rates did not fall in Eastern Partnership countries(except in Ukraine).In 2021,the female employment rate increased in most countries in which employment rates were falling between 2019

273、 and 2020,except in Morocco;Kyrgyzstan and Ukraine(where they continued to fall).Despite catching up,in most countries,the employment rates of women remained below their level in 2019.A survey conducted in Jordan showed that only 56.3%of women experiencing unemployment in Jordan in the spring of 202

274、0 had managed to be re-integrated to the labour market by February 2020(Karbala et al.2022).Third,informal employment presented a high risk for the employment situation of women40.Within this group,women informal workers experienced more difficulties than men in maintaining employment and gaining a

275、new job(UfM,2022).Globally,womens and mens self-employment activities have also been negatively affected by containment measures.Female informal workers experienced sharper declines and slower recovery in working days and earnings than their male counterparts.Negative effects were more pronounced fo

276、r women who had to increase unpaid care work(UN Women and UNDP,2022).Fourth,women left more often the labour force than men because of the high burden of childcare and home schooling imposed by containment measures.Thus,for example,in the Western Balkans,between the second quarter 2019 and the secon

277、d quarter 2020 a continued narrowing of gender employment gaps has been recorded(as a catching-up process of women employment).The fact that employment rates for women fell less than for men is not a positive outcome as such,as more women are leaving the labour force and become inactive.Negative emp

278、loyment impacts were also observed from the second quarter 2020 to the first 2021(Suta et al.2021).Also in the SEMED region,women were disproportionately affected as they had been encouraged to take leave from paid jobs in order to assume care-work within their households(UfM,2022,Karbala et al 2022

279、).The effects of COVID-19 on increased unpaid care work for women are also presumed in Central Asian countries(for example in Tajikistan,World Bank 2021).Women have been disproportionately affected by the COVID-19 pandemic also in EU countries.In particular,the pandemic is likely to have aggravated

280、gender inequalities in the labour market though the unequal division of exceptional unpaid care work between men and women due to the closure of schools and care services,reinforcing traditional gender roles(European Commission 2022).Recovery has been impacted by the war in Ukraine,the energy crisis

281、 and inflation.The newest projections of the IMF issued in April 2023(including projections for some ETF PCs)indicate a slowing down of GDP growth in 2023 as compared to 2022(in Algeria,Armenia,Azerbaijan,Georgia,Israel,Kyrgyzstan,Serbia,Tajikistan,Trkiye(IMF,2023).It is too early to state how this

282、will affect the employment of women and men,but there is a risk that inflationary pressure on food,and energy crisis will further weaken womens position in society and in the labour market.Reduced GDP growth also may affect budgets for Active Labour Market Programmes(ALMPs)from which women may benef

283、it.2.5 Employment opportunities for women in the twin transition Digital transition and employment in the field of ICT As discussed in the previous section,digitalisation of the economy requires digital skills at different proficiency levels across occupations and women are at risk of lagging behind

284、 in acquiring relevant skills.This affects their employment opportunities.Digitalisation leads to both job creation and job destruction(depending on how automatable jobs are).For the OECD,the Survey of Adult Skills(PIAAC)gives some insights on the use of ICT and digital tools at the workplace.One fi

285、nding is that 40 https:/data.unwomen.org/features/three-ways-contain-covid-19s-impact-informal-women-workers#:text=To%20prevent%20COVID%2D19%20measures,and%20supporting%20informal%20workers%E2%80%99%20organizations GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|28 no difference emerges between men an

286、d women in the use of ICTs for low-skilled groups of occupations.However,women often work in some elementary occupations or craft and trade ones,they perform relatively more routine tasks than men,and thus are more exposed to risks of automatization(OECD 2018a).Differences in ICT intensity of occupa

287、tional groups show that ICT intensity is higher for men than for women for service and sales workers,and for professionals.In the EU,the data show that women at work used computers and portable devices,exchanged emails and enter information in databases slightly more often than men.Men used more oft

288、en occupation-specific software and computerised equipment in production and transport and more than twice as often as women developed and maintained IT systems or software41.At the level of professionals,ICT intensity is likely to increase for many professions and the need for interdisciplinarity i

289、ncreases(e.g.medical IT).It is a challenge to collect data on the employment of women in different ICT intensive occupations across sectors.This also holds true when comparing the position of women in ICT professions.Details are not easily accessible and data collection is restricted by data availab

290、ility(ILO 2019).Nevertheless,some insights to the employment situation of ICT specialists in ETF partner countries can be given:Evidence from the Western Balkans shows that only 29%of Montenegrin and 22%of Serbian ICT specialists were female in 2019(Suta et al.2021).Despite the comparatively high sh

291、are of female graduates in STEM tertiary education(see section 2.2 above),women from SEMED struggle to enter the labour market.This situation is explained firstly by the perception that womens abilities are unsuited for scientific work,and secondly,by the lack of recognition for their expertise and

292、working conditions that do not take into account womens needs(Assaad,et al.,2018).Nevertheless,transition to the labour market appears easier for female STEM graduates than for those who specialise in education and/or humanities(Dimova,Elder and Stephan,2016).Box 1:Labour market barriers for women t

293、o enter the IT sector in Tunisia An experimental study conducted in Tunisia on discrimination in the recruitment process(by sending fictional CVs of male and female candidates with the same levels of qualifications and experience)indicates that discrimination exists,and recruitment practices follow

294、gender stereotypes(Alaref et al.2020).The results of this study show for the IT sectorwhere there is gender parity in enrolment at the higher education levelthat women are 15 percentage points(43%)less likely to receive a callback from an employer.This finding may explain in part why the unemploymen

295、t rate of female graduates is 36 percentage points higher than that of their male peers in the Tunisian IT sector.On the other hand,no discrimination was found against women in male-dominated engineering occupations,even as the actual unemployment gap in this field reached a staggering 48 percentage

296、 points in 2014.For the EU,it is argued that work-life balance measures are key to attracting and retaining women in ICT jobs.Some ICT companies have demonstrated their interest in setting up and implementing work-life policies42.Evidence for Germany,for example,shows that it may be challenging to r

297、etain ICT specialists in ICT occupations,as male-dominated working environments and working hours that render reconciliation of work and family life difficult,render ICT jobs often unattractive for women(ILO 2020).Digital transition facilitates new opportunities within online and remote work,often f

298、acilitated by digital platforms.However,while at a first glance those types of work could positively impact gender equality bringing more flexibility in terms of works schedules and location and offset labour market entry barriers for women,recent studies confirm strong inequalities in the EU(EIGE,2

299、02043)and in EU 41 https:/eige.europa.eu/publications-resources/toolkits-guides/gender-equality-index-2020-report/job-automation-use-new-technologies-and-transformation-labour-market,accessed 1 July 2023 42 https:/eige.europa.eu/publications-resources/toolkits-guides/work-life-balance/work-life-bala

300、nce-in-ict?language_content_entity=en 43 Artificial intelligence,platform work and gender equality|European Institute for Gender Equality(europa.eu)GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|29 neighbouring countries(ETF,202244;ETF 202345).The gender gap is very pronounced,both in terms of partic

301、ipation and wages.Women are underrepresented in the digital labour market in the occupations related to IT professional services,which tend to be well paid.At the same time the share of women providing translation or clerical services is higher(ETF,2022).Employment in the green economy The greening

302、of the economy affects labour markets in different ways:in some sectors and regions(e.g.coal-mining regions,regions with energy-intensive productions),employment losses have already been observed in the past and expected in the future.Employment is expected to grow in some other sectors as a result

303、of the green transition(for example in the circular economy and in the construction sector).The agricultural and energy sectors may be among the most affected,with diverging employment effects.An electro-mobility scenario would engender losses of conventional blue-collar mechanical jobs in the autom

304、otive industry,and other sectors will be affected as well(e.g.chemical industry,and textiles46).For the EU,small net employment effects are predicted in scenarios that promotes the greening of the economy.The largest effects are expected in changing jobs and tasks,while shifts across sectors and occ

305、upations will be sizeable(see European Commission 2019,and for an overview of different studies Duell et al.2021).The employment effects(job losses,employment gains,and the need for skills adaptation and the volume of job transitions)of the green transition in ETF PCs will depend on the economic str

306、ucture of each country,including the energy-intensity of production and resource consumption in agricultural production,the role of fossil energy extraction,the direct effects of climate change e.g.on agriculture(drought,flooding)and the capacity of the countries to promote new sectors(e.g.renewable

307、 energies,waste management,ecological agriculture,eco-tourism).The employment effects for men and women depend on their share of employment in the respective industries and their shares in green jobs.Looking to the future,it is important that both women and men are equipped with skills needed for gr

308、een jobs.As for the digital transition,women are at the risk of being left behind for employment opportunities in the green transition,as relevant occupations are often technical,and often require good digital skills.Across the OECD countries and regions,72%of green jobs47 are hold by men(OECD 2023)

309、.For example,data from France shows that women were largely underrepresented among workers holding green or greening jobs.Women were largely overrepresented among greening occupations in tourism,and only slightly below the national average in the area of greening public research occupations and the

310、green occupational group of environmental engineers and professionals(Duell et al 2021).Similar occupational patterns can also be found in other EU countries and may also shape the green economy in ETF PCs(more research would be needed to confirm this hypothesis).Employment potential for women in se

311、veral ETF PCs may exist in the context of sustainable agriculture and agri-food production).The International Renewable Energy Agency(IRENA,2019)found that the share of women in employment(32%)is higher in the renewable energy sector than in conventional energy.Job losses in coal mining have typical

312、ly affected more men than women,in the EU and a number of ETF countries.Employment effects in the textile industry48 typically affects more women than men,therefore more women than men will be affected by restructuring this sector.It has been advocated that in order to increase the share of women in

313、 green jobs,PES can provide vocational guidance,and can support women to take up related STEM fields and jobs.A study prepared for the European Network of Public Employment Services recommended that PES provide vocational guidance to girls and young women in such a way as to motivate them to enrol m

314、ore in 44 https:/www.etf.europa.eu/en/publications-and-resources/publications/future-work-new-forms-employment-eastern-partnership 45 https:/www.etf.europa.eu/en/publications-and-resources/publications/embracing-digital-age-0 46 https:/ec.europa.eu/commission/presscorner/detail/en/QANDA_22_2015 47 T

315、here is no common definition of green jobs used across countries.There are also a variety of ways to measure green jobs with different methodology.The OECD uses a task-based approaches.Broadly speaking,tasks identified as green contribute to environmental objectives such as preserving the environmen

316、t and reducing emission.The classification of the greenness of tasks is made on the basis of the US classification of occupations O*Net.The OECD basis its estimates of green jobs on the EU LFS.48 https:/unfccc.int/sites/default/files/resource/Samantha-BO3_ILO.pdf GENDER DIMENSION OF LABOUR MARKET TR

317、ANSITIONS|30 STEM study fields,possibly with a specialisation in green skills(such as climate,energy and environmental engineering)(Duell et al.,2021).2.6 Conclusions In most ETF PCs,gender activity and employment are high and above EU average.Gender gaps in labour force participation and gender emp

318、loyment gaps have narrowed in a number of ETF PCs over the past decade(and earlier).However,in some countries,progress has been slow,or has even been reversed.Those countries with very high gender employment gaps are also characterised with very low employment rates of women(mainly in SEMED countrie

319、s).This points to a double challenge for policymakers;namely to increase employment rates while reducing gender employment gaps.The quality of female employment and thus employment and working conditions and pay matters.Women are at a higher risk than men to be in vulnerable employment.Women are poo

320、rly represented among entrepreneurs and as owners/leaders/managers of medium-sized and large companies.The gender pay gap is generally high.One reason in all ETF PCs is that women tend to be more often employed in occupations and sectors where wages are relatively lower for a given level of educatio

321、n and skills.Another reason is that they are not well represented in managerial positions.In most ETF PCs,the enrolment rate of women in secondary and tertiary education is well above that of men.In all ETF PCs,there are issues of gender segregation in graduations by field of studies.One exception i

322、s the ICT sector,where differences are less visible,in particular in the SEMED region.This is in contrast with the EU,where gender disparities among ICT graduates are much larger.Another general issue across ETF PCs is the significantly lower participation of girls in technical study fields within v

323、ocational education and training as compared to boys,and in particular in the technical study fields(such as in EU countries).Gender segregation in vocational education and training(VET)tends to be higher than for tertiary education.In most ETF PCs,women have greater difficulties than men to access

324、the labour market,despite the fact that they are often better educated;although having a high education level in general increases the probability for women to find an employment.The reason is that women continue to face discrimination in the labour market,in addition to skills mismatch issues.The g

325、ender unemployment gap tends to be larger in those countries where unemployment rates are at a high level for both men and women.Young people not in employment,education and training(NEETs)represent a major challenge in many ETF PCs.Women seem to be more vulnerable than men in times of crisis.This h

326、as been evident during the pandemic.Migration is affecting the labour market position of women.Often female migrants have lower participation rates,due to different motivations for migration of women,even more so in the past(family reunification),gender stereotypes and social norms.Another issue is

327、overqualification.Women are also particularly vulnerable in times of conflicts and wars.The data indicate that women refugees encounter a high level of obstacles when they wish to enter the host country labour market.GENDER DIMENSION OF LABOUR MARKET TRANSITIONS|31 3.Challenges for women to access t

328、he labour market and root causes of gender inequalities 3.1 Gender stereotypes and social norms Gender stereotypes and social norms have a big impact on the female labour market participation rate,the guidance and choice of VET and tertiary education study fields,and gender distribution of unpaid ca

329、re work.They also influence mens beliefs and attitudes and pressure on womens activities related to employment and vocational choices.Social norms also influence employers behaviour in recruitment,they generate and foster prejudices about womens and mens abilities and competences,and influence their

330、 human resource approaches to career progression.Gender stereotypes affect career choices and lead to occupational segregation and sector segregation.This explains large parts of the gender wage gap,as women tend to be employed in occupations and sectors with lower wages than men.Social norms and ob

331、stacles to reconciling work and family lives,in particular the scarcity childcare options,lead to a higher uptake of part-time employment,which in turn has negative effects on career progression and on pensions.In ETF PCs,as in other countries around the world,gender stereotypes and social norms are

332、 the roots of gender inequality.However,there are large differences in the strictness of social norms,the patriarchal models and breadwinner models between urban and rural areas(with rural areas having stricter social patriarchal norms),between education levels,with more conservative views on womens

333、 and mens roles in lowly educated groups.There are also large differences between regions and between countries within a region,as progress in politics and the legal and institutional frameworks happens at a different pace.For example,worldwide,57 countries have legal provisions in place that subordinate women to their husbands authority.This includes for example Egypt and Jordan,where the family