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Figure 4.37. Members of parliaments by sex in EU Member States, 2010 Women Men 100 % 80 % 60 % 77 % 40 % 20 % 0 % 23 % SE FI BE NL DK ES DE PT AT EU-27 EE BG LV FR IT LU UK LT CZ PL SK EL IE CY HU SI RO MT Source: European Commission’s database ‘Women & Men in Decision-Making’ 4.5.3. Regional assemblies The third gender indicator to measure the representation of women and men in political decision-making measures the share of seats between women and men at the level of regional assemblies. Variable definition: Share of members of regional assemblies (%) This indicator measures the share of women and men members of regional assemblies. Although regional authorities are situated between the central government and local authorities, this does not necessarily imply a hierarchical relationship between regional and local. In addition, regional authorities are not applicable in all countries (EC, 2013). In those cases the data on local and municipal members, including mayors and other leaders, were taken (BG, EE, IE, CY, LT, LU, MT and SI) (Included within the framework of the Beijing Plaform for Action indicators, see Annex 5). Data source: Database on ‘Women & Men in Decision- Making’, DG Justice, European Commission Periodicity: annual except in the case of elections when the data for affected regions are updated with the next quarterly update of political data. The representation of women at EU level in regional assemblies increased steadily from 22 % to 30 % between 2000 and 2010. At national level, this figure also masks differences. The representation of women in regional assemblies ranges from just above one in 10 women in Italy (12 %) to near parity in Sweden (47 %) and France (48 %) (see Figure 4.38.). 90 Gender Equality Index – Report
Figure 4.38. Members of regional assemblies by sex in EU Member States, 2010 Women Men 100 % 80 % 60 % 40 % 20 % 0 % 70 % 30 % FR SE ES FI BE DK NL DE AT UK EU-27 EE BG LT MT PT SI LU EL LV CY PL CZ IE RO SK HU IT Source: European Commission’s database ‘Women & Men in Decision-Making’ 4.5.4. Members of the boards of largest quoted companies The first gender indicator used to measure power through representation in decision-making in economic activities looks at the largest quoted companies at national level. Variable definition: Share of members of boards in largest quoted companies (supervisory board or board of directors) (%). This indicator measures the share of women and men as board members (including chairpersons) in the largest publicly listed companies (traded on the stock exchange) at the national level. Data source: Database on ‘Women & Men in Decision- Making’, DG Justice, European Commission Periodicity: annual The representation of women on the boards of quoted companies increased from 9 % in 2000, to 12 % in 2010, representing a relatively small increase. Only five Member States (FI, SE, LV, RO and SK) had more than 20 % of women as members of the largest quoted companies. In addition, a further five Member States had less than 5 % representation (CY, IT, LU, MT and PT) in 2010 (see Figure 4.39.). Gender Equality Index – Report 91
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Gender Equality Index Report Report
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Halfway towards equality Equality b
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Contents Acknowledgements 2 1. Intr
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Finally, the report concludes with
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The measures range from getting mor
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Table 1.1. Existing gender indices
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The Gender Equality Index ensures t
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The gender framework developed by F
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equal work and work of equal value;
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Figure 2.1. Domains of the Gender E
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The second sub-domain examines gend
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Another important source of income,
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learning remains segregated in term
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The topic of power in decision-maki
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Figure 2.7. Domain of health and it
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complexity of the inequalities that
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disadvantage in terms of accessing
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3.1. Indicators and measures During
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This yields values where 1 stands f
Page 39 and 40: age, as there is only one missing v
Page 41 and 42: Workers caring for and educating th
Page 43 and 44: Additionally, several variables wer
Page 45 and 46: Domain Conceptual framework Measure
Page 47 and 48: 3.2. Computing the Index The Gender
Page 49 and 50: The arithmetic mean allows full com
Page 51 and 52: Table 3.8. Mean experts’ weights
Page 53 and 54: Table 3.10. Pearson’s correlation
Page 55 and 56: Gender Equality Index - Report 55
Page 57 and 58: Table 4.1. Measurement framework fo
Page 59 and 60: 4.1.2. Duration of working life The
Page 61 and 62: Figure 4.5. Employment in the Educa
Page 63 and 64: The overall gender gap, for the per
Page 65 and 66: 4.1.6. Training at work The final i
Page 67 and 68: Table 4.2. Measurement framework fo
Page 69 and 70: 4.2.2. Mean equivalised income In a
Page 71 and 72: 4.2.3. Not-at-risk-of-poverty The f
Page 73 and 74: Figure 4.19. Income distribution (S
Page 75 and 76: 4.3.1. Tertiary education The gende
Page 77 and 78: On the contrary, at EU level in 201
Page 79 and 80: 4.3.3. Formal and non-formal educat
Page 81 and 82: Table 4.5. Measurement framework of
Page 83 and 84: 4.4.2. Cooking and housework Wide d
Page 85 and 86: Figure 4.32. Involvement in sportin
Page 87 and 88: Figure 4.35. Gender gap in involvem
Page 89: Figure 4.36. Ministers by sex in EU
Page 93 and 94: 4.5.6. Summary Women, compared with
Page 95 and 96: Figure 4.41. Good or very good self
Page 97 and 98: Figure 4.44. Life expectancy by gen
Page 99 and 100: The issue of unmet medical needs is
Page 101 and 102: Figure 4.50. Individuals without un
Page 103 and 104: Figure 4.51. Employment rates for p
Page 105 and 106: 4.7.3. Employment for lone parents/
Page 107 and 108: 4.8.1. Direct violence The first su
Page 109 and 110: Table 5.1. Scores of the Gender Equ
Page 111 and 112: Participation is measured by focusi
Page 113 and 114: 5.2.2. Money matters The domain of
Page 115 and 116: Figure 5.4. Relationship between th
Page 117 and 118: The sub-domain educational attainme
Page 119 and 120: Table 5.5. Gender Equality Index sc
Page 121 and 122: In conclusion, gender equality in t
Page 123 and 124: Figure 5.10. Relationship between t
Page 127 and 128: Country Intersecting inequalities F
Page 129 and 130: Table 5.10. Gender Equality Index s
Page 131 and 132: The domain of violence, due to a la
Page 137 and 138: methodology based on sound statisti
Page 139 and 140: is an important area of gender equa
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Women remain less likely to partici
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Sex-disaggregated indicators to mea
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7. Annexes Annex 1: Domains of the
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Table 1.3. Domains of the Index in
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Table 1.5. Domains of the Index cov
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Women and the Economy (F) F1. Emplo
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G15. The proportion and number of w
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Annex 3: Correlation matrix of the
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Domain Money Money Financial resour
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2.5 Screeplot: Time 2.0 1.5 1.0 0.5
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Annex 5: Indicators correspondence
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Table 6.2 . Percentage of women (15
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Annex 8: Scores of the Gender Equal
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Annex 10: Scores of the Gender Equa
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Annex 12: Scores of the Gender Equa
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8. References Anker, R. (1998), Gen
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Cueva, B. H. (2006), ‘What is Mis
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European Commission (2010), Communi
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Hakim, C. (1996), Key Issues in wom
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Rubery, J. (2002),’Gender mainstr
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European Institute for Gender Equal
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