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Measuring and Monitoring Gender related Social Development
Goals in Africa
Jane Kabubo-Mariara PhD*
Judith M. Mutuku
School of Economics, University of Nairobi
Nairobi, Kenya
Paper presented at the Measurement of Well Being and Development in Africa Conference
held at Durban International Convention Center, South Africa
12-14 November, 2015
______________________________________________________________________________
Abstract
While many poor countries continue to make considerable progress in improving gender
wellbeing and equity, data gaps for measuring and monitoring such achievements remain
daunting. This paper examines eight gender dimensions of wellbeing, with a particular focus on
how they are operationalized in the Sustainable Development Goals (SDGs), how they are
currently measured on the ground and the challenges of measurement and monitoring. A
detailed analysis of the data available for such monitoring, in the specific case of Kenya is
carried out. The paper concludes that issues of data availability and gathering need to be
addressed of poor countries (such as Kenya) are to achieve the very ambitious SDGs.
Key words: Gender, wellbeing, measurement, monitoring, SDGs, data, Kenya
*
Corresponding author. Email: jkmariara@yahoo.com
1
1.0 Introduction
The United Nations Conference on Sustainable Development (Rio+20 Conference) which was
held in June 2012 observed that although some progress had been made in the implementation of
sustainable development since the Earth Summit in 1992, the implementation was still a
challenge for many countries (United Nations, 2012). The main reasons for the lack of
implementation include; insufficient progress and setbacks in the integration of the various
dimensions (economic, social and environmental) of sustainable development. Therefore, in
2014, the intergovernmental Open Working Group (OWG) on Sustainable Development Goals
proposed 17 Sustainable Development Goals (SDGs) and 169 associated targets to be achieved
by the year 2030. The United Nations Sustainable Development Summit for world leaders
adopted the 2030 Agenda for Sustainable Development Goals (17 SDGs) to end poverty, fight
inequality and injustice, and tackle climate change by 2030 on the 25th
of September, 2015
(Loewe, 2015).
The SDGs propose major improvements over weaknesses in the Millennium Development Goals
(MDGs). Among other goals and targets, the SDGs address key systemic barriers to sustainable
development such as inequality, unsustainable consumption patterns, weak institutional capacity,
and environmental degradation which were neglected in the MDGs. The MDGs failed to account
for the root causes of poverty and gender inequalities and also completely left out peace, security
and disarmament as well as human rights, democracy and good governance (World Bank, 2011).
They also failed to measure the socio-cultural, political capabilities and protective capabilities
and thus did not address the holistic nature of development, specifically economic development.
Some MDGs also measure outputs or inputs rather than outcomes or impacts of the development
(United Nations, 2012). Unlike the MDGs which in theory applied to all countries, but in reality
were targets for the developing or poor countries, in the post-2015, every country will be
expected to work towards achieving its own SDGs (Rio+20 or Earth Summit (2012).
Some MDGs could not be measured mostly due to absence of indicators or lack of adequate data
for certain indicators. To avoid this pitfall in the post 2015 agenda, it is important that the targets
for the SDGs have clearly defined indicators which are measurable. The indicators should form
the backbone of monitoring the progress of the SDGs at all levels. Monitoring of the SDGs is
2
very vital because it will help countries to develop implementation strategies and allocate
resources accordingly. Moreover, a sound indicator framework for monitoring the SDGs will
help the countries to develop a report card for measuring the progress of the SDGs towards
sustainable development (OECD, 2013). According to Ocampo (2015), the SDGs should be
monitored at four levels: national, regional, global, and thematic. Regional and global level
monitoring will aim at complementing country level monitoring whereas thematic monitoring
and review will complement monitoring and review at national, regional, and global levels. The
key challenge of measurement and monitoring of SDGs at any level is the absence of accurate
and up to date data, especially in low income countries. Therefore, a data revolution will be
required for successful measurement and monitoring of SDGs. This underlines the logic of
strengthening data collection and processing capacity especially for developing countries
(SDSN, 2015).
The interest of this paper is the place of gender dimensions of well-being in the SDGs and how
these dimensions of well-being can be measured and monitored effectively. Though the MDGs
aimed at reducing poverty and gender inequality, failure to tackle the root causes of poverty and
gender inequality has lead to failure to achieve the MDG targets for some indicators. Moreover,
although many countries have adopted a gender mainstreaming approach, assessment of gender
mainstreaming is marred by lack of indicators and data to measure outcomes and impacts (Moser
and Moser 2005). According to Anderson and Roche (2006), gender-sensitive indicators are
crucial for evaluation of the outcomes of interventions and policies, assessment of challenges,
and adjustment of programmes and activities to reduce adverse gendered impacts. Today, while
many poor countries continue to make considerable progress in gender equality and equity, lack
of adequate data for measurement and monitoring the progress still abound. This paper focuses
on eight dimensions: education, health, political voice, justice and governance, work (personal
activities), material wellbeing, good security, environment and gender based violence. Though
these indicators may not encompass all gender dimensions of wellbeing, they cover the most
important dimensions and can be viewed as indicators of multidimensional wellbeing. The paper
illustrates the challenges of measuring and monitoring these dimensions through an analysis of
data availability in Kenya.
3
The rest of the paper is structured as follows: section 2 outlines the gender dimensions of
wellbeing and how they are measured. Section 3 presents an analysis of adequacy of data for
monitoring gender dimensions of well being in Kenya. Section 4 concludes.
2. Gender Dimensions of Wellbeing
Gender dimensions of wellbeing are the indicators of wellbeing which are sex disaggregated or
which may affect men and women differently. The gender indicators could be quantitative and/or
qualitative statistical data, which provide separate measures for men and women on different
aspects (Barker et al., 2004). Differences and inequalities between the sexes are shaped by the
history of social relations; change over time and cultures (United Nations, 2006). There are
several gender dimensions of wellbeing related to the SDGS. These are discussed below:
2.1 Education
Equality in education access and quality is the foundation of improving people’s lives and
ensuring sustainable development (United Nations, 2006). The right to education is a human
right having major implications both for the individual as well as for socio-economic
development. Education is important for empowerment of women as lack of education limits
their access to well-paid, formal sector jobs and also limits their job mobility. Low education
attainment also limits women’s political empowerment, leading to low participation in and
representation in government and civil organs. Women’s education is associated with better child
health (nutrition, morbidity and mortality) and education outcomes (WEF 2015). Yet women fall
behind men in education attainment in many developing countries and constitute two-thirds of
the world’s illiterate population. In many developing countries (Kenya included) girls and boys
do not have equal access to basic education. Moreover, in low-income countries with low
enrolment levels, girls are less likely than boys to enter primary schooling (United Nations
Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics, 2011).
SDG4 aims to ensure inclusive and equitable quality education and to promote life-long learning
opportunities for all. One critical target of this goal is to eliminate gender disparities in education
4
and ensure equal access to all levels of education and vocational training by 2030. Availability of
good statistics is crucial for monitoring improvements in education and ensuring that the set
targets are met.
The main indicators used to measure gender dimension of education are: sex disaggregated
literacy levels, enrollment rates and attainment (UNDP, 2006). While enrolment rates measure
the input side of education, they fail to capture school completion rates and learning outcomes.
Literacy is not a good measure of education as literacy data is often unreliable (Grown et al.,
2003). Likewise, enrolment statistics may overstate the educational participation of girls and
boys in school because enrolment refers to the number of pupils officially enrolled or registered
at a given level of education, and so children who are enrolled but not attending school are
included in enrolment statistics (UNESCO Institute for Statistics, 2010). Enrolment therefore
captures the intent to participate in education rather than actual participation, and as a result, the
overall statistics of gender disparity may be underestimated or overestimated. Some suggestions
for improving the enrollment indicator include additional data on population, disaggregated by
sex and age from other sources such as population censuses, population registers or a
combination of population censuses and household surveys or civil registration systems.
Moreover, inclusion of education expenditure of households for each child by sex may be of
particular interest in countries with considerable gender inequality in education such as Kenya.
Compared to other gender dimensions of wellbeing, education is perhaps the best measured as all
household surveys and censuses include a module on education. The challenge for most
countries, Kenya included is lack of panel data at the household or individual level for
monitoring progress in education indicators.
2.2 Health
Ensuring healthy lives and promoting the well-being for all at all ages is essential for sustainable
development (UNIFEM, 2005). The health gender dimension is in line with SDG3 which aims at
ensuring healthy lives and promoting well-being for all at all ages. The reproductive health
targets in this goal have important implications for women’s wellbeing which include;
5
decreasing the global maternal mortality ratio to less than 70 per 100,000 live births by 2030;
reducing neonatal mortality to at least as low as 12 per 1,000 live births and under 5 mortality to
at least as low as 25 per 1,000 live births. The key indicators for monitoring gender dimensions
of health include:
(i) Reproductive health (all aspects of maternal health):
(ii) Sexual health indicator (use of contraceptives and adolescent fertility rates)
(iii) Children health (morbidity, mortality, and nutrition
(iv) Mortality and cases of death (life expectancy by age and sex)
(v) HIV AIDS prevalence, coverage of antiretroviral therapy and knowledge of
HIV/AIDS
Reliable data on many of the above indicators are lacking. For instance, in many African
countries, there is underreporting and misclassification of deaths, leading to unreliable estimates
of maternal mortality, making it difficult to monitor changes over time and to assess differences
between population groups (United Nations, 2010a).
2.3 Political voice, justice and governance
Women are grossly under-represented in decision-making structures the world over and lack
voice in policy formulation (WEF, 2015). This dimension of well-being is partially covered in
SDG16 which focuses on promoting peaceful and inclusive societies for sustainable
development, provision of access to justice for all and building effective accountable institutions
at all levels. This SDG targets among others to ensure responsive, inclusive, participatory and
representative decision-making at all levels. This dimension is also partially covered by SDG5
which aims at achieving gender equality and empowering all women and girls. This SDG
assumes that representation in political and economic decision-making processes will fuel
sustainable economies and benefit societies and humanity at large. The SDG has among other
targets for reducing gender inequality, a target to ‘ensure women’s full and effective
participation and equal opportunities for leadership at all levels of decision making in political,
economic and public life’. The gender dimension indicators for measuring the political voice
and governance include: legal protection, legal awareness and adjudication (UNDP 2004; Lopez-
Claros and Zahidi, 2005).
6
This dimension of wellbeing can be measured through:
(i) The number of female Ministers,
(ii) Number of seats in parliament held by women,
(iii) Number of women holding senior, legislative and managerial positions
(iv) The number of years a female has been head of state (president or prime minister)
National statistical offices in many developing countries however do not routinely produce data
on positions of power and decision-making in politics and governance, making monitoring of
this gender dimension of wellbeing difficult.
2.4 Work (personal activities)
This dimension relates to SDG8 whose aim is to promote inclusive and sustainable economic
growth, full and productive employment and decent work for all. One of the key targets of SDG8
is to achieve, by 2030, full and productive employment and decent work for all women and men,
and equal pay for work of equal value. SDG5 also targets to provide women and girls equal
access to decent work and equal rights to economic resources as their male counterparts. Lopez-
Claros and Zahidi (2005) and Oxfam (2002), advance that work or personal activities can be
measured using economic participation and access to economic opportunities.
Indicators/measures of economic participation include:
(i) Participation in private and public decision-making
(ii) Access to and control over economic and natural resources, and basic social services
(iii) Gender stereotypes and discriminatory attitudes
(iv) Establishment, strengthening and collaboration of women’s organizations
(v)Women empowerment, self-confidence, leadership skills, and capacity to organize
Access to economic opportunities relates to the quality of women’s economic involvement This
can be measured by the duration of maternity leave, percentage of wages paid during the covered
period, number of women in managerial positions, availability of government provided
childcare, impact of maternity laws on the hiring of women and wage inequalities between men
and women in the private sector (Lopez-Claros and Zahidi 2005).
7
Measuring work and accounting for gender differences in work in developing countries is
complicated due to data gaps. The international guidelines suggest that the mainstreaming of
gender in labor statistics, definitions and measurement methods should cover and adequately
describe all workers and work situations in sufficient detail to allow relevant gender comparisons
to be made (International Labor Office, 2003). However, based on conventional labor statistics,
the participation of women in work activities and their contribution to the economy tend to be
underestimated (United Nations, 2001).
2.5 Material living standards
The key indicator which measures the living standards of people in a society is poverty,
conventionally measured using consumption and income levels. According to UNDP (2004), a
decent standard of living is measured by women’s and men’s share of earned income. This
gender dimension is related to SDG1 whose objective is to end poverty in all its forms
everywhere. This SDG targets among others to eradicate extreme incomes poverty ($1.25) for all
by 2030. Consumption expenditures are often used as proxies of material wellbeing due to
difficulties of measuring incomes. The dimension also related to SDG10 which aims at reducing
inequalities within and across countries, more so for vulnerable groups. Gender dimensions of
material wellbeing can be assessed by profiling the following indicators by gender of household
head:
i). Headcount poverty index,
ii). Poverty gap
iii). Poverty gap squared
iv). Inequality measures (such as Gini index )
v). Assets (both physical and financial)
2.6 Food security
Food security is related to material wellbeing, but goes further to cover quality of wellbeing.
SDG 2 sets to end hunger, achieve food security and improved nutrition and promote sustainable
agriculture. Some of the key targets under this goal focus on improving the wellbeing of
vulnerable women and children by providing sufficient and nutritious food. This SDG must
8
therefore ensure that all three dimensions of food security: food access, food availability and
food utilization (FAO, 2006; WFP, 2009) are catered for. Gender dimensions of food security
can be measured by:
(i) Gender differences in levels of food consumption,
(ii) Diversity of diets by gender of household head
(iii) Differences in exposure to changes in food access by gender of household head
(iv) Differences in feeding practices by sex of children
Like other indicators, lack of consistent data to monitor this dimension abound. For instance, in
Kenya, welfare monitoring and household budget surveys are the most comprehensive datasets
on food consumption, yet, no specific attention is given to various aspects of food security. In
addition, there is no national level panel data available to monitor consumption and food security
over time.
2.7 Environment
Environmental degradation, inadequate access to natural resources and natural disasters have
different levels of impact on women’s and men’s livelihoods as well as time use and food
security; with women in the developing countries being particularly vulnerable (United Nations,
2010b). Recognition that the MDGs failed to pay adequate attention to environment has ensured
that this is given a lot of attention with several SDGs focusing on environment and natural
resources. These include SDG6, (related to water and sanitation), SDG7 (energy), SDG11 (urban
cities), SDG13 (climate change), SDG14 (resources under the water), and SDG15 (land
resources).
Gender dimension of environment can be measured through the involvement of women and men
in the management of the environment. According to United Nations Environment Programme
(2012), this indicator can be measured through:
i) Representation of women and men in high-level decision-making related to
environmental issues;
ii) Enrollment in (and graduation from) environment, water, agriculture, forestry and
energy fields of study;
9
iii) Involvement of women and men in sustainable consumption and environmentally-
friendly behavior (e.g. saving water or saving energy), and;
iv) Membership of men and women in local non-governmental organizations (NGOs)
involved in environmental protection.
Measurement of this dimension is a real challenge in African countries because such information
is not readily available, especially at the national scale.
2.8 Insecurity/Gender based violence
Physical and sexual violence against women is widespread, with prevalence levels varying
considerably across countries (United Nations, 2010b). Psychological and economic violence are
also not reported as often as physical and sexual violence, but affect the well-being of many
women (WHO, 2005). Men’s vulnerability to domestic violence is more pronounced during
childhood, adolescence and at older ages.
Gender based violence dimension of wellbeing is related to SDG5, which targets, among others,
to end all forms of discrimination and violence against women and girls and also to eliminate all
harmful practices, such as child, early and forced marriage and female genital mutilation.
Indicators of this dimension include number of cases of:
(i) Harassment, physical assault and molestation by gender
(ii) Domestic violence by gender
(iii) Rape of adult women
(iv) Rape of minors
Measurement of gender violence is perhaps one of the most difficult of all dimensions due to
lack of data and also because many cases, especially of domestic violence and report go
unreported as victims fear the stigma that tend to come with exposure.
10
3.0 Data for measurement and monitoring gender dimensions of wellbeing
in Kenya
As alluded to in the previous section, there is a considerable amount of data for monitoring
gender dimensions of wellbeing in Kenya. Such data is however often inconsistent in depth and
spatial coverage, often has glaring gaps and, is in most cases is highly aggregated. The data
available is also mostly cross sectional, which makes it rather difficult to measure and monitor
wellbeing over time. Appendix table 1 presents a comprehensive analysis of the data available by
dimension and source, the period over which data is available, and the shortcoming.
4.0 Conclusion
Achievement of the SDGs discussed in this paper would go a long way in improving the plight
of vulnerable women and children. An analysis of the availability of data for monitoring the
eight gender dimensions of wellbeing in Kenya show that data is generally inadequate. Even for
education where relatively good data is available, disaggregated panel data is not available.
Accurate measurement and monitoring of SDGs however require good data and regular
reporting. Poor data and data gaps require much greater investments in building independent,
impartial national statistical capacities and strengthening of statistical quality and standards
(UNDP, 2004). The new expanded set of SDGs and targets cover a wide range of topics for
which current, detailed, and reliable data does not exist. Additionally, the existing traditional
data collection and integration methods may be technically difficult or very outdated to
implement and monitor some of the new set of targets, necessitating the development of new
indicators. Kenya is one such case, where data is in many respects inadequate to measure and
monitor SDGs.
The is therefore need for capacity building and funding support to national governments in
developing countries in order to consolidate database (including gender-responsive database) to
facilitate better implementation of the SDGs targets. Additionally, increased attention should be
given to the development of harmonized sets of indicators appropriate at the nation, regional and
international level. Such indicators should also be easily disaggregated at sub-national levels.
Attention should also be given to measurement methodologies to ensure that gender dimensions
11
such as time use, the informal sector and unpaid work, as well as other difficult to measure
multidimensional issues such as advocacy and sexuality are adequately captured. There is also
need to move beyond sex disaggregation of the data to further examine the gender dimensions of
ethnicity, disability status, place of residence, religion and age in order to have a wider and better
understanding of the gender dimensions of wellbeing.
12
5. References
Barker, G., Nascimento, M., Segundo, M. and Pulerwitz, J., 2004. ‘How Do We Know if Men
have Changed? Promoting and Measuring Attitude Change with Young Men: Lessons from
Program H in Latin America’, in Ruxton, S. (ed.) Gender Equality and Men: Learning from
Practice, Oxford: Oxfam
Food and Agriculture Organization of the United Nations, 2006. Food security: policy brief No.
2. Rome.
Grown, C., Rao Gupta, G. and Khan, Z., 2003. ‘Promises to keep: achieving gender equality and
the empowerment of women’, background paper for the UN Millennium Project Task Force on
Education and Gender Equality, Washington, DC: ICRW.
Loewe, M., 2015. Post 2015: How to Reconcile the Millennium Development Goals (MDGs)
and the Sustainable Development Goals (SDGs)? Briefing Paper 18/2012 Summary.
http//:post2015.files.wordpress.com/2013/01/loewe-2012. Accessed 29th
October 2015.
Lopez-Claros, A. and Zahidi, S., 2005. Women’s Empowerment: Measuring the Global Gender
Gap. World Economic Forum. Geneva, Switzerland.
Moser, C. and Moser, A., 2005. ‘Gender Mainstreaming since Beijing: a Review of Successes
and Limitations in International Institutions’, in Porter, F. and Sweetman, C. (eds)
Mainstreaming Gender in Development: a Critical Review, Oxford: Oxfam.
Ocampo, J. A., 2014. A Post-2015. Monitoring and Accountability Framework. Paper prepared
for the UN Department of Economic and Social Affairs.
OECD, 2013. Beyond the Millennium Development Goals: Towards an OECD contribution to
the post-2015 agenda”, OECD and Post- 2015 Reflections series, OECD, Paris.
Oxfam, 2002. Gender Mainstreaming Tools: Questions and Checklists to Use across the
Programme Management Cycle, Version 1, November 2002, Oxfam.
The Rio+20, Earth Summit, 2012. United Nations Conference on Sustainable Development
(UNCSD). http://www.uncsd2012.org/. Accessed 20th
October 2015.
UNESCO Institute for Statistics, 2011. Global Education Digest 2011: Comparing Education
Statistics Across the World – Focus on Secondary Education, Montreal.
13
Sustainable Development Solutions Network (SDSN), 2015. Indicators and a Monitoring
Framework for the SDGs, Draft Report. Paris, France and New York, USA: SDSN.
UNDP (United Nations Development Programme), 2006. Measuring Democratic Governance: a
Framework for Selecting Pro-Poor and Gender-Sensitive Indicators, New York:
http://www.undp.org/oslocentre/docs06/Framework%20paper%20-%20entire%20paper.pdf.
Accessed, 30th
October 2015
United Nations Development Programme (UNDP), 2004. ‘Note on statistics in the Human
Development Report’, in Human Development Report 2004: Cultural Liberty in Today’s Diverse
World, 251–85, New York: UNDP.
United Nations Development Fund for Women (UNIFEM), 2005. Untitled.
http://siteresources.worldbank.org/INTGENDER/Resources/UNIFEM.doc. Accessed, 15th
October 2015.
United Nations, 2010a. The World’s Women 2010: Trends and Statistics. Series K, No. 19. Sales
No. E.10.XVII.11.
United Nations, 2010b. Economic Commission for Europe and World Bank Institute.
Developing gender statistics: a practical tool. Geneva. ECE/CES/8.
World Economic Forum (WEF), 2015. World Economic Forum Annual Meeting 2015. Davos-
Klosters, Switzerland 21 - 24 January 2015.
World Food Programme (WFP), 2009. Comprehensive Food Security and Vulnerability
Analysis: Guidelines, 1st ed. Rome.
WHO (2005). WHO multi-country study on women’s health and domestic violence against
women: summary report of initial results on prevalence, health outcomes and women’s
responses. Geneva, World Health Organization, 2005. http://www.who.int/. Accessed 35th
October 2015.
World Bank, 2011. World Development Report 2012: Gender Equality and Development.
Washington, D.C.
14
Table 1: Data for Measuring and Monitoring Gender dimensions of wellbeing in Kenya
Dimension
of wellbeing
Indicator Surveys available Period data available Assessment
Education Literacy
Enrollment
Attainment levels
Kenya Demographic and
Health Survey (KDHS)
1988/1989; 1993; 1998
2003; 2008/2009; 2014
Data from 2003 and later are
nationally representative.
Data before 2003 exclude North
Eastern region and several northern
districts in the Eastern and Rift
Valley regions.
Population and housing
census
2009; 1999; 1989; 1979;
1969
Census is done after every 10 years.
This data is periodic thus difficult to
use to monitor progress in SDGs
Kenya Integrated Household
Budget Survey (KIHBS)
Welfare Monitoring Surveys
2005/6
1992, 1994, 1997
Second largest survey dataset after
the census with comprehensive data
on education.
No time series for monitoring
individuals/households
Kenya National Bureau of
Statistics (KNBS)-Statistical
Abstract
2007-2012 Data not disaggregated by gender
(but secondary enrollment, data is by
gender for the years 2009-2012)
Ministry of Education and
other relevant institutions
Various Data not readily available to users.
African Development
Indicators
Various Data too aggregated
World Bank- World
development indicators
1960-2015 The data is disaggregated by gender
for all the education indicators. It is
reliable, but may not give a
complete picture of the spatial
dimension within a country.
15
Work Economic
participation
Kenya National Bureau of
Statistics (KNBS-sectoral
statistics)/ Ministry of Labor,
Social Society and Services.
Integrated labour force survey
International Labor
Organization
Population and housing
census
2008-2012
1998/1999
2005/6
1986-2015
2009
Data too aggregated and not always
comprehensive
2005/6 was part of labor module in
KIBHS and thus not comprehensive
Data not always comprehensive of
SDGs.
Data is disaggregated by gender but
excludes labor from home makers,
other unpaid caregivers and some
workers in informal sector, which
are sectors dominated by women
Employment/econo
mic opportunities
Kenya National Bureau of
Statistics (Sectoral statistics)
Population and housing
census
2008-2012
2009
Data too aggregated
Only latest census had labour force
module. Future censuses should
include the same to facilitate
monitoring of SDGs.
Health Sexual &
reproductive health
Maternal mortality
Child nutrition
HIV AIDS
Kenya Demographic and
Health Survey (KDHS)
1988/1989; 1993; 1998
2003; 2008/2009; 2014
The data is not consistent over the
years. Moreover, the data is
aggregated.
Multiple Indicator Cluster
Survey (MICS) - United
Nations International
Children's Emergency Fund
(UNICEF)
1996-2015 UNICEF has conducted four rounds
of MICS 1995-1996, 2000-2001,
2005-2006, 2009-2012 and a fifth is
now under way (2013-2015). Some
of the data is disaggregated by
gender and age.
16
World Health Organization
(WHO)--
Global Health Observatory
(GHO) data
2002-2015 Good data, disaggregated by gender,
but not always available at the local
scale
National Aids control Council
(NACC)
Varied Disaggregated by gender, but
periodic surveys. Need for time
series data
Material
Living
standards
Income and
consumption
Kenya Integrated Household
Budget Survey (KIHBS)
Welfare Monitoring Surveys
2005/6
1992, 1994, 1997
Not very good data, though has
improved over WMS. 2015/16
survey is ongoing.
No panel data available for
monitoring material living standards.
The World Bank- World
development indicators
1990-2014 This is data on mean consumption
and income, often based on the
WMS and KIHBS data.
Political
voice,
justice and
governance
Candidates in
elections by male
and females
World Governance indicators 1996-2014 This data is aggregated
Electoral Commission of
Kenya (data on voter
registration and turnout).
Varied This data is not always gender
disaggregated.
Data not publicly available
Gender
based
violence
Victims of violence
against women
Kenya Demographic and
Health Survey (KDHS )
1988/1989; 1993; 1998
2003; 2008/2009; 2014
Data prior to 2003 not nationally
representative.
KNBS - Justice and crime
statistics.
Administrative police and
court records
Health administrative records.
The Ministry of Gender,
Sports, Culture and Social
Services
Varied This data is periodic and aggregated
thus not reliable for monitoring
SDGs
17
Food
security
Food access Kenya Integrated Household
Budget Survey (KIHBS)
Welfare Monitoring Surveys
2005/6
1993, 1994, 1997
Not very good data, though has
improved over time.
Best available for monitoring food
access.
Yet, no panel data available for
monitoring material living standards
Food utilization-
consumption,
nutritional status
Kenya Integrated Household
Budget Survey (KIHBS)
Kenya Demographic and
Health Survey (KDHS)
2005/6
1988/1989; 1993; 1998
2003; 2008/2009; 2014
No panel data available
Environment Enrollment in
environment-
related fields of
study.
Gender
representation in
environmental
managerial
positions
School administrative records
The National Environment
Management Authority
(NEMA)
Ministry of Environment and
natural resource
Varied
Varied
This data is scanty and not readily
available

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HLEG thematic workshop on Measurement of Well Being and Development in Africa, Jane Mariara Paper

  • 1. 0 Measuring and Monitoring Gender related Social Development Goals in Africa Jane Kabubo-Mariara PhD* Judith M. Mutuku School of Economics, University of Nairobi Nairobi, Kenya Paper presented at the Measurement of Well Being and Development in Africa Conference held at Durban International Convention Center, South Africa 12-14 November, 2015 ______________________________________________________________________________ Abstract While many poor countries continue to make considerable progress in improving gender wellbeing and equity, data gaps for measuring and monitoring such achievements remain daunting. This paper examines eight gender dimensions of wellbeing, with a particular focus on how they are operationalized in the Sustainable Development Goals (SDGs), how they are currently measured on the ground and the challenges of measurement and monitoring. A detailed analysis of the data available for such monitoring, in the specific case of Kenya is carried out. The paper concludes that issues of data availability and gathering need to be addressed of poor countries (such as Kenya) are to achieve the very ambitious SDGs. Key words: Gender, wellbeing, measurement, monitoring, SDGs, data, Kenya * Corresponding author. Email: jkmariara@yahoo.com
  • 2. 1 1.0 Introduction The United Nations Conference on Sustainable Development (Rio+20 Conference) which was held in June 2012 observed that although some progress had been made in the implementation of sustainable development since the Earth Summit in 1992, the implementation was still a challenge for many countries (United Nations, 2012). The main reasons for the lack of implementation include; insufficient progress and setbacks in the integration of the various dimensions (economic, social and environmental) of sustainable development. Therefore, in 2014, the intergovernmental Open Working Group (OWG) on Sustainable Development Goals proposed 17 Sustainable Development Goals (SDGs) and 169 associated targets to be achieved by the year 2030. The United Nations Sustainable Development Summit for world leaders adopted the 2030 Agenda for Sustainable Development Goals (17 SDGs) to end poverty, fight inequality and injustice, and tackle climate change by 2030 on the 25th of September, 2015 (Loewe, 2015). The SDGs propose major improvements over weaknesses in the Millennium Development Goals (MDGs). Among other goals and targets, the SDGs address key systemic barriers to sustainable development such as inequality, unsustainable consumption patterns, weak institutional capacity, and environmental degradation which were neglected in the MDGs. The MDGs failed to account for the root causes of poverty and gender inequalities and also completely left out peace, security and disarmament as well as human rights, democracy and good governance (World Bank, 2011). They also failed to measure the socio-cultural, political capabilities and protective capabilities and thus did not address the holistic nature of development, specifically economic development. Some MDGs also measure outputs or inputs rather than outcomes or impacts of the development (United Nations, 2012). Unlike the MDGs which in theory applied to all countries, but in reality were targets for the developing or poor countries, in the post-2015, every country will be expected to work towards achieving its own SDGs (Rio+20 or Earth Summit (2012). Some MDGs could not be measured mostly due to absence of indicators or lack of adequate data for certain indicators. To avoid this pitfall in the post 2015 agenda, it is important that the targets for the SDGs have clearly defined indicators which are measurable. The indicators should form the backbone of monitoring the progress of the SDGs at all levels. Monitoring of the SDGs is
  • 3. 2 very vital because it will help countries to develop implementation strategies and allocate resources accordingly. Moreover, a sound indicator framework for monitoring the SDGs will help the countries to develop a report card for measuring the progress of the SDGs towards sustainable development (OECD, 2013). According to Ocampo (2015), the SDGs should be monitored at four levels: national, regional, global, and thematic. Regional and global level monitoring will aim at complementing country level monitoring whereas thematic monitoring and review will complement monitoring and review at national, regional, and global levels. The key challenge of measurement and monitoring of SDGs at any level is the absence of accurate and up to date data, especially in low income countries. Therefore, a data revolution will be required for successful measurement and monitoring of SDGs. This underlines the logic of strengthening data collection and processing capacity especially for developing countries (SDSN, 2015). The interest of this paper is the place of gender dimensions of well-being in the SDGs and how these dimensions of well-being can be measured and monitored effectively. Though the MDGs aimed at reducing poverty and gender inequality, failure to tackle the root causes of poverty and gender inequality has lead to failure to achieve the MDG targets for some indicators. Moreover, although many countries have adopted a gender mainstreaming approach, assessment of gender mainstreaming is marred by lack of indicators and data to measure outcomes and impacts (Moser and Moser 2005). According to Anderson and Roche (2006), gender-sensitive indicators are crucial for evaluation of the outcomes of interventions and policies, assessment of challenges, and adjustment of programmes and activities to reduce adverse gendered impacts. Today, while many poor countries continue to make considerable progress in gender equality and equity, lack of adequate data for measurement and monitoring the progress still abound. This paper focuses on eight dimensions: education, health, political voice, justice and governance, work (personal activities), material wellbeing, good security, environment and gender based violence. Though these indicators may not encompass all gender dimensions of wellbeing, they cover the most important dimensions and can be viewed as indicators of multidimensional wellbeing. The paper illustrates the challenges of measuring and monitoring these dimensions through an analysis of data availability in Kenya.
  • 4. 3 The rest of the paper is structured as follows: section 2 outlines the gender dimensions of wellbeing and how they are measured. Section 3 presents an analysis of adequacy of data for monitoring gender dimensions of well being in Kenya. Section 4 concludes. 2. Gender Dimensions of Wellbeing Gender dimensions of wellbeing are the indicators of wellbeing which are sex disaggregated or which may affect men and women differently. The gender indicators could be quantitative and/or qualitative statistical data, which provide separate measures for men and women on different aspects (Barker et al., 2004). Differences and inequalities between the sexes are shaped by the history of social relations; change over time and cultures (United Nations, 2006). There are several gender dimensions of wellbeing related to the SDGS. These are discussed below: 2.1 Education Equality in education access and quality is the foundation of improving people’s lives and ensuring sustainable development (United Nations, 2006). The right to education is a human right having major implications both for the individual as well as for socio-economic development. Education is important for empowerment of women as lack of education limits their access to well-paid, formal sector jobs and also limits their job mobility. Low education attainment also limits women’s political empowerment, leading to low participation in and representation in government and civil organs. Women’s education is associated with better child health (nutrition, morbidity and mortality) and education outcomes (WEF 2015). Yet women fall behind men in education attainment in many developing countries and constitute two-thirds of the world’s illiterate population. In many developing countries (Kenya included) girls and boys do not have equal access to basic education. Moreover, in low-income countries with low enrolment levels, girls are less likely than boys to enter primary schooling (United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics, 2011). SDG4 aims to ensure inclusive and equitable quality education and to promote life-long learning opportunities for all. One critical target of this goal is to eliminate gender disparities in education
  • 5. 4 and ensure equal access to all levels of education and vocational training by 2030. Availability of good statistics is crucial for monitoring improvements in education and ensuring that the set targets are met. The main indicators used to measure gender dimension of education are: sex disaggregated literacy levels, enrollment rates and attainment (UNDP, 2006). While enrolment rates measure the input side of education, they fail to capture school completion rates and learning outcomes. Literacy is not a good measure of education as literacy data is often unreliable (Grown et al., 2003). Likewise, enrolment statistics may overstate the educational participation of girls and boys in school because enrolment refers to the number of pupils officially enrolled or registered at a given level of education, and so children who are enrolled but not attending school are included in enrolment statistics (UNESCO Institute for Statistics, 2010). Enrolment therefore captures the intent to participate in education rather than actual participation, and as a result, the overall statistics of gender disparity may be underestimated or overestimated. Some suggestions for improving the enrollment indicator include additional data on population, disaggregated by sex and age from other sources such as population censuses, population registers or a combination of population censuses and household surveys or civil registration systems. Moreover, inclusion of education expenditure of households for each child by sex may be of particular interest in countries with considerable gender inequality in education such as Kenya. Compared to other gender dimensions of wellbeing, education is perhaps the best measured as all household surveys and censuses include a module on education. The challenge for most countries, Kenya included is lack of panel data at the household or individual level for monitoring progress in education indicators. 2.2 Health Ensuring healthy lives and promoting the well-being for all at all ages is essential for sustainable development (UNIFEM, 2005). The health gender dimension is in line with SDG3 which aims at ensuring healthy lives and promoting well-being for all at all ages. The reproductive health targets in this goal have important implications for women’s wellbeing which include;
  • 6. 5 decreasing the global maternal mortality ratio to less than 70 per 100,000 live births by 2030; reducing neonatal mortality to at least as low as 12 per 1,000 live births and under 5 mortality to at least as low as 25 per 1,000 live births. The key indicators for monitoring gender dimensions of health include: (i) Reproductive health (all aspects of maternal health): (ii) Sexual health indicator (use of contraceptives and adolescent fertility rates) (iii) Children health (morbidity, mortality, and nutrition (iv) Mortality and cases of death (life expectancy by age and sex) (v) HIV AIDS prevalence, coverage of antiretroviral therapy and knowledge of HIV/AIDS Reliable data on many of the above indicators are lacking. For instance, in many African countries, there is underreporting and misclassification of deaths, leading to unreliable estimates of maternal mortality, making it difficult to monitor changes over time and to assess differences between population groups (United Nations, 2010a). 2.3 Political voice, justice and governance Women are grossly under-represented in decision-making structures the world over and lack voice in policy formulation (WEF, 2015). This dimension of well-being is partially covered in SDG16 which focuses on promoting peaceful and inclusive societies for sustainable development, provision of access to justice for all and building effective accountable institutions at all levels. This SDG targets among others to ensure responsive, inclusive, participatory and representative decision-making at all levels. This dimension is also partially covered by SDG5 which aims at achieving gender equality and empowering all women and girls. This SDG assumes that representation in political and economic decision-making processes will fuel sustainable economies and benefit societies and humanity at large. The SDG has among other targets for reducing gender inequality, a target to ‘ensure women’s full and effective participation and equal opportunities for leadership at all levels of decision making in political, economic and public life’. The gender dimension indicators for measuring the political voice and governance include: legal protection, legal awareness and adjudication (UNDP 2004; Lopez- Claros and Zahidi, 2005).
  • 7. 6 This dimension of wellbeing can be measured through: (i) The number of female Ministers, (ii) Number of seats in parliament held by women, (iii) Number of women holding senior, legislative and managerial positions (iv) The number of years a female has been head of state (president or prime minister) National statistical offices in many developing countries however do not routinely produce data on positions of power and decision-making in politics and governance, making monitoring of this gender dimension of wellbeing difficult. 2.4 Work (personal activities) This dimension relates to SDG8 whose aim is to promote inclusive and sustainable economic growth, full and productive employment and decent work for all. One of the key targets of SDG8 is to achieve, by 2030, full and productive employment and decent work for all women and men, and equal pay for work of equal value. SDG5 also targets to provide women and girls equal access to decent work and equal rights to economic resources as their male counterparts. Lopez- Claros and Zahidi (2005) and Oxfam (2002), advance that work or personal activities can be measured using economic participation and access to economic opportunities. Indicators/measures of economic participation include: (i) Participation in private and public decision-making (ii) Access to and control over economic and natural resources, and basic social services (iii) Gender stereotypes and discriminatory attitudes (iv) Establishment, strengthening and collaboration of women’s organizations (v)Women empowerment, self-confidence, leadership skills, and capacity to organize Access to economic opportunities relates to the quality of women’s economic involvement This can be measured by the duration of maternity leave, percentage of wages paid during the covered period, number of women in managerial positions, availability of government provided childcare, impact of maternity laws on the hiring of women and wage inequalities between men and women in the private sector (Lopez-Claros and Zahidi 2005).
  • 8. 7 Measuring work and accounting for gender differences in work in developing countries is complicated due to data gaps. The international guidelines suggest that the mainstreaming of gender in labor statistics, definitions and measurement methods should cover and adequately describe all workers and work situations in sufficient detail to allow relevant gender comparisons to be made (International Labor Office, 2003). However, based on conventional labor statistics, the participation of women in work activities and their contribution to the economy tend to be underestimated (United Nations, 2001). 2.5 Material living standards The key indicator which measures the living standards of people in a society is poverty, conventionally measured using consumption and income levels. According to UNDP (2004), a decent standard of living is measured by women’s and men’s share of earned income. This gender dimension is related to SDG1 whose objective is to end poverty in all its forms everywhere. This SDG targets among others to eradicate extreme incomes poverty ($1.25) for all by 2030. Consumption expenditures are often used as proxies of material wellbeing due to difficulties of measuring incomes. The dimension also related to SDG10 which aims at reducing inequalities within and across countries, more so for vulnerable groups. Gender dimensions of material wellbeing can be assessed by profiling the following indicators by gender of household head: i). Headcount poverty index, ii). Poverty gap iii). Poverty gap squared iv). Inequality measures (such as Gini index ) v). Assets (both physical and financial) 2.6 Food security Food security is related to material wellbeing, but goes further to cover quality of wellbeing. SDG 2 sets to end hunger, achieve food security and improved nutrition and promote sustainable agriculture. Some of the key targets under this goal focus on improving the wellbeing of vulnerable women and children by providing sufficient and nutritious food. This SDG must
  • 9. 8 therefore ensure that all three dimensions of food security: food access, food availability and food utilization (FAO, 2006; WFP, 2009) are catered for. Gender dimensions of food security can be measured by: (i) Gender differences in levels of food consumption, (ii) Diversity of diets by gender of household head (iii) Differences in exposure to changes in food access by gender of household head (iv) Differences in feeding practices by sex of children Like other indicators, lack of consistent data to monitor this dimension abound. For instance, in Kenya, welfare monitoring and household budget surveys are the most comprehensive datasets on food consumption, yet, no specific attention is given to various aspects of food security. In addition, there is no national level panel data available to monitor consumption and food security over time. 2.7 Environment Environmental degradation, inadequate access to natural resources and natural disasters have different levels of impact on women’s and men’s livelihoods as well as time use and food security; with women in the developing countries being particularly vulnerable (United Nations, 2010b). Recognition that the MDGs failed to pay adequate attention to environment has ensured that this is given a lot of attention with several SDGs focusing on environment and natural resources. These include SDG6, (related to water and sanitation), SDG7 (energy), SDG11 (urban cities), SDG13 (climate change), SDG14 (resources under the water), and SDG15 (land resources). Gender dimension of environment can be measured through the involvement of women and men in the management of the environment. According to United Nations Environment Programme (2012), this indicator can be measured through: i) Representation of women and men in high-level decision-making related to environmental issues; ii) Enrollment in (and graduation from) environment, water, agriculture, forestry and energy fields of study;
  • 10. 9 iii) Involvement of women and men in sustainable consumption and environmentally- friendly behavior (e.g. saving water or saving energy), and; iv) Membership of men and women in local non-governmental organizations (NGOs) involved in environmental protection. Measurement of this dimension is a real challenge in African countries because such information is not readily available, especially at the national scale. 2.8 Insecurity/Gender based violence Physical and sexual violence against women is widespread, with prevalence levels varying considerably across countries (United Nations, 2010b). Psychological and economic violence are also not reported as often as physical and sexual violence, but affect the well-being of many women (WHO, 2005). Men’s vulnerability to domestic violence is more pronounced during childhood, adolescence and at older ages. Gender based violence dimension of wellbeing is related to SDG5, which targets, among others, to end all forms of discrimination and violence against women and girls and also to eliminate all harmful practices, such as child, early and forced marriage and female genital mutilation. Indicators of this dimension include number of cases of: (i) Harassment, physical assault and molestation by gender (ii) Domestic violence by gender (iii) Rape of adult women (iv) Rape of minors Measurement of gender violence is perhaps one of the most difficult of all dimensions due to lack of data and also because many cases, especially of domestic violence and report go unreported as victims fear the stigma that tend to come with exposure.
  • 11. 10 3.0 Data for measurement and monitoring gender dimensions of wellbeing in Kenya As alluded to in the previous section, there is a considerable amount of data for monitoring gender dimensions of wellbeing in Kenya. Such data is however often inconsistent in depth and spatial coverage, often has glaring gaps and, is in most cases is highly aggregated. The data available is also mostly cross sectional, which makes it rather difficult to measure and monitor wellbeing over time. Appendix table 1 presents a comprehensive analysis of the data available by dimension and source, the period over which data is available, and the shortcoming. 4.0 Conclusion Achievement of the SDGs discussed in this paper would go a long way in improving the plight of vulnerable women and children. An analysis of the availability of data for monitoring the eight gender dimensions of wellbeing in Kenya show that data is generally inadequate. Even for education where relatively good data is available, disaggregated panel data is not available. Accurate measurement and monitoring of SDGs however require good data and regular reporting. Poor data and data gaps require much greater investments in building independent, impartial national statistical capacities and strengthening of statistical quality and standards (UNDP, 2004). The new expanded set of SDGs and targets cover a wide range of topics for which current, detailed, and reliable data does not exist. Additionally, the existing traditional data collection and integration methods may be technically difficult or very outdated to implement and monitor some of the new set of targets, necessitating the development of new indicators. Kenya is one such case, where data is in many respects inadequate to measure and monitor SDGs. The is therefore need for capacity building and funding support to national governments in developing countries in order to consolidate database (including gender-responsive database) to facilitate better implementation of the SDGs targets. Additionally, increased attention should be given to the development of harmonized sets of indicators appropriate at the nation, regional and international level. Such indicators should also be easily disaggregated at sub-national levels. Attention should also be given to measurement methodologies to ensure that gender dimensions
  • 12. 11 such as time use, the informal sector and unpaid work, as well as other difficult to measure multidimensional issues such as advocacy and sexuality are adequately captured. There is also need to move beyond sex disaggregation of the data to further examine the gender dimensions of ethnicity, disability status, place of residence, religion and age in order to have a wider and better understanding of the gender dimensions of wellbeing.
  • 13. 12 5. References Barker, G., Nascimento, M., Segundo, M. and Pulerwitz, J., 2004. ‘How Do We Know if Men have Changed? Promoting and Measuring Attitude Change with Young Men: Lessons from Program H in Latin America’, in Ruxton, S. (ed.) Gender Equality and Men: Learning from Practice, Oxford: Oxfam Food and Agriculture Organization of the United Nations, 2006. Food security: policy brief No. 2. Rome. Grown, C., Rao Gupta, G. and Khan, Z., 2003. ‘Promises to keep: achieving gender equality and the empowerment of women’, background paper for the UN Millennium Project Task Force on Education and Gender Equality, Washington, DC: ICRW. Loewe, M., 2015. Post 2015: How to Reconcile the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs)? Briefing Paper 18/2012 Summary. http//:post2015.files.wordpress.com/2013/01/loewe-2012. Accessed 29th October 2015. Lopez-Claros, A. and Zahidi, S., 2005. Women’s Empowerment: Measuring the Global Gender Gap. World Economic Forum. Geneva, Switzerland. Moser, C. and Moser, A., 2005. ‘Gender Mainstreaming since Beijing: a Review of Successes and Limitations in International Institutions’, in Porter, F. and Sweetman, C. (eds) Mainstreaming Gender in Development: a Critical Review, Oxford: Oxfam. Ocampo, J. A., 2014. A Post-2015. Monitoring and Accountability Framework. Paper prepared for the UN Department of Economic and Social Affairs. OECD, 2013. Beyond the Millennium Development Goals: Towards an OECD contribution to the post-2015 agenda”, OECD and Post- 2015 Reflections series, OECD, Paris. Oxfam, 2002. Gender Mainstreaming Tools: Questions and Checklists to Use across the Programme Management Cycle, Version 1, November 2002, Oxfam. The Rio+20, Earth Summit, 2012. United Nations Conference on Sustainable Development (UNCSD). http://www.uncsd2012.org/. Accessed 20th October 2015. UNESCO Institute for Statistics, 2011. Global Education Digest 2011: Comparing Education Statistics Across the World – Focus on Secondary Education, Montreal.
  • 14. 13 Sustainable Development Solutions Network (SDSN), 2015. Indicators and a Monitoring Framework for the SDGs, Draft Report. Paris, France and New York, USA: SDSN. UNDP (United Nations Development Programme), 2006. Measuring Democratic Governance: a Framework for Selecting Pro-Poor and Gender-Sensitive Indicators, New York: http://www.undp.org/oslocentre/docs06/Framework%20paper%20-%20entire%20paper.pdf. Accessed, 30th October 2015 United Nations Development Programme (UNDP), 2004. ‘Note on statistics in the Human Development Report’, in Human Development Report 2004: Cultural Liberty in Today’s Diverse World, 251–85, New York: UNDP. United Nations Development Fund for Women (UNIFEM), 2005. Untitled. http://siteresources.worldbank.org/INTGENDER/Resources/UNIFEM.doc. Accessed, 15th October 2015. United Nations, 2010a. The World’s Women 2010: Trends and Statistics. Series K, No. 19. Sales No. E.10.XVII.11. United Nations, 2010b. Economic Commission for Europe and World Bank Institute. Developing gender statistics: a practical tool. Geneva. ECE/CES/8. World Economic Forum (WEF), 2015. World Economic Forum Annual Meeting 2015. Davos- Klosters, Switzerland 21 - 24 January 2015. World Food Programme (WFP), 2009. Comprehensive Food Security and Vulnerability Analysis: Guidelines, 1st ed. Rome. WHO (2005). WHO multi-country study on women’s health and domestic violence against women: summary report of initial results on prevalence, health outcomes and women’s responses. Geneva, World Health Organization, 2005. http://www.who.int/. Accessed 35th October 2015. World Bank, 2011. World Development Report 2012: Gender Equality and Development. Washington, D.C.
  • 15. 14 Table 1: Data for Measuring and Monitoring Gender dimensions of wellbeing in Kenya Dimension of wellbeing Indicator Surveys available Period data available Assessment Education Literacy Enrollment Attainment levels Kenya Demographic and Health Survey (KDHS) 1988/1989; 1993; 1998 2003; 2008/2009; 2014 Data from 2003 and later are nationally representative. Data before 2003 exclude North Eastern region and several northern districts in the Eastern and Rift Valley regions. Population and housing census 2009; 1999; 1989; 1979; 1969 Census is done after every 10 years. This data is periodic thus difficult to use to monitor progress in SDGs Kenya Integrated Household Budget Survey (KIHBS) Welfare Monitoring Surveys 2005/6 1992, 1994, 1997 Second largest survey dataset after the census with comprehensive data on education. No time series for monitoring individuals/households Kenya National Bureau of Statistics (KNBS)-Statistical Abstract 2007-2012 Data not disaggregated by gender (but secondary enrollment, data is by gender for the years 2009-2012) Ministry of Education and other relevant institutions Various Data not readily available to users. African Development Indicators Various Data too aggregated World Bank- World development indicators 1960-2015 The data is disaggregated by gender for all the education indicators. It is reliable, but may not give a complete picture of the spatial dimension within a country.
  • 16. 15 Work Economic participation Kenya National Bureau of Statistics (KNBS-sectoral statistics)/ Ministry of Labor, Social Society and Services. Integrated labour force survey International Labor Organization Population and housing census 2008-2012 1998/1999 2005/6 1986-2015 2009 Data too aggregated and not always comprehensive 2005/6 was part of labor module in KIBHS and thus not comprehensive Data not always comprehensive of SDGs. Data is disaggregated by gender but excludes labor from home makers, other unpaid caregivers and some workers in informal sector, which are sectors dominated by women Employment/econo mic opportunities Kenya National Bureau of Statistics (Sectoral statistics) Population and housing census 2008-2012 2009 Data too aggregated Only latest census had labour force module. Future censuses should include the same to facilitate monitoring of SDGs. Health Sexual & reproductive health Maternal mortality Child nutrition HIV AIDS Kenya Demographic and Health Survey (KDHS) 1988/1989; 1993; 1998 2003; 2008/2009; 2014 The data is not consistent over the years. Moreover, the data is aggregated. Multiple Indicator Cluster Survey (MICS) - United Nations International Children's Emergency Fund (UNICEF) 1996-2015 UNICEF has conducted four rounds of MICS 1995-1996, 2000-2001, 2005-2006, 2009-2012 and a fifth is now under way (2013-2015). Some of the data is disaggregated by gender and age.
  • 17. 16 World Health Organization (WHO)-- Global Health Observatory (GHO) data 2002-2015 Good data, disaggregated by gender, but not always available at the local scale National Aids control Council (NACC) Varied Disaggregated by gender, but periodic surveys. Need for time series data Material Living standards Income and consumption Kenya Integrated Household Budget Survey (KIHBS) Welfare Monitoring Surveys 2005/6 1992, 1994, 1997 Not very good data, though has improved over WMS. 2015/16 survey is ongoing. No panel data available for monitoring material living standards. The World Bank- World development indicators 1990-2014 This is data on mean consumption and income, often based on the WMS and KIHBS data. Political voice, justice and governance Candidates in elections by male and females World Governance indicators 1996-2014 This data is aggregated Electoral Commission of Kenya (data on voter registration and turnout). Varied This data is not always gender disaggregated. Data not publicly available Gender based violence Victims of violence against women Kenya Demographic and Health Survey (KDHS ) 1988/1989; 1993; 1998 2003; 2008/2009; 2014 Data prior to 2003 not nationally representative. KNBS - Justice and crime statistics. Administrative police and court records Health administrative records. The Ministry of Gender, Sports, Culture and Social Services Varied This data is periodic and aggregated thus not reliable for monitoring SDGs
  • 18. 17 Food security Food access Kenya Integrated Household Budget Survey (KIHBS) Welfare Monitoring Surveys 2005/6 1993, 1994, 1997 Not very good data, though has improved over time. Best available for monitoring food access. Yet, no panel data available for monitoring material living standards Food utilization- consumption, nutritional status Kenya Integrated Household Budget Survey (KIHBS) Kenya Demographic and Health Survey (KDHS) 2005/6 1988/1989; 1993; 1998 2003; 2008/2009; 2014 No panel data available Environment Enrollment in environment- related fields of study. Gender representation in environmental managerial positions School administrative records The National Environment Management Authority (NEMA) Ministry of Environment and natural resource Varied Varied This data is scanty and not readily available