united nations economic and social council disaggregated data from existing sources. this may...

Report of the workshop on

Sex-Disaggregated data for the SDG indicators in Asia and

the Pacific: What and How?

25-27 May 2016, Bangkok, Thailand

I. Background

1. Corresponding to the strong focus of the 2030 Agenda on promoting

gender equality and women’s empowerment, the implementation of the global monitoring framework is to be guided by the overarching principle that “SDG indicators should be disaggregated, where relevant, by income, sex, age, race, ethnicity, migratory status, disability and geographic location, or other characteristics”.1 The framework requires sex-disaggregation for a number of

the indicators, with Goal 5 focusing specifically on its achievement and gender-related indicators.

2. The regional workshop, “Sex-Disaggregated data for the SDG

indicators in Asia and the Pacific: What and How?”, took stock of and made recommendations on ways to improve data production and dissemination to

provide the information needed to achieve the SDG aim to “leave no one behind” in Asia and the Pacific, with focus on the promotion of gender equality and women’s empowerment (refer to Annex I for the Workshop Programme).

3. The workshop was organized by ESCAP in collaboration with partner United Nations agencies including the regional offices of FAO, ILO, UNDP,

UNEP, UNESCO, UNICEF, UNFPA, WHO and UN Women. The workshop brought together experts in policy issues regarding gender and statistics

development from governments of 15 countries, representatives from research institutes and international development agencies (See Annex II for the list of participants).

II. Main outcomes of the workshop

4. The workshop discussions resulted in eight recommendations that address six key issues regarding the strengthening of national capacity to produce and disseminate sex-disaggregated and gender-responsive statistics in support of the implementation of Agenda 2030. Section III of this report

provides the rationale behind the recommendations.

Reviewing legal and policy frameworks to identify information needs for

addressing the “leave no one behind” focus

5. Recommendation 1: Governments should review national legal and policy frameworks in light of national and international development priorities

(including SDG framework) to identify population groups for targeted

1 United Nations Statistical Commission. 19 February 2016. Report of the Inter-Agency and Expert Group on

Sustainable Development Goal Indicators: Note by the Secretary General (E/CN.3/2016/2/Rev.1*). Discussed at the

forty-seventh session of the United Nations Statistics Commission held in New York from 8-11 March 2016.

United Nations

Economic and Social Council

E/ESCAP/CST(3)/1

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intervention and their issues, and incorporate them in relevant monitoring frameworks which are to serve as the basis for establishing requirements for sex-disaggregated and gender-responsive statistics. This work should be led by SDG units within national planning offices and line ministries, and other

national policy bodies and involve the national women's machineries.

Communicating information needs to relevant statistical producers

6. Recommendation 2: National policy bodies, including the national

women’s machineries, and producers of relevant statistics, should use and enhance existing mechanisms to regularly communicate and discuss their needs

in order to establish a common understanding of policy priorities that are translated into data requirements.

Supporting the production and dissemination of required sex-

disaggregated and relevant statistics

7. Recommendation 3: The national statistical system should build capacity

to maximize the use of existing data and resources and make available sufficiently disaggregated statistics that are required to monitor the SDGs and other national development priorities.

8. Recommendation 4: Where needs cannot be met through existing data collection programs, national statistical systems, with support from

international development partners, should work with national policy bodies and civil society to gain the political, institutional and financial support needed to produce and disseminate the required sex-disaggregated and gender-

responsive statistics.

Developing new approaches to meet data needs

9. Recommendation 5: National statistical systems, with support from international development partners, should explore the use of new methods for

producing disaggregated data from existing sources. This may include developing regional or global guidance on data linking, collecting good and poor practices on integrating a human rights perspective in data production processes, and mainstreaming gender in future rounds of data collection across all subject areas.

Increasing the use of data in policy processes

10. Recommendation 6: Narrow the gap between data availability and use by developing capacity to analyse and disseminate statistics, to explain the

stories behind the numbers and to increase data literacy to correctly interpret the information.

Ensuring sustainability to produce and disseminate quality sex-

disaggretated and gender-responsive statistics

11. Recommendation 7: Establish statistical mandates and processes to

sustain production and dissemination of required disaggregated and gender-responsive statistics.

12. Recommendation 8: Development partners are encouraged to support national efforts to improve the production and dissemination of gender-responsive statistics, including disaggregation by sex and other characteristics

in alignment with national strategies for statistical development.

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III. Summary of discussions

A. Reviewing legal and policy frameworks to identify information

needs for addressing the “leave no one behind” focus

13. Workshop participants were informed that sex-disaggregation of data

featured throughout the global monitoring framework, aside from the indicators under Goal 5 which focused specifically on gender equality and women’s

empowerment. Some SDG indicators explicitly mention required disaggregation (for example indicator 5.4.1: “Proportion of time spent on unpaid domestic and care work, by sex, age and location”), although the implementation of the entire monitoring framework was to be guided by the overarching principle that “SDG indicators should be disaggregated, where

relevant, by income, sex, age, race, ethnicity, migratory status, disability and geographic location, or other characteristics…”.

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14. The workshop discussions highlighted that sex-disaggregated data,

where relevant, was a pre-requisite for producing gender statistics and gender analysis. Sex-disaggregation alone, however, is insufficient. In sharing national practices to address gender-related inequalities in economic participation and other areas under scrutiny, and discussing required data disaggregation in view of the above-referred intersections, the workshop participants suggested

additional characteristics by which data should be disaggregated for gender analysis. Such population characteristics included the education level of

individuals, their marital status, age, sex of the household head, and household composition including number and age of children, which are key to understanding gender relations and domestic care. Much of this information is included in current data collections, such as population and housing census and sample surveys of households and individuals. On the other hand, key

information on some of the population groups, such as migrants, foreign workers and refugees, is typically not collected and disseminated through

regular statistical surveys, although issues regarding these population groups are becoming quite important in national and international policy dialogues.

15. The challenge of producing useful sex-disaggregation of household survey data based on sex of the household head was discussed. Depending on how this concept is defined, disaggregation may provide no useful insight into

the distribution of resources within and between households. Combining the sex of the household head with other characteristics, such as marital status and household composition can provide more useful data for gender analysis.

Specifically, the fact that the head of the household is a woman can be due to several reasons, including husbands having migrated for work, household head being a single parent or a widow, etc. Therefore, having a woman as the head of household generally would have major policy implications for gender equality and women’s empowerment.

16. In discussing sex-related disaggregation of data, the workshop participants highlighted the importance of addressing the intersection of gender

issues and the other population characteristics associated with disadvantage in economic, social and environmental development, including those highlighted in the overarching principle of data disaggregation of the global monitoring framework. To achieve this, disaggregation may be required by multiple variables simultaneously or nested disaggregation, e.g. sex by age by location,

2 United Nations Statistical Commission. 19 February 2016. Report of the Inter-Agency and Expert Group on

Sustainable Development Goal Indicators: Note by the Secretary General (E/CN.3/2016/2/Rev.1*). Discussed at the

forty-seventh session of the United Nations Statistics Commission held in New York from 8-11 March 2016.

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in order to reach the level of detail needed to accurately identify the vulnerable population subgroups and design appropriate policy responses.

17. The workshop discussions suggested that depending upon the specific policy issues and the corresponding indicator, the priorities for disaggregation

may vary. For instance, for indicators relating to economic participation and poverty, income, migrant status, and family situation (e.g. number of children, marital status) are important for monitoring gender disparities, and surveys

should include not only those in private households, but also in communal housing. Concerning health-related indicators, sex, geographical location (rural/urban), ethnicity or race and social conditions are in general crucial variables to reach the vulnerable groups in the region. A substantial amount of research had also identified linkages between education and the health

outcomes. For instance, child mortality between 1 to 5 years old is very much related to mother’s education. One of the important issues raised concerned the

measurement of inter-linkages such as determining and contributing factors to health outcomes from a gender perspective, e.g. links between gender-based violence and poor outcome in pregnancy, child marriage and poor sexual and

reproductive health outcomes. Identifying the key determinants of health outcomes, including population characteristics for data disaggregation,

remained a challenge which should involve all stakeholders including health experts, education experts, statisticians, possibly national budget officials and representatives from health ministries. The discussions highlighted challenges

in data disaggregation for some indicators, such as maternal mortality and mortality due to non-communicable diseases, or NCD, where the sample size

was usually too small to provide accurate estimates when the data came from sample surveys. On the other hand, censuses are not frequently conducted and

the administrative data often is of not acceptable quality, partially due to cultural factors. In Vietnam, for instance, deaths mostly occur at home where cause of death is not identified and coded in civil registration records.

18. Workshop participants agreed that the exact requirements for data disaggregation, including the structure of the nested disaggregation, would likely vary by countries as well as development areas. As such, national policy frameworks should be the basis for establishing required data disaggregation to identify the population subgroups that need particular attention in economic,

social and environmental development. Such policy frameworks include relevant legislation, national development plans, gender equality strategies, as

well as sectoral policies and plans. Workshop participants reiterated that clear specification of goals and targets to address disadvantaged population groups in national policy frameworks would generate the demand for appropriate

statistics, including those disaggregated by sex and other relevant characteristics, to monitor progress and assess impacts of policies.

19. Clear stipulations in development policy frameworks on what population groups to target for interventions and what exactly the issues are for these population groups determine the information needs for national policy-

making and implementation and are the basis for mandates for national statistical systems. They are also a pre-requisite for budgetary allocations for

statistical work and for investing in national statistical capacity to collect and disseminate the required data. Workshop participants heard the example regarding disability statistics, where important statistical data were yet to be

regular national statistical collection and dissemination, due to lack of clear policy demands. Another example was time use statistics. High quality time use

statistics is crucial to understanding the unequal distribution of responsibilities of household work and domestic care between men and women, and thus the

contribution of women to the economy and society. Time poverty affecting

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women usually results in human capital depletion and poorer chances A good understanding of such issues is indispensable for designing policies and

programmes to promote gender equality by removing restrictions on the engagement and performance of women in the labour market, including

limitations related to social norms that affect women’s human capital formation, mobility, and time management between unpaid household and care work and paid employment activities. However, most countries in the region do not

regularly collect time use statistics even though a significant progress has been achieved in the methodology to measure unpaid work through time use surveys.

Some of the challenges include lack of expertise in time-use survey at the national level as well as limited funds and perhaps limited political will/lack of prioritization of the unpaid work issue. These examples illustrate the importance of reviewing national policies to identify and specify target population groups and issues for intervention, which would in turn become the

mandate the collection and use of disaggregated statistics on those groups to promote gender equality.

20. Recognizing specific population groups as well as their issues in national policies and programmes and related monitoring frameworks is also essential for existing data used. Workshop participants heard of examples where

national data collection often included various key population characteristics, but such information was not made available when data were disseminated due

to lack of demand.

21. Clear stipulation in national policies and programmes of goals and targets on gender equality should take into consideration cultural and religious

norms which may create hurdles for data collection. The workshop participants heard of an example where collecting of data on abortion was difficult since

people generally avoided talking about abortion, despite two official provisions on abortion to save life of the mother.

22. The workshop concluded that national development policies should provide directions on the possible types of data and disaggregations that are required to monitor the achievement of policy goals and targets, identify

priority population groups and understand issues. It is recommended countries conduct a review of national development plans, gender equality laws, and gender-related goals in sectoral policies to identify target populations and data

needs for achieving gender-related goals (e.g. time use; violence against women). Such reviews should be guided by existing government commitments,

such as the goals and targets of the 2030 Agenda as well as the relevant international conventions, especially those regarding human rights. The main actors driving this process should be the relevant line ministries and agencies

with the national planning office, or whichever agency responsible for SDG implementation, taking the lead.

23. National policy priorities and local context determine data disaggregation requirements and needs may vary within and between countries. As the framework is implemented and localized, the issue of minimum data disaggregation will be reviewed. Discussion during the workshop highlighted the necessity of taking gender into consideration even within goals and targets

that do not directly address gender, such as those on climate change and the environment.

24. Consideration should also be given to whether legislation determines any characteristics be excluded from official statistics (e.g. ethnicity). Furthermore, any evidence to suggest that particular variables or characteristics are strong predictors of social inclusion should be used to guide decisions on data disaggregation requirements (for example, statistical modelling has been

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used in some countries to determine that household income was the main variable influencing access to water and sanitation).

Recommendation 1: Governments should review national legal and

policy frameworks in light of national and international development

priorities (including SDG framework) to identify population groups for

targeted intervention and their issues, and incorporate them in relevant

monitoring frameworks which are to serve as the basis for establishing

requirements for sex-disaggregated and gender-responsive statistics.

This work should be led by SDG units within national planning offices

and line ministries, and other national policy bodies and involve the

national women's machineries.

B. Communicating information needs to relevant statistical producers

25. Workshop participants agreed that once data needs regarding national policies to promote gender equality are identified and agreed, they must be

prioritized and communicated to the national statistical system, which can then translate them into measurement concepts and determine to what extent it can

meet those needs with the data it currently collects. Underpinning this is the ability of data users and producers to work closely together and to find a common language for discussion. Meeting data needs involves producers

understanding sectoral and cross-cutting development issues and anticipating how official statistics can help to inform those issues. Similarly users need to

broadly understand statistical production, the limitations of different data sources, and how to correctly interpret and use the information.

26. In discussing examples of intersections of multiple population characteristics and factors driving gender disparities in such areas as unpaid work, educational attainment, health outcomes, etc., workshop participants highlighted the often iterative and complex process of identifying data needs. This is especially the case given the inter-linkages of multiple contributing

factors for development outcomes in such areas as health. Setting policy goals and targets about reducing deprivation and vulnerabilities generally requires understanding who the disadvantaged population groups are, their current status

vis-à-vis national goals and targets, as well as barriers to progress towards the goals for these groups. Existing information, both statistical and qualitative, should be used to inform the setting of the goals and targets to address the leave-no-one-behind issue in national policies. In reference to the goals and targets of policies and programmes to promote gender equality and women’s

empowerment, rigorous analysis of existing information, identifying where the gaps are, and recommending efficient ways of collecting data to fill these gaps

require collaboration between statisticians and policy analysts, including those from the research community.

27. The workshop noted that data disaggregation is only one important way to inform policies and programmes to address inequality. Researchers should have access to a wide range of microdata that national statistical systems collect

in order to understand the drivers of inequalities related to gender and other population characteristics and inform policy debates.

28. Participants identified existing methods for communicating and

understanding data needs, such as consultative meetings with the statistical office, inter-agency coordination groups, data user forums and stakeholder forums. It was highlighted that getting the right people and a diversity of representation on these groups can be problematic. Existing mechanisms should

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be enhanced to support greater collaboration and understanding between data producers and users. For example, inviting statistical experts to contribute to

policy design and implementation processes can allow data needs and issues to be taken into consideration early so they are more likely to be met. National

SDG monitoring is an opportunity to increase the availability and appropriate use of official statistics. While the global SDG indicators have been formulated, they still have to develop further in the national context. As this process moves

forward, communication between producers and users should remain a top priority.

29. In fact, the ability for data users and producers to communicate effectively and work together underlies all stages of identifying required data disaggregation and ultimately making that available for use. Policymakers may

not know what ‘data’ they want, but instead think in terms of issues and vulnerable groups they want to target and therefore need information about.

Continuous consultation should be planned by both parties to understand each other and work out the appropriate language for clear communication. The

national statistical system led by the national statistical office should be proactive in seeking to identify and understand these policy priorities and subsequent data needs. Civil society and other organizations working at grass

roots level should play a key role in this.

Recommendation 2: National policy bodies, including the national

women’s machineries, and producers of gender-related statistics, should

use and enhance existing mechanisms to regularly communicate and

discuss their needs in order to establish a common understanding of

policy priorities that are translated into data needs.

C. Supporting the production and dissemination of required sex-disaggregated and gender-responsive statistics

30. Workshop participants suggested that the national statistical system, under the leadership of the national statistical office or other appropriate

authority, should determine the feasibility of producing required data disaggregations by assessing existing and regularly collected data. The extent to which data disaggregation requirements can be met depends on a number of factors. Firstly, the information has to be collected and in such a way that makes it possible to disaggregate to the level required. Each of the three sources

of official statistics have strengths and limitations in this regard:

a) Census data can be disaggregated to small groups and areas, the

main limitations being that censuses use limited questions to collect data for relatively few variables, as well as the need to protect confidentiality of individuals and small populations when disaggregating data.

b) Sample survey data usually collect the wide range of variables in

the way needed for monitoring gender-related goals, but such surveys are typically designed to produce aggregate figures and the possibilities for multivariate disaggregation are limited. For

example, the ability to disaggregate statistics on violence against women by vulnerable groups is limited: disability is not usually

measured, small sample size limits disaggregation possibilities, and some measures, such as current prevalence rate of sexual violence are so small that it cannot be disaggregated.

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c) Administrative data sources, like censuses, are usually complete records that are therefore suited to disaggregation. However, as a by-product of administrative processes, the variables needed for disaggregation may not be collected and/or data may not be

complete or of sufficient quality to disaggregate accurately.

31. Gender mainstreaming across all areas of official statistics must be a

priority in order to produce the type of disaggregated data that is needed to monitor gender-related SDGs and other goals. Existing methods of data

collection and monitoring must change to include sex disaggregation, and countries must be encouraged to develop initiatives to collect new forms of disaggregated data. Options include expanding data collection to include

disability and migratory status, for example, and reviewing measures of concepts such as income poverty which at present captures the situation at

household level and does not enlighten policymakers on unequal intra-household distribution. Additional challenges include how to capture other dimensions of poverty, beyond income, including, for instance, empowerment. Another aspect of gender mainstreaming in statistical production is removing bias by taking gender into consideration at each stage of the production process,

including the design, collection, analysis and dissemination of data. Countries should draw on the existing resources and mechanisms to strengthen gender statistics that have been developed at regional and global levels. Civil society

organizations should be brought in as partners in data collection on gender-related issues, for example, in training of enumerators to be gender-sensitive. These organizations are most familiar with the issues facing women and men, and are able to assist data producers in removing gender bias from the data

production process.

32. The challenges hindering statistics production, such as limited financial resources, lack of support for gender statistics, limitations in national statistical

capacity, lack of internationally agreed methodologies, insufficient attention to the sensitivity of data, and inadequate collection of data from hard-to-reach

populations, should be identified and documented. The gaps between what is required and what is feasible should be explained to data users and stakeholders, including estimated costs for producing currently unavailable data so that

decisions can be made to fund new collections where appropriate. Many ministries have statistical departments that play a role in producing official

statistics and are part of the national statistical system. These units should be adequately resourced and their role as a part of the national statistical system should be taken into account in strategic processes such as the national strategy for the development of statistics (NSDS). Linking statistical collection and dissemination to the monitoring of national development frameworks, including

sectoral development goals and targets, is essential for political and budgetary support for statistical work (see Recommendation 1).

33. Even if feasible, appropriately disaggregated data still needs to be made

available for use and in a form that is easy to understand and interpret. The capacity to make data available is shaped by knowing and understanding user requirements, as well as having the resources and ability to disseminate and communicate those data in a suitable way. Statistical systems should be proactive in order to meet data disaggregation needs for monitoring SDGs. For

example, some statistical systems provide data upon request rather than making it publically available to all known and potential users. This limits data

availability to those that request it, often those that know the data exists, who to ask and how to formulate the request.

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34. Participants emphasised the need to increase accessibility to data by enacting laws or policies that require disaggregated data to be disseminated,

increasing online dissemination, establishing central databases, and using tools such as REDATAM to disseminate microdata. It was noted that information

and communication technology infrastructure is weak in some countries, limiting the possibilities with online dissemination. The importance of metadata and providing information relevant to the correct interpretation of disaggregated

data, such as confidence intervals, sampling and non-sampling errors, was also highlighted in the discussions.

35. The comprehensive nature of the SDG framework will make it a challenge for the national statistical system to meet data needs. Coupled with existing reporting processes for international conventions and instruments, the

demands on national statistical offices are already high and likely to increase. To minimise this burden, monitoring of the SDGs should be aligned with other

national, regional and international reporting mechanisms. Awareness by the political leadership of the importance of national monitoring underpinning by

reliable, timely and disaggregated data is critical for political, administrative and financial support to statistics and efforts to improve quality and availability of disaggregated data. Participants suggested that high level representatives

from the United Nations system can assist in convincing decision makers to support this process, particularly if changes to laws are required to be able to

produce required statistics. Technical assistance, capacity building and financial support are also needed at national level.

Recommendation 3: The national statistical system should build capacity

to maximize the use of existing data and resources and make available

sufficiently disaggregated statistics that are required to monitor the

SDGs and other national development priorities.

Recommendation 4: Where needs cannot be met through existing data

collection programs, national statistical systems, with support from

international development partners, should work with national policy

bodies and civil society to gain the political, institutional and financial

support needed to produce and disseminate the required sex-

disaggregated and gender responsive statistics.

D. Developing new approaches to meet data needs

36. The workshop participants were informed that more than half of the global SDG indicators are those for which many countries currently do not

produce data (Tier 2 indicators) or internationally definitions and measurement standards are yet to be established (Tier 3 indicators). Give the above, it will not be possible to produce all the indicators with current collection methodologies.

Techniques on combining data from different sources are potential cost-effective solutions to meet growing needs and produce required disaggregations.

The examples of using small area estimation techniques presented by Thailand, Philippines and Nepal show promise for being able to do more with existing data sets. Statistics New Zealand’s Integrated Data Infrastructure brings

together data on tax, employment and crime and other information from government agencies providing such services as in health, education and

welfare, as well as survey data from Statistics New Zealand. Through integration of information from different sources, it becomes possible to examine underlying relationships between various cross-sections of society,

thus improving the knowledge and understanding about a particular subject. It offers a less time consuming and less costly alternative than other investigative

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methods such as surveys. It also reduces respondent burden by making more effective use of existing data sources.

37. In discussing country practices on combining data from different sources, participants raised a number of questions and issues, seeking guidance on how

these techniques can be implemented, how to protect confidentiality, what steps countries at earlier stages of development can take to prepare for achieving data linking in the future and to learn from the experiences of those more progressed

in this area. It was suggested that the United Nations system produce a manual on data linking if such technical resources do not already exist. The discussions also highlighted the importance of having high-level champions for initiatives on data linkages.

38. The workshop participants were informed of the human rights-based

approach to data disaggregation and collection by population groups, where such principles of participation (active and meaningful participation in data

collection by marginalized groups), self-identification (doing no harm (self-identification), freedom to seek, receive and impart information), privacy, accountability should be observed. The workshop agreed that the human rights-based approach to data provides an important framework for reconsidering data production processes from a human rights perspective.. It was suggested to

collect good practices to illustrate this framework, as well as collecting poor practices to show what to avoid.

39. The workshop emphasized that existing sources should be maximised

for producing gender-related statistics. For example, the upcoming round of agricultural censuses is commencing and this should be a source of sex-

disaggregated data. A challenge faced in this data collection procedure is defining ownership and capturing the types of land tenure, and in particular,

aligning definitions used in the census versus the land title offices (e.g. agriculture census uses the main decision maker of the land rather than title owner). The difficulties of capturing information on ethnic minorities and

customary rights to land were also mentioned.

Recommendation 5: National statistical systems, with support from

international development partners, should explore the use of new

methods for producing disaggregated data from existing sources. This

may include developing regional or global guidance on data linking,

collecting good and poor practices on integrating a human rights

perspective in data production processes, and mainstreaming gender in

future rounds of data collection across all subject areas.

E. Increasing the use of data in policy processes

40. The workshop participants pointed out that producing data and making it

available do not necessarily ensure the data reach those who need it and are actually used. While gaps in data exist, workshop participants noted that there

are large amounts of data collected by the national statistical system that do not get used. This may be a reflection of the lack of demands from the policy

community, as well as clear communication from the policy community to the statistical community. Hence the importance of updating or revising policies to include plans for monitoring goals and targets as recommended above.

Insufficient use of existing data in many cases results from limited access to such data. Since statistical surveys and administrative data are collected with

public funds, they are public goods and government agencies have a responsibility to make them available for other government agencies,

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businesses, civil society organizations, the academia, the media, etc. Limited use of existing data may also be a reflection of limited capacity to analyse,

disseminate and interpret statistics, and to make them available in a form in which it can be readily applied to the policy process. In this case, efforts to

strengthen the capacity of both data producers and users will take to take place.

41. Participants highlighted the importance of providing contextual and qualitative information in order to correctly interpret data and find the ‘story

behind the numbers’. Qualitative and quantitative indicators are interconnected because they reveal the realities of inequalities. For example, when it comes to

understanding land rights, indicators should examine documented ownership, reported ownership, and rights over land and land use. In this vein, indicators must be qualitative and responsive to the nuances of how land tenure manifests

under various contexts, in addition to accounting for different types of ‘ownership.’ Both qualitative and quantitative measures are necessary to

capture the present inequalities and also help prioritize policy reforms.

42. Efforts to strengthen statistical capacity should focus on addressing the

gap between data availability and use. This includes developing statistical skills in policy areas, increasing statistical literacy of development practitioners, and investing more in data dissemination and communication. SDG implementation

is an opportunity to identify best practices in this area and direct resources towards practical and sustainable solutions to these issues.

Recommendation 6: Narrow the gap between data availability and use

by developing capacity to analyze and disseminate statistics, to explain

the stories behind the numbers and to increase data literacy to correctly

interpret the information.

F. Ensuring sustainability of produce and disseminate quality sex-

disaggretated and gender-responsive statistics

43. Efforts to identify, produce and use appropriately disaggregated

statistics for gender-related SDGs should be aligned with other work on SDG indicators, as well as to the national strategy for the development of statistics.

Policy priorities and the resulting data needs should be embedded in national statistical strategies as the basis for statistical production. The specific disaggregations should be reflected in the statistical work programmes of the

government, i.e. the work programmes of national statistical offices as well as statistical units within line ministries.

44. Mechanisms for coordinating and streamlining the monitoring of national and internationally agreed development goals and targets should be established and reflected in ongoing statistical mandates. This is essential for

achieving SDG targets 17.8 and 17.9 on the sustainability of data, monitoring and accountability. To do this, national statistical systems should review and

revise statistical master plans, data collection and data dissemination plans to ensure that policy priorities are captured. Coordinators of statistical systems should advocate to policy and decision-makers to institutionalize the production

and use of disaggregated data.

Recommendation 7: Establish statistical mandates and processes to

sustain production and dissemination of desirable disaggregated and

gender-response statistics.

Recommendation 8: Development partners are encouraged to support

national efforts to improve the production and dissemination of gender-

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responsive statistics, including disaggregation by sex and other

characteristics in alignment with national strategies for statistical

development.

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Annex I: The workshop programme

Sex-disaggregated data for the SDG indicators in Asia and the Pacific: What

and how?

25-27 May 2016, UNCC, Bangkok, Thailand

PROGRAMME

25 May (Day 1)

Session 1 Setting the scene

Objective: All participants share understanding of the objectives of the workshop, as well as priority policy and

statistical issues regarding promoting gender equality in SDG implementation in the region

08:00-09:00 Registration

Chair

09:00-10:15 a) Welcome and putting it in the context -- Achieving gender equality in

Asia and the Pacific through SDG implementation: Development

trends and data issues

• Yanhong Zhang (ESCAP)

b) Objectives & expected outcomes of the workshop, and structure to

achieve them

• Arman Bidar Bakhtnia (ESCAP)

c) Participants share their expectations and plans of contribution

• Janneke Kukler (UN Women)

d) Data disaggregation for global SDG indicators: overarching principles

• Papa Seck (UN Women)

Janneke

Kukler

(UN Women)

10:15-10:30 Group photo and networking

Session 2 Diving into priority goal areas

Objective:

A series of sessions, each focusing on an area of SDGs and addressing the following issues

• What types of sex-disaggregation (in combination with other population characteristics) are required to

address policy priorities specific SDG areas in Asia and the Pacific? What would be the desirable

requirements for such disaggregation? Review of (country, subregional, regional) evidence on sex-related

disparities regarding this goal area, including the variability of such disparities by other population

characteristics.

• What are country practices in producing and disseminating the above required data disaggregation in Asia

and the Pacific? Where are the main gaps? What opportunities are there for such practices to be replicated

in other countries?

• What existing methodologies can be used to improve production of data of required disaggregation? What

further methodological developments are necessary? What do these mean for additional financial and

human resources?

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10:30-12:00 A. Economic participation & poverty

Trigger presentations:

a) Eradicating Extreme Poverty: Malaysian Indicators and Issues. 30

minutes

• Cecilia Ng and Yeong Pey Jung (Penang Women’s

Development Corporation, Malaysia)

b) Unpaid work: An Obstacle to Gender Equality and Economic

Empowerment including Women’s Labour Force Participation.

15 minutes.

• Indira Hirway (Center for Development Alternatives,

India)

c) Measuring asset ownership and entrepreneurship: Vulnerable

population group and data gaps. 15 minutes.

• Kaushal Joshi (ADB)

Papa Seck

(UN Women)

12:00-13:00 Lunch break

13:00-14:50

Trigger presentation:

d) Data to inform policy: Who is being left behind in Asia?

15 minutes.

• Tanvi Bhaktal (Overseas Development Institute)

Facilitated group activity: Arman Bidar Bakhtnia (ESCAP)

Summary: TBC

14:50-15:10 Coffee break

15:10-16:40

B. Health


Which population (sub-) group(s) tends to fall behind in Asia and

the Pacific? – The case of SDG 3 on health. 15 minutes.

• Nima Asgari-Jirhandeh (WHO Country Office,

Thailand)

• Kunihiko Chris Hirabayashi (UNICEF EAPRO)

Facilitated group activity: Valery Dugain (ESCAP)

Summary: TBC

Ingrid

Fitzgerald

(UNFPA)

16:40-17:00 Participants reflect on discussions of the day

Issues to be addressed for next day

15

26 May (Day 2)

Session 2 Diving into priority goal areas (continued)

Objective: See above

08:30-10:00 C. Participation & leadership in political and public life


Monitoring women’s leadership and political participation in Asia and

the Pacific.20 minutes.

• Papa Seck (UN Women)

Facilitated group activity: Yanhong Zhang (ESCAP)

Summary: Papa Seck

Janneke Kukler

(UN Women)


10:30-12:00 D. Violence & harmful practices against women & girls


Violence and harmful practices against women and girls: SDG

indicators - Needs and challenges around data disaggregation.

20 minutes

• Henriette Jansen (UNFPA/APRO)

Discussants: 5 minutes each

a) Data on Violence against Women in Lao PDR.

• Ms. Thirakha Chanthalanouvong (Lao PDR) &

Malaykhan Keomounty (National Commission for the

Advancement of Women)

b) Current use of VAW data for policy formulation needs and

challenges, from the perspective of Women’s Machinery in

Viet Nam.

• Ms Ha Nguyen Thi Thu (Viet Nam)

Facilitated group activity: Henriette Jansen (UNFPA/APRO)

Summary: TBC

Henriette Jansen

(UNFPA/APRO)


13:00-14:30 E. Natural resources, energy and disaster risk management


a) The Gender, Climate Change and Environment nexus- What is

missing in the SDG indicators? 8 minutes.

• Annette Wallgren (UNEP)

b) Gender equality in agriculture and rural development:

Challenges and opportunities around women’s access to land

and rural women’s advancement. 8 minutes

• Clara Park (FAO)

Koh Miyaoi

(UNDP)

E/ESCAP/CST(3)/1

16

c) Regional trends on gender data collection and analysis. 8

minutes.

• Rajesh Sharma (UNDP)

Plenary Q&A discussion: Koh Miyaoi


14:50-16:20 F. Inclusive and equitable quality education &

lifelong learning opportunities


a) Literacy and Learning Outcomes: Identifying Population

Groups which tend to fall behind EFA Target: Case of SDG

4.6, 4.1 and 4.7. 15 minutes.

• Ethel Agnes P Valenzuela (SEAMEO)

b) Bringing All Children in School – Identifying the “Left

Behind”. 15 minutes.

• Roshan Bajracharya (UNESCO)

Facilitated group activity: Valery Dugain

Summary: TBC

Bertrand

Tchatchoua,

(UNESCO)

16:20-17:00 A. Pulling all together

Recap:

• “Shell table” for required sex-related disaggregation of data to

address policy issues in selected target areas

• Data gaps and potential commonalities in data sources, statistical

methods, etc & associated constraints in national statistical capacity

Arman Bidar

Bakhtnia

(ESCAP)

27 May (Day 3)

Session 3 Exploring solutions to meet data demands

Objective: Shared understanding of available technical solutions to address data gaps

08:30-09:15 A. Tracking progress in promoting gender equality

Benchmark Publication on Gender Equality and the SDGs in Asia and the

Pacific. Max 45 minutes.

• Ryce Chanchai & Jose Ramon Gatmaitan Albert

(UNWomen) & Laurence Levaque (ADB)

Q&A

Janneke

Kukler

(UN Women)

09:15-10:30 B. Power of multiplication: combining data from different

sources to improve data disaggregation

a) Integrated Data Infrastructure and its benefits for producing and

disseminating disaggregated data: 15 minutes

• Aaron Beck (Statistics New Zealand)

[Video conference]

b) PSA Project on Small Area Poverty Estimation: 15 minutes

• Ms. Bernadette B. Balamban & Ms. April Mendoza

Ms Fauzia

Viqar

(Pakistan)

17

(Philippines)

c) Data challenges for tracking progress in policies for women’s

empowerment and family planning in Thailand: 15 minutes

• Ms. Panida Hansawasdi, Ms. Natpatson Nithiprapawat

& Ms. Nattanan Wisuchartpong (Thailand)

Q&A


10:45-12:00

d) Combining different sources of data for analyzing situation of

women: 15 minutes

• Ms. Rozita Binti Abd Matalib & Mr. Mohd Sofi Ali

(Malaysia)

e) Using various sources of administrative data for producing (sex)-

disaggregated statistics: 15 minutes

• Ms. Young Shil Park (Korea)

f) Small Area Estimation and its application for producing

disaggregated statistics in Nepal: 15 minutes

• Mr Rudra Suwal (Nepal)

Q&A

Cesar Melito

Dos Santos

Martins

(Timor Leste)


Session 4 Ways forward

Objective: Shared understanding of possible actions by countries and development partners for

improvement

13:00–13:30 Data disaggregation: Issue of protecting rights:

• Ms Heike Alefsen (UNDG)

Janneke

Kukler

(UN Women)

13:30-15:00

Roundtable reflections on ways forward:

• Country teams and partner agencies

Considering role of key stakeholders:

Data producers: NSO and other government statistical departments &

agencies, private data providers, researchers

Data users: High-level political decision-makers in the government,

government planners, policy analysts, researchers

Yanhong

Zhang

(ESCAP)

15:40-16:00 Summary

Adjourn

ESCAP

E/ESCAP/CST(3)/1

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Annex II: List of participants

MEMBER STATES

BANGLADESH

Mr Mir Hossain, Deputy Secretary, Statistics & Informatics Division, Planning Ministry, Dhaka

Ms Laila Jesmin, Joint Secretary, Ministry of Women and Children Affairs, Dhaka

BHUTAN Ms Pema Choden, Planning Officer, Gross National Happiness Commission, Thimphu

Mr Sonam Penjor, Chief Program Officer, Women Division, National Commission for Women and

Children Secretariat, Thimphu

CAMBODIA Ms Lina Hang, Director General, National Institute of Statistics, Phnom Penh

Mr Lay Chhan, Deputy Director General, National Institute of Statistics, Phnom Penh

Ms Vouchlim Te, Director of Planning and Statistics Department, Planning and Statistics Department, Ministry of Women’s Affairs, Phnom Penh

Ms Sovanny Khim, Deputy Chief of Statistics Office, Planning and Statistics Department of the Ministry of Women’s Affairs, Phnom Penh

INDIA

Ms Sunitha Bhaskar, Director, Social Statistics Division, Ministry of Statistics and Programme

Implementation, New Delhi

IRAN (ISLAMIC REPUBLIC OF)

Ms Maryam Roghanchy, Expert on Household Economic Statistics, Office of Population and Labour

Force Statistics and Census, Tehran Ms Firoozeh Sadat Saadati, Head of Training and Public Participation Office at DOE, Training and Public

Participation Office, Isfahan

LAO PEOPLE'S DEMOCRATIC REPUBLIC

Ms Thirakha Chanthalanouvong, Deputy Director General, Department of Social Statistics, Lao Statistics Bureau, Ministry of Planning and Investment, Vientiane Ms Malaykanh Keomounty, Director of Administrative and Personal Division, National Commission for the Advancement of Women-Secretariat’s office, Vientiane

MALAYSIA

Ms Rozita ABD Matalib, Deputy Director, Economic Planning Unit, Prime Minister's Department, Putrajaya

19

Mr Mohd Sofi Ali, Principal Assistant Director, Department of Statistics Malaysia, Putrajaya

NEPAL

Mr Bharat Raj Sharma, Director of Monitoring, Evaluation and Data Analysis Division from the Ministry of Women, Children and Social Welfare, Kathmandu

Mr Yemendra Upadhyay, Under Secretary, National Women Commission, Kathmandu

Dr Rudra Suwal, Deputy Director General, Social Statistics Division, Central Bureau of Statistics, Kathmandu

PAKISTAN

Ms Fauzia Viqar, Chairperson, Punjab Commission on the Status of Women, Punjab

Ms Rabia Awan, Director and Gender, Pakistan Bureau of Statistics, Islamabad

PHILIPPINES

Ms April Mendoza, Supervising Economic Development Specialist, Social Development Staff, National Economic and Development Authority, Pasig

Ms Bernadette Balamban, Chief Statistical Specialist, Philippine Statistical Authority, Diliman Quenzon

REPUBLIC OF KOREA

Ms Young Shil Park, Deputy Director, Statistical Research Institute, Statistics Korea, Daejeon

SAMOA

Mr Benjamin Sebastian, Assistant Chief Executive Officer, Samoa Bureau of Statistics, Apia

Ms Leutogitupaitea Uesele-Maiava, Senior Information Officer, Ministry of Women, Community, Social Development, Apia

THAILAND

Ms Nattanan Wisuchartpong, Statistician, National Statistical Office, Bangkok

Ms Tassanee Sushevagul, Social Development Worker Senior, Professional Level, Division of Strategy and Planning Office of Women’s Affairs and Family Development, Bangkok Ms Natpatson Nithiprapawat, Chief of Social Statistic Coordination Group, National Statistical Office,

Bangkok Ms Panida Hansawasdi, Social Development Officer, Department of Women Affairs and Family

Development, Bangkok

TIMOR-LESTE

Ms Sara Maria Pereira, Liaison Officer for Education and Health, Office of Prime Minister, Social Audit Unit, Dili

E/ESCAP/CST(3)/1

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Mr Cesar Melito Dos Santos Martins, SDGs-Focal Point for Timor Leste, General Directorate of Statistics, Dili Ms Santina Soares, Gender Advisor to Ministry of Finance, Ministry of Finance, Dili

Mr João Lino Guterres, Staff of the Department of Monitoring and Evaluation, Secretary of State for Support and Socio-Economic Promotion of Women, Dili

VIET NAM Mr Chung Nguyen Dinh, Deputy Director, Social and Environmental Statistics Department, General

Statistical Office, Ha Noi

Ms Ha Nguyen Thi Thu, Senior Official, Ministry of Labour Invalids and Social Affairs, Department of Gender Equality, Ha Noi

------------------

UNITED NATIONS SECRETARIAT

UN WOMEN Mr Papa Seck, Policy Specialist, UN Women, New York

Ms Janneke Van Der Graaff Kukler, Regional Strategic Planning and Coordination Specialist, UN

Women Regional Office for Asia and the Pacific, Bangkok Ms Ruangkhao Ryce Chanchai, Programme Specialist, UN Women Regional Office for Asia and the

Pacific, Bangkok

Mr Jose Ramon Gatmaitan Albert, Lead statistician / Consultant, Zero Poverty Solutions, New York

------------------

UNITED NATIONS BODIES

UNITED NATIONS DEVELOPMENT PROGRAMME (UNDP)

Ms Koh Miyaoi, Asia and the Pacific Gender Team Leader, UNDP, Bangkok

Ms Yumiko Yamamoto, Policy Specialist, Inclusive Growth, UNDP, Bangkok Ms Britany Duncan, UNDP, Bangkok

UNITED NATIONS POPULATION FUND (UNFPA) Ms Lubna Baqi, Deputy Director, UNFPA Asia and the Pacific Regional Office, Bangkok Ms Ingrid FitzGerald, Technical Adviser, Gender and Human Rights, UNFPA Asia and the Pacific

Regional Office, Bangkok

Ms Henriette Jansen, International Researcher, UNFPA Asia and the Pacific Regional Office, Bangkok Ms Sujata Tuladhar, Technical Specialist, Violence against Women, UNFPA, Dili

------------------

21

SPECIALIZED AGENCIES

ILO REGIONAL OFFICE FOR ASIA AND THE PACIFIC

Mr Tite Habiyakare, Regional Labour Statistician, ILO, Bangkok Ms Fernanda Barcia de Mattos, Microdata Analyst, ILO, Bangkok

------------------

UNITED NATIONS EDUCATIONAL, SCIENTIFIC AND CULTURAL ORGANIZATION (UNESCO) Mr Bertrand Tchatchoua, Regional Adviser/ Head, UIS-AIMS Unit, UNESCO, Bangkok

Mr Roshan Bajracharya, Assistant Programme Specialist, UIS-AIMS Unit, UNESCO, Bangkok

Ms Aki Osawa, Project Assistant, UIS-AIMS Unit, UNESCO, Bangkok

------------------

INTERGOVERNMENTAL ORGANIZATIONS

ASIAN DEVELOPMENT BANK (ADB)

Mr Kaushal Joshi, Principal Statistician, ADB, Manila

Ms Vivian Francisco, Strategy and Policy Officer, Strategy and Policy Department, ADB, Manila

Ms Laurence Levaque, Social Development Specialist (Gender and Development), Social Development, Governance and Gender Division, Sustainable Development and Climate Change

Department, ADB, Manila

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SOUTHEAST ASIAN MINISTERS OF EDUCATION ORGANIZATION (SEAMEO) SECRETARIAT

Ms Asmah Ahmad, Programme Officer II (Evaluation), SEAMEO, Bangkok

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RESOURCE PERSONS

Ms Indira Hirway, Director, Center for Development Alternative, Gujarat, India Ms Choon Sim Cecilia Ng, Gender Responsive Participatory Budgeting (GRPB) Advisor, Penang Women’s Development Corporation (PWDC), Penang, Malaysia

Ms Shariza Kamarudin, GRPB Senior Project Officer, PWDC, Penang, Malaysia Ms Tanvi Bhatkal, Senior Research Officer, Overseas Development Institute, London, United Kingdom

Ms Rohana Ghani, PWDC, Penang, Malaysia

Ms Jessica Gardner, Statistical Consultant, Stats2info.com, Sydney, Australia

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E/ESCAP/CST(3)/1

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SECRETARIAT

Mr Yanhong Zhang, Chief, Population and Social Statistics Section (PSS), Statistic Division (SD)

Mr Valery Dugain, Statistician, PSS, SD

Mr Matthew Perkins, Statistician, PSS, SD

Ms Sharita Serrao, Statistics Assistant, SD Ms Diana Rodriguez, Associate Social Affairs Officer, Social Development Division

Mr Arman Bidhar Bakhtnia, Lecturer/Statistician, Statistical Institute for Asia and the Pacific

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