Inter-Regional Workshop on the Production of Gender Statistics NASC Complex New Delhi, India 6-10 August 2007

1. Inter-Regional Workshop on the Production of Gender Statistics NASC Complex New Delhi, India 6-10 August 2007 Data Availability, Accessibility and Quality By Dr. Grace Bediako Government Statistician Ghana Statistical Service

2. Some key concerns with regards to gender statistics • Poor cooperation between users and producers of gender statistics • Under-utilization of existing data • Inadequate or biased concepts, definitions and measures • Data gaps on many critical areas of concern

3. Dealing with inadequacies in data Beijing Platform for action requires that Governments: Ensure that producers and users of statistics in each country regularly review the adequacy of the official statistical system and its coverage of gender issues, and prepare a plan for needed improvements, where necessary. (Para. 210(b))

4. Focus of the presentation • What are the issues with respect to: • Data availability • Accessibility of the data • Quality • How do they influence the production of gender statistics? • How can these be improved?

5. Data availability • Questions of data availability at the fore of the production of data • Having considered problems and goals with respect to gender in society • And identified statistics and indicators required to plan, programme and monitor change • There needs to be a review of national sources to determine what data are available and what need to be collected anew. • Has direct bearing on the responsibilities of the national statistics office • Relate to whether and how data are used • How relevant the data are to a target audience • What further plans are to be made for data collection

6. Major steps in the gender statistics production process Defining data requirements Statistics required from various fields Defining issues Relevant statistics/indicators Dissemination Problems and questions on gender issues in society Assembling data Statistics to be analysed Data gaps Available statistics Analysis Required improvements in the situation of women and men Determine data sources Presentation Other sources Review quality Dissemination Goals for equal opportunity Assess adequacy of concepts, methods, classifications, etc. Collect new data

7. Promoting the utilization of available data Identify available data Review sources of data Generate statistics to be analysed Assess quality of data relative to need Identify new data needs Need for improvements in content, concepts, measurement, classifications

8. Required statistics reflect the several dimensions • Subject matter (topics) • Unit of analysis (individual, household, institution, enterprise, etc.) • Reference period • Classified by other characteristics • Geographical coverage • Periodicity

9. Sources of available statistics • National censuses of population, housing, industry, agriculture, distributive trade, etc. • Sample surveys of households, economic units • Registration and administrative records

10. Considerations in reviewing existing sources of data • How closely the original purpose for the data matches the present needs • If data were collected without regard for gender, it would be necessary to consider that there is: • Sex dissagregation • Topics of interest are covered at the broad level, as well as at a level of detailed relating to specific gender issues • Concepts and definitions are relevant • Dissaggregations with respect to age, socio-economic characteristics, geographic locations, etc. • Time reference

11. Accessibility: Data may be characterized by the following: Required data were collected: • Tabulated and published in at least one form (including yearbooks, booklets, diskettes and compact discs) • Tabulated but not published (such data can only be obtained from the responsible office by request) • May not have been tabulated (data are available in the form of individual records on computer media, such as magnetic tapes, compact discs, or computer diskettes) and can only be obtained by submitting a specific request to the responsible office • Data are collected but not processed (i.e., although the relevant questions were asked in surveys/censuses, responses are not coded or extracted from the questionnaires) Data are not collected at all or are not collected by sex

12. Quality considerations further limit use of available data

13. Components in data quality assessments • Validity • Reliability • Relevance to policy • Potential for disaggregation • Currency • Punctuality • Coherence across different sources • Clarity and transparency (regarding limitations) • Accessibility and affordability • Comparability (conformity to international standards) • Consistency over time and space • Efficiency in the use of resources.

14. The combination of these components use to determine the quality of any particular set of data may vary from one purpose to another. Data that are acceptable for one purpose might be inadequate for next. • Since use of data for gender-specific analysis differs from other purposes, the process of determining `fitness for purpose' requires wide consultation. • The trade-offs to balance the different components of quality cannot satisfy all users simultaneously, but the needs of users may be addressed through flexible presentations of the data. Denise Lievesley United Nations Educational, Scientific and Cultural Organisation, Paris

15. Basic considerations in data quality for gender statistics • Relevance of concepts • Comparability of data over time • Consistency and comparability among sources • Applicability of the classifications and disaggregations

16. Quality concerns with respect to data available on gender issues • Is the concept/definition used in data collection consistent with the definition required for the gender issue? • Do the definitions change from one source to another or between periods? • Is the classification for the gender issues appropriate? • Have changes occurred in measurements over time or between sources?

17. General quality issues • Introduction of errors at various stages of data collection stemming from practices • Problems with concepts and definitions • Problems with measurements

18. Errors may occur at different stages in the data collection process • Planning and designing the survey • Advertising the survey • Defining the coverage and target • Defining the sampling frame and design • Formulating concepts and definitions • Designing the questionnaire • Defining the reference period • Selecting and training the enumerators • Selecting the respondents • Final checking and coding of the results

19. Difficulties with concepts and definition • Family/household • Household headship • Marital status • Economic activities • Population economically active • Status in employment • Unemployment

20. Household composition Infant mortality Maternal mortality Access to safe water Internal and international migration Economic and non-economic activities School enrolment Time-use Agricultural labour Access to resources Access to credit Individual & household income Violence Measurement problems for still many topic/variables

21. Thank You