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
23 July 2016
1
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
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23 July 2016
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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))
23 July 2016
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Focus of the presentation
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What are the issues with respect to:
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Data availability
Accessibility of the data
Quality
How do they influence the production of
gender statistics?
How can these be improved?
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Data availability
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Questions of data availability at the fore of the
production of data
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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
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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
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Major steps in the gender statistics
production process
Defining data requirements
Defining issues
Statistics required from various
fields
Problems and
questions on
gender issues in
society
Relevant statistics/indicators
Required
improvements in
the situation of
women and men
Determine
data sources
Goals for equal
opportunity
23 July 2016
Assembling data
Available
statistics
Data gaps
Review quality
Dissemination
Statistics to
be analysed
Analysis
Other sources
Assess adequacy of concepts,
methods, classifications, etc.
Collect new data
Presentation
Dissemination
6
Promoting the utilization of
available data
Identify available data
Review sources of data
Assess quality of data
relative to need
Need for improvements in content, concepts,
measurement, classifications
23 July 2016
Generate
statistics
to be analysed
Identify new
data needs
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Required statistics reflect the
several dimensions
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Subject matter (topics)
Unit of analysis (individual, household,
institution, enterprise, etc.)
Reference period
Classified by other characteristics
Geographical coverage
Periodicity
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Sources of available statistics
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National censuses of population, housing,
industry, agriculture, distributive trade,
etc.
Sample surveys of households, economic
units
Registration and administrative records
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Considerations in reviewing existing
sources of data
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How closely the original purpose for the data
matches the present needs
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If data were collected without regard for gender, it
would be necessary to consider that there is:
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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
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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
23 July 2016
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Quality considerations further
limit use of available data
23 July 2016
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Components in data quality
assessments
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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.
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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
23 July 2016
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Basic considerations in data quality
for gender statistics
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Relevance of concepts
Comparability of data over time
Consistency and comparability among
sources
Applicability of the classifications and
disaggregations
23 July 2016
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Quality concerns with respect to
data available on gender issues
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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?
23 July 2016
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General quality issues
Introduction of errors at various stages
of data collection stemming from
practices
 Problems with concepts and definitions
 Problems with measurements
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Errors may occur at different stages in
the data collection process
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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
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Difficulties with concepts and definition
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Family/household
Household headship
Marital status
Economic activities
Population economically active
Status in employment
Unemployment
23 July 2016
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Measurement problems for still many
topic/variables
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Household
composition
Infant mortality
Maternal mortality
Access to safe water
Internal and
international
migration
Economic and noneconomic activities
23 July 2016
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School enrolment
Time-use
Agricultural labour
Access to resources
Access to credit
Individual &
household income
Violence
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Thank You
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