1. African Centre for Statistics
4/6/2019
Census Micro Data
A Discussion
Prof. Ben Kiregyera
Director
African Centre for Statistics
August 2007
4/6/2019

2. Value of data and information Issues arising from presentations
COVERAGE
Value of data and information
Issues arising from presentations
Conclusion
COVERAGE
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3. I. VALUE OF DATA AND INFORMATION
data and information now universally
recognized as:
part of the enabling environment for
development
a priority for results-based agenda
(PRSPs, MDGs, etc) (e.g. Marrakech
Roundtable, 2004)
data and information have no intrinsic value
– they are not gold or silver. They have
extrinsic value which lies in their power to
inform processes e.g. policy debate &
design, planning, monitoring, etc.
their value lies in fact that:
they can reach those who need them,
can be easily understood
are usable and actually used
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4. LIS-based research has catalyzed changes in national policies
(LIS paper)
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5. Analysis/Interpretation
DATA CYCLE
Planning
Stage 1
Stage 2
Implementation
Dissemination
Feedback
Stage 3
Reporting
Processing
Analysis/Interpretation
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6. Need information from this these data
More and more data
Need information from this
these data
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7. Policy-related Analysis
Policy-related information
Raw Data
Tables
Basic Analysis
Policy-related Analysis
Policy/
decision-
maker
information
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8. Informed Actions/ decisions
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Data, Information, Knowledge, Actions
Informed Actions/ decisions
Value addition
Knowledge
Information
Data
See NSDS Essentials in PARIS21 documentation
Some issues important to the success of an NSDS are…….
Importance of high level political support and clearly defined leadership, typically by a country’s central statistics bureau
Need for a well planned process (or road map) to design the NSDS
Thorough process for identifying and prioritising user needs and to assess data gaps and weaknesses
Review of existing statistical production and analysis; capacity, legal and institutional framework and coordination arrangements
Agreeing (at the appropriate political level) on desired outcomes, building on what already exists and is in progress, e.g. GDDS improvement programmes
Setting priorities and strategies for implementation
Managing change
And engaging and motivating staff
NSDSs may take many forms depending on country experiences and progress. Much has already been done in the context of PRS and MDG monitoring and many countries participate in the GDDS programme.
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9. statisticians/data producers (NSO)
Who should do data analysis?
Preliminary or general analysis
statisticians/data producers (NSO)
Definitive or in-depth or detailed analysis
subject-matter specialists
researchers
Importance of involving subject-matter specialists and
researchers in analysis
enriches analysis by adding subject-matter
perspectives
possibility to link policy variables to micro-level
outcomes (paper on LIS)
enhances collaboration (advancing from
coordination to collaboration)
spreads ownership of statistical products
feedback and advocacy
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10. Basic principle of data analysis
Once
Data Collection
Feedback
Many times
Data Analysis
NSO
Policy analysts
Researchers
Students
etc.
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11. II. ISSUES ARISING FROM PRESENTATIONS
All presentations make a case for enhancing data management including:
Country level – we see great need for:
data archiving (IPUMS-International)
creation of user-friendly and accessible
databases (documentation crucial - metadata) –
Benin’s “Jupiter”
ensuring that databases are not empty boxes or
have “garbage”
encouraging researchers to do more detailed data
analysis (Benin example shows need for this)
a lot of value in doing broad range of analysis
(through space and time)
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12. ISSUES ARISING FROM PRESENTATIONS (ctd) Challenges:
i) appreciation of value of data (by data producers and users)
Users: use data for evidence-based policy (debate, design)
& decision-making; invest more to build statistical capacity &
development
Producers: ensure data quality & relevance; better data
management
inconsistencies through time caused by changes in
definitions(1992 & 2002 Benin censuses)
- special attention to harmonization to permit comparability
technical capacity (Benin paper – mutually beneficial TA)
Statistics Acts which are not congenial
Other laws (e.g. designating areas as rural or urban)
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13. International level – we see increasingly:
construction of cross-national micro databases to
enhance research infrastructure
Integrated European Census Microdata (IECM)
Luxembourg Income Study (LIS)
Redatam Software for micro data dissemination
& analysis
IPUMS-International initiative – archiving,
integration and disseminate high-density census
micro data samples
defining features of these databases include:
research centres not only involved in data
analysis but also in “coordination, dissemination
and harmonization activities” (IECM)
interest and cooperation of NSOs
emphasis on integration & documentation
- IECM major part of project
- IPUMS – International (post-harmonization)
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14. Creating databases become a driver for data harmonization and integration
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15. reliability and comparability of data sources across countries
Challenges
reliability and comparability of data sources across
countries
lack of consistency, terminology, classifications,
question numbers and wording (all papers)
confidentiality (strict conditions set by countries & more)
ownership (IPUMS - International)
dissemination
Redatam developed by CELADE, Popn. Division
of ECLAS (UN) allows on-line processing of any
database over Internet
LIS uses remote-access system (primary means
to access data)
IPUMS posts census documents on Internet, etc
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16. improved analytical capacity at NSOs
Other issues
improved analytical capacity at NSOs
training institutions should strike a productive
balance between “data demand” and “data
supply” in training programmes
bigger dose of data analysis in training centres
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17. III. CONCLUSION
Case made by all papers about need to add value to data
through more detailed analysis
Papers urge NSOs to move away from “risk avoidance” to
“risk management” (European statisticians)
Enhance research infrastructure by creating user-friendly
databases including micro databases
Issues to address include integration, harmonization,
confidentiality
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18. Thank You
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