Census Micro Data A Discussion Prof. Ben Kiregyera Director African Centre for Statistics

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

2. COVERAGE • COVERAGE • Value of data and information • Issues arising from presentations • Conclusion

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 nointrinsic value – they are not gold or silver. They have extrinsic valuewhich 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

4. LIS-based research has catalyzed changes in national policies (LIS paper)

5. DATA CYCLE Planning Stage 1 Stage 2 Implementation Dissemination Feedback Stage 3 Reporting Processing Analysis/Interpretation

6. More and more data • Need information from this • these data

7. information Policy/ decision- maker Policy-related Analysis Basic Analysis Tables Raw Data Policy-related information

8. Data, Information, Knowledge, Actions Informed Actions/ decisions Knowledge Value addition Information Data

9. 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

10. Basic principle of data analysis Once Data Collection Feedback Many times Data Analysis • NSO • Policy analysts • Researchers • Students • etc.

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)

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)

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)

14. Creating databases become a driver for data harmonization and integration

15. 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

16. 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

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

18. Thank You