Module 10: Data Sources and Metadata

1. Tools for Civil Society to Understand and Use Development Data: Improving MDG Policymaking and Monitoring Module 10: Data Sources and Metadata

2. What you will be able to do by the end of this module • Identify and use effectively the different types of data used to produce indicators • Understand the concept of metadata and the role it plays in using indicators

3. Sources of Data • Administrative or routine data • Census data • Survey data • Surveillance data

4. Administrative (or Routine) Data • Primary purpose is management of processes • Summary and/or dissemination occurs later (but usually within one or two years) Example • Registration of birth • Record birth a child, to be used later for purposes of child health, education, etc. • Immunization against measles • Purpose is to manage the national immunization programme

5. Administrative Sources • Vital registration (births, deaths, etc) Moldova: the civil registration offices (birth, death, marriages and divorces). Information on migration is received from the Ministry of Information Development and the National Bureau for Migration Belarus:the data on vital events comes from the acts of civil status registered by the Offices of Civilian Registration (ZAGS), and data on migration of population is collected from the Ministry of Internal Affairs • Health systems (immunization rates, mortality rates, maternal health data, etc.)

6. Administrative Sources and Statistical authorities • Education (Enrollment and completion data) Belarus: NSC collects annual information on pre-school, higher, and special secondary education and the Ministry of Education –general secondary education and out-of-school education, on educational establishments for children with psychophysical traits, vocational technical education, children's homes, and tutelage authorities. student-teacher ratio, etc.) Moldova: For primary and secondary education, NBS collects information from private schools only. Information about other schools is received from the Ministry of Education; data are processed by the NBS. For other types of education, the data are collected by NBS itself, from colleges, professional schools and universities

7. Administrative Sources and Statistical authorities • Employment (numbers employed, industry, level of participation) Moldova: NBS of Moldova is responsible for Labour Force Survey Belarus: There is no Labour Force Survey • Business (Industry, sector, size) Moldova: NBS of Moldova is responsible for business register Belarus: NSC is responsible for keeping of a business register. Information comes from the registration authorities responsible for state registration/ cessation

8. Censuses • Collect data from every unit in the population • 100% coverage (in theory) • Expensive • Time consuming

9. Population Census • Identify each member of the population • Collect certain basic data about them • age, gender, location, etc. (Moldova 2004, Belarus 2009) • Modules to collect data on specific topics may be added • Normally about every 10 years • Modeling methods used to generate population estimates between censuses • Good for small-area poverty mapping

10. Population Census Data • Advantage • Excellent coverage • Creates sampling frame for household surveys • Disadvantage • Potential for some bias – for example, could miss nomadic groups or homeless • May be inaccurate due to infrequency • Limited data collected • Lag before data produced

11. Establishments Censuses Censuses of businesses, hospitals, other organizations • Provide a frame for later surveys • Collect basic data, as for population census • Problems: • Smaller or informal establishments often excluded • Establishments may change more frequently than households

12. Sample Surveys • Vehicle for collecting data from a subset of the population • Advantages of focusing on a subset: • Save money and resources • Reduce time to collect data • Reduce time to analyse data

13. Characteristics of Sample Surveys • Primary purpose is to get data • Some units will be omitted • Well designed survey should be representative of the population • There needs to be reliable sampling frame (e.g. generated from census data)

14. Sample Survey Data • Advantage • Cheaper and quicker than census • More frequent than census, though usually only every 1 to 3 years • Can collect wider range of data than census and administrative systems • Reduced potential for bias than in census and administrative data • Disadvantage • Sampling error since coverage < 100% • Requires more sophisticated design to ensure consistency and accuracy

15. Household Surveys • Reporting usually takes about 1 year after completion of data collection • Focus is on socio-economic and health issues • Governments should develop inter-census survey programs

16. Household Surveys (2) • Multi Indicator Cluster Surveys (MICS) • Demographic and Health Surveys (DHS) • Living Standards Measurement Study Surveys (LSMS) • World Health Surveys (WHS) • Core Welfare Indicators Questionnaires (CWIQ)

17. Household Surveys (3) • Household budget surveys Moldova:NBSconducts Household Budget Survey (HBS),the sample size is 9.000 households, half of which remain in the sample for 4 years, while the other half is replaced after two years. Response rate is about 70% • Household income and expenditure surveys Belarus:Minstat conducts the Household Income and Expenditure Survey (HIES), which is held annually. The sample consists of 6,000 households. The households participated at the survey are rotated every year.Response rate is 91%

18. Demographic Surveillance Systems (DSS) • Longitudinal monitoring of sentinel populations (60,000 to 100,000) • Follow same people every year through life of survey • 100% event registration • 40 countries

19. Demographic Surveillance Systems (DSS) (2) • Advantages • Coverage of sentinel pop = 100% • Rapid data availability • Facilitates targeting and short term monitoring • Disadvantages • Few large clusters – potential for serious bias • Expensive to include many clusters http://indepth-network.htm

20. Data Sources Compared

21. Data Sources Compared (2)

22. Synergy Across Data Sources • Potential to use different types of data together to • Build a wider picture • Provide a means for cross-checking • Population estimates from censuses needed to supplement other sources • Need to ensure compatibility of • Definitions • Time frames

23. Metadata • Clearly vital to know, when using data • How they were collected • When they were collected • By whom • Potential for bias • How data items are defined • Methodology • The whole collection of this type of data is called the metadata

24. Major Purposes of Metadata • Confirm definitions • Facilitate decisions about compatibility of data from different sources • Guides and validates the interpretation of data and their indicators

25. Summary In this module we have discussed • The main sources of data used in the production of indicators • The definition and importance of metadata

26. Practical 10 • Which of the surveys discussed in this module are carried out in your country? How frequently? • Summarize the progress towards Goal 3, using the MDG report. Include in your assessment a discussion of the limitations of the data which contribute to the relevant indicators. Use the metadata to inform this discussion