2010 Indonesia Population Census Evaluation

1. 2010 Indonesia Population Census Evaluation Presented in the “Workshop on Census Evaluation” Hanoi, Viet Nam 2-6 December 2013 BPS-Statistics Indonesia

2. Background of 2010 Indonesia Population Census (IPC) • Coverage: • 33 provinces • 497 districts/municipality • 6.580 sub-districts • 76.581 villages • Around 724.052census blocks. • Around 1.100.528 local administrative unit • Estimated 63.645.055 households • Estimated 233.596.970 people • The 2010 Indonesia Population Censustook place within the period of May 1st through May 31st2010. • The census date was on 15 May 2010

3. Background of 2010 Indonesia Population Census (IPC) Field Workers: • Involve 800.000 field workers • Data collection wasconducted by enumeration teams • Total teams: 200.000 teams • One team consists of 3 enumerators and 1 supervisor • Workload for field work is 3 – 9 census blocks per team • Every 10 teams, supervised by 1 field coordinator • Note: Beside team, there were also Task Force Unit who had responsibility to enumerate non permanent residence and specific areas (elite and corps diplomatic)

4. IPC Result: Population by age and sex, 2010

5. Demographic Parameters

6. 2010 PC Data evaluation In general, quality of 2010 PC depends on: • Complicated variables • Unclear manuals • Unproper training • Quality of enumerators • Quality of enumeration prosedure • Quality of monitoring • Data cleaning process in the field • Data processing • Data evaluation

7. Purpose of census data evaluation To obtain ”clean raw data” and “tabulation consistencies” -> to produce “realible indicators” -> can be used for “planning purposes” -> for “advanced analysis”

8. Census data evaluation • During enumeration • Post Enumeration Survey ((PES) • Before preliminary result • During/after processing individual questionnaire • Before final result

9. During enumeration • 2010 PC field enumeration -> using team, this has impact on data quality • Enumeration using team gives chance to make editing in the field and has resulted in better supervision. • Any problems relating to enumeration can be solved immediately in the field • Enumeration can be finished on-schedule • Self confidence of enumerator is much better • Enumeration using team is intended to obtain clean data in the field • Data cleaning is done within one team, and among team coordinators under one field coordinator

10. During enumeration • As a part of quality assurance in producing qualified statistics -> BPS conducted “monitoring the quality of the census” and “Post Enumeration Survey” • Monitoring quality of the census were conducted in the beginning period of field work (May, week I-II) • Monitoring quality is to ensure the quality of PC data -> focusing on the operational procedure in all enumeration process, to minimize the coverage error and content error • Monitoring quality is intended to correct the miss-procedure during the enumeration • 1,676 students, lecturers of Institute of Statistics, and BPS employees involved in this activity • Monitoring result is reported through SMS-Gateway and can be observed and download by BPS executives in the website http://kualitassp2010.bps.go.id

11. Post Enumeration Survey (PES) • PES was conducted in 1200 census blocks in 33 provinces, from 5-18 July 2010 • Purpose to evaluate instrument, procedure, and result of census related to coverage and content • PES using best enumerators in PC, but working in different CBs of PC • In general, PES result indicates that there is undercount of coverage for population and household • PES also indicates that in general, content quality is still accurate • There are variations in coverage rate and content quality in provinces

12. Population Net Coverage Error Rate (%) Indonesia: 3.6 %; range: 0.36 % – 9.77 %

13. Household Net Coverage Error Rate (%) Indonesia: 2.5 %; range: -1.20 % – 7.97 %

14. National Gross Difference Rate %) and Aggregate Index of Inconsistency %) by Variables

15. Before preliminary result • Evaluation was also conducted before preliminary result of total population released • Preliminary results of total population -> based on recapitulation from listing questionnaires • Preliminary results were announced on 16 August 2010, during national speech by President on Indonesia’s independence day • Preliminary results include: • Total population by administrative areas: national, province, district • Total population by gender • Population growth rate 2000-2010

16. Before preliminary result • BPS prepared worksheet in Excel as template to facilitate BPS Province/District to do the evaluation • The evaluation include: • Population distribution 2000 and 2010 • Population growth rate: 1990-2000 and 2000-2010 • Sex ratio: 2000 and 2010 • Total household 2000 and 2010 • Household growth rate: 1990-2000 and 2000-2010 • Household size Note: • Comparison of population in one region, was based on the recent condition of the administrative region. Proliferation of administrat ve region in Indonesia happens rapidly • Evaluation was done from the smallest administrative area to the highest administrative area • Total population also evaluated by comparing with other sources: ministrative records, population projection

17. Table Population by Reg/Mun

18. Table population growth rate for evaluation

19. Table sex ratio for evaluation

20. Table population distribution for evaluation

21. During/after processing individual questionnaire • There were evaluations based on individual questionnaires during/after processing individual questionnaires • Internal Evaluation (BPS), based on 80 primary tables for publication, this includes: • Evaluation on consistencies within tables • Evaluation on content • Evaluation based on indicators trend • Evaluation on consistency and imputation related to data processing, and evaluation on some demographic parameters by expert Michael J. Levin, from Harvard Center for Population and Development Studies.

22. Internal Evaluation (BPS), based on 80 primary tables for publication • Consistencies evaluation: • Within tables • Out of range data in table • Wrong recognizion by machine • Editing and rule validation programe are not strictly • Tracing to raw data • Checking trend indicators (national and province), such as: • Percentage population by age group • Percentage of urban population • Percentage of population by religion • Population by gender • Percentage of single women • Percentage of population by schooling status • Mean age at marriage • Mean children ever born per woman • Mean children surviving per woman • Percentageof migrant population • Percentage of labour force • Percentage of working people • Content checking: disability data, deaths by age group, labour force -> also compared by other sources

23. Evaluation assisted by International Expert • Evaluation of consistency and imputation • Consistency was done to confirm that the data is consistent with the master file and range, for field which has certain range • Imputation was done for inconsistent data and empty field that should be filled. Imputation used cold-deck and hot-deck • Rule validation program was upgraded gradually to produce consistent data

24. Evaluation assisted by International Expert • Evaluation on some demographic parameters • Population pyramids • UN Age Sex Indices • Single-Year ages: Whipple’s index, Myer’s, producing various graphs for interpreting data • Running Own-children methods -> to see ASFRs and TFRs and compares with last censuses • Children ever born and children surviving -> to see the change in parity over time and the percentage of children surviving by age group

25. Evaluation on age of males using Index Myers

26. Evaluation on age of females using Index Myers

27. Evaluation on age using UN Index

28. Evaluation before final result • Evaluation on maternal death data • Starting with the consultation to international expert from Harvard University: Prof.Kenneth Hill -> to finalize questions on maternal mortality in PC questionnaires • Workshop on calculation of maternal mortality ratio from census data • Evaluation of maternal mortality data from 2010 PC by senior experts/demographers -> maternal mortality ratio (pregnancy-related death ratio). • Comparing MMR with PMDF method, MMR with other sources

29. Further evaluation on maternal death data • Detail evaluation by tracing the raw data and verifying/visiting the household again to ascertain death as maternal death. • Household is revisited and verified, if: • there was an ever married woman who died during pregnancy, delivery or childbirth within two months after delivery • there was a woman age 15-49 died • there was a male household member with the marital status widower • there was household member age 0 year and there was no married women living in the house • Revisiting the households for cases no.1 and 2 • Sampling the households for cases no.3 and 4 • Using snowballing method (by asking to head of community), whether there is a maternal death in their neighbouring unit.

30. Maternal mortality ratio (pregnancy-related death ratio) • Total cases of maternal deaths from Popultion Census: 13.956 • Total cases of maternal deaths after revisiting the household: 8.437 • Maternal Mortality Ratio: 259 deaths per 100.000 births.

31. Challenges in evaluation • Methods of evaluation on census data should be planned and organized since the beginning of census preparation; and there should be a standard format of census evaluation (from UN) particularly on assessing demographic parameters • Evaluation on census data should be done in all BPS regional offices, started from lowest level administrative area (bottom up areas). Staffs in regional offices know exactly their area’s condition • The role of international and internal experts are important in the collaboration of census evaluation

32. THANK YOU