Matching Pres. 7

1. MatchingPres. 7

2. Matching Purpose of matching Determine enumeration status Correct enumeration Erroneous enumeration Missed in census

3. Objectives of matching Matching aims at identifying: For persons from the P-sample: Matched non-mover Matched out-mover Non-matched non-mover Non-matched out-mover In-mover Born after Died after

4. Objectives of matching For persons enumerated in the census (E-sample): Matched non-mover Matched out-mover => correctly enumerated Erroneously enumerated

5. Matching (contd.) Basic process of matching Matching carried out in two phases Phase 1 – strict rules to result in Obvious matches Possible matches Phase 2 – possible matches are re-examined using relaxed rules to determine Matches Field follow-up to obtain more information to resolve match status

6. Matching Operations Matching can be done by computer, manually or both Basic process involves comparison of addresses, names & demographic characteristics Housing units & persons enumerated in a census are compared with those enumerated in the PES Computer matching can first involve scanning of questionnaire & installation of a matching software Computer matching ensures speed and objectivity using matching algorithms

7. Steps Followed in Matching Housing Unit Match Identify Search areas – good knowledge of geography of the country and having good maps to work with Phase 1 matching to determine Obvious matches Possible matches Phase 2 matching to determine Matches with relaxed rule Field follow-up to obtain more information to resolve match status

8. Steps Followed in Matching (contd.) Person matching Identify E-sample persons with sufficient information eligible for matching Identify Search areas – good knowledge of geography of the country and having good maps to work with Phase 1 matching to determine Obvious matches Possible matches Phase 2 matching to determine Matches with relaxed rule Field follow-up to obtain more information to resolve match status

9. Matching Rules Need for documentation of detailed matching rules In developing the rules consideration must be given to the possibility of making erroneous matches and erroneous non-matches If rules are relaxed and made flexible more matches and fewer non-matches may be possible-possibility of increasing erroneous matches Put in place a system that minimizes net error

10. Matching Rules (contd.) Matching rules specify characteristics, e.g. age, sex, name etc. Specifying some tolerance ranges, e.g. for age - this allows for limited misreporting Ranges can vary according to characteristics Care not to increase gross matching error (erroneous matches + erroneous non-matches) while minimizing net matching error

11. Reconciliation Visits Helps to identify erroneous census enumeration Good training of field staff essential Follow-up directed to no-matched persons and households Resolution of doubtful cases and definitive match status for every P and E sample element For persons in census records and not in the PES reconciliation helps to: Determine whether such persons were usual residents as of census date or whether they were erroneously enumerated

12. Reconciliation Visits (contd.) For persons appearing on PES list but not on census records, reconciliation helps to: Confirm whether such persons were usual residents as of census date (non-movers or out-movers) or Whether they arrived or were born after census (in-movers) Collect additional information to determine the final match-to confirm whether such persons were residents of particular households as of census date

13. Thank You!