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Measuring Coverage: Post Enumeration Surveys Owen Abbott Office for National Statistics, UK.

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Presentation on theme: "Measuring Coverage: Post Enumeration Surveys Owen Abbott Office for National Statistics, UK."— Presentation transcript:

1 Measuring Coverage: Post Enumeration Surveys Owen Abbott Office for National Statistics, UK

2 Agenda Introduction Why have a PES? Essential features of a PES –Survey Design –Fieldwork Analysing the data –Matching –Estimation Results from 2001 UK Census Discussion

3 Why do we need a PES? Census wont count every household or person Undercount causes bias in estimates In the UK in 2001, we estimated that 3 million persons (6%) did not fill in the form Increasing problem from 1981 to 1991 to 2001 The undercount is not evenly spread –Inner Cities –Deprived areas –Young persons

4 Why do we need a PES? Census counts alone not good enough UK Users demand robust census population estimates –Central Government resource allocation –Yearly demographic population estimates –Government Policy So we need to measure how many households and persons the census misses, and work out: –where they are missed from –their characteristics

5 Basic Methodology PES - Census Coverage Survey (CCS) in UK –In the UK approx 1% population Match the PES to the Census Use the people the PES sees that the census didnt to estimate how many missed – where and characteristics Add to the Census counts (either at aggregate level or impute (UK))

6 2001 UK One Number Census framework

7 Post Enumeration Survey Key features: A - Design –Sample survey –Sample size dependent on accuracy (and geographic level) requirements B - Fieldwork –Conducted after the census has finished –Independent re-enumeration –Area based –Door to door interview –Focused on measuring coverage

8 Post Enumeration Survey - Design Multi-stage Stratified sample Select a sample of (small) geographical areas that can be re-enumerated –UK uses Postcodes (about 20 hhs) –US uses blocks (about ????100 hhs) Sample stratified by: –Geography –Area type –Demography

9 2001 UK PES Design Geographical Strata: Local Authorities (mean pop 120k) grouped into contiguous groups called Estimation areas (EAs), each having 500k pop Area Type and Demographic strata: Within every EA a sample of 1991 Enumeration Districts was selected, stratified using a hard-to- count index and the 1991 age-sex structure –(1991 EDs have about 200 households)

10 2001 UK PES Design Hard to count index was a national stratification using a combination of variables associated with undercount e.g: –Unemployed –Multi-occupied –Private rented –Language difficulty 3 level index, split into 40%, 40%, 20% nationally Within each selected ED a sample of 3, 4 or 5 postcodes was selected

11 Post Enumeration Survey - Field Aim: enumerate all the people and households in the sampled areas Carry out the survey after the Census –Census fieldwork finished Independence critical (see later) –Interview based –Independent re-enumeration –Separate fieldforce and management –No address list (UK have address list for Census) –Difficult if doing quality at same time, as not independent

12 Post Enumeration Survey - Field In UK, focused on measuring coverage –Previously measured quality as well –Found that separate surveys more effective –Can focus on getting maximal response in sampled areas UK 2001 PES used very short interview –key household and demographic questions only Accommodation type Tenure Name Gender Date of Birth (or Age) Student Ethnicity Activity last week

13 Post Enumeration Survey - Field Other initiatives to maximise response: –Pairwork and teamwork –Refusal avoidance training –Calling strategy –Up to 10 attempts to interview –Last attempt deliver form to return in post

14 Post Enumeration Survey Interviewer Duties: –Establish the postcode boundaries –Conduct independent listing of all residential and non- residential addresses –Seek out obscure accommodation –Deliver advance notification cards –Identify/probe for all households at an address –Make contact with householders –Conduct doorstep interviews –Persuade potential refusals –Report Progress

15 Post Enumeration Survey Map

16 Post Enumeration Survey Property Listing

17 Analysing the data - Matching Match Census returns to CCS returns Require very high quality –Minimise false negative matches (missed matches, see later) In 2001, we used hierarchical nature of data to help match –Match within sampled areas (geographical blocking) –First match household –Then match persons within households

18 Analysing the data - Matching Used a five stage strategy, designed to minimise false negative matches: –Exact matching –High probability matching –Clerical assisted probability matching –Clerical matching –Final expert review of non-matches Developed our own in-house system Allowed access to scanned form images (this was crucial)


20 Analysing the data - Matching Output: –Match between Census and CCS –Census only –CCS only

21 Analysing the data – Estimation Dual System Estimation (DSE) –Capture-recapture as used for wildlife Simple example: How many fish in a lake? –Catch as many as possible on day 1 Count them (N 1 ) Mark with a red dot Return them to the lake –Catch as many as possible on day 2 Count them (N 2 ) Count how many have red dots (N 12 ) –Number of fish in lake= (N 1 * N 2 )/N 12

22 Analysing the data - Estimation Use matched Census+CCS data DSE estimates adjustment for those missed in both Census and CCS Counted By CCS Yes No Counted Yesn 11 n 10 n 1+ By Census Non 01 n 00 n 0+ n +1 n +0 n ++ DSE count (for a postcode): n ++ = n 1+ x n +1 n 11

23 Analysing the data - Estimation DSE assumptions –Independence –Homogeneity of capture probabilities –Perfect matching –Closure –No list inflation Violation of these assumptions leads to bias (in both directions) Lots of literature on DSE

24 Analysing the data – Estimation DSE can only be used within the sample Need additional step to get to population totals In 2001, we used DSE at postcode level Then used a ratio estimator to predict for non- sampled postcodes (again lots of literature)

25 Analysis – Getting to small areas Ratio estimator produced estimates for 500k population blocks Needed estimates for Local Authorities (about 120k population) Sample size not sufficient to do directly So used small area estimation techniques –these borrow strength across areas –We used a fixed effect to model LA differences LA population estimates from the model then constrained to EA totals

26 Quick summary of 2001 UK method In 2001, One Number Census methodology was developed –Large CCS (320,000 households) –Matching –Capture Recapture –Modified ratio estimator –Small area estimation to get LA totals –Imputation Estimated 1.5 million households missed 3 million persons missed (most from the missing households but some from counted households)

27 Results England and Wales population about 50m individuals in 20m households Estimated 1.5 million households missed 3 million persons missed (most from the missing households but some from counted households)

28 Underenumeration in 2001

29 Response Rates in 2001

30 Summary Fundamental that the census is good –This does not make a bad census good, it makes a good census better! US, Australia, NZ, Canada, UK all measure coverage (and most use a PES) –All aim at measuring coverage for assessing census quality, most do not fully adjust the outputs –Coverage for most is around 96-98% –Increasing problems of overcoverage The design and fieldwork of the PES are important to get right

31 More info Brown, J.J., Diamond, I.D., Chambers, R.L., Buckner, L.J., and Teague, A.D. (1999), A methodological strategy for a one-number census in the UK, Journal of the Royal Statistical Society A, 162, 247-267.

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