The First Rolling Integrated CensusMethodology, Results & Flaws

Pnina Zadka, Israel

ECE/CES 2015 –Experts on Population and Housing Censuses

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Background

Incentives for modification

Diversions from previous census

Methodology in “a nut shell”

Implementation and data collection

Results

Results review and evaluation

Content

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2008 Integrated Census (IC)Theoretical method

– Dual Estimation System

– Use of CPR as the backbone

– Improved CPR with external data sources (ICPR)

– Two independent samples to adjust the ICPR

• Under registration - area sample with CAPI• Over registration - sample from ICPR with CATI• Record linkage of both survey responses to ICPR

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Incentives for Modifications

Organizational constrains evolving from

future strategic plans

Produce more timely and updated

estimates in a era of rapid changes

Reduce cost and insure budget flow

Graduate progress towards a full register

based census

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Rolling Integrated Census (IRC) Principles

Maintain IC methodology

Maximize use of current surveys (adjust

surveys for compatibility)

Increase use of administrative sources

Census procedures incorporated into

current workflow and reduce peaks

Reduce response burden

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Diversions of IRC from 2008 IC

IRC 2011 IC 2008

Two un-linked samples Linked samples

Dwelling Register (DR) as the sample frame for the under registration survey

Area cells as the sample frame

Sample size 10% of the HH Sample size 20% of the HH

Simultaneous data collection for both surveys

Surveys conducted in a row with record linkage in between

Data collection over 11 months

Data collection over 6 months

LFS adjusted to complete census data

LFS used as source for quality review

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Data Collection

Training - – 5 days for the CAPI– 1 Day for CATI

Sample size– “U” sample + LFS sample = 22K+18K dwellings– “O” sample + LFS sample = 44K “administrative families”

Response rate – “U” = 87% (63,937 + 40,680 persons enumerated)

– “O” = 74% (72,022 + 58,399 persons enumerated)

Time span of data collection – 11 months for both surveys

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Calculated Estimates

PLU = Under coverage parameter for localityPLU =persons residing in a locality and registered there

persons enumerated in the locality

PSU = Under coverage parameter for SAPLU =persons residing in an SA and registered there

persons enumerated in the SA

Po= Over coverage parameter for locality

PLO =persons registered in a locality but not living there

persons enumerayed in the locality

Pso = Over coverage parameter for SA

Wight for locality ωL=1/ (PLU + PLO)

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Coverage parameters

Higher Pu => higher quality ICPR

Lower Po => higher quality ICPR

1≥Po,Pu≥0

If Po≈0 and Pu≈1

Move to full register based Census

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Results (1)

Comparisons with 2008 IC PU parameters

95% of PU (L,S) were higher in 2011-RIC than in 2008-IC

a. Significant improvement in the ICPR quality???

b. Biased parameter???

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Results (2)

Comparisons with 2008 IC Po parameters

42% of Po (L,S) were higher in 2011-RIC than in 2008-IC

≈ Random expected variation

No change in ICPR quality!

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Results (3)

Comparison final estimates to current population

estimates

Estimated bias=5% -27%

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Methodological Review

1. High correlation between probability of correct registration in the DR and in the ICPR

Chi-square = 67451, p value=0.00001

Cramer phi (φc) = 0.54 (no association =0)

Odds ratio = 34.2 (no association =1)

2. No failure in linkage

3. No impact of prolonged enumeration period

4. Bias not correlated with size of locality

5. No detected bias in un-enumerated dwellings

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Enumeration procedures review

1. Minor deviation in following instruction

manual by some interviewers (mainly

by less experienced staff)

2. No exceeded refusals rate in RIC

compared to current surveys, slightly

higher than in 2008 IC

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Outcome

1. DR as sampling frame for under-

coverage in the ICPR for census

estimation is not yet appropriate due to

high correlation with ICPR

2. Most available registers link their

addresses to the CPR

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Decisions taken

Terminate the pilot RIC and adjust census statistical methodology

Return to the area sampling for the “U” sample (area cells)

Two stage sample to improve area coverage

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What next?

Develop Statistical models to predict quality registration in the ICPR

Differential sample size according to probability of correct registration in the ICPR

Increase total annual sample size

Conduct a pilot census over two consecutive years

Technological adjustments; tablets and internet

18Fennel in Sunset , Ilan Zadka-Schuldiner

Thank You