1. Presentation to Pacific Statistics Methods Board
Household Statistics Model for Pacific Island Countries and Territories
Presentation to Pacific Statistics Methods Board

2. Purpose In line with section 2a and 2c of the Terms of reference
Identify best practice for household survey methodology
Determine priorities for Board advice and recommendations on aspects of household survey methodology
Determine priorities for the development of tools or for capability building to support best practice methods
Provide a framework to facilitate discussion on drivers of regular statistical production in terms of methods
A discussion-starter, not a final proposal
6/11/2018

3. Vision – where are we going and what do we build to get there?
20 year plan
Population Spine
Link Census and administrative data
Allows household and person level analysis
Uses models and data fusion techniques to populate with survey data
Encompass all PICTs
Detailed content may vary from country to country
Common core content (eg for SDGs)
Long-term goal of continuous collection?
Avoids set-up costs, maintains the capability and corporate knowledge
6/11/2018

4. Statistical tools to build and strengthen capability
“How to” guides and manuals
“Plain vanilla” survey model
Standard toolkit of methods
Excel or other tools
Can be used “off the shelf”
Can be tailored and modified to meet country or survey needs
Use HIES as the starting point for a general model?
6/11/2018

5. Statistical infrastructure
Population register and frames
Initialised through Census
Census used to produce a sampling frame for post-Census surveys
Concentrate on household level initially
Future registers or frames could potentially be expanded to include people nested under households (e.g. to identify subpopulations)
6/11/2018

6. Area-based sampling Multi-stage area sampling framework
Use HIES framework?
2 stages: Census Enumeration Area (EA); Dwelling cluster from within each EA
There may be benefits in a third stage, PSUs formed by amalgamating EAs
EAs (or PSUs) assigned to an area classification / stratification
Area classification to reflect costs / level of difficulty in surveying
It may be desirable to have further area stratification to reflect population types (socio-economic; e.g. % of low income hh in area)
May not be an initial priority
6/11/2018

7. Cluster sizes Cluster size set for each area type
Choice of cluster size determined to optimise HIES results
Aims to give the greatest accuracy per dollar cost
Set these cluster sizes as standard clusters
Allow flexibility through use of half cluster surveys, or double cluster surveys to cater for surveys with different cost or variance structures
May be desirable to set cluster sizes as multiples of 4
6/11/2018

8. Libraries of tools and methods
Libraries / Manuals of methods
Data collection methods
Applying coverage rules and other operational procedures
Data processing rules
Aim for a standard set, allowing tailoring for country or survey needs
6/11/2018

9. Program of surveys following Census
Aim to take advantage of the Census to aid the design of upcoming surveys and target key subpopulations
Identify EAs/PSUs for oversampling of key subpopulations
Determine if it necessary to consider socioeconomic stratification for upcoming surveys
Initially agree on HIES being ‘first cab off the rank’ after Census?
6/11/2018

10. Sample design Look at rollover designs initially
Potential to use Census area-level information to better control representivity of samples
Modifications may be needed to reflect new / emerging statistical requirements
Build in an evaluation stage post-survey to consider how sample design can be improved (targeting of sub-populations)
Continuous improvement cycle after cycle
Knowledge management is key
Stagger surveys across countries so e.g. learning from one countries HIES is then applied to next countries HIES
6/11/2018

11. Estimation
Standard benchmarking / post-stratification for household weights
Consider need for / benefits of person weighting vs household weighting
Census benchmarking could help with subpopulations at risk of being missed (e.g. education, income, household size)
Gradually build capability and weighting ability, aiming for small but continual improvement cycle to cycle
Modelling to build towards long-term vision of data fusion and small area estimation techniques (i.e. one country drawing strength from other countries in the region)
Modelling may be driven or conducted by a central agency
6/11/2018

12. Reporting systems
Can processes and tools used in one country be rolled over to the next country
This should include training tools
Gradually move towards standard reporting
6/11/2018

13. Issues for discussion
What elements of this model offer the greatest potential benefit?
What are our priorities for strengthening statistical infrastructure and capability? – long-term and short-term (quick wins and big payoff)
How can we resource this work?
6/11/2018