1. The estimation of unknown multiway distributions Paul Williamson University of Liverpool, UK To IPF or to Reweight? That is the question…

2. 1. The need for IPF/Reweighting Survey distribution [of age by sex] …for local area?

3. Sampling Error: Conditional Probability Over-exaggerate problem? 2% sample Minimally multivariate Not based on minorities (e.g. unemployed ethnic minority) Min. geog. threshold: 120k

4.  Need to make most of all available data… Survey distribution [of age by sex] Local age distribution Local sex distribution

5. 2. IPF v. Reweighting

7. Comparison for margin-constrained tables Target: age x sex x tenure x economic position (64 counts) at district level (17 districts) % NFC (17 district average) 32 18 22 37 2% SAR CO IPF N IPF U

8. Simpson & Tranmer (2005) Target: Car ownership (2) x Tenure (3) (6 counts; 3%s) for residents at ward level

9. Household in ‘unaffordable’ housing if: household income in bottom 40% of national equivalised gross household income rent/mortgage >= 30% of gross household income Estimated by reweighting HES to fit 74 SLA constraints [cell counts] for each of 953 SLAs (SLA~Ward) GREGWT estimates produced by NATSEM (University of Canberra) [GREGWT≈GENLOG] 3. Housing affordability

10. Measures of Fit Cells: AE; APE; Z-score; Z m -score; NFC Table(s): TAE; TAPE; ΣZ 2; RSSZ; NFT

14. Solution: CO with non-integer increments? Cause: Patterns of weight distribution?

15. 4. Conclusion (a) Accuracy of estimates (b) Unanswered questions