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Weighting Methodology for the Private Landlords Survey

Weighting Methodology for the Private Landlords Survey. Robert Bucknall, ONS. Presentation outline. Overview of Private Landlords Survey Potential sources of bias Weighting of the Survey Dwelling weights Landlord weights Calibration Recommendations. Overview of the PLS.

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Weighting Methodology for the Private Landlords Survey

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  1. Weighting Methodology for the Private Landlords Survey Robert Bucknall, ONS

  2. Presentation outline • Overview of Private Landlords Survey • Potential sources of bias • Weighting of the Survey • Dwelling weights • Landlord weights • Calibration • Recommendations

  3. Overview of the PLS • Follow up to English Housing Survey • Collects information about: • Ownership • Occupation • Management Practices • of privately rented dwellings in England • No available list of private landlords from which to conduct survey. Based on sample of landlords derived from the EHCS and EHS

  4. EHCS/EHS Questions about Landlord

  5. PLS sample selection

  6. PLS sample selection

  7. PLS sample selection

  8. PLS sample selection

  9. PLS sample selection

  10. PLS sample selection

  11. Dwelling and Landlord weights • Dwelling derived sample • Previously, distributions reported always related to % of dwellings rather than % of landlords • Became issue as policy focus of the survey shifted from dwelling condition and maintenance to landlord letting and management practices

  12. Dwelling based output table Example of dwelling based table from 2006 PLS:

  13. Landlord based output table Example of landlord based table from 2006 PLS:

  14. Stage 1 weight • A response model was developed: • For each dwelling on the EHCS/EHS private renters dataset, a PLS response marker was created: • 1 if on PLS sample • 0 if not on PLS sample • A survey weighted logistic regression was conducted to model the likelihood of receiving landlord details from each dwelling

  15. Stage 1 weight

  16. Stage 1 weight • The following variables were considered as predictors in logistic regression: • Region • Ethnicity of household reference person • Housing benefits • Property type • Satisfaction with the service provided by the landlord • Furnished or unfurnished • Employment status of household reference person • Age of household reference person • Marital status

  17. Stage 1 weight • The logistic regression model identified the following variables as predictors of a tenant’s propensity to provide their landlord’s contact details: • Region • Housing benefits • Satisfaction with the service provided by the landlord • Age of household reference person • Marital status

  18. Stage 1 weight • The probability of receiving landlord contact details from tenant i is given by the logistic function: where are regression coefficients and are explanatory variables for tenant i.

  19. Stage 1 weight • The Stage 1 weight for dwelling i on the PLS is: where is the EHCS/EHS weight for dwelling i and is the probability that landlord contact details are provided by dwelling i

  20. Stage 2 weight (landlord weight) • Landlords who own large portfolios of properties have a greater chance of being included on the frame than landlords who own small portfolios of properties • Analysis has shown that there is significant variation in landlord response rates across region and landlord portfolio size

  21. Stage 2 weight (landlord weight)

  22. Stage 2 weight (landlord weight) • The landlord weight should reflect the probability of the landlord being sampled • A dwelling adjustment reflects the size of the portfolio of tenant i’s landlord: where is the Stage 1 weight for dwelling i and is the portfolio size of landlord L

  23. Stage 2 weight (landlord weight) • The initial weight for landlord L is: where is the dwelling adjustment and is the Stage 1 weight for dwelling i

  24. Stage 2 weight (landlord weight)

  25. Stage 2 weight (landlord weight) • Adjustments required to minimise landlords non-response bias • 18 weighting classes (9 GOR x 2 sizebands) • Landlord weights were adjusted to account for landlord non-response: where is the number of sampled landlords in GOR g sizeband z, and is the number of responding landlords in GOR g sizeband z

  26. Calibration • Estimates of private renters within GOR available from LFS • PLS landlord weights calibrated to LFS private renter estimates • GES ensures weights sum to predetermined totals

  27. Calibration Initial landlord weights and portfolio sizes Control variables (LFS household totals by GOR) Final landlord weights

  28. Recommendations • New PLS weighting method minimises potential bias in the survey: • Tenant’s reluctance to provide landlord contact details • Over representation of larger landlords on the PLS • Loss of landlords due to non-response to PLS • Method for producing landlord weights developed due to a shift in policy focus of the survey

  29. Questions / Comments

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