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Improving the Quality of the HMRC Personal Wealth Statistics

Improving the Quality of the HMRC Personal Wealth Statistics. Rebecca Ambler and Abeda Malek - HMRC. Overview. Background Proposed solution Modelling the mortality adjustments Results Involving users Publication Next Steps. Background – Previous Method.

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Improving the Quality of the HMRC Personal Wealth Statistics

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  1. Improving the Quality of the HMRC Personal Wealth Statistics Rebecca Ambler and Abeda Malek - HMRC

  2. Overview • Background • Proposed solution • Modelling the mortality adjustments • Results • Involving users • Publication • Next Steps

  3. Background – Previous Method • Personal Wealth Statistics produced based on Inheritance Tax (IHT) returns. • Prior to ONS’s Wealth and Assets Survey (WAS) main source of data on wealth inequality. • Provides a historical time series on wealth inequality.

  4. Background – Previous Method: Step 1 All estates requiring a grant of representation Grossed for sampling rate Sampled data from IHT returns Concerns: • Not all estates captured on death. • Sampling biases. • Small samples for large estates.

  5. Background – Previous Method: Step 2 All estates requiring a grant of representation Grossed for sampling rate Sampled data from IHT returns Concerns: • Method for adjusting the relationship between wealth and mortality out of date. Grossed for mortality rates “Identified wealth”

  6. Background – Previous Method: Step3 All estates requiring a grant of representation Grossed for sampling rate Sampled data from IHT returns Grossed for mortality rates Concerns: • Adjustments based on assumptions. • Adjustments possibly out of date. • Don’t know which estates to adjust. Adjusted for under-recording and valuation differences “Identified wealth” “Adjusted wealth”

  7. Background – Previous Method: Step 4 All estates requiring a grant of representation Grossed for sampling rate Sampled data from IHT returns Concerns: • Lack of data on missing estates Grossed for mortality rates “Marketable wealth” Adjusted for under-recording and valuation differences Adjusted for missing estates and trusts “Identified wealth” “Adjusted wealth”

  8. Background - Problems

  9. Background - Problems

  10. Solution – Data • Sampling had been improved – capturing all estates requiring a grant of representation. • Service Level Agreement in place and regular meetings with the data suppliers. • While some problems still arising, more are minor.

  11. Proposed Solution – Methodology • Volatility due to small number of large cases – use a combined 3 year sample. • Concerns about adjustments for valuation and under-recording – remove. • Concerns about estimates for missing estates – remove. • Concerns about adjustments to mortality for levels of wealth – use newly available longitudinal data to revise these.

  12. Modelling the Mortality Adjustments – Data Sources • English Longitudinal Survey of Ageing (ELSA) • - 2006 survey, Dept. of Health, Over 50’s mainly, England only, link between mortality and wealth • Wealth and Assets Survey (WAS) • - 2006-08 survey, ONS, all adults over 16, all GB • Comparisons • - Advantages and disadvantages • Availability of data - ELSA: October 2010 - WAS: November 2011

  13. Modelling the Mortality Adjustments – Regression Model using ELSA • Raw Data - UK Data Archive - Waves 1, 2 and 3 - Assumptions • Variables - Dependent: Year of Death (Mortality variable) - Predictive: Gender, Age and Marital Status Gross Housing Wealth (Wealth variable) • Binary Logistic Regression in SPSS - Merging files, cleaning data

  14. Modelling the Mortality Adjustments – Mortality Adjustment Calculation Calculating the mortality adjustments for each gender, age, marital status and wealth category: Log (Mortality) = Gender Indicator + Age Group Indicator + Marital Status Indicator + Wealth Indicator + Constant

  15. Modelling the Mortality Adjustments – Regression Outputs

  16. Modelling the Mortality Adjustments – Example of Mortality Adjustments

  17. Results

  18. Results

  19. Involving Users • Major change to methodology - consultation to get user views. • Mixed response – concerns about timeliness but no alternative proposed. • Allowed us to collect views on other issues.

  20. Publication • New statistics published on HMRC website on 30th June (http://www.hmrc.gov.uk/stats/personal_wealth/menu.htm) • Uses new methodology • Developed commentary and added new tables to meet users needs.

  21. Publication

  22. Publication

  23. Publication

  24. Publication

  25. Next Steps • Investigate mortality adjustments for under 45s. • Comparison with WAS data. • New tables currently published as experimental statistics – investigate quality of those.

  26. Questions? For further information please contact: • Rebecca Ambler rebecca.ambler@hmrc.gsi.gov.uk • Abeda Malek abeda.malek@hmrc.gsi.gov.uk Or look on our website http://www.hmrc.gov.uk/stats/personal_wealth/menu.htm

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