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Measuring Social Transfers in Kind in the UK

Measuring Social Transfers in Kind in the UK. Richard Tonkin, James Lewis & Nathan Thomas 2 nd - 4 th December 2013 Email: richard.tonkin@ons.gsi.gov.uk Twitter: @richt2. Overview. Introduction Why measure STIK? UK poverty statistics Measuring STIK in the UK: Education services

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Measuring Social Transfers in Kind in the UK

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  1. Measuring Social Transfers in Kind in the UK Richard Tonkin, James Lewis & Nathan Thomas 2nd - 4th December 2013 Email: richard.tonkin@ons.gsi.gov.uk Twitter: @richt2

  2. Overview • Introduction • Why measure STIK? • UK poverty statistics • Measuring STIK in the UK: • Education services • Healthcare (NHS) services • Public transport subsidies • Impact of STIK on income distribution • Impact of STIK on poverty estimates • Conclusions

  3. Introduction • Canberra Group Handbook (2011): • “Social Transfers in Kind (STIK) are … goods and services provided by government and non-profit institutions that benefit individuals but are provided free or at subsidised prices.” • Accounting for STIK important for cross-country comparisons of income distribution/poverty • Not included in operational definition of disposable income due to practical challenges

  4. Introduction • Analysis of STIK included in “Effects of Taxes & Benefits on Household Income” (ETB) • ETB also includes analysis of indirect taxes (including VAT & fuel/alcohol duties) • In-kind benefits included in ETB: • Education services • Health services (NHS) • Rail/bus subsidies • Housing subsidies • Free school meals

  5. Introduction • ETB based on UK Household Budget Survey • Living Costs and Food Survey (LCF) • Annual survey of 5,000+ households • CAPI interview plus 2-week expenditure diary • Main UK poverty statistics produced from different source • Family Resources Survey (FRS) • Larger sample (20,000 households) • Not possible to estimate STIK or indirect taxes

  6. Measuring education services • ‘Actual consumption’ approach applied • Use admin data on cost per pupil/student for different types of schools, nurseries, universities, etc. • Value attributed to those recorded in LCF as receiving each kind of state education • No benefit allocated for pupils attending private schools/receiving home schooling

  7. Measuring health services (NHS) • ‘Insurance value’ approach applied • Use data on cost of providing various types of healthcare: e.g. hospital inpatient/outpatient; GP consultations; pharmaceutical services, etc. • Each individual allocated value based on data on average use by age/sex • No adjustment made for use of private healthcare • Not feasible from data • Argument that all individuals benefit from existence of public healthcare services

  8. Measuring public transport subsidies • Subsidies allocated to households based on expenditure data from LCF • Rail subsidy calculated separately for those living in London/South East, reflecting higher levels of subsidy for London transport • Allowances made for use of rail travel by business sector and tourists • Bus travel calculate in similar way, but with additional benefit allocated for individuals holding concessionary bus pass

  9. Impact of STIK on income distribution • STIK by equivalised disposable income quintile, 2011/12:

  10. Impact of STIK on income distribution • Original, disposable, adjusted disposable & final income by income quintile, 2011/12: 14 x 3.5 x 5 x

  11. Impact of STIK on poverty statistics • STIK not included in published UK poverty statistics • Standard equivalisation scales designed for cash income • Don’t take into account varying needs for e.g. education/health services • Simplified Needs Adjusted (SNA) scale (Aaberge et al., 2013):

  12. Impact of STIK on poverty statistics • Relative at-risk-of-poverty rates, 2011/12: • Rates based on percentage of population below 60% of median equivalised household income

  13. Impact of STIK on poverty statistics • Relative at-risk-of-poverty rates by age group, 2011/12:

  14. Impact of STIK on poverty statistics • Relative at-risk-of-poverty rates by household type, 2011/12:

  15. Conclusions • Poverty statistics including STIK very beneficial for international comparisons • For within-country comparisons, measurement of STIK important for analysis on income redistribution • Appropriateness for income poverty less clear: Should in-kind income be treated as comparable to cash income? • Selection of appropriate equivalisation scale vital • Outcome of analysis dependent on other choices/ assumptions, including: • Which STIK included in analysis • Actual consumption vs. insurance value vs. flat rate • Allocation of benefit at household vs. individual level

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