Measuring Social Transfers in Kind in the UK Richard Tonkin, James Lewis & Nathan Thomas 2 nd - 4 th December

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

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

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

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

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

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

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

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

Impact of STIK on income distribution Original, disposable, adjusted disposable & final income by income quintile, 2011/12: 14 x 3.5 x5 x

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): Constant years to education age0.57 Education age below Education age above Above education age and above0.75

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

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

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

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