Measuring Social Transfers in Kind in the UK

Richard Tonkin, James Lewis & Nathan Thomas2nd - 4th 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• 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:

Bottom 2nd 3rd 4th Top All house-holds

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000 School meals and Healthy Start Vouchers

Bus travel subsidy

Rail travel subsidy

Housing subsidy

National health service

Education

Average per household (£ per year)

Impact of STIK on income distribution

Original, disposable, adjusted disposable & final income by income quintile, 2011/12:

Bottom 2nd 3rd 4th Top All households 0

10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

Original income

Disposable income

Adjusted disposable income

Final income

Average per household (£ per year)

14 x3.5 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 0.46

0 - 3 0.41

3 years to education age 0.57

Education age below 14 0.69

Education age above 13 0.95

Above education age - 54 0.54

55 - 64 0.60

65 - 74 0.67

75 and above 0.75

Impact of STIK on poverty statistics

Relative at-risk-of-poverty rates, 2011/12:

0

2

4

6

8

10

12

14

16

18

Percentages

• 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:

Under 18 18-24 25-49 50-64 65+0

5

10

15

20

25

30

Disposable income (OECD-modified)

Adjusted disposable income (OECD-modi-fied)

Adjusted disposable income (SNA)

Percentages

Impact of STIK on poverty statistics

Relative at-risk-of-poverty rates by household type, 2011/12:

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2+

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2 a

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Retired Non-retired

0

5

10

15

20

25

30

35

Disposable income (OECD-modified)

Adjusted disposable income (OECD-mod-ified)

Adjusted disposable income (SNA)

Percentages

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