1. Who emits most? An analysis of UK households’ CO2 emissions and their association with socio-economic factors Milena Büchs & Sylke V. Schnepf with Nick Bardsley RSS Workshop, 5 July 2012 ESRC grant RES-000-22-4083

2. Motivation Consensus on the need to implement environmental policies. Less known on the distributional impact of these policies There is an emerging literature that examines the role of socio-economic factors (SEF) for emissions – but there is a lack of research comparing the association between SEF and CO2 emissions between different emission areas –total hh emissions (Baiocchi 2010); –hh emissions from transport (Brand et al 2008, 2010) –direct hh emissions (Fahmy et al 2011) –per capita CO2 emissions (DEFRA 2008) –Per capita GHG emissions (Gough et al. 2011) –CO2 emissions at output area level and 7 OAC groups (Druckman eta l 2008, 2009) 2

3. Research question Which role do household characteristics play for household CO2 emissions, separately for –Home energy emissions (gas, electricity) –Transport emissions (motor fuels, public transport, flights) –Other indirect emissions from food and other consumption items –Total emissions Which areas of emissions should be targeted such that low income / disadvantaged households are least affected? 3

4. Data recap Merged the Expenditure and Food Survey 2006 and 2007 with the Living Cost and Food Survey 2008 and 2009; total household sample size 24,446 Conversion for expenditure to CO2 emissions used (‘mixed’) –Home energy & transport emissions: Exploit as much information as possible from LCF/EFS that can be merged with external sources (i.e. external price statistics (home energy, motor fuels); estimated passenger km (public transport) to estimate units of consumption. Apply DEFRA conversion factors to estimate CO2.) –Indirect emissions: use REAP to estimate CO2/£ expenditure for 56 COICOP consumption categories 4

5. Structure talk 1Annual average household emissions by emission area 2Association of socio-economic factors with emissions Household size Income Age Education 3 Which characteristics still matter conditional on income? –OLS regression results –Quantile regression results 5

6. 1 Annual mean hh CO2 emissions are 21.1 tonnes, with 5.1 t home energy, 5.3 t transport and 10.7 t indirect emissions 6 t % of total t Gas2.5 11 Indirect he and mf 2.612 Electricity2.1 10 Food 1.57 Other home energy0.5 2 Catering/hotels 1.15 Total Home energy 5.124Recreation 0.84 Clothing 0.73 Motor fuels2.4 11 Furniture, appliances, tools 0.73 Flights2.0 9 Cars 0.42 Public transport1.0 4 Other indirect 3.717 Total Transport5.325 Total Indirect 10.751

7. 2 Association of SES with CO2 emissions 7

8. The role of household size & composition Average % increase in CO2 emissions by each additional household member compared to single adult household 8 Note: all figures significant at 1%. Ns denotes not significant. Results derive from OLS regressions with dependent variable type of emission. Sample size 21920 for total CO2, home energy and indirect emissions, and 18764 for transport. Model fit is 0.36 for total Co2, 0.37 for indirect emissions, 0.14 for home energy and 0.16 for transport Total Co2 Home energy IndirectTransport Adults 2 nd 903797131 3 rd 29213135 4 th 189 27 5 th +141816ns Children 1 st 181224ns 2 nd 14121518 3 rd ns10ns-11

9. Annual hh CO2 emissions (tonnes) and income deciles 9

10. 10 th, 50 th, 90 th CO2 emissions percentiles over income deciles 10

11. Percentage increase of CO2 emissions if income increases by 1% (log log OLS regression) 11 All coefficients significant at the 1% level; households with 0 emissions in area excluded Total CO2 Indirect Home energy Transport Income0.60.70.30.9 Constant-1.1-2.1-0.2-4.2 Observations21914 18761 R-squared0.500.510.110.28

12. Change elasticity once focus on CO2 distribution (quantile regressions) 12 Total CO2 emissions Indirect emissions Quantile Income Elasticity

13. The role of age 13

14. Low total CO2 High total CO2l Low home energy High home energy Low transport High transport Low income 52.66.939.116.750.67.2 High income 4.151.815.135.76.748.6 Age<35 22.520.832.916.021.224.2 Age35-64 17.133.520.930.917.232.1 Age>65 43.610.327.619.544.410.8 High education 9.242.619.032.59.140.4 Low education 35.414.330.719.135.016.4 Rural 19.232.522.432.019.929.8 Urban 26.822.525.622.326.523.6 Workless hh 45.512.439.519.844.512.5 Female head 34.416.928.920.834.617.4 Male head 19.130.122.527.619.029.8 Ethnic 27.321.127.325.922.823.8 14 Row percent of hh in low (<=25 th percentile) and high (75 th percentile +) CO2 emission groups by hh characteristic Note: The table provides row percentages. I.e. 0 values for home energy and transport are included.

15. 3Log CO2 emissions and socio-economic factors; OLS 15 Bold printed coefficients significant at 1 % level, results conditional on household composition VARIABLESLn CO2 LN home energy Ln indirect emissions Ln transport Lnincome0.3670.1220.4080.529 Age0.0110.0140.0080.020 age2_100-0.011-0.009 -0.023 Agetop-0.0520.052-0.093-0.158 Female hh0.0450.0520.053-0.033 Education 12150.0510.0140.0650.090 Education 160.063-0.0080.0870.109 Workless hh0.0230.0520.019-0.091 Ethnicity-0.0570.012-0.1350.066 Rural hh0.0500.0330.0370.088 No vehicle-0.270-0.044-0.267-0.822 # bedroom0.1060.1660.0890.053 Constant-0.081-0.309-0.926-2.657 Observations21908 18963 R-squared0.6140.2510.6240.355

16. Tax burden expressed as proportion of disposable equivalised hh income assuming £100/ tonne CO2 tax 16

17. Conclusions Our research examines the role of socio-economic factors for different areas of emissions – something that has not yet been directly compared using the same dataset Household size impacts differently in areas of transport, energy and indirect emissions. While a second adult living in a household doubles indirect emissions he/she only increases home energy CO2 emissions by 30% Surprisingly, high education still significant positive influence even after controlling for income for indirect and transport Taxes on home energy are likely to affect disadvantaged households most (including older and workless households) Whilst taxes on transport are still regressive overall, they are less regressive than all other forms of taxes. But will hit households in rural areas (even conditional on their income) 17