The Carbon Footprint of Indian Households. Nicole Grunewald, Mirjam Harteisen,Jann Lay, Jan Minx and Sebastian Renner

Transcription

1 The Carbon Footprint of Indian Households Nicole Grunewald, Mirjam Harteisen,Jann Lay, Jan Minx and Sebastian Renner

2 Hypothesis Research Questions: 1. What are the main determinants of the growing carbon footprint in fast growing emerging countries? 2. Which consumption categories are the most carbon intensive, which ones are the least intensive? 3. How will carbon emissions develop over time when household income increases?

3 Hypothesis Unique features: Detailed view on household carbon footprint in India Valuable insight for future climate & development research by adopting a micro perspective on carbon emissions Why focus on the household carbon footprint in India? We expect to see large income gains in this countries Accounting for emissions consumed rather than emissions produced fulfills equity criteria

4 Hypothesis Household Carbon Footprint 2004/05 Source: NSS 2006 and CSO 2005

5 Hypothesis Monthly per capita Income Footprint Monthly per capita Income Footprint Corr. Source: CSO 2005, NSS Monthly per capita Income Footprint Corr Corr Monthly per capita Income Corr Footprint Income (mthl. p.c. in Rupee) Income (mthl. p.c. in Rupee) Income - Carbon Footprint Relationship by Quintile Monthly per capita Income Footprint Corr Monthly per capita Income Footprint Corr.

6 Related Literature Parikh et al. (1997) estimate CO 2 requirements / carbon footprint of households in India with different incomes, rural and urban, estimations for 1990 and 2010 Differing energy intensities enable CO 2 reductions by changing consumption patterns Pachauri and Spreng (2002) analyze energy requirements of households in India for Higher energy requirements due to rising income and population Pachauri (2004) analyzes energy requirements of households in India controlling for household characteristics in 1993 and 1994 and divide 9 consumption categories Income matters but characteristics as well

7 Data NSS survey on Indian household expenditure Representative survey of India consisting households Data on overall household expenditure disaggregated to around 400 items Household characteristics like: rural or urban, type of housing, income class, status, size, religion IO Tables from Central Statistical Organization 2004 The whole Indian economy disaggregated to 130 sectors

8 Methodology - Carbon Intensities

9 Methodology - Carbon Intensities

10 Descriptive Analysis Emission Intensities of Indian Household Expenditure 04/05 Source: NSS 2006 and CSO 2005

11 Descriptive Analysis Household Expenditure 04/05 Urban and Rural Source: NSS 2006 and CSO 2005

12 Hypothesis Household Carbon Footprint 2004/05 Source: NSS 2006 and CSO 2005

13 Descriptive Analysis Expenditure categories with high carbon intensity and growing share of total expenditures: fuel and light: coal, electricity etc. Entertainment: recreation goods Toilet articles: soap, shampoo etc. Clothing Expenditure categories with low carbon intensity and growing share of total expenditures: Consumer services: telephone charges, barber etc. Education: books, school fees etc.

14 Methodology Household Carbon Footprint CF = + Income + β Characteristics + i i β0i β1 i i x i u i Where: CF i is the (log) carbon emissions by each household i Income i is measured as total expenditure of household i and in the following results it is represented by income quintiles Characteristics i are household control variables such as religion, gender of the household head, education u i is the error term

15 Hypothesis Monthly per capita Income Footprint Monthly per capita Income Footprint Corr. Source: CSO 2005, NSS Monthly per capita Income Footprint Corr Corr Monthly per capita Income Corr Footprint Income (mthl. p.c. in Rupee) Income (mthl. p.c. in Rupee) Income - Carbon Footprint Relationship by Quintile Monthly per capita Income Footprint Corr Monthly per capita Income Footprint Corr.

16 Results Determinants of the HH CO2 Footprint Income Determinants of the Carbon Footprint quint_5 quint_4 quint_3 quint_ Note: OLS regression, dependent variable is the (log) household carbon footprint, R 2 =0.87 and 124,643 Observations; Source: Authors estimations

17 Results Determinants of the HH CO2 Footprint Main Determinants of the Carbon Footprint hhsize_cu hhsize_sq hhsize urban Note: OLS regression, dependent variable is the (log) household carbon footprint, R 2 =0.87 and 124,643 Observations; Source: Authors estimations

18 Results Determinants of the HH CO2 Footprint Energy Determinants of the Carbon Footprint nocooking othercoooking electricity kerosine charcoal dung gas LPG Note: OLS regression, dependent variable is the (log) household carbon footprint, R 2 =0.87 and 124,643 Observations; Source: Authors estimations

19 Results Determinants of the HH CO2 Footprint Determinants of the Carbon Footprint edu1_sq edu1 age1_cu age1_sq age1 sex1 cerem christ islam hindu employee agrilab selfemplagri selfempl Note: OLS regression, dependent variable is the (log) household carbon footprint, R 2 =0.87 and 124,643 Observations; Source: Authors estimations

20 Results Income is the strongest driver of household carbon emissions Moving from the poorest quintile to the richest increases the household carbon footprint by more than 80% One further household member increases the carbon footprint by about 35% But household characteristics also play a role, female headed households and households of Hindu religion emit on average less The choice of energy source for cooking plays role, LPG households emit more then those using kerosene

21 Outlook There are currently household's living of less than 2$ ppp per day and are causing about 57% of total emissions If we would want to cut this number of household's living of less then 2$ ppp per day total into half (we anticipate that their income rises to more than 2$ ppp, total emissions could rise from 133kt CO 2 to 157kt CO 2 These scenarios could help countries to get realistic estimates about their future emissions

22 Conclusion Higher income leads to a higher carbon footprint especially due to the following consumptionn categories: Fuel and light, clothing and beverages The household carbon footprint of the richest quintile is almost five times the carbon footprint of the poorest quintile When reducing poverty future emissions will have to rise but a change in consumption habits such as energy sources can make this rise less steep

23 Thank you for your attention!

24 Outlook Income Elasticities building personal goods transport jewellery recreation house rent services toiletry entertainment medical goods education clothing fuellight tobacco food Note: TSLS regression, dependent variable is share of expenditure for each consumption category in total consumption, 101,662 Observations; Source: Authors estimations

25 Outlook Distribution of Income Groups and Respective Emissions Income Group N. Households Share Mean CO 2 in t Total CO2 in kt Share in total Low Middle High All Note: High > 10 $ ppp, Middle <10>2 $ppp, Low 2 $ppp; Source: Authors estimations