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Practices by proxy: Climate, Consumption and Water

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Anderson, B., Browne, A., and Medd, W., (2012) Practices by proxy: climate, consumption and water. Paper presented at Living Costs and Food Survey user meeting, Tuesday 20 March 2012 at the Royal Statistical Society, London

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Practices by proxy: Climate, Consumption and Water

  1. 1. Practices by proxy:Climate, Consumption andWaterDr Ben AndersonDepartment of Sociology, University of Essex &Lancaster Environment CentreESRC Sustainable Practices Research Group20 March 2012
  2. 2. Practices: Climate, Consumption and WaterWhy?How?What?Where next?
  3. 3. Why?
  4. 4. Water is (going to be) a problem Supply problems: » Locally/regionally scarce » Climate change effects? Energy problems: » ‘Clean’ water costs and ‘clean’ is a moving target Demand problems: » 50% used by households » Drivers not well understood » Climate change effects? Demographic problems » Increasing single person households Source: Environment Agency, 2008
  5. 5. Water is (going to be) a problem  With no ‘behaviour’ change and no flow controls 2050 Source: DEFRA, 2011
  6. 6. Micro water: Conceptual Framework ‘habits’ Why people don’t do ‘bodily and mental routines’ what they ‘should’ ‘permanent dispositions’ Consumption = f(price + demographics + practices + attitudes) + error Regulation/ Education Market/ ?! ? Information Supply Exhortation Policy levers Climate change
  7. 7. What is currently unclear… Consumption Price Demographics Practices Attitudes Error Climate change (uncertainty/things we can’t measure)
  8. 8. What is currently unclear… Consumption Price Demographics Practices Attitudes Error Climate change (uncertainty/things we can’t measure)
  9. 9. What is currently unclear… Consumption Price Demographics Practices Attitudes Error Climate change (uncertainty/things we can’t measure)
  10. 10. What is currently unclear… Consumption Price Demographics Practices Attitudes Education Information Exhortation? Error Climate change (uncertainty/things we can’t measure)
  11. 11. What is currently unclear… Consumption Price Demographics Practices Attitudes Error Climate change (uncertainty/things we can’t measure)
  12. 12. How?
  13. 13. Data I (Household water demand) Ideal Proxy (EFS 2002-2009) water (l/day) £ water/week Demographics Demographics Shampoo,soap Fruit & Veg detergents Practices £/week Tea, coffee, juices Garden products Price Price Attitudes Attitudes
  14. 14. Data II (Weather/Climate)  MetOffice Regional Weather records Weather data http://www.metoffice.gov.uk/climate/uk/  Linked to 25 £5.05 – household government office region £5.00 – Lagged survey month 20 £4.95 £4.90  Observed 15 £4.85 £4.80 – 10 Mean rainfall £4.75 £4.70 –5 Number of rain days £4.65 –0 Mean temperature £4.60 £4.55 – Mean sunshine hours january february march april may june july august october september december november Climate data  3 year anomalies Water £/week Mean rainfall (cm) Mean number raindays Mean sunshine Mean temperature hours (/10)
  15. 15. Modelling approach 2005 prices £7.00 40.00% Selection: £6.00 35.00% 30.00% £5.00 – Have water meter (England) £4.00 25.00% 20.00% £3.00 15.00% £2.00 10.00% £1.00 5.00% £0.00 0.00% 2002 2003 2004 2005 2006 2007 2008 2009 No water me- Has water % metered ter meter
  16. 16. Modelling approach 2005 prices All households 39121 Selection: Metered 11119 – Have water meter (England) Separate water & 1387 – Pay water & sewerage combined sewerage Remaining 9732
  17. 17. Modelling approach 2005 prices All households 39121 Selection: Metered 11119 – Have water meter (England) Separate water & 1387 – Pay water & sewerage combined sewerage Split sample into ‘seasons’ 20 £4.90 Remaining 9732 15 £4.85 10 £4.80 5 £4.75 0 £4.70 Winter (Dec – Feb) Spring (Mar – May) Summer (Jun – Aug) Autumn (Sep – Nov) Water £/week Mean rainfall (cm) Mean number raindays Mean sunshine Mean temperature hours (/10)
  18. 18. Modelling approach 2005 prices Selection: Proxy (EFS 2002-2009) – Have water meter (England) – Pay water & sewerage combined £ water/week Model 1 – Demographics & practices, no weather/ Demographics climate Fruit & Veg Shampoo,soap Model 2 by season £/week detergents – includes lagged weather & climate Garden products Tea, coffee, juices Plus controls: Price – Ownership of dishwasher, income, Climate data Weather data region, tenure, number rooms, number of cars, number of earners, Attitudes accommodation type
  19. 19. What?
  20. 20. Model 1: Demographics & practices Contributions to model Practices Illness, age, gender & ethnicity of HRP Age composition (adults) Age composition (young people) R2 change in r2 Cars, earners, employment, composition Housing type, rooms, tenure Govt Office Region & Year Washing machine, dishwasher, income 0 0.05 0.1 0.15 0.2 0.25 0.3
  21. 21. Model 1: Demographic effects N adults 70+ N adults 65-70 N adults 60-65 N adults 45-60 N female adults < 45 N male adults < 45 N single females 16-18 N single males 16-18 N Children 14-16 N Children < 14 -0.8 -0.3 0.2 0.7 1.2 b
  22. 22. Model 1: ‘Practices’ effects Contributions to model Plants, flowers, seeds Lawn mowers Garden tools Kitchen gloves/cloths Detergents/washing powder Laundry/Laundrettes Soap/shower gel Mineral/spring water Vegetable juices Fruit juices (incl squash) Coffee Tea Pasta Rice Leaf & stem vegetables Potatoes -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 b
  23. 23. Model 2: Demographics & practices & weather Contributions to model (all seasons) Weather/climate Practices Illness, age, gender & ethnicity of HRP Age composition (adults) Age composition (young people) R2 change in r2 Cars, earners, employment, composition Housing type, rooms, tenure Govt Office Region Washing machine, dishwasher, income 0 0.05 0.1 0.15 0.2 0.25 0.3
  24. 24. Model 2: Weather effects Only in Autumn: Unusually hot & dry (rain days, 3 year anom) Unusually hot & dry (rainfall, 3 year anom) Mean temperature (3 year anom) Mean temperature Mean sunshine (3 year anom) Mean sunshine Rain days (3 year anom) Rain days Mean rainfall (3 year anom) Mean rainfall -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 b
  25. 25. Conclusions The practice proxies approach offers value? The weather data doesnt? Confounding problems? – Expenditures as proxies? – Garden/soil type? – Period of water use? – Included sewerage costs? – Poorly matched and coarse grained weather regions? – Consumer water saving responses to dry weather?
  26. 26. Where next?• Multilevel model? – Weather data clustered – But is it worth it?• More accurate water bill period? – Closer match to weather• Better geo-coding? – More accurate match to weather, soils, water prices/company Practices Survey  Linked to water meter data Small area estimates of demand  Census 2001 – 2011
  27. 27. Where next?• Multilevel model? – Weather data clustered – But is it worth it?• More accurate water bill period? – Closer match to weather• Better geo-coding? – More accurate match to weather, soils, water prices/company Practices Survey  Linked to water meter data Small area estimates of demand  Census 2001 – 2011 Application to energy demand?
  28. 28. Thank you!• ESRC Sustainable Practices Research Group • www.sprg.ac.uk/projects-fellowships/patterns-of-waterContact: – Ben Anderson (benander@essex.ac.uk)

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