Estimating the small area effects of austerity measures in the UK

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Dr Ben Anderson (benander@essex.ac.uk)
Dr Paola De Agostini (pdeago@essex.ac.uk) Tony Lawson (tlawso@essex.ac.uk)

Governments across Europe are starting to implement a range of cost-cutting and income- generating programmes in order to re-balance their fiscal budgets following substantial investments in stabilising domestic financial institutions in 2008 and 2009. One method of doing this has been to increase tax rates such as the increase in VAT in the UK from 17.5% to 20% from January 1st 2011. In this paper we explore the different spatial impact of this VAT rise on household expenditure on public and private transport and communication technology from 2006 to 2016. We do this by combining three elements: an agent-based dynamic population microsimulation model that produces projected snapshots of the UK population in 2006, 2011 and 2016; an expenditure system model based on the familiar Quadratic Almost Ideal Demand System approach; and synthetic small area census tables produced by projecting historical UK census data. Taken together these elements provide a toolkit for assessing the potential spatial impact of rising taxes or prices (or both) and we use them to compare small area projections of household expenditure under two scenarios. The first is a 'no intervention' scenario where prices and income align to UK government inflation forecasts and the second is a one-off non-reversed 2.5% increase in VAT on goods and services rated at 17.5% on 1st January 2011. We present results for different areas (rural vs urban/deprived vs affluent) and for different income groups within them and discuss the potential implications for the telecommunications industry and for the usage of public and private transport.

Paper presented at the 3rd General Conference of the International Microsimulation Association, 8-10 June 2011, Stockholm (http://www.scb.se/IMA2011)

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  • As car fuel price increases, demand falls but at smaller rate - 1% increase in price, 0.57% decrease in demand Demand for public transport falls slightly faster than price increases
  • 1% increase in car fuel price -> 0.1% increase in public transport demand But 1% increase in public transport price -> 0.31% increase in car fuel demand NB - s.d values -> greater heterogeneity of response to increase in price of public transport
  • Car fuel and public transport price rises increase demand for landline (but not mobile telephony) Land line prices and car fuel price rises (weakly) increase demand for internet
  • It looks like the dynamic population microsimulation has ‘over-weighted’ high spending public transport households in 2006? Low income households are defined as households with income below the poverty line (below 60% of median income ); high income households correspond to the highest 5% income in the sample; medium income households fall in the middle between the previous two categories.
  • Negatives -> use last positive value or zero
  • Negatives -> use last positive value or zero Definition problems with employment status Tenure not shown, number of rooms not shown 2+ cars too high as calc as residual of 0 + 1
  • There are a range of statistical methods Multilevel and hierarchical modelling etc But we’re not using them We’re creating a synthetic ‘Income Census’ We fill each ‘area’ (LSOA)… with ALL households from the relevant region Then give them fractional weights so that key constraint variables in each area match known Census distributions
  • NB: no model of internet ‘uptake’ here - change driven by ‘year’ variable in QUAIDS?
  • Basically flat although more variation in more income deprived areas & possible inability to offset higher costs by switching to something else - ref elasticities analysis
  • Town and Fringe | 532 14.99 14.99 Urban > 10K | 2,480 69.86 84.85 Village, Hamlet & Isolated Dwellings | 538 15.15 100.00
  • Basically flat, possibly slightly higher rises for income deprived areas
  • Basically flat, possibly slightly higher rises for income deprived areas
  • Essentially flat
  • Essentially flat
  • Notably less ability to offset rising costs in higher income deprivation areas - elasticities different at different part of the income distribution
  • Notably less ability to offset rising costs in higher income deprivation areas
  • Census: problems of inconsistent boundaries, definition changes
  • Census: problems of inconsistent boundaries, definition changes
  • Estimating the small area effects of austerity measures in the UK

    1. 1. Spatially Microsimulating UK ‘austerity’ measures <ul><li>Ben Anderson, Paola De Agostini & Tony Lawson </li></ul><ul><li>Centre for Research in Economic Sociology & Innovation </li></ul><ul><li>9 June 2011 </li></ul>
    2. 2. The menu <ul><ul><ul><li>Background </li></ul></ul></ul><ul><ul><ul><li>The pieces: </li></ul></ul></ul><ul><ul><ul><ul><li>Projecting the UK census </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Projecting a UK population sample </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Modeling Household Expenditure </li></ul></ul></ul></ul><ul><ul><ul><li>Combining the pieces </li></ul></ul></ul><ul><ul><ul><li>Preliminary results </li></ul></ul></ul><ul><ul><ul><li>Concluding thoughts </li></ul></ul></ul>
    3. 3. Background
    4. 4. What are we trying to achieve? <ul><ul><ul><li>Estimate changes in household expenditure if: </li></ul></ul></ul><ul><ul><ul><ul><li>Nothing different happens (base) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Something different happens </li></ul></ul></ul></ul><ul><ul><ul><li>Estimate change in small areas </li></ul></ul></ul><ul><ul><ul><ul><li>Now </li></ul></ul></ul></ul><ul><ul><ul><ul><li>In the ‘future’ - 2006, 2011, 2016 </li></ul></ul></ul></ul><ul><ul><ul><li>Why? </li></ul></ul></ul><ul><ul><ul><ul><li>Equity analysis - rural vs urban, deprived vs affluent etc </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Product and service infrastructure planning </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Local ‘revenue risk’ assessment </li></ul></ul></ul></ul>
    5. 5. So what pieces do we need? <ul><ul><ul><li>A way to project a household population (sample) </li></ul></ul></ul><ul><ul><ul><ul><li>A dynamic microsimulation </li></ul></ul></ul></ul><ul><ul><ul><li>A way to model household expenditure </li></ul></ul></ul><ul><ul><ul><ul><li>So that prices, preferences and demand drivers can be manipulated </li></ul></ul></ul></ul><ul><ul><ul><li>A way to project small area statistics </li></ul></ul></ul><ul><ul><ul><ul><li>‘ Census’ over time </li></ul></ul></ul></ul><ul><ul><ul><li>A way to combine these to produce small area estimates </li></ul></ul></ul><ul><ul><ul><ul><li>Spatial microsimulation </li></ul></ul></ul></ul>
    6. 6. Worked Example: <ul><ul><ul><li>VAT rise (Jan 1st 2011) </li></ul></ul></ul><ul><ul><ul><ul><li>17.5% -> 20% </li></ul></ul></ul></ul><ul><ul><ul><li>Spatial estimates of: </li></ul></ul></ul><ul><ul><ul><ul><li>Car fuel </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Public transport </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Telephony </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Mobile telephony </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Internet subscriptions </li></ul></ul></ul></ul><ul><ul><ul><li>“ Will additional fuel costs hit telecoms? And where?” </li></ul></ul></ul><ul><ul><ul><li>For 2011 - 2016 </li></ul></ul></ul>http://www.ifs.org.uk/budgets/budgetjune2010/browne.pdf
    7. 7. Household Sample Projection
    8. 8. Piece 1: Population projection 2001 2006 2011 2016 1991 1981 1971 2021 British Household Panel Survey Transition probabilities Logistic regressions <ul><ul><ul><li>PhD Project </li></ul></ul></ul><ul><ul><ul><ul><li>Tony Lawson </li></ul></ul></ul></ul><ul><ul><ul><li>Inspired by: </li></ul></ul></ul><ul><ul><ul><ul><li>SAGE, Pensim, Dynasim </li></ul></ul></ul></ul><ul><ul><ul><li>Netlogo </li></ul></ul></ul><ul><ul><ul><ul><li>‘ Agent based model’ </li></ul></ul></ul></ul><ul><ul><ul><li>Transition probabilities </li></ul></ul></ul><ul><ul><ul><ul><li>BHPS analysis </li></ul></ul></ul></ul><ul><ul><ul><ul><li>ONS Life Tables </li></ul></ul></ul></ul><ul><ul><ul><ul><li>SAGE Technical notes </li></ul></ul></ul></ul>Employment transition
    9. 9. Piece 1: Population projection (Income) 2001 2006 2011 2016 1991 1981 1971 2021 British Household Panel Survey Transition probabilities Logistic regressions If changes Import income from ‘similar’ household Matching by age/composition/employment etc Assume 5% p.a. income inflation Employment transition Expenditure and Food Survey (n = c 8,000 households) Projected Households and Expenditures (base)
    10. 10. Piece 1: Population projection (Validation) <ul><ul><ul><li>E.g. Composition </li></ul></ul></ul><ul><ul><ul><ul><li>Model vs observed BHPS </li></ul></ul></ul></ul>
    11. 11. Piece 1: Population projection - Results <ul><ul><ul><li>Projected: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul>Household Income
    12. 12. Piece 1: Population projection - Results <ul><ul><ul><li>Projected: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul>Household composition
    13. 13. Piece 1: Population projection - Results <ul><ul><ul><li>Projected: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul>Employment status of household response person
    14. 14. Piece 1: Population projection - Results <ul><ul><ul><li>Projected: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul>Age of household response person
    15. 15. Household Expenditure Projection
    16. 16. Piece 2: Expenditure modelling Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 British Household Panel Survey UK Census Projected Census Projected Households and Expenditures (base) Transition probabilities Area re-zoning Smoothing & Projection Holt-Winters non-seasonal smoothing, gravity-based projection Logistic regressions Projected Households and Expenditures (change scenario) Elasticities QUAIDS Demand System Model <ul><ul><ul><li>Quadratic Almost Ideal Demand System </li></ul></ul></ul><ul><ul><ul><ul><li>Banks, Blundell et al. 1997 </li></ul></ul></ul></ul><ul><ul><ul><ul><li>System of budget share equations </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Links the various expenditure items to prices, demographics, time (year) and each other </li></ul></ul></ul></ul><ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    17. 17. Piece 2: Expenditure modelling - Results <ul><ul><ul><li>We are going to use these later! </li></ul></ul></ul><ul><ul><ul><li>Coefficients for years not shown </li></ul></ul></ul>
    18. 18. Piece 2: Expenditure modelling - Results <ul><ul><ul><li>Price elasticity </li></ul></ul></ul><ul><ul><ul><ul><li>Own price are -ve </li></ul></ul></ul></ul> <ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    19. 19. Piece 2: Expenditure modelling - Results <ul><ul><ul><li>Price elasticity </li></ul></ul></ul><ul><ul><ul><ul><li>Own price are -ve </li></ul></ul></ul></ul> <ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    20. 20. Piece 2: Expenditure modelling - Results <ul><ul><ul><li>Price elasticity </li></ul></ul></ul><ul><ul><ul><ul><li>Own price are -ve </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Cross price </li></ul></ul></ul></ul> <ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    21. 21. Piece 2: Expenditure modelling - Results <ul><ul><ul><li>Price elasticity </li></ul></ul></ul><ul><ul><ul><ul><li>Own price are -ve </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Cross price </li></ul></ul></ul></ul>  <ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    22. 22. Piece 2: Expenditure projections (base) Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 Projected Households and Expenditures (base) QUAIDS Demand System Model <ul><ul><ul><li>QUAIDS relates prices, income, demographics and year to budget share </li></ul></ul></ul><ul><ul><ul><li>QUAIDs -> projected budget share for future years </li></ul></ul></ul><ul><ul><ul><li>We can model total expenditure as a function of income & demographics & time for future years </li></ul></ul></ul><ul><ul><ul><li>Projected budget share * projected total expenditure => projected expenditure </li></ul></ul></ul><ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    23. 23. Piece 2: Expenditure projections (2.5% VAT rise) Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 Projected Households and Expenditures (base) Elasticities Projected Households and Expenditures (change scenario) QUAIDS Demand System Model +2.5% VAT <ul><ul><ul><li>Increases prices to reflect 2.5% VAT on 1/1/2011 </li></ul></ul></ul><ul><ul><ul><li>Use QUAIDS to re-calculate budget shares </li></ul></ul></ul><ul><ul><ul><li>Etc </li></ul></ul></ul><ul><ul><ul><li>To 2016 </li></ul></ul></ul><ul><ul><ul><li>Variables: </li></ul></ul></ul><ul><ul><li>• Household income </li></ul></ul><ul><ul><li>• Number of persons </li></ul></ul><ul><ul><li>• Number of children </li></ul></ul><ul><ul><li>• Household composition </li></ul></ul><ul><ul><li>• Employment status </li></ul></ul><ul><ul><li>• Age </li></ul></ul><ul><ul><li>• Tenure </li></ul></ul><ul><ul><li>Year </li></ul></ul>
    24. 24. Piece 2: Expenditure projections - Results <ul><ul><ul><li>Mean weekly household expenditure (2006 prices) </li></ul></ul></ul>Telephone Mobile phone Car fuel Public transport ?
    25. 25. Next? Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 British Household Panel Survey UK Census Projected Census Projected Households and Expenditures (base) Transition probabilities Elasticities Projected Households and Expenditures (change scenario) QUAIDS Demand System Model Logistic regressions
    26. 26. Next? Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 British Household Panel Survey UK Census Projected Census Projected Households and Expenditures (base) Transition probabilities Elasticities Projected Households and Expenditures (change scenario) QUAIDS Demand System Model Logistic regressions Projected Households and Expenditures (change scenario) Small area estimates of expenditure Lower Layer Super Output Areas (LSOAs 2001) Spatial microsimulation (IPF)
    27. 27. Census Projection
    28. 28. Piece 3: Census projection - method 2001 2006 2011 2016 1991 1981 1971 2021 UK Census Projected Census Area re-zoning Smoothing & Projection Holt-Winters non-seasonal smoothing, gravity-based projection <ul><ul><ul><li>Small area boundaries change </li></ul></ul></ul><ul><ul><ul><ul><li>A lot! </li></ul></ul></ul></ul><ul><ul><ul><li>And so do definitions! </li></ul></ul></ul><ul><ul><ul><li>Aerial interpolation </li></ul></ul></ul><ul><ul><ul><ul><li>Update 1971/1981/1991 -> 2001 geography </li></ul></ul></ul></ul><ul><ul><ul><li>Smoothing & projection </li></ul></ul></ul><ul><ul><ul><ul><li>Negatives not allowed! </li></ul></ul></ul></ul><ul><ul><ul><li>Normalised against Government projections </li></ul></ul></ul>
    29. 29. Piece 3: Census projection - Results
    30. 30. Small Area Estimates
    31. 31. Putting the ‘pieces’ together Expenditure and Food Survey (n = c 8,000 households) 2001 2006 2011 2016 1991 1981 1971 2021 UK Census Projected Census Projected Households and Expenditures (base) Projected Households and Expenditures (change scenario) Small area estimates of expenditure Lower Layer Super Output Areas (LSOAs 2001) Spatial microsimulation (IPF)
    32. 32. Spatial microsimulation <ul><li>Survey data cases </li></ul>LSOA 1 in Region X LSOA 2 in Region X If region = X <ul><li>Constraints = variables common to survey and census tables </li></ul><ul><li>Cases iteratively re-weighted for each LSOA until the sample ‘fits’ the census results </li></ul>Census XXXX ‘constraint’ tables Weights Iterative proportional fitting Ballas et al (2005) etc
    33. 33. Small area estimates: 2001 expenditures Car fuel Public transport Equivalised income
    34. 34. Small area estimates: 2001 expenditures Landline Telephone Mobile telephone Equivalised income
    35. 35. Small area estimates: change over time 2001 2006 2016 Internet subscriptions (baseline)
    36. 36. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>IMD: Index of Multiple Deprivation 2010 Income score (deciles) </li></ul></ul></ul>
    37. 37. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>IMD: Index of Multiple Deprivation 2010 Income score (deciles) </li></ul></ul></ul><ul><ul><ul><li>Car fuel </li></ul></ul></ul>
    38. 38. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>Car fuel </li></ul></ul></ul>
    39. 39. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>IMD: Index of Multiple Deprivation 2010 Income score (deciles) </li></ul></ul></ul><ul><ul><ul><li>Public transport </li></ul></ul></ul>
    40. 40. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>Public transport </li></ul></ul></ul>
    41. 41. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>IMD: Index of Multiple Deprivation 2010 Income score (deciles) </li></ul></ul></ul><ul><ul><ul><li>Mobile telephone </li></ul></ul></ul>
    42. 42. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>Mobile telephone </li></ul></ul></ul>
    43. 43. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>IMD: Index of Multiple Deprivation 2010 Income score (deciles) </li></ul></ul></ul><ul><ul><ul><li>Landline telephone </li></ul></ul></ul>
    44. 44. Small area estimates: 2.5% VAT effect <ul><ul><ul><li>Landline telephone </li></ul></ul></ul>
    45. 45. Summary
    46. 46. So what pieces did we need? <ul><ul><ul><li>A way to project small area statistics </li></ul></ul></ul><ul><ul><ul><ul><li>‘ Census’ over time </li></ul></ul></ul></ul><ul><ul><ul><li>A way to project a household population (sample) </li></ul></ul></ul><ul><ul><ul><ul><li>A dynamic microsimulation </li></ul></ul></ul></ul><ul><ul><ul><li>A way to model household expenditure </li></ul></ul></ul><ul><ul><ul><ul><li>So that prices, preferences and demand drivers can be manipulated </li></ul></ul></ul></ul><ul><ul><ul><li>A way to combine these to produce small area estimates </li></ul></ul></ul><ul><ul><ul><ul><li>Spatial microsimulation </li></ul></ul></ul></ul>   
    47. 47. But how well did it work? I <ul><ul><ul><li>Household projection: </li></ul></ul></ul><ul><ul><ul><ul><li>Some strange effects for composition (may be a weighting issue) </li></ul></ul></ul></ul><ul><ul><ul><li>Demand system model </li></ul></ul></ul><ul><ul><ul><ul><li>Strange ‘peak’ for public transport </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Presumes constant relationships - although we did re-calculate elasticities in each year </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Oversimplified? </li></ul></ul></ul></ul><ul><ul><ul><li>Census projection: </li></ul></ul></ul><ul><ul><ul><ul><li>‘ best effort’ </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Will validate against Census 2011 results </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Unclear how to improve </li></ul></ul></ul></ul>?
    48. 48. But how well did it work? II <ul><ul><ul><li>Spatial microsimulation </li></ul></ul></ul><ul><ul><ul><ul><li>Depends on too few ‘constraints’ </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Probably ‘suppresses’ between-area differences </li></ul></ul></ul></ul><ul><ul><ul><li>Next steps: </li></ul></ul></ul><ul><ul><ul><ul><li>Revisit & expand census projection with 2011 Census data </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Expand system demand model </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Expand population projection model to new variables/processes </li></ul></ul></ul></ul><ul><ul><ul><li>And finally… </li></ul></ul></ul> ? 
    49. 49. Thank you! <ul><ul><ul><li>Try something more interesting </li></ul></ul></ul><ul><ul><ul><ul><li>e.g. household water and energy demand! </li></ul></ul></ul></ul><ul><ul><ul><li>Ben Anderson </li></ul></ul></ul><ul><ul><ul><ul><li>[email_address] </li></ul></ul></ul></ul><ul><ul><ul><ul><li>http: //cresi . essex .ac. uk/getperson ? personID=1 </li></ul></ul></ul></ul><ul><ul><ul><li>Paola De Agostini </li></ul></ul></ul><ul><ul><ul><ul><li>[email_address] </li></ul></ul></ul></ul><ul><ul><ul><ul><li>http: //cresi . essex .ac. uk/getperson ? personID=5 </li></ul></ul></ul></ul><ul><ul><ul><li>Tony Lawson </li></ul></ul></ul><ul><ul><ul><ul><li>[email_address] </li></ul></ul></ul></ul><ul><ul><ul><ul><li>http: //cresi . essex .ac. uk/getperson ? personID=6 </li></ul></ul></ul></ul>Mean weekly household water expenditure 2005/6

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