economic appraisal of climate change adaptation at the local level alistair hunt department of...
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Economic Appraisal of Climate Change Adaptation at the Local Level
Alistair Hunt Department of Economics,
University of Bath
University of Exeter September 24th 2009
Contents of Presentation
• Motivation for research
• Estimating economic welfare costs of CC impacts at local scale, within UK.
• Some aspects of the economics of adaptation to climate change
Motivation for Research
• Essentially practical
• Scope size of potential CC impact costs/benefits to inform national & sectoral decisions
• Formulation of policy on CC adaptation at any level, involves trade-offs:– Comparing costs of adaptation, versus future damages resulting from
inaction.– Relative risks facing different sectors/regions
Projected Baseline Impacts
‘without’ Climate Change (no adaptation)
Impacts(e.g. average annual total market and non-market
damages of flood)
Time2002 2030 2050 2080
Influence of Socio-economic change - e.g. increase in
number of properties, change in occupancy rates, change in value of property / contents
Stylised Analytical Framework: No CC Impacts/Adaptation
Historical analogue (1-250 yr flood)
(NB only linear to simplify presentation)
e.g. River Flooding in UK
Physical Impact Assessment
• Use of Socio-Economic scenarios to:– Quantify magnitude of physical impacts under CC
scenarios relative to climate baseline on consistent SE scenarios
– Inform unit values ( e.g. changing with GDP growth per capita)
• Use scenarios developed for UK Climate Impacts Programme – Up to 2050s, linear extrapolation to 2080s
Interpretation of Socio-Economic scenarios
• Key dimensions of socio-economic change include:
– Governance & capacity of institutions at different levels to manage change.
– Orientation of social and political values
4 scenarios (UKCIP, 2002) World markets National Enterprise Local Stewardship Global Sustainability
Use of SES : River flooding example
• Quantitative: population and household size
• Qualitative:
Socio-economic factor Socio-economic scenario GS NE LS WM Planning Policy - ve + ve ? + ve Building Design - ve + ve + ve + ve Insurance policy + ve ? ? + ve Overall net effect - ve + ve Same? + ve
Future Impacts‘with’ Climate Change & no
Adaptation(predicted change in return
period)
Projected Baseline‘without’ Climate
Change & no Adaptation
Time2002 2030 2050 2080
Gross annual average cost of climate change
Impact of climate change on return
period
Stylised Analytical Framework
Impacts(e.g. average annual total market and non-market
damages of flood)
Generic methods for linking climate variables with physical impacts
• Using historical analogues of weather extremes to identify impacts. – E.g. flooding events. – Sectors: Building, Transport
• Simulation modeling of behavioural change– E.g. carbon enrichment– Sectors: Tourism, Health, Agriculture and Biodiversity
• Stakeholder-led and Ad-hoc projections– E.g. retailing responses to warmer summers– Sectors: Retail & Manufacturing, Water, Energy
Physical Impact Assessment
• Climate data• Basis: UKCIP02 Climate scenarios
Data presented for:• precipitation & temperature• 5 X 5 km areas• individual months • in three time-slices of 30 years covering 2010 – 2100
Assume climate change manifests itself either by:• - changes in means of climate variable or;• - climate variability (extremes)
Results – 2080s time-slice Annual Average Welfare Costs (£ million, 2004 prices)
(-ve denotes benefit)
Low M-L M-H H
HealthMortality - summer 3 3 4 8 Mortality - winter -8 -8 -10 -15
AgricultureCrops - mean precpn. (Eng. only) 49 NQ NQ 294 Flooding (Eng & Wales) <1 18 2 -4
BiodiversitySelected species and habitats NQ NQ NQ NQ
TransportInfrastructure subsidence 35 19 62 101 Flooding & coastal inundation 13 19 19 26 Winter disruption & maintenance -102 NQ NQ -340
Built Environment & Cultural Heritage Flooding - fluv. & coastal (Eng. & Wales) -272 -470 419 353 Flooding - intra-urban -131 -100 368 32 Subsidence (Eng. only) 162 114 213 316
Results – 2080s time-slice Changes in Consumer Expenditure (£ million, 2004 prices)
TourismVisitor Spend. 14,830 11,280 12,620 28,930
EnergyHeating -1,200 -1,300 -2,100 -2,800 Cooling 300 100 300 1,200
-ve denotes reduction in consumer spend; +ve denotes increase in consumer spend
Annual Impact multipliers over baseline
(2011–2040 time period, undiscounted) Impact considered Cost multipliers
Road maintenance in summer (subsidence) and; winter (salting - ice)
13 – 15
(-) 1.3 – 1.6
Domestic property subsidence 12 - 15
Historic garden maintenance in Cornwall (lawn mowing and pest control)
1.2 – 1.5
Health impacts of hot summers in Hampshire
16 - 18
Future Impacts‘with’ Climate Change
& no Adaptation
Projected Baseline‘without’ Climate
Change & no Adaptation
Time2002 2030 2050 2080
Gross benefit of adaptation for
comparison with costs of adaptation
Future Impacts (‘with’ Climate Change) after
Adaptation(e.g. reduction in predicted
return period)
Residual Impacts of Climate Change
Stylised Analytical FrameworkImpacts
(e.g. average annual total market and non-market cost
of flood)
Application to Flood Management
• Riverine flood risks in Shrewsbury, Shropshire – Impacts
• Direct physical damage to residential and non-residential property
• Forgone output from short-term disruption to non-residential properties.
• Direct impacts on human health (mortality, injuries and stress).
Total damage costs associated with different flood
frequencies in Shrewsbury (£'000s) Average waiting time (yrs) between events/frequency per year
Average waiting time (yrs) between events 3 5 10 15 25 50 100 150 Infinity
Frequency per year 1 0.33 0.2 0.1 0.067 0.04 0.02 0.01 0.007 0
Damage category
Residential property 5 12 78 84 98 188 326 352 352
Ind/commercial (direct) 7 146 376 440 570 1217 1514 1558 1558
Car damage 76 128 256 256 256 256 290 306 306
Infrastructure damage 12 25 29 31 36 48 77 79 79
Health 8 15 29 55 108 115 122 133 133
Total damage (000) 107 325 767 866 1068 1824 2329 2427 2427
Area (damage X frequency) 35.62 28.78 54.62 55.07 55.07 36.48 20.73 7.93 16.18
Application to Flood Management
• Riverine flood risks in Shrewsbury, Shropshire – Adaptation
• Key problem: uncertainty in impacts may result in inappropriate level or type of adaptation
May be better to adopt a portfolio of options that reflect the decision-makers’ preferences relating to (economic?) optimisation versus reducing the chances of getting it wrong (variance from the “optimal”)
Flood management decision-making: portfolio analysis
• Portfolio Analysis– utilises the principle that since individual assets are
likely to have different and unpredictable rates of return over time, an investor should ensure that she maximises the expected rate of return and minimises the variance and co-variance of her asset portfolio as a whole rather than aim to manage the assets individually, (Markowitz (1952)).
As long as the co-variance of assets is low then the overall portfolio risk in minimised, for a given rate of overall return.
Flood management decision-making: portfolio analysis
• economic efficiency criterion (Net Present Value) is, here, the principal determinant of the measure of portfolio return. Also measure NPV variance as indicator of uncertainty
instead of appraisal of single flood response options using the economic efficiency criterion, a group of options are collectively appraised.
may be better able to capture variations in effectiveness of responses across a wider range of possible (climatic and socio-economic) futures.
NPV =
N
nnnn
N
nn
nN
nn
n
i
CB
i
C
i
B
000 111
Potential Flood Management Options Option Type Specific Options
Managing the Rural Landscape to reduce runoff
Rural infiltration
Rural catchment storage
Rural conveyance
Managing the Urban Landscape Urban storage
Urban infiltration
Urban conveyance
Managing Flood Events Pre-event measures
Forecasting and warning systems
Flood fighting actions
Collective damage avoidance
Individual damage avoidance e.g. property resistance
Managing Flood Losses Land use management
Flood-proofing
Land use planning
Building codes
Insurance, shared risk and compensation
Health and social measures
River Engineering River conveyance
Engineered flood storage
Flood water transfer
“Hard” defences
Economic returns to flood management options
• 3 options: hard defence; property resistance; warning system
• CBA for each option– Three degrees of implementation (20%, 50%, 100%)– Constant-scale economies in costs assumed– Four (consistent) CC/SE scenario combinations– Portfolios created from combinations of two options
and three options, each option disaggregated according to degree of implementation
Two-option Portfolio Analysis
0
2000
4000
6000
8000
10000
12000
14000
0 20000000 40000000 60000000 80000000 100000000
Variance
EN
PV
Three-option Portfolio Analysis
0
2000
4000
6000
8000
10000
12000
14000
0 10000000 20000000 30000000 40000000 50000000 60000000
Variance
EN
PV
Results
• Economic efficiency – variance trade-off exists for both 2 and 3 option portfolios
• Sub-optimal portfolios can be identified
• Hard defences generally contribute most to higher NPV and higher variance; property resistance option has opposite effect.
Conclusions• Seems possible to scope out identified climate change impacts
against specified climate scenarios, though socio-economic scenarios add significant (even more!) complexity
• Adaptation assessment may be enriched by use of portfolio analysis – incorporates uncertainty more explicitly into decision-making. But reliant on reliable, quantitative data relating to both the costs and benefits of identified adaptation options.
• Future research priorities may, inter alia, include:– Applying portfolio analysis within a portfolio of alternative decision rules – Improving representation of non-market values within decision rules– Application of non-market valuation techniques to evaluation of “softer”,
behavioural-based, adaptation options