Transcript - University of Bath

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
Stylised Analytical Framework: No CC Impacts/Adaptation
Impacts
(e.g. average annual total
market and non-market
damages of flood)
e.g. River Flooding in UK
Influence of Socio-economic
change - e.g. increase in
number of properties, change in
occupancy rates, change in
value of property / contents
Projected Baseline
Impacts
‘without’ Climate
Change (no
adaptation)
Time
2002
Historical analogue
(1-250 yr flood)
2030
2050
2080
(NB only linear to
simplify presentation)
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
Planning Policy
Building Design
Insurance policy
Overall net effect
Socio-economic scenario
GS
NE
LS
- ve
+ ve
?
- ve
+ ve
+ ve
+ ve
?
?
- ve
+ ve
Same?
WM
+ ve
+ ve
+ ve
+ ve
Stylised Analytical Framework
Impacts
(e.g. average annual total
market and non-market
damages of flood)
Future Impacts
‘with’ Climate Change & no
Adaptation
(predicted change in return
period)
Gross annual
average cost of
climate change
Impact of climate
change on return
period
Projected Baseline
‘without’ Climate
Change & no
Adaptation
Time
2002
2030
2050
2080
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
3
-8
3
-8
4
-10
8
-15
49
<1
NQ
18
NQ
2
294
-4
NQ
NQ
NQ
NQ
35
13
-102
19
19
NQ
62
19
NQ
101
26
-340
-272
-131
162
-470
-100
114
419
368
213
353
32
316
Health
Mortality - summer
Mortality - winter
Agriculture
Crops - mean precpn. (Eng. only)
Flooding (Eng & Wales)
Biodiversity
Selected species and habitats
Transport
Infrastructure subsidence
Flooding & coastal inundation
Winter disruption & maintenance
Built Environment & Cultural Heritage
Flooding - fluv. & coastal (Eng. & Wales)
Flooding - intra-urban
Subsidence (Eng. only)
Results – 2080s time-slice
Changes in Consumer Expenditure (£ million, 2004 prices)
Tourism
Visitor Spend.
14,830
11,280
12,620
28,930
-1,200
300
-1,300
100
-2,100
300
-2,800
1,200
Energy
Heating
Cooling
-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
13 – 15
Road maintenance in summer
(subsidence) and;
winter (salting - ice)
(-) 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
Stylised Analytical Framework
Impacts
(e.g. average annual total
market and non-market cost
of flood)
Future Impacts
‘with’ Climate Change
& no Adaptation
Future Impacts (‘with’
Climate Change) after
Adaptation
(e.g. reduction in predicted
return period)
Gross benefit of
adaptation for
comparison with
costs of adaptation
Residual Impacts
of Climate Change
Projected Baseline
‘without’ Climate
Change & no
Adaptation
Time
2002
2030
2050
2080
Application to Flood Management
• Riverine flood risks in Shrewsbury,
Shropshire
– Impacts
• Direct physical damage to residential and nonresidential property
• Forgone output from short-term disruption to nonresidential 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
Frequency per year
1
3
5
10
15
25
50
100
150
Infinity
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
8
15
29
55
108
115
122
133
133
107
325
767
866
1068
1824
2329
2427
2427
35.62
28.78
54.62
55.07
55.07
36.48
20.73
7.93
16.18
Health
Total damage (000)
Area (damage X
frequency)
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
N
NPV =
Bn
 1  i 
n 0
n
N

n 0
N
Cn
1  i 
n

n 0
Bn  C n
1  i n
 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.
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
14000
12000
ENPV
10000
8000
6000
4000
2000
0
0
20000000
40000000
60000000
Variance
80000000 100000000
Three-option Portfolio Analysis
14000
12000
ENPV
10000
8000
6000
4000
2000
0
0
10000000 20000000 30000000 40000000 50000000 60000000
Variance
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