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Climate Change Budgeting and
Planning
2
Historical Context
Rio 1992
Limits to Growth 1970s
Climate Science
and IPCC
GCF $100bn
KyotoUNFCCC
Mainstreaming and CPIERssince 2011
Source: IPCC AR5
3
Terminology
• Adaptation: actions that reduce the vulnerability to CC• Mitigation: actions that reduce net emissions
• Low regret: actions that are viable if CC doesn’t happen• Climate Risky: actions that are not viable without CC
• Mainstreaming: integrated in budget, not separate project• Performance Based Budgeting: budget linked to results
• Leveraging: added private finance created by public exp.
4
Climate Public Expenditure and Institutional ReviewsNepal CPEIR 2011 Policy, institutions, expenditure, PFM, SNA
Bangladesh CPEIR 2012 Policy, institutions, expenditure, PFM, SNALeading to tagging work
Thailand CPEIR 2012 Policy, institutions, expenditure, PFM, SNALeading to MOAC initiative
Cambodia CPEIR 2010CCFF 2014
Policy, institutions, expenditure, PFM, SNACosted action plans to support CC StrategyLinks expenditure to benefits
Samoa CPEIR 2012 Policy, institutions, expenditure, PFM, SNA
Indonesia MFF 2013 Mitigation spending, effectiveness, impactLeads to tagging, GPB Strategy
Vietnam Ongoing Policy, institutions, expenditure, PFM, SNALinks expenditure to CC policies
Africa Ongoing Expenditure and institutions
Philippines Ongoing
Latin America Planned
5
What is Climate Finance?
• UNFCCC & HLAG (on the $100bn), based on source of finance• CPI definition, based on tracking all steps• Distinguishes between direct and indirect
• OECD DAC definition for donor tracking• Principle objective (2), if the aim is direct and explicit• Significant objective (1), if secondary aim declared
• CPEIR definitions from country perspective• High-mid-low-marginal relevance• Scores (0%-100%)
6
CPEIR Definitions
7
Comparison of Classifications
8
Implications of Differences Bottom Top Bangladesh Cambodia Renewable energy 75%, if motivated mainly by cost 100% (mitigation) 75%-100% 80% Electricity (non-RE) -ve, if seen as increasing emissions 25% (?) if used for reducing losses or stopping
use of fuelwood or generators Some 25%
Some 0% Forestry 50%, if motivated mainly by incomes or
biodiversity 100%, if motivated entirely by mitigation 75%-100% 80%
Disaster management 25%, reflecting the increased frequency of extreme climate events
100%, if seen as fully relevant to climate change 80%
Disaster relief 0%, if seen as related only to current extreme climate, not changes
100%, if seen as part of a deliberate adaptation strategy
80%
Water supply and water quality
25%, reflecting increase in extreme climate events and/or rainfall/ET trends
100%, if seen as fully relevant to climate change, or if all used for climate proofing
Some 80% Some 50% Some 25%
Irrigation 25% (?) if considering only the increased frequency
100%, if all for climate proofing Some 75%-100% 50%
Agriculture Some 75%-100% Some 50%-75%
Treated as livelihoods
Biodiversity/conservation 0%, if unrelated to climate 50% (?) if partly affected by climate change 50% Eco-tourism 0% if not contributing to household
resilience or climate-related biodiversity 50% (?) if giving incomes for climate vulnerable, or helping climate-related biodiversity
50%
Livelihoods 0%, if not helping the climate vulnerable 50% (?) if highly focused on increasing the incomes for climate vulnerable
25%-50% Some 50%, Some 25%
Social protection (<) 25%, if designed primarily for current day risks
100%, if specifically designed to respond to increased climate risks
50%-75% 0%
Railway (<) 25%, if impact on emission is small 50%, if impact on emissions is large 50% Roads and infrastructure (<) 25%, if some proofing undertaken, of if
there are secondary benefits to welfare of climate vulnerable households
100%, if all spent on climate proofing Some 75%-100% Some 50%-75% Some 25%-50% Some 0%-25%
Some 80% Some 50% Some 25% Some 0%
Health (climate sensitive diseases)
25% (?) if considering only the increased frequency
100%, if all for climate proofing 80%
Health (General) <10%, if no focus on climate diseases (<?) 25%, if climate diseases important 25% Planning for CC 100% 100% 25%-50% 80% Governance/planning (General)
0%, if unrelated to climate change (<?) 25%, if supporting systems that could help climate planning
25%
9
Some of the Programme most difficult to classify
• Disaster relief – disasters will become more common, but should all relief to existing climate count• Climate proofing – knowing what part of the design is
for extreme events and is it protecting against existing or future extremes• Livelihoods – all vulnerability studies show that
increased incomes/savings is the best way to reduce vulnerability, but that includes a huge part of public expenditure• Social protection – it does reduce vulnerability, but it is
rarely linked with CC
10
Key Elements of CC Planning and Budgeting
Actual Expenditure
Effectiveness
Damage from Climate Change
CC Strategy
Budget Influence
Impact
Private Sector and Revenue
Policy
11
Application of methodology
12
Application of methodology 2
13
CC Damage and Loss
14
CC Modelling - IPCC
Best B1 = high growth esp. in tertiary sectors A1T = high growth, non-fossil energy A2 = slow growth and technological change B2 = mid growth, regional solutions A1B = high growth mixed technical changeWorst A1FI = high growth and fossil intensive
Source: IPCC AR4
Source: SREX Report 2012
Source: IPCC AR4
15
Downscaled models
Supnithadnaporn et al
16
CC Damage and Loss• Global – Stern Review suggested 5% of GDP ‘now and forever’• Agriculture
• Cambodia – last 10 years loss to flood, drought and dry spell is 0.71%, so by 2050 losses will be 1.42%, under B1 with no adaptation – loss is each year, accumulated
• FAO suggest varies from 5% to 75% lower in 2050• WB in India suggest degradation of farmland reduced national GDP by 1.7% in 2009
• Forestry losses depend on the national situation with forest stocks and dependency of GDP on forest exploitation
• Energy • Infrastructure losses 0.07% cumulative in Cambodia• Pollution related to urban emissions has health costs that reduce urban labour
productivity by 4.2% in US, 3.1% in China, 3.0% in India, 1.1%-1.5% in Philippines
• Accelerated infrastructure degradation costing 0.71% of GDP by 2050 in Cambodia, based on engineers estimates
• Damage to people/property from storms/floods cost average of 0.12% of GDP in last 10 years in Cambodia and will double by 2050
• WHO suggests increased burden from climate sensitive diseases: 0.85% GDP
17
Thailand’s Second National Communication to the UNFCCC• Climate change projections
• Uncertainty over trends in precipitation, but likely to increase• But climate variability and the frequency of extreme events is
already increasing and this will continue• And sea level rise is also clear
• Policy response to climate change• Disaster reduction management for floods, droughts etc• Support for farmers response• Some complex hydrology modelling• Early research on health effects• Support for local level resilience plans
• Mitigation is 70% power, but also 23% agriculture, mainly from rice paddy and livestock• Food security is essential, so agricultural mitigation is win-win
18
Other Research on CC Impact in Thailand and SE Asia
• TRF doing lots of work on climatology• ADB 2009. PAGE2002 model. Total cost of CC in SE Asia is
6.7% GDP/year by 2100. Adaptation of 0.2% GDP/year will reduce costs by 1.9% of GDP.• CSIRO 2010. Aquacrop model. Rice yields up 8%-28% by 2050
in Thailand/Laos. Mixed in rest of SE Asia.• DAI USAID 2013 Mekong ARCC. Aquacrop model. Most crop
yields declining by 3% to 12% by 2050, but some parts of Thailand increase by 5%.• WorldFish 2013 Coastal SE Asia, using changes in
vulnerability index.• WB global EACC, incl. Vietnam. IMPACT model (CERES). GDP
growth down 0-3% by 2050. Agri VA down 6-14%.
19
Selected International Analysis
• Lots of work with crop water modelling, based on FAO I&D Papers 24, 33 & 56 (eg CERES, CLICROP, CROPWAT, Aquacrop, WOFOST, DSSAT …)• Models integrating crop response with
economics (eg IFPRI IMPACT, FAO MOSAICC …)• Some statistical regression analysis (eg US/EU
Ricardian studies and UK CCRA time series)• Zoning produces more varied projections but
explores farmer response (eg in Brazil, FAO Ecocrop and FAO/IIASA Agro-Ecol Zone model)• HRW review of value of sophisticated models
20
Influence on Strategy and the
Budget
21
Budget Influence
• CC Planning and Budgeting ensures that existing spending is used in the most efficient ways• It facilitates marginal shifts towards those
programmes that can deliver higher benefits with CC (and away from those that are climate risky)• It gives a good overview of uncertainty about CC
and a good mix of low and high regret options• It guides any additional financing that may be
available, either international or domestic
22
Benefits to the Budget of CC Planning and Budgeting in MOAC• Smaller increases in yield variability reduces cost of
rice price support and other social support schemes• More resilient agricultural growth protects revenue
from crop processing• If rural communities have their own adaptation, relief
for floods and droughts costs less• Improved agricultural yields reduces pressure on
deforestation and emissions• More resilient crop production reduces export
variability and so vulnerability to oil shocks (because food and oil prices are linked)
Source: IMF Commodity Prices
23
Strategy Preparation
24
CC Finance Scenarios
Measuring Climate Expenditure
25
CPEIR Headlines on Climate Expenditure
26
27
Trends in Climate Spending
28
Breakdowns
29
Action Plans
30
Benefits Analysisand
Cost Effectiveness
31
Main processes
• Any indicator that is linked to rainfall variability can be assumed to double by 2050, as a working rule of thumb• This change can be expected to take place linearly
between now and 2050, as a first approximation• There may be some places where more detailed CC
evidence is available, especially on seasonality, but these are likely to be limited• Trends in average rainfall are generally difficult to model
in SE Asia, so it may be best to leave these at present• In a few cases, performance will be affected by
temperature (eg related to water balance, health …)
32
Main sources of evidence• Simulation models (eg the crop models, but also livestock …)
• may appear to require less data, but are only as good as the calibration, which does require data (often they are used with international parameters – eg standard FAO values)
Source: DDPM 2007Source: Saito et al 2006
• Statistical analysis, either geographical or time series• because of the big
structural difference over time and space, this may be best used to cross-check other evidence
• Expert opinion (including that of farmers)• essential to check with this and
especially valuable for more complex farmer response options
33
Effectiveness and Benefits
Has to accommodate three types of CC expenditure:A. Rescaling of existing expenditure simply because it
gives higher benefitsB. Modifying existing expenditure (eg ‘proofing’)C. New dedicated actions (which could be the
proofing element of modifying expenditure)
34
High and Low Regret and Climate Risky
35
Mitigation Effectiveness
Source: McKinsey 2010
Source: DNPI 2010
Source: Wetzelaer et al 2007
36
Impact of CC on Benefits - Type A
• Actions already producing reasonable BCRs• Benefits increased by CC (eg
because the action provides protection against temp/floods/drought and this protection becomes more important)• These actions should get a
marginally higher priority• The CC weight is the %
increase in benefits
37
Impact of CC on Benefits - Type ANote
Increase in average yield 10%Risk related benefits/yield related 50%
NPV Y1 Y2 Y3 Y4 Y5+Costs ($/ha)
Reserch investment 1 81 85Extension 81 85
Benefits ($/ha)Without CC
Average annual improved crop margins 2 276 16.5 16.5 16.5 16.5 16.5Risk related benefits 3 138 8.25 8.25 8.25 8.25 8.25
With CCAverage annual improved crop margins 276 16.5 16.5 16.5 16.5 16.5Risk related benefits 276 16.5 16.5 16.5 16.5 16.5
Net Benefits ($/ha) BCRWithout CC 2.56 252 -145 25 25 25 25With CC 3.42 390 -137 33 33 33 33
CC relevance measure 33%
1 According to http://ageconsearch.umn.edu/bitstream/126037/2/1-PS-Birthal.pdf, the global investment in drought resistent varieties is about $1bn, to date, with benefits of about 292m $/yr. The return on reseach investment is scare. Lybbert and Bell (2010) estimates that the investment in drought tolorance crossed $1 B. Gollin (2006) estimates an imrovement of yields in developping countries, generating wheat and maize at $149M and $143M per year respectively.2 According to above, typical yield increases are 10% to 15% from new varieties3 According to above source, risk aversion benefits are typically an additional 50% above aggregate benefits.
38
Impact of CC on Benefits: Type B
• Actions already producing reasonable BCRs• CC generates losses (mainly
because rehabilitation costs increase with floods)• Proofing involves some costs,
but reduces the losses• CC weight is the % change in
benefits• The estimate of losses
contributes to aggregate GDP losses
39
Adaptation Effectiveness
Wet season yield lost from rainfall variability, without CC /1 16.7%Wet season yield lost from rainfall variability, with CC /2 33%
Dry
Rice cultivation No CC With CCCosts of production, excl. labour & irrigation ($/ha) 75 75 120 221Labour (days/ha) 120 120 150 220Yield (t/ha) 2.00 1.60 3.20 4.40Price ($/t) 270 270 270 270Income ($/ha) 540 432 864 1188 13%Margin ($/ha) 165 57 369 417Margin ($/t) 83 36 115 95
NPV Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 Y11 Y12 Y13 Y14 Y15 Y16 Y17 Y18 Y19 Y20 Y21 Y22 Y23 Y24 Y25 Y26 Y27 Y28 Y29 Y30 Y31 Y32 Y33 Y34 Y35 Y36 Y37NEW CONSTRUCTION: no proofingCosts ($/ha)
Investment costs 1143 1200Rehab costs, without CC 1760 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105Rehab costs, with CC 3521 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211Annual operation and maintenance 1003 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60
Benefits ($/ha)Dry season (with/without CC) 6969 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417Wet season without CC 3409 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204Wet season with CC 5214 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312
Net Benefits ($/ha) BCRWithout CC 2.66 6472 -744 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456 456With CC 2.15 6516 -742 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458 458
NEW CONSTRUCTION: proofedCosts ($/ha)
Investment costs 1714 1800Rehab costs, with/without CC 880 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53Annual operation and maintenance 1504 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90
Benefits ($/ha)Dry season (with/without CC) 6969 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417Wet season without CC 3409 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204Wet season with CC 5214 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312
Net Benefits ($/ha) BCRWithout CC 2.53 7159 -1269 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531 531With CC 2.97 8964 -1161 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639 639
REHABILITATION: no proofingCosts ($/ha)
Investment costs 952 1000Rehab costs, without CC 1760 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105 105Rehab costs, with CC 3521 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211 211Annual operation and maintenance 836 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50
Benefits ($/ha)Dry season (with/without CC) 6969 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417Wet season without CC 3409 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204Wet season with CC 5214 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312
Net Benefits ($/ha) BCRWithout CC 2.92 6830 -534 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466 466With CC 2.29 6874 -532 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468 468
REHABILITATION: proofingCosts ($/ha)
Investment costs 1429 1500Rehab costs, with/without CC 880 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53Annual operation and maintenance 836 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50
Benefits ($/ha)Dry season (with/without CC) 6969 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417 417Wet season without CC 3409 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204 204Wet season with CC 5214 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312 312
Net Benefits ($/ha) BCRWithout CC 3.30 7233 -982 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518 518With CC 3.87 9038 -874 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626 626
Wet SeasonRainfed Irrigated
New, Unproofed
New, Proofed
Rehab, Unproofed
Rehab, Proofed
40
Supplementing Research with Expert Opinion
Benefit estimates based on whatever scientific evidence is available, Thailand, SE Asia or international.But they can also be based on expert opinion, eg using the structure below1.5-2.0 = the benefit, on its own, is strongly positive and easily enough to justify
the cost (public and/or private)
1.2-1.7 = the benefit, on its own, is just enough to justify the cost
0.7-1.3 = the benefit is about equal to the cost – probably not enough to justify, but not a disastrous waste of resources
0.3-0.8 = important contribution of benefits, but not enough to justify cost – so a secondary objective
0.1-0.4 = minor benefits, worth noting and protecting, but not at the expense of more importance benefits
Benefits
41
Benefits
42
Conclusions from Samoan CBA• Reliability of cost benefit analysis is subject to uncertainty and subjectivity
of assumptions
• The main output is not a quantitative analysis, but a qualitative assessment of strengths and weaknesses found through the definition of the methodology.
• Adaptation projects are harder to assess than mitigation ones because economic benefits are different from financial benefits.
• Benefits under a climate change scenario are higher than a no CC scenario by 3.6% to 15%. This figure can be used to advocate for climate change expenditure.
• Policy makers should start to include in their policies and in their CBAs the impact of the climate change because it can bias completely the profitability of an investment.
43
44
Using Benefits as a Relevance Scores
The score = (B – A) / B, whereA = the benefits that would be
generated by the action, if there was no CC
B = the benefits that would be generated with CC
Potentially used for estimating appropriate top-up funding for CC finance
AB
45
Modalities and the Private
Sector
46
Modalities
• Direct public expenditure• National Climate Fund, considered in Samoa and
Cambodia, but full of challenges
• Transfers and subsidies• Financial instruments through banks (eg loan
guarantees, cheap loans …)• Regulatory controls and promotional work (eg the
whole of the UK Carbon Plan)• Transfers to local government, with/without targeting• Public awareness and capacity building
47
Instruments and Leverage Ratios
48
Patterns of Expenditure (CPI)
49
Impact
50
Impact• Extent to which existing finance delivers the mitigation target or
reduces the damage loss from CC• (But international rule of thumb (Stern) that you can only expect to
avoid two thirds of the damage from CC)• Indonesia mitigation 15%• Cambodia adaptation 27.5%
• Complicated timing issues about investment now followed by impact later, so we can’t leave it all until 2050 – in fact, the benefits of a constant level of spending now roughly matches the need to offset increasingly high damage/loss
• To reduce CC damage loss by 2/3 would require about $1000m, in 2018, when the low growth scenario is only $275m
• So the CCAP will achieve only 27.5% of what could be achieved• Because adaptation funding usually gives higher BCRs that standard
investment, it is worth switching resources to adaptation
51
Avoiding lower GDP growth
52
Reducing the losses• There is a Green GDP Gap associated with resource loss• There will also be a large reduction in GDP growth from CC
damage and further resource degradation• To protect 7% growth (in Green GDP), and reverse these losses,
total public GE expenditure needs to rise from IDR 20tr in 2013 (weighted) to IDR 46tr in 2020 (data to be finalised), assuming switch to pro-private sector instruments
53
Overall Conclusions• So far, country systems for mainstreaming climate finance
have focused on description of patterns to reveal trends and the big picture• Plus a review of the policies and institutions• Next phase is to start using this to influence the budget by
linking it more clearly to policy• Two main (complementary) ways being explored
• Classifying expenditure according to policies - Vietnam• Linking expenditure to any existing results-based prioritisation –
Cambodia and Indonesia
• Both are challenging and need judgement• But the costs of failing to mainstream could stall growth
completely in the more vulnerable countries, by 2050
54
The END
(Thank goodness)
and Thank You