Climate Change Budgeting and Planning
Historical Context Mainstreaming and CPIERs since 2011 GCF $100bn Kyoto UNFCCC Climate Science and IPCC Rio 1992 Limits to Growth 1970s Source: IPCC AR5 2
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. 3
Climate Public Expenditure and Institutional Reviews Nepal CPEIR 2011 Policy, institutions, expenditure, PFM, SNA Bangladesh CPEIR 2012 Policy, institutions, expenditure, PFM, SNA Leading to tagging work Thailand CPEIR 2012 Policy, institutions, expenditure, PFM, SNA Leading to MOAC initiative Cambodia CPEIR 2010 Policy, institutions, expenditure, PFM, SNA CCFF 2014 Costed action plans to support CC Strategy Links expenditure to benefits Samoa CPEIR 2012 Policy, institutions, expenditure, PFM, SNA Indonesia MFF 2013 Mitigation spending, effectiveness, impact Leads to tagging, GPB Strategy Vietnam Ongoing Policy, institutions, expenditure, PFM, SNA Links expenditure to CC policies Africa Ongoing Expenditure and institutions Philippines Ongoing 4 Latin America Planned
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%) 5
CPEIR Definitions 6
Comparison of Classifications 7
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 Some 25% use of fuelwood or generators Some 0% Forestry 50%, if motivated mainly by incomes or 100%, if motivated entirely by mitigation 75%-100% 80% biodiversity Disaster management 25%, reflecting the increased frequency of 100%, if seen as fully relevant to climate change 80% extreme climate events Disaster relief 0%, if seen as related only to current 100%, if seen as part of a deliberate adaptation 80% extreme climate, not changes strategy Water supply and water 25%, reflecting increase in extreme climate 100%, if seen as fully relevant to climate change, Some 80% quality events and/or rainfall/ET trends or if all used for climate proofing Some 50% Some 25% Irrigation 25% (?) if considering only the increased 100%, if all for climate proofing Some 75%-100% 50% frequency Agriculture Some 75%-100% Treated a Some 50%-75% livelihoods Biodiversity/conservation 0%, if unrelated to climate 50% (?) if partly affected by climate change 50% Eco-tourism 0% if not contributing to household 50% (?) if giving incomes for climate vulnerable, 50% resilience or climate-related biodiversity or helping climate-related biodiversity Livelihoods 0%, if not helping the climate vulnerable 50% (?) if highly focused on increasing the 25%-50% Some 50% incomes for climate vulnerable Some 25% Social protection (<) 25%, if designed primarily for current day 100%, if specifically designed to respond to 50%-75% 0% risks increased climate risks 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 100%, if all spent on climate proofing Some 75%-100% Some 80% there are secondary benefits to welfare of Some 50%-75% Some 50% climate vulnerable households Some 25%-50% Some 25% Some 0%-25% Some 0% Health (climate sensitive 25% (?) if considering only the increased 100%, if all for climate proofing 80% diseases) frequency 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 0%, if unrelated to climate change (<?) 25%, if supporting systems that could help 25% 8 (General) climate planning
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 9
Key Elements of CC Planning and Budgeting Damage from CC Strategy Impact Climate Change Private Sector Budget and Revenue Effectiveness Influence Policy Actual Expenditure 10
Application of methodology 11
Application of methodology 2 12
CC Damage and Loss 13
CC Modelling - IPCC Source: IPCC AR4 Source: IPCC AR4 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 change 14 Worst A1FI = high growth and fossil intensive Source: SREX Report 2012
Downscaled models Supnithadnaporn et al 15
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 i ncreased burden from climate sensitive diseases: 0.85% GDP 16
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 17
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%. 18
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 19
Influence on Strategy and the Budget 20
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 21
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