LEVERAGING PRIVATE FINANCE

FOR CLIMATE MITIGATION THROUGHFOR CLIMATE MITIGATION THROUGH

POLICY DESIGN

Presentation by

Nick Johnstone

at

Joint OECD-GGGI Workshopp

Green Growth Development Paths for a Better Future

Paris, Nov. 22nd , 2012Paris, Nov. 22nd , 2012

Why expanding low-emission finance matters?1 Closing the emission gap1. Closing the emission gap

GtCO2e

GHG emissions projection – 2010-2050

90100110120130

2Outlook Baseline 450 ppm Core

3-6°C by 2100

5060708090

3 y

1020304050

2°C by 2100

02010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Source: OECD Environment Outlook to 2050

2

Build more of the right type of infrastructure now

Why expanding green, low-emission finance matters? 2 Closing the financing gap2. Closing the financing gap

Scale-up sources of capital, public/ private, international/ domesticShift sources from brown to green

Infrastructure needs (annual, in USDtn illustration, need to be adapted to country context)

3

Shift sources from brown to green

?2

2.5

?

1

1.5

?

?

0.5

1

Source: OECD illustration, based on estimates from WB, WEF, OECD and Kennedy and Corfee2012,”Mobilizing private sector investment in low carbon infrastructure”

0Actual spending in infrastructure

Infrastructure needs Mitigation and adaptation needs

How to leverage private sector investments?Elements of a Green Investment Policy FrameworkElements of a Green Investment Policy Framework

1. CLEAR GOALSStrategic goal setting and policy  

alignment2. ENABLING GREEN 

INVESTMENTEnabling policies for

4. RESOURCESHarnessing public and private resources and

5. ENGAGEMENTPromoting green 

b i d Enabling policies for competitive, open markets; 

incentives for green  investment

3. MOBILISING GREEN FINANCE 

private  resources and capacity

business and consumers behaviours

Financial policies, tools and instruments

Source: Corfee-Morlot et al., 2012 forthcoming, Towards a green investment policy framework: the case of low-carbon, climate -resilient infrastructure

Policy Questions (some examples)y p

• The role of different policy measures (e.g. FITs and RECs) on the p y ( g )allocation of private finance for projects

• The extent of crowding out/crowding in which exists between different public (i.e. grants) and private (i.e. equity) sources of finance ;

• The targeting of public support to reduce the risk of “(not) picking i ” dwinners” ; and,

• Implications of projects of different technological maturity for policy design design .

Background – Leveraging Private FinanceFinance

• Allocation of private finance towards ‘clean’ energy (and other en ironmental fields) has t o ke attributesenvironmental fields) has two key attributes

• Public policy context plays a key role in determining the returns on investmentinvestment

• Many of the expenditures are irreversible (i.e. long-lived and ‘specific’ capital) p )

Small differences in policy conditions can have long-lived implications for finance volumes across countries

Small changes in policy conditions can have significant implications for changes in flows across time

Methodological Approachg pp

Case studies are a useful way to assess these issues. OECD work in areas such as transport and energ across a range of OECD and non OECD countries as transport and energy across a range of OECD and non-OECD countries.

However, more formal empirical analysis can be a useful complement . Analysis of > 22 000 financial deals Steps to implement: Analysis of > 22,000 financial deals. Steps to implement:

- Development of commensurable (countries, years, sectors) database of policy measures (in progress)p y ( p g )

-Development of a relational database of finance (type of finance, project characteristics, organiszational attributes, etc….) (initiated)

- Links with other relevant relational databases (i.e. UDI/Platts, Orbis, PATSTAT etc…) (to be done)

Targeting Support Without “Picking Winners”

l i i l• Some general principles:

• Support a ‘portfolio’ of projects and technologies to diversify downside risk of getting it “wrong”y g g g

• Benefits of chosen portfolio should be robust with respect to information uncertainty (i.e. ancillary benefits)

• Identify “local general purpose” technologies and investments which complement a variety of emission-reducing strategies

=> An example related to renewable energy

An Example: Intermittency of (some) Renwables and Targeting of Incentivesg g

Challenge of Increased Penetration of RenewablesRenewables

• The most important renewable energy sources (wind, solar, p gy (ocean/tide) are ‘intermittent’

• Generation potential is subject to significant temporal variation (minutes hours days seasons) which is uncertain and often(minutes, hours, days, seasons), which is uncertain and often correlated, and negatively correlated with peak demand (in some cases)

• This means that increased capacit of rene able energ• This means that increased capacity of renewable energy generation is not a perfect substitute for ‘dispatchable’ generation capacity (e.g. fossil fuels)

• Challenge of LOLP becomes greater as share rises – note that some countries have targets > 40%, where capacity credit starts to converge to zero

Means of Overcoming Intermittency

• Reduce correlation of variation in intermittent sources and/or allow for ex ante/ex post adjustment. How?

o “Back up” dispatchable sources (include some hydro)

o Disperse (space) and diverse (type) of sourceso Disperse (space) and diverse (type) of sources

o Improvements in load management and distribution

o Trade in electricity services (states, countries) o Trade in electricity services (states, countries)

o Investment in advanced energy storage

o Malleability of demand (e.g. smart grids)

• Benefits hypothesised to vary at different levels of ‘penetration’ of intermittent renewable power

11

Summary Results of Empirical Model(Estimated Effects of ‘Strategy’ Variables)( gy )

Although ECF mostly

depends on ecological

factors (wind speed),

it is also significantly

ff d b haffected by other

explanatory variables

Note. Summary results (elasticities) for the European sample (21 countries – 322 obs). Source: D. Benatia et al. ‘Increasing the Productivity and Penetration of Intermittent Renewable Energy Power Plants’ (ENV/WPCID(2012)2).

Benefits of Investing in Transmission Capacity: Simulation of Capacity Requirements to Meet Penetration T tTargets

.12

2250

09

.1

.11

.1.1

2R

200

2G

W

06

.07

.07

.08

.09

.08

WP

EN

_EU

R

015

0C

apac

ity in

G

.05.05

.06.06

.04

.06

5010

0

2010 2012 2014 2016 2018 2020Product

WCAP_ABS WCAP_denspathWCAP_congpath WPEN_EUR

13

Benefits of Investing in Transmission Capacity:Value of Capital Stock

4020

40

$200

9 bi

llion

-20

$-4

0

2012 2015 2018 2020

mean of cost_denspath mean of cost_densify

14

mean of cost_congpath mean of cost_congestion

Asset Finance for ‘New Build’ Renewable Energy Projects* ($US Million)Energy Projects* ($US Million)

* Wind, solar, geothermal, biomass, waste, small hydro. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming). Note – only ‘new build’

Exposure to “New Energy” of Asset Finance ProvidersProviders

Note: Based on Weighted Mid-Point of BNEF Classes. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

% of Renewable Energy Projects* Financed from Balance Sheetfrom Balance Sheet

100%

70%

80%

90%

40%

50%

60%

10%

20%

30%

0%

* Wind, solar, geothermal, biomass, waste, small hydro. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Targeting of Grants for Renewable Energy Projects in Selected Countries (1990-2011)Selected Countries (1990 2011)

United States Canada

GP_CapitalSubsidy

GP_Demonstration

GP_CapitalSubsidy

GP_Demonstration

GP_ProductDevelopment

GP_PureResearch

GP_ProductDevelopment

GP_PureResearch

Australia China

GP_CapitalSubsidy

GP_Demonstration

GP ProductDevelopment

GP_CapitalSubsidy

GP_Demonstration

GP ProductDevelopmentGP_ProductDevelopment

GP_PureResearch

GP_ProductDevelopment

GP_PureResearch

Largest Grant-Giving Agencies (all “new energy” 2000 2012)(all “new energy” – 2000-2012)

$US Million Recipients > $50M

Asian Development Bank 1257.25 China, Indonesia, Nepal, Sri Lanka, Philippines, Thailand, Vietnam

Inter-American Development Bank 1102.97 Argentina, Barbados, Bolivia, Dominican Republic, Nicaragua, Peru

Norway Ministry of Foreign Affairs 1000 Brazil

Japan Int’l Cooperation Agency 988.4 Egypt, Indonesia, Kenya, Vietnam

World Bank 785.2 India, Uganda, Philippines, Thailand, Vietnam

Agence Francaise de Developpement 421.9 Kenya, Morocco, Vietnam

European Investment Bank 338.6 China, Nicaragua, South Africa

Federal Republic of Germany 257.25 Kenya, South Africa, Chinap y y , ,

European Commission 196.6 Bulgaria

Nordic Investment Bank 146.6 Lithuania

International Finance Corp 71 7 South AfricaInternational Finance Corp 71.7 South Africa

International Bank for R&D 62.2 Argentina Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Main North-South Asset Finance Flows in Renewable Energy* (2000 2012)Renewable Energy* (2000-2012)

* Wind, solar, geothermal, biomass, waste, small hydro. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Main North-South VC Flows in Renewable Energy* (2000 2012)Energy* (2000-2012)

* Wind, solar, geothermal, biomass, waste, small hydro. Source: OECD “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Estimated Effects of FITs/RECs on the Value of Assets (Preliminary)Assets (Preliminary)

Note: Figure shows the estimated elasticity in terms of disclosed transaction values of assets per

22

Note: Figure shows the estimated elasticity in terms of disclosed transaction values of assets per MW to a 1% increase in the level of the respective policy measures. Unbalanced panel of 31 countries (OECD & BRICs) over 12 years (2000-2012). Unfilled bars indicate not statistically significant at 5% level. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Estimated Effects of Different Renewable Energy Project Characteristics on Gearing Ratio (Preliminary)

0.05

0

-0.05

0 15

-0.1

-0.2

-0.15

Note: Elasticities for continuous variables and marginal effects for discrete variables. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

Estimated Effects of Policy Leveraging on Private Finance Flows (Preliminary)Private Finance Flows (Preliminary)

1000

1200

800

on

400

600

$U

S M

illi

o

200

4

0

No

Yes No

Yes No

Yes No

Yes No

Yes No

Yes No

Yes

Capital Subsidy** Prod Dvlpmt Research FP_single*** FP_stream*** FIT_d* REC_d

24

Note: Figure shows predicted effect of the presence of different policies on allocation of private finance towards different clean energy projects. Dotted line represents mean value. *’s represent degree of significance. Source: OECD Project on “Leveraging Private Finance for Clean Energy Through Public Policy Design: Finding Evidence from Micro-Data” (OECD, forthcoming)

What role for governments?There is no one-size-fits-allThere is no one-size-fits-all

London

• Specific country contexts (resources and capacity, maturity of financial markets, access to international climate finance)

• Specific sectors (transport, energy)

S ifi h ll f d t ti Lagos

• Specific challenges of adaptation finance

• Staged approach: Short-term vs. g pplong-term responses

Jakarta

25

Tailor government’s interventions to specific challenges and capacities 2

5

MORE INFORMATION AT:

WWW.OECD.ORG/ENVIRONMENT/FINANCEWWW.OECD.ORG/ENVIRONMENT/FINANCE

&

WWW OECD ORG/ENV/CC/FINANCINGWWW.OECD.ORG/ENV/CC/FINANCING

&

WWW.OECD.ORG/ENVIRONMENT/INNOVATION

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