A climate investment trap in developing countries: higher cost of capital, investment suitability and path dependency perpetuate inequity in low-carbon finance

1. ‘Climate Investment Traps’
in developing countries
Investment Suitability, Path-dependency
and Higher cost of capital perpetuate
inequity in low-carbon finance
Waddesdon Club Research Conference
Nadia Ameli
Institute for Sustainable Resources, UCL

2. A call for a new global architecture of climate finance
“We have to recognize that if we don’t pause at this stage and settle the
financing framework, we’re going to have problems”

3. A climate investment trap
A climate investment trap occurs when climate-related investments remain
chronically insufficient, due to a set of self-reinforcing mechanisms
High cost of capital
Low emission reduction
• Low production
• High unemployment
• High instability
• Under-developed financial market
• High domestic risks
High risk-premiums Low climate investment
Worse climate impacts
Ameli et al. "Higher cost of finance exacerbates a climate investment trap in
developing economies." Nature Communications 12.1 (2021): 1-12.

4. Climate investments are unequal distributed globally
US & Canada
$83 bn
Latin America
& Caribbean
$35 bn
Western Europe
$105 bn
Eastern Europe &
Central Asia
$33 bn
Oceania
$9 bn
Middle East &
North Africa
$16 bn South Asia
$30 bn
East Asia & Pacific
$292 bn
Transregional
$11 bn
Sub-Saharan
Africa
$19 bn
CPI (2021). Global Landscape of Climate Finance 2021

5. … but also across developing countries
Data: BNEF wind and solar capacity additions between 2010-2019 (India and China are excluded)
World Bank classification: upper middle income (UMI), lower middle income (LMI), low income (LI)

6. * BNEF does not provide full data on financial transaction values so we use capacity additions as a proxy
… but also across developing countries

7. Investment suitability drives international private finance
The drivers of public and private sector investment and the effect of the Paris Agreement. Results of the feature model tested on 6
country-specific features: Economic fitness, electricity access (% of the population with access to electricity), renewables policy (Regulatory
Indicators for Sustainable Energy), ease of doing business, climate vulnerability, and renewables capacity level (logarithm of installed MWs).
Coefficient estimates (𝜃) for the period (2010-2019) and the effect of the Paris agreement (Δ𝜃) for the period 2016-2019 are given with
standard errors in brackets. N is the number of observations per estimation. *Significant at p < 0.01.
Public Private N
𝜃 ∆𝜃 𝜃 ∆𝜃
Economic fitness 1.34***
(0.02)
0.37***
(0.02)
1.69***
(0.01)
0.28***
(0.02)
1145
Electricity access 0.75***
(0.02)
-0.15***
(0.02)
1.69***
(0.03)
-0.28***
(0.03)
1153
Renewables policy 0.4
(0.02)
0.25***
(0.02)
1.19***
(0.02)
-0.29***
(0.02)
1123
Climate vulnerability -0.7*
(0.02)
0.05*
(0.02)
-1.21*
(0.02)
0.33*
(0.03)
1153
Ease of doing business 0.85***
(0.02)
-0.31***
(0.02)
1.07***
(0.02)
-0.3***
(0.02)
1148
Renewables capacity level 1.32***
(0.01)
0.1***
(0.02)
1.37***
(0.01)
0.02***
(0.02)
1156

8. Disparity in investment suitability across countries explains
inequalities in the distribution of private finance
Average investment suitability scores per income group. Charts show average feature scores
across income groups; upper middle-income (UMI), lower middle-income (LMI) and low-income (LI)
and in two time periods; pre-Paris (2010-2015) and post-Paris (2016-2019). Features are normalised
to between 0 and 1.

9. A track record of investments creates path dependency
Track record of renewables deployment  technological & financial learning  path-dependency

10. Investment unsuitability is reinforced by path dependency
Historical inequalities in financing are ‘locked-in’ across countries and perpetuate over time
41% of capacity
additions between
2010 and 2019 go
to Mexico and S.
Africa.

11. Escaping lock-in investment effects
Empirical relationship between relative probability of private investment and installed capacity.
Plots show the relative probability of private investment for each country against installed capacity.
Probabilities are normalised against the country with the highest probability of private investment (wind:
Argentina, solar: Mexico). Upper middle income (UMI), lower middle income (LMI) and low income (LI).

12. Access to finance varies significantly across countries
Energy transition in developing countries are affected by unequal access to
finance (“cost of capital”)
11.8%
9.2%
8.2%
6.8%
6.8%
6.6%
6.1%
5.8%
5.4%
5.1%
4.4%
4.2%
2.4%
9.2%
Ameli et al. "Higher cost of finance exacerbates a climate investment trap in
developing economies." Nature Communications 12.1 (2021): 1-12.

13. Scenarios implemented in the TIAM-UCL model
Ameli et al. "Higher cost of finance exacerbates a climate investment trap in
developing economies." Nature Communications 12.1 (2021): 1-12.
Scenarios Cost of Capital (CoC)
REG Regional CoC constant over the period
GBL Uniform CoC, 5.9% and 5.1% (low and high carbon)
FAST Regional differentiation until 2020 linear reduction to 2050
SLOW Regional differentiation until 2020 linear reduction to 2100
Cost of capital
for Africa

14. Impact of the cost of capital on the cost of low-carbon
transition in Africa
0
5
10
15
20
25
30
2020 2030 2040 2050 2060 2070
EJ
a)
0
50
100
150
200
2020 2030 2040 2050 2060 2070
Billion
USD
b)
• Cost of capital reduced from 11.8% (REG) to 5.9% (GLB)
• 35% more low-carbon electricity in 2050 (GLB)
• 20% lower emissions in 2050 (GLB)
• 2050 similar investment levels 80B $
Generation Investment

15. Impact of reduction policies on cost of capital
Generation Investment
• Low-carbon electricity is 43.1% and 6.5% higher for FAST and SLOW than REG in 2050
• Investment (cumulative 2020-2070) are $370 and $310 billion in FAST and SLOW (10%
and 9% more than REG respectively)

16. -1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
2020 2030 2040 2050 2060 2070
GtCO
2
REG C2050 C2100
CO2 emissions
• Net-zero emissions in Africa would be achieved in 2058 for FAST, in 2062 for SLOW and only
in 2066 for the REG
• FAST would allow AFR to reach net-zero emissions roughly 8 years earlier than in the REG
case
Impact of reduction policies on cost of capital

17. Key takeaways
Unequal access to capital and distributional inequities are inherent in
present climate finance structures
• Higher cost for RE & delayed low-carbon transitions
• Significant disparity in obtaining the necessary finance
Principle of equity
For a just global transition, it is necessary that access to finance is provided
equitably and at favourable terms in line with current agreements
COP26  climate commitments and increased cooperation will depend on
the delivery of “adequate and reliable finance” to meet climate targets
Art 9, Paris Agreement  financial flows need to meet the needs and
priorities of developing countries (particularly least developed countries) who
are financially constrained and extremely vulnerable to climate impacts

18. Final remarks
Distributional considerations/finance allocation & access to capital have
to be key pillars of future global climate finance architectures to avoid
‘climate investment traps’:
• Ensure an equitable distribution of finance amongst developing countries as
flows are driven by perception of the enabling investment environment
• mitigate the weakness in the investment environment
• de-risk entire sectors
• enable better climate policies and deliver coordinated action for low-
income and vulnerable countries
• Better alignment of public and private finance
• International efforts need to break the investment lock-ins/path-
dependency that perpetuate inequity in global climate finance
• Reframe international market finance by improving financing conditions to
accelerate the speed of the transition

19. THANK YOU!
Get in touch n.ameli@ucl.ac.uk
Acknowledgements
This research was made possible by support from three European Union’s
Horizon 2020 research and innovation programme, namely LINKS (grant
agreement number 802891), COP21 RIPPLES (Grant Agreement No 730427)
and GREEN-WIN (Grant Agreement No 642018); and the EPSRC as a Standard
Research Studentship (Grant number: EP/M507970/1).

20. Supplementary slides

21. Investment suitability
Indices tested as investment suitability features. A variety of indices were collated
from publicly available sources and Bloomberg New Energy Finance data and used to
build features to be tested in feature model.

22. Cost of capital
E is the value of equity and D is the value of debt
𝑬
𝑫 + 𝑬
and
𝑫
𝑫 + 𝑬
represent the percentage of equity and debt in the tot financing
𝐾𝑒 and𝐾𝑑 are the cost of equity and debt
T is the tax rate on corporate income
𝑊𝐴𝐶𝐶 =
𝐸
𝐷+𝐸
∗ 𝐾𝑒 +
𝐷
𝐷+𝐸
∗ 𝐾𝑑 (1 − 𝑇𝑎𝑥)

23. Regions in TIAM-UCL model WACC dataset
Africa Global emerging countries plus Africa risk premium
Australia Australia
Canada Canada
Central and South America Latin American countries
China China
Eastern Europe Bulgaria, Croatia, Czech Republic, Hungary, Poland,
Slovakia, Slovenia
Former Soviet Union Lithuania
India Emerging countries
Japan Japan
Mexico Mexico
Middle-East Asian countries
Other Developing Asia Asian countries
South Korea Asian countries
United Kingdom United Kingdom
USA USA
Western Europe Austria, Belgium, Denmark, Finland, France, Germany,
Greece, Ireland, Italy, Luxembourg, Malta, Netherlands,
Portugal, Spain, Sweden, Switzerland

24. Regions in TIAM-UCL model Country Risk Premium
Africa 8.11%
Australia 1.15%
Canada 0.00%
China 0.00%
Central and South America 4.03%
Eastern Europe 2.80%
Former Soviet Union 1.45%
India 3.11%
Mexico 7.28%
Middle-east 1.76%
South Korea 1.76%
Japan 0.00%
United Kingdom 0.00%
USA 0.00%
Other Developing Asia 1.76%
Western Europe 0.83%