Costs or benefits? Assessing the economy-wide effects of the electricity sector’s low carbon transition – The role of capital costs, divergent risk perceptions and premiums (updated title)

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Costs or benefits? Assessing the economy-wide effects of the electricity sector’s low carbon transition – The role of capital costs, divergent risk perceptions and premiums (updated title)

Gabriel Bachner¹, Jakob Mayer¹, Karl W. Steininger^1,2

1) Wegener Center for Climate and Global Change, University of Graz 2) Department of Economics, University of Graz

20. Österreichischer Klimatag, 25.4.2019, Wien

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Introduction

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 Electricity sector plays key role in transition to low carbon society

 Crucial to understand the macroeconomic effects of a transition of the electricity sector

 For assessing such effects integrated energy-economy models have been developed



use information from bottom-up energy sector models and feed it into top-down macroeconomic models



very sensitive to assumptions on technology costs



Especially “weighted average costs of capital” (WACC) strongly drive results, as renewables are very capital intensive

I NT RO DU C T I O N

𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 = 𝑖𝑖_𝐸𝐸 𝐸𝐸

𝐸𝐸 + 𝐷𝐷 + 𝑖𝑖^𝐷𝐷 𝐷𝐷 𝐸𝐸 + 𝐷𝐷

E… Equity [€]

D… Debt [€]

i_E… Return on Equity i_D… Return on Debt

 levelized costs of electricity (LCOE)

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1. WACC typically chosen without differentiation across technologies & regions



even though it has been shown that there are substantial differences

(Angelopoulos et al., 2016; Oxera, 2011; Sweerts et al., 2019; ECOFYS, 2014)



Ignores potential differences and changes in risk (perceptions), which would be reflected in different risk premiums

2. De-risking of renewables focuses on developing regions (Africa, MENA)



De-risking could be an effective leverage point also in developed regions (Schmidt, 2014)

3. Strong focus on the WACC of renewables, fossil fuels are left unattended



Fossil fuel based assets: technological-change-driven risk from loss of

competitiveness or stranding – even without any further climate policy (Mercure et al., 2018)



Moreover, future (climate) policy add to uncertainty (and risk) of fossil fuel based assets; e.g. “ratcheting-up” (Noothout et al., 2016)

I NT RO DU C T I O N

G ^{APS I N} L I T E RAT U RE

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We address the stated shortcomings to:

 demonstrate the importance of WACC differentiation in energy-economy modeling in general

 demonstrate the importance of possible diverging risk perceptions

For the case of a transition to a renewable electricity system in Europe

I NT RO DU C T I O N

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Methodology

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 Computable General Equilibrium (CGE) model (Mayer et al., 2019)



Economy-wide model



Multi-regional: Global, 16 regional aggregates



Europe: Austria (AUT), Greece (GRC), Northern, Eastern, Southern and Western Europe (NEU, EEU, SEU, WEU)



Multi-sectoral

 16 economic sectors

 Focus on electricity sector: eight different generation technologies; vintage based investment module

 Two scenarios:



Baseline: EU-reference scenario (Capros et al., 2016)



RES-e: transition to 100% renewables by 2050 (Pleßmann and Blechinger, 2017)

 by imposing a renewable portfolio standard (RPS), enforced by policy

 Comparison: RES-e versus Baseline until 2050

M E T H O DO L O GY

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Comparison (RES-e versus Baseline) is done under different WACC settings:

 UNIFORM: uniform WACC assumption of 8%

 MAIN: region and technology specific WACC



based on World Bank and IMF data as well as Steffen (2018)



Fossil technologies: high equity shares; Renewables: high debt shares

 DRR: “de-risking of renewables”



perceived policy signal (i.e. RPS), elevates investors’ trust in renewables  reduces WACC for renewables in the RES-e scenario



WACC reduced to levels as observed in recent years in Germany (Egli et al., 2018)

 FFR: “fossil fuel risk”



investors price-in carbon-content-related risks for new investments

 In EU-ref: technological change-driven

 In RES-e: in addition also risk from uncertain “ratcheting-up”

 COMBINED: DRR+FFR

M E T H O DO L O GY

WA C C S E T T I NGS

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M E T H O DO L O GY

WA C C S E T T I NGS

UNI MAIN DRR FFR (technological change-driven) 0%

10%

20%

30%

40%

UNI SF PE GS PV WI

AUT

0%

10%

20%

30%

40%

UNI SF PE GS PV WI

GRC

0%

10%

20%

30%

40%

UNI SF PE GS PV WI

EEU

0%

10%

20%

30%

40%

UNI SF PE GS PV WI

NEU

0%

10%

20%

30%

40%

UNI SF PE GS PV WI

SEU

0%

10%

20%

30%

40%

UNI SF PE GS PV WI

WEU

WACC rates across regions and technologies of the Uniform (UNI), Main (MAIN), Fossil Fuel Risk (FRR) and De-risking Renewables (DRR) settings. Whiskers show

the maximum of

assumed WACC increase from climate policy instability risk.

(UNI=Uniform WACC across all regions and technologies; SF=Solid Fossil Fuels (coal);

PE=Petrol (oil); GS=Gas;

PV=Photovoltaics;

WI=Wind)

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Results

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R ^{E S U LT S} – C H ANGE S I N U ^{NI T} C O S T S O F

E L E C T RI C I T Y G E NE RAT I O N

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R ^{E S U LT S} – C H ANGE S I N GD P

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Conclusions

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 Immediate positive effects emerge at macroeconomic scales when using more accurate data on capital costs



Significant bias in results from uniform WACC assumption

 De-risking renewables further improves the effects of renewable electricity transition across all regions in Europe



Particularly in eastern and southern Europe, where electricity production is relatively CO₂-intensive in the reference scenario

 To increase trust in renewables, credible long-term conditions are most important



Does not necessarily involve large direct costs; can be implemented unilaterally

 Investors’ expectations should be given a more prominent role



Going beyond carbon pricing

C O NC L U S I O NS

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Warum ist Ihre Forschung für eine Transformation zur low-carbon society relevant?

Zeigt, dass eine solche Transformation erheblichen volkswirtschaftlichen Zusatz-Nutzen bringen kann.

Zeigt Richtung für mögliche neue effektive Klimapolitik Maßnahmen, die über

Bepreisung von Treibhausgas-Emissionen hinaus gehen.

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Vielen Dank für die Aufmerksamkeit!

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BACKUP SLIDES

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M E T H O DO L O GY

S C E NARI O S : E L E C T RI C I T Y M I X I N 2 0 5 0

0% 20% 40% 60% 80% 100%

Nuclear Gas Petroleum Solid Fuels Hydro Biomass PV Wind 0% 20% 40% 60% 80%100%

AUT

0% 20% 40% 60% 80%100%

EEU

0% 20% 40% 60% 80%100%

GRC

0% 20% 40% 60% 80%100%

NEU

0% 20% 40% 60% 80%100%

SEU

0% 20% 40% 60% 80%100%

WEU

RES-e target EU-ref target Benchmark

Benchmark electricity mix (2011) across EU regions and mixes for 2050 for the reference scenarios (EU-ref) and for the large-scale expansion of renewables scenarios (RES-e).

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Figure 1: WACC rates across regions and technologies of the MAIN setting. (SF=Solid Fossil Fuels (coal); PE=Petrol (oil);

GS=Gas; BM=Biomass, WI=Wind, PV=Photovoltaics; HY=Hydropower; NU=Nuclear) Cost of Equity Cost of Debt Regional mean

12.9% 13.0% 13.5%

8.3%

5.0% 2.9%

13.0%

n.a.

9.8%

0%

5%

10%

15%

20%

SF PE GS BM WI PV HY NU mean

AUT

9.8% 9.9% 10.2%

6.6%

4.3% 2.9%

9.9% 9.9%

7.9%

0%

5%

10%

15%

20%

NEU

4.5% 4.5% 4.5%

4.9% 5.2% 5.3%

4.5%

n.a 4.8%

0%

5%

10%

15%

20%

GRC

8.6% 8.6% 8.9%

6.5% 5.0% 4.1%

8.6% 8.6% 7.4%

0%

5%

10%

15%

20%

SEU

11.3% 11.4% 11.5%

9.7% 8.5% 7.7%

11.4% 11.4% 10.3%

0%

5%

10%

15%

20%

EEU

14.7% 14.8% 15.4%

9.6%

5.8% 3.5%

14.8% 14.8%

11.7%

0%

5%

10%

15%

20%

WEU

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Figure A 1: Regional return on equity and return on debt rates, based on long-term country data on equity (IMF, 2019) and debt (ECB, 2019; World Bank, 2019) for non-financial corporations.

Return on Equity

(left panel) Return on Debt (right panel)

16.2%

14.2%

11.8%

10.7%

9.2%

4.4%

11.1%

0.0%

3.0%

6.0%

9.0%

12.0%

15.0%

18.0%

WEU AUT EEU NEU SEU GRC mean

2.4% 2.6% 3.0% 3.9%

5.4%

7.6%

4.1%

0.0%

3.0%

6.0%

9.0%

12.0%

15.0%

18.0%

AUT NEU WEU SEU GRC EEU mean

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Table A 1: OPEX, investment costs (2011 and 2050) and economic lifetime of electricity generation technologies (Pleßmann and Blechinger, 2017).

Investment costs

[EUR/kW] Economic lifetime

[years]

Operating expenditures [EUR/kWh]

2011 2050 AUT GRC EEU NEU SEU WEU

Solid Fuels 1,523 1,523 40 118 78 95 79 73 94

Petroleum 400 400 30 309 168 329 397 312 197

Gas 653 653 30 87 95 126 75 86 82

Nuclear 6,528 6,528 40 - - 89 84 81 102

Hydro 3,263 3,263 100 2 3 3 2 2 3

Biomass 2,485 1,951 30 26 11 82 38 16 28

PV 3,800 445 25 4 2 3 4 2 4

Wind 2,563 1,330 25 35 24 29 36 29 38

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Table A 1: Technology-specific LCOE 2011 in EUR/kWh (EC, 2016; ECOFYS, 2014) LCOE 2011

[EUR/kWh]

AUT GRC NEU WEU EEU SEU

Solid Fuels 0.11 0.07 0.08 0.08 0.10 0.06

Petroleum 0.27 0.15 0.36 0.17 0.30 0.29

Gas 0.08 0.09 0.07 0.07 0.12 0.08

Nuclear - - 0.10 0.10 0.10 0.09

Hydro 0.03 0.04 0.04 0.05 0.04 0.03

Wind 0.09 0.09 0.10 0.09 0.09 0.09

Biomass 0.10 0.04 0.07 0.09 0.08 0.03

Solar 0.13 0.09 0.15 0.12 0.13 0.09

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Costs or benefits? Assessing the economy-wide effects of the electricity sector’s low carbon transition – The role of capital costs, divergent risk perceptions and premiums (updated title)