Estimation of carbon cost pass-through in electricity markets

Transcription

1 Estimation of carbon cost pass-through in electricity markets B. Hintermann a H. Fell b H. Vollebergh c a University of Basel b Colorado School of Mines c Netherlands Environmental Assessment Agency IEW 2013, June Paris 1 / 28

2 Motivation Price for CO 2 emissions in EU since 2005 Carbon cost passed through to consumers First two phases: allocation mostly for free Research question: To what extent are carbon costs passed through to electricity prices? 2 / 28

3 Motivation Price for CO 2 emissions in EU since 2005 Carbon cost passed through to consumers First two phases: allocation mostly for free Research question: To what extent are carbon costs passed through to electricity prices? 2 / 28

4 Previous work Sijm et al. (2006; 2008): OLS on dark and spark spreads Zachmann & von Hirschhausen (2008): ECM for DE Fezzi & Bunn (2010): VECM for UK Fell (2010): VECM for Nordpool All Phase I, all single-country Problems: Marginal generator varies across countries and hours Electricity and input prices jointly determined Electricity markets integrated across borders 3 / 28

5 Previous work Sijm et al. (2006; 2008): OLS on dark and spark spreads Zachmann & von Hirschhausen (2008): ECM for DE Fezzi & Bunn (2010): VECM for UK Fell (2010): VECM for Nordpool All Phase I, all single-country Problems: Marginal generator varies across countries and hours Electricity and input prices jointly determined Electricity markets integrated across borders 3 / 28

6 This paper Phase II Range of approaches: Single-country to multi-country Exogenous to endogenous treatment of input prices Weekly one-year futures for base and peak load, / 28

7 Input prices 5 / 28

8 Baseload power futures 6 / 28

9 Peakload power futures 7 / 28

10 Generation by energy source 100% 90% 80% Generation shares by energy source, all hours 70% 60% 50% 40% 30% 20% Gas Hard coal Other Thermal Other renewables Solar and wind Hydro Nuclear 10% 0% 8 / 28

11 Carbon cost pass-through P = K (R) + ηf(r) + ψa(r) [ dp ψ + η F da = A + Γ R ] ( A + ψ A F + η + Γ R ) df F da 1 η F P ψ A P Γ R P with Γ K R + η R F + ψ R A 9 / 28

12 Carbon cost pass-through P = K (R) + ηf(r) + ψa(r) [ dp ψ + η F da = A + Γ R ] ( A + ψ A F + η + Γ R ) df F da 1 η F P ψ A P Γ R P with Γ K R + η R F + ψ R A 9 / 28

13 Range of models 1 ARCH on first-differences, single-country df = F/ A = F/ P = A/ P = Γ = 0 dp da = ψ 2 VECM with electricity and input prices Γ = 0 10 / 28

14 Range of models 1 ARCH on first-differences, single-country df = F/ A = F/ P = A/ P = Γ = 0 dp da = ψ 2 VECM with electricity and input prices Γ = 0 10 / 28

15 ARCH Single-country 2 EUA price effect tco 2 / MWh Elec / 28

16 ARCH Connections to neighboring countries 2 EUA price effect (markets linked) tco 2 / MWh Elec / 28

17 Installed capacity (End of year; 2012=100) 120 Generation capacity index (2012=100) Solar and wind Other renewables Others Fossil Hydro Nuclear 0 13 / 28

18 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Generation by energy source Peakload Generation shares by energy source, peakload Gas Hard coal Other thermal Other renewables Solar and wind Special regime Hydro Nuclear 14 / 28

19 VECM Start with single-country VECM Cointegration across electricity markets? Rank order test: If elec. prices of N countries are cointegrated with inputs, but not with each other, should get rank order of N Result: DE-FR, DE-NL, FR-NL: 1 link each 15 / 28

20 Single-country VECM 16 / 28

21 Multi-country VECM All countries Base (r = 4) DE NL FR ES NP Euro/MWh Weeks Peak (r = 3) DE NP FR NL Euro/MWh Weeks 17 / 28

22 /MWh /MWh Multi-country VECM Base (r = 2) DE-FR-NL Weeks Weeks Peak (r = 3) Base (r = 2) Peak (r = 3) DE FR NL DE FR NL DE FR NL DE FR NL /MWh /MWh / Weeks

23 /MWh Multi-country VECM Long-run responses, all countries / 28

24 /MWh Multi-country VECM Long-run responses, restricted / 28

25 sensitive to allowing for various degrees of cointegration Tradeoff betw. complexity of approach, and ability to interpret what s going on In general: Cost pass-through high Most models: CPT during base and peak similar Exceptions: DE and FR when combined with NL NP in single-country VECM Crowding out of gas during peakload by renewables? Futures data: Expected carbon content 21 / 28

26 Backup slides 22 / 28

27 GARCH (Generalized autoregressive conditional heteroskedasticity model with AR and MA terms) D.E t =α 0 + α 1 D.G t + α 2 D.G t 1 + α 3 D.C t + α 4 D.C t 1 + γ 1 D.A t + γ 2 D.A t 1 + β D.sin(2πt/52 + ω) + ɛ t P Q ɛ t = ρ p ɛ t p + θ q u t q + u t p=1 q=1 Var[ɛ t ] = σ 2 t = δ 0 + δ 1 ɛ 2 t 1 + δ 2σ 2 t 1 23 / 28

28 VECM (Vector error-correction model) K y t = Πyt 1 + Γ k y t k + γx t + ɛ t k=1 y t = [Et 1...E n C t G t A t ] yt 1 = [y t 1 1] X t = [ sin(t/52) cos(t/52) ] Π = α β; Γ k ; γ: Parameter matrices 24 / 28

29 ARCH Coal price effect t Coal / MWh Elec / 28

30 ARCH MWh Gas / MWh Elec Gas price effect 26 / 28

31 Single-country VECM Effect of coal Euro/MWh Base Electricity Price Response to 1Euro Coal Price Shock DE FR NL NP ES Weeks Euro/MWh Peak Electricity Price Response to 1Euro Coal Price Shock DE FR NL NP Weeks 27 / 28

32 Single-country VECM Effect of natural gas Euro/MWh Base Electricity Price Response to 1Euro Nat. Gas Price Shock DE FR NL NP ES Weeks Euro/MWh Peak Electricity Price Response to 1Euro Nat. Gas Price Shock DE FR NL NP Weeks 28 / 28