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Motivation Model VAR estimation Explaining the interplay of three markets: Green certificates, carbon emissions and electricity Sandra Schusser 13 Jurate Jaraite 23 1 Swedish University of Agricultural Sciences 2 Ume a School of Business and

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Motivation Model VAR estimation

Explaining the interplay of three markets: Green certificates, carbon emissions and electricity

Sandra Schusser 13 Jurate Jaraite 23

1Swedish University of Agricultural Sciences 2Ume˚

a School of Business and Economics

3Centre for Environmental and Resource Economics (CERE)

23 August 2016

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Motivation Model VAR estimation

The TGC System

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Motivation Model VAR estimation

TGC issued by source, cancelled and accumulated

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Motivation Model VAR estimation

Motivation

Why is it important to understand price development of TGC? price signals whether to invest in RES-based electricity generation or not possibility to improve legislative framework to assure RES-goals are reached Legal framework interactions with price frequent legislation changes interactions with EU ETS expected

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Motivation Model VAR estimation

Legislation: Percentage Requirement

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Motivation Model VAR estimation

Theoretical Paradoxes with both Policies in Place

Intuition Black quota will have a negative effect on electricity generation based on conventional sources and favour the use of RES. Literature emission-intensive technologies might increase their emissions (B¨

hringer and Rosendahl, 2010)

EU ETS might have negative effects on both types of electricity generation (Widerberg, 2011)

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Motivation Model VAR estimation

Variables that explain TGC price

Factor Effect on electricity price Effect on TGC price Temperature − Industrial production + Non-renewable resource price + EUA price + − Renewable electricity supply − − TGCs banked −

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Motivation Model VAR estimation

Data Sources

Table: Data sources Variable Source Period Frequency TGC Spot Price SKM 2005-2015 Weekly Electricity Spot Price Nordpool 2005-2015 Weekly EUA Futures Price ICE Futures Europe 2005-2015 Weekly

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Motivation Model VAR estimation

Price Development

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Motivation Model VAR estimation

Vector Autoregression (VAR) Model

yt =

6

Aiyt−i + c + ut (1) Where yt is the (3 × 1) vector of endogenous variables TGC price, electricity price, and EUA prices, Ai are (3 × 3) coefficient matrices for lag i = 1, · · · , 6, ut is the error term with zero mean and time invariant covariance, c is a (3 × 1) vector of constant.

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Motivation Model VAR estimation

Impulse Responses: A shock from TGC Price

elPrice −10 −5 5 10 euaPrice −10 −5 5 10 4 8 13 18 23 28 33 38 43 48 Orthogonal Impulse Response from tgcPrice 90 % Bootstrap CI, 100 runs Schusser, Jaraite Tradeable Green Certificates

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Motivation Model VAR estimation

Impulse Responses: A shock from Electricity Price

tgcPrice −4 −2 2 euaPrice −4 −2 2 4 8 13 18 23 28 33 38 43 48 Orthogonal Impulse Response from elPrice 90 % Bootstrap CI, 100 runs Schusser, Jaraite Tradeable Green Certificates

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Motivation Model VAR estimation

Impulse Responses: A shock from EUA Price

tgcPrice −5 5 10 elPrice −5 5 10 4 8 13 18 23 28 33 38 43 48 Orthogonal Impulse Response from euaPrice 90 % Bootstrap CI, 100 runs Schusser, Jaraite Tradeable Green Certificates

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Motivation Model VAR estimation

Conclusion

no indication of negative effects of carbon prices on green certificate prices we find short-run positive effects price signals are in line with the goals to reduce GHG emissions and increase renewable electricity share

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Motivation Model VAR estimation

Descriptive Statistics

Table: Descriptive statistics (values in SEK)

Obs Min Max Mean Median Stdev TGC price 558 136.80 376.00 214.16 194.25 61.74 Electricity price 558 69.89 965.97 356.46 335.40 129.80 EUA price 558 28.39 298.11 122.57 116.00 63.91

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Motivation Model VAR estimation

Model Diagnostics I (P-values)

Model Serial Correlation Testa Normality Testb ARCH Testc in Levels 0.16 in First Differences 0.59 Schusser, Jaraite Tradeable Green Certificates

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Motivation Model VAR estimation

(Cross-)Correlations

5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag ACF tgcPrice 5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag tgcP & elPr 5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag tgcP & ePrc −20 −15 −10 −5 0.0 0.2 0.4 0.6 0.8 1.0 Lag ACF elPr & tgcP 5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag elPrice 5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag elPr & ePrc −20 −15 −10 −5 0.0 0.2 0.4 0.6 0.8 1.0 Lag ACF ePrc & tgcP −20 −15 −10 −5 0.0 0.2 0.4 0.6 0.8 1.0 Lag ePrc & elPr 5 10 15 20 0.0 0.2 0.4 0.6 0.8 1.0 Lag euaPrice

(a) Cross-Correlations.

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Motivation Model VAR estimation

Model Diagnostics II (Stability Test)

OLS−CUSUM of equation tgcPrice

Time Empirical fluctuation process 0.0 0.2 0.4 0.6 0.8 1.0 −1.0 0.0 1.0

OLS−CUSUM of equation elPrice

Time Empirical fluctuation process 0.0 0.2 0.4 0.6 0.8 1.0 −1.0 0.0 1.0

OLS−CUSUM of equation euaPrice

Time Empirical fluctuation process 0.0 0.2 0.4 0.6 0.8 1.0 −1.0 0.0 1.0

(a) Stability of Standard VAR

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