Carbon Pricing in New Zealand’s Emissions Trading Scheme Stranded Assets, CAPEX and Investment Consultants Dr. Daniel J. Tulloch Email: Daniel J. Tulloch Smith School of Enterprise and the Environment daniel.tulloch@smithschool.ox.ac.uk Research Associate and SARN Coordinator University of Oxford Twitter: Smith School of Enterprise and the Environment Email Twitter @djtulloch daniel.tulloch@smithschool.ox.ac.uk @djtulloch University of Oxford With: Dr. Ivan Diaz-Rainey (University of Otago)
O UTLINE 1. Introduction 2. Theoretical Framework and Hypotheses 3. Methodology 4. Results 5. Conclusions NZ ETS
1. I NTRODUCTION • What: What are the determinants of NZU prices? (local market fundamentals/policy vs. imports) • Why: NZ ETS unique • Second oldest national scheme • No hard cap: intensity based scheme • Highly international (unlimited offsets) • Forestry incorporated • Originally agriculture expected • Low domestic carbon price • Prior analyses not explored price determinants and impact of import/export (need registry data) • How: Structural breaks; Vector Autoregression (VAR), Granger NZ ETS 3
N EW Z EALAND ' S T OTAL GHG E MISSIONS BY S ECTOR 100,000 80,000 60,000 Emissions (Gg CO 2 -e) 40,000 20,000 0 -20,000 -40,000 LULUCF Agriculture Energy Industrial Processes Waste Solvent and Other Product Use NZ ETS 4
NZ ETS: A N O VERVIEW • Introduced in 2008 as the first ETS to encompass all sectors and all six Kyoto greenhouse gases. • Only ETS to include forestry sector, able to generate carbon credits (Moyes, 2008, ELQ; Adams & Turner, 2012, FPE; Bullock, 2012, EnP) . • Not a cap-and-trade, but a mandatory surrender of carbon credits (Richter & Mundaca, 2013, NCC) . • Government provides free allocation of units to at-risk sectors (Kerr & Zhang, 2009, Motu) . NZ ETS 5
NZ ETS: A N O VERVIEW • Unlike other ETSs, the NZ ETS had no restrictions on overseas carbon credits. • 2009 - National government’s amendments argued to be cost-containment measures. • Transition Period (01 July 2010 to 31 December 2012) • Delayed entry, ‘one -for- two’ scheme, $25 fixed price (MfE, 2011; Sinclair, 2011; MfE, 2012a; Bullock, 2012, EnP) . • Doubles the utility of each carbon credit ($12.50 per unit ) (Moyes, 2008, ELQ) . • Cannot convert domestic NZUs for offshore sales. NZ ETS 6
T HE I MPORTANCE OF F ORESTRY • Forestry expected to generate 79 million units during CP1 (MfET, 2007) • Selling surplus was expected to generate NZ$430 million (MfE, 2005) • Net contribution to the NZ economy • Encourage afforestation • However, low NZU prices and a push towards farming intensification lead to deforestation Carbon Pricing in NZ’s ETS 7
L INKING S YSTEMS AND P OLICY C HANGES • Linking Systems increases liquidity and acts as a safety value on price • From mid- 2011, NZ ETS became a ‘price taker’ • Declining CER prices and large imports ‘dragged down’ the price of NZUs • New Zealand banned certain international units • Questions over CER integrity (HFC-23 and HCFC-22 controversy). • New Zealand withdrew from CP2 but pledged to reduce emissions to 11% below 1990 levels. • The NZ ETS will remain the main instrument achieving climate change mitigation. Carbon Pricing in NZ’s ETS 8
2. T HEORETICAL F RAMEWORK : L INKING SYSTEMS • Marginal Abatement Curves (MAC) and the Incentives Minimise MAC = and Benefits of Emissions Trading unrestricted trading welfare p maximising • Models where trading does 𝑁𝐵𝐷 1 not maximise welfare • Terms of trade effects 𝑞 1 a • 𝑁𝐵𝐷 2 Intensity based systems a ’ a ’’ b' ’ 𝑞 ′ • Other critiques b' • Loss of control 𝑞 2 b • Distortions e.g “hot air” • Market integrity issues e.g HFC-23 ′ 𝑨 1 𝑨 2 𝑨 2 ′ 0 𝑨 1 Z (CO2 abated) NZ ETS 9
H YPOTHESES • H 1 : Domestic NZU prices will experience a negative structural shift in returns during the period at which international CER prices become relatively cheaper and are eligible for surrender obligations. • H 2 : There will be an interdependent relationship between the NZU and CER returns, with CERs leading and NZUs following. • CERs are Clean Development Mechanism units • H 3 : Increasing net import of units will negatively impact NZUs returns NZ ETS 10
3. L ITERATURE R EVIEW – EU ETS F UNDAMENTALS Fundamental Positive Impact Negative Impact No Impact Oil Mansanet-Bataller et al. (2007) – 1 lag Alberola et al. (2008) A Hintermann (2010) B Natural Gas Mansanet-Bataller et al. (2007) – 1 lag Alberola et al. (2008) A Hintermann (2010) B - 1 lag Coal Hintermann (2010) B Alberola et al. Mansanet-Bataller et al. (2007) (2008) A Hintermann (2010) B Electricity Price Alberola et al. (2008) Weather* Dry - Benz & Trück (2006) Rain and temp - Hintermann (2010) AB Dry - Benz & Trück (2009) Temp – Christiansen et al. (2005) Rain - Mansanet-Bataller et al. Temp - Mansanet-Bataller et al. (2007) (2007) wind - Mansanet-Bataller et al. (2007) Temp - Hintermann (2010) AB Rain- Hintermann (2010) A Temp - Alberola et al. (2008) A A Varies across time. B Varies depending on model specification. NZ ETS 11
3. M ETHODOLOGY - D ATA • Data • Market data: ICE, Bloomberg etc. • NZ Registry: FOI to get daily registry data of import and exports. • All data is daily, between 01 July 2010 and 31 December 2013. • Quoted in NZD$ to better represent import and export costs to NZ participants. • Returns are calculated using first log-difference. 12
3. M ETHODOLOGY - D ATA Variable Definition NZU price (Domestic) Daily spot prices (1 Jul 2010 to 31 Dec 2013; 914 obs) CER price (International) Daily futures (shortest strip) from ICE Oil price Arabian Gulf Dubai Fateh Crude Oil Spot Price Natural Gas price Henry Hub Natural Gas Spot Price Index Coal price European coal (API2YR1) Electricity price NZ Potah Temperature Auckland Extreme temperatures Upper and lower 95% and 5% (dummies) Import volume Sum of AAUs, CERs, RMU, and ERUs 13
3. M ETHODOLOGY - MODELS • Structural Breakpoint tests • Bai-Perron (2003) dynamic algorithm. • Minimizes sum of squared residuals. • Identifies multiple breakpoints. • Vector Autoregression • Captures linear interdependencies among variables. • Granger Causality • Determines when one series is useful in forecasting another. • Flow of time plays a central role – Does lagged Y forecast X? NZ ETS 14
4. R ESULTS – VAR (S PECIFICATION ) • The VAR regressions are presented in regression notation below: 𝑘 𝑠 𝑘 𝐷𝐹𝑆 2,𝑢−𝑘 + σ 𝑘=1 𝑘 𝑂𝑓𝑢𝐽𝑛𝑞𝑝𝑠𝑢 3,𝑢−𝑘 + 2 2 2 1,𝑢 = 𝛽 𝑗 + σ 𝑘=1 1,𝑢−𝑘 + σ 𝑘=1 (A) 𝑠 𝛾 1,1 𝛾 1,2 𝛾 1,3 𝛾 1,4 𝑃𝑗𝑚 4,𝑢 + 𝛾 1,5 𝐻𝑏𝑡 5,𝑢 + 𝛾 1,6 𝐷𝑝𝑏𝑚 6,𝑢 + 𝛾 1,7 𝐹𝑚𝑓𝑑 7,𝑢 + 𝛾 1,8 𝑈𝑓𝑛𝑞 8,𝑢 + 𝛾 1,9 𝐷𝑝𝑚𝑒 9,𝑢 + 𝛾 1,10 𝐼𝑝𝑢 10,𝑢 + 𝜁 1,𝑢 𝑘 𝑠 𝑘 𝐷𝐹𝑆 2,𝑢−𝑘 + σ 𝑘=1 𝑘 𝑂𝑓𝑢𝐽𝑛𝑞𝑝𝑠𝑢 3,𝑢−𝑘 + 2 2 2 (B) 𝐷𝐹𝑆 2,𝑢 = 𝛽 𝑗 + σ 𝑘=1 1,𝑢−𝑘 + σ 𝑘=1 𝛾 2,1 𝛾 2,2 𝛾 2,3 𝛾 2,4 𝑃𝑗𝑚 4,𝑢 + 𝛾 2,5 𝐻𝑏𝑡 5,𝑢 + 𝛾 2,6 𝐷𝑝𝑏𝑚 6,𝑢 + 𝛾 2,7 𝐹𝑚𝑓𝑑 7,𝑢 + 𝛾 2,8 𝑈𝑓𝑛𝑞 8,𝑢 + 𝛾 2,9 𝐷𝑝𝑚𝑒 9,𝑢 + 𝛾 2,10 𝐼𝑝𝑢 10,𝑢 + 𝜁 2,𝑢 𝑘 𝑠 𝑘 𝐷𝐹𝑆 2,𝑢−𝑘 + 2 2 (C) 𝑂𝑓𝑢𝐽𝑛𝑞𝑝𝑠𝑢 3,𝑢 = 𝛽 𝑗 + σ 𝑘=1 1,𝑢−𝑘 + σ 𝑘=1 𝛾 3,1 𝛾 3,2 𝑘 𝑂𝑓𝑢𝐽𝑛𝑞𝑝𝑠𝑢 3,𝑢−𝑘 + 𝛾 3,4 𝑃𝑗𝑚 4,𝑢 + 𝛾 3,5 𝐻𝑏𝑡 5,𝑢 + 𝛾 3,6 𝐷𝑝𝑏𝑚 6,𝑢 + 𝛾 3,7 𝐹𝑚𝑓𝑑 7,𝑢 + 2 σ 𝑘=1 𝛾 3,3 𝛾 3,8 𝑈𝑓𝑛𝑞 8,𝑢 + 𝛾 3,9 𝐷𝑝𝑚𝑒 9,𝑢 + 𝛾 3,10 𝐼𝑝𝑢 10,𝑢 + 𝜁 3,𝑢 15
4. R ESULTS Daily Close Prices for NZ NZUs and CERs. Sources: ICE (2014) and the EPA . 30 100 Net Volume Imported (Millions) 90 25 80 70 Unit Cost ($NZD) 20 60 50 15 40 30 10 20 10 5 0 0 -10 2010 2011 2012 2013 Net Import CER NZU 5 (NZU-CER) Spread 0 -5 -10 2010 2011 2012 2013
Total Units Surrendered by Unit Type, 2010-2012. 30 25 Total Units Surrendered (Millions) 20 15 10 5 0 2010 2011 2012 Forestry NZUs Other NZUs NZ AAUs CERs ERUs RMUs NZ$25 Fixed Price Carbon Pricing in NZ’s ETS 17
4. R ESULTS : S TRUCTURAL BREAKS • Structural Breaks (Bai-Perron, 2003) • Expected: • Tues 21 June 2011 – CERs drop below NZUs • Mon 11 February 2013 – surrender of some international CERs and ERUs (Joint Implementation/Annex 1: developed and transition) banned (effective banning date) • Results: • Mon 20 June 2011 and • Tues 19 February 2013 . • Support for H 1 – a significant negative intercept shifts when CERs fell below NZUs (while eligible for surrender purposes). NZ ETS 18
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