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TOWARDS FINDING THE TAX INCIDENCE OF CARBON TAXES IN SOUTH AFRICA Jan H van Heerden Heinrich Bohlmann OUTLINE OF THE PAPER • • • • • The Problem Possible Solutions Previous Study The Data Adjusting the Model • • • • Policy Simulations Results Conclusion Further work THE PROBLEM • South Africa ranks amongst the first world countries in the world in CO2 pollution, and its footprint looks bad CO2 per capita: 1999 25 20 15 10 5 Ki ng Cz do ec m h Re pu bl ic Au st ra Un lia it e d St at es Ko re a Un it e d Po la nd So ut h Af ric a Ita ly Po rtu ov ga ak l Re pu bl ic Sl co ex i M In di a 0 Ton CO2 per capita CO2/95 pppUS$ GDP: 1999 1,2 1 Emissions intensity 0,8 0,6 0,4 0,2 Ko Un re a it e d St at es Au st Sl ra ov lia ak Re pu Cz bl ec ic h Re pu bl ic Po la nd So ut h Af ric a co ex i M ng do m Ki In di a Un it e d Po rtu ga l Ita ly 0 kg CO2/95 pppUS$ GDP Source: International Environmental Agency (IEA). 2001. Key world energy statistics. Paris: IEA. (www.iea.org/statist/key2001/keyworld-2001.pdf) GHG Emissions M-Tons - 2009 Rank Country M - ton % 1 China 7 711 25.40% 2 United States 5 425 17.80% 3 India 1 602 5.30% 4 Russia 1 572 5.20% 5 Japan 1 098 3.60% 6 Germany 766 2.50% 7 Canada 541 1.80% 8 Korea, South 528 1.70% 9 Iran 527 1.70% 10 United Kingdom 520 1.70% 11 Saudi Arabia 470 1.50% 12 South Africa 450 1.50% 13 Mexico 444 1.50% 14 Brazil 420 1.40% 15 Australia 418 1.40% 16 Indonesia 413 1.40% 17 Italy 408 1.30% 18 France 397 1.30% 19 Spain 330 1.10% 20 Taiwan 291 1.00% 21 Poland 286 0.90% POSSIBLE SOLUTIONS 1. Carbon Emissions Tax Actual measured emissions; or 2. Proxy tax bases: A. Fossil Fuel Input (Upstream): where fuels enter the economy based on the carbon content of the fuel. B. Output Tax (Downstream): (i) At point where fuel is combusted. (ii) May be based on average emissions of production processes. Previously • In 2004/5 the Dutch government funded a project (PREM) to search for double dividends in the environment and economy of South Africa. • We used a static CGE model to simulate the effects of carbon, fuel and energy taxes in the country. • We found triple dividends with some tax and recycling combinations (environment, economy and poverty) • Van Heerden, et al., Searching for Triple Dividends in South Africa: Fighting CO2 pollution and poverty while promoting growth, The Energy Journal, 2006 This paper • Gives preliminary results of a World Bank project to search for double dividends in the environment and economy of South Africa. • We use a dynamic CGE model to • expand the electricity industry from being a single producer and distributor of electricity to a few generators and one distributor, and • simulate the effects of a fuel input tax in the country. THE DATA (1) • Updated 2011 database of South Africa • Core data taken from the 2011 SU tables (StatsSA) • Database aggregated to 45 sectors, with the electricity sector then split between 8 generators transmitter/distributor based on available data. and 1 THE DATA (2) Electricity Supply, R Leontief Good 1 up to (not electricity) Good N (not electricity) Primary factors CES CES CES Imported Good 1 Domestic Good 1 Imported Good N Electricity Domestic Good N Land CES Good 1 from region 1 Good 1 from region 2 Other costs Labour Capital CES up to Good 1 from region R Labour type 1 Labour type 2 NEM CES Generation 1, NEM region 1 Generation M, NEM region 1 Source: MMRF document from http://www.copsmodels.com/archivep.htm#tppa0080 up to Generation M, NEM region N up to Labour type O Database split of the electricity sector • We used the procedure followed by the MMRF model of CoPS: • Database split.docx THE MODEL (1) • Change in revenue dR= T.dX + X.dT • T is rate and X is base • But % change in X is x = 100*dX/X • Therefore dR = TxX/100 + X.dT • = Rx/100 + X.dT • dR affects government revenue and dT all prices THE MODEL (2) • ! Leontief demand for inputs ! • Equation E_x1_sa # Demands for commodity composites # (all,c,COM)(all,i,IND52) x1_s(c,i) - [a1_s(c,i) + a1tot(i)] = z(i); • Equation E_x1_sb # Demands for commodity composites # (all,c,COM45) x1_s(c,"ElecSup") - [a1_s(c,"ElecSup") + a1tot("ElecSup")] = z("ElecSup"); ! CES demand for inputs ! • Equation E_x1_sc (all,c,GEN) x1_s(c,"ElecSup") - a1_s(c,"ElecSup") • = z("ElecSup") - SIGMAGEN(c)*[p1_s(c,"ElecSup") + a1_s(c,"ElecSup") - p1_gen]; POLICY SIMULATIONS • The modelling exercises focus on two pieces of government policy in South Africa • Integrated Resource Plan (IRP) for Electricity (2010-2030) • http://www.doe-irp.co.za/content/IRP2010_updatea.pdf • Carbon tax of R120/ton CO2e from 2016 • http://www.thedti.gov.za/parliament/Reducing_greenhouse_gas.pdf Baseline forecast (1) 120 % change in selected macro-economic variables (cumulative) 100 80 60 40 20 0 2012 2017 Real GDP 2022 2027 2032 CO2: CoalGen constrained Baseline forecast % change in output growth for different power generation sources (cumulative) 140 120 100 80 60 40 20 0 -20 2012 CoalGen 2017 WindGen 2022 SolarPVGen 2027 SolarCSPGen 2032 GasGen OtherGen RESULTS: Carbon tax/no recycling 1,400 Million ton CO2-equiv 1,200 1,000 800 600 400 200 0 2015 2020 Growth without constraints (range) Required by science (range) Baseline CO2: No CoalGen Constraints 2025 2030 Baseline & Tax 2035 CONCLUSIONS • Implementing a CES demand function for generated electricity by the supplying industry causes a switch to green electricity but not nearly enough. Currently the supplier merely uses coal generated power much more efficiently and not enough substitution takes place. • The carbon tax by itself – especially with all the exemptions for the first five years – is not enough. Regulation of coal generated power, as well as pro-active stimulation of green generation together with the tax will be necessary to reach the targets.