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

0

5

10

15

20

25

India

Mex

ico

Portu

gal

Slovak

Rep

ublic

Ita

ly

Poland

South

Afric

a

Korea

United

King

dom

Czech

Rep

ublic

Austra

lia

United

Sta

tes

Ton CO2 per capita

CO2/95 pppUS$ GDP: 1999

0

0,2

0,4

0,6

0,8

1

1,2

kg CO2/95 pppUS$ GDP

Emissions intensity

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 and 1

transmitter/distributor based on available data.

THE DATA (2)

Electricity Supply, R

Leontief

up to Electricity Other costs Primary factors

CES

Good 1 (not electricity)

Imported Good 1

Domestic Good 1

CES

Good N (not electricity)

Imported Good N

Domestic Good N

CES

Land Labour Capital

CES

Labour type 1

Labour type O

up to

CES

Good 1 from region 1

Good 1 from region 2

Good 1 from region R

up to Labour type 2

NEM

CES

Generation 1, NEM region 1

Generation M, NEM region 1

Generation M, NEM region N up to

Source: MMRF document from http://www.copsmodels.com/archivep.htm#tppa0080

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)

Baseline forecast

RESULTS: Carbon tax/no recycling

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.