1. GTAP-E Incorporating Energy Substitution into the GTAP Model

2. Introduction to GTAP-E Why do we care about representing CO2 in a CGE?  CO2 emissions are “well-mixed” gases creating a global problem.  Reducing CO2 will have region and sector specific economic impacts because of the increasing cost of energy.  Economic effects of reductions will be felt to various extent world wide no matter who reduces emissions.  CGE modeling useful in breaking out complex interactions between countries and sectors emitting CO2 emissions.

3. Introduction to GTAP-E Two major types of instruments: Tax and Cap- and-Trade  Trade off between unilateral vs. international trading system.

4. Production Structure: GTAP-E = GTAP + energy substitution (inter-KE and inter-fuel) Output Value AddedIntermediate goods (energy, non-energy) CapitalUnskilled Lab. Skilled Lab. Nat. Resources Land GTAP GTAP-E Output Value AddedIntermediate goods (non-energy) Unskilled Lab. Skilled Lab. Nat. Resources Land Capital-Energy GasOilPetroleum prods Energy Capital Electricity Non-Coal Non-Electricity Coal

5. Macro relationships in GTAP-E (USA) +9.5 -0.64  VA >   -0.64 +0.02 +0.12-0.04+0.19 +0.01

6. Macro relationships in GTAP-E (USA) -0.040 -0.08+0.11+0.02+0.21 -0.04 00 0 -0.08 +0.11 +0.22 -1.1

7. Macro relationships in GTAP-E (USA) -0.04+0.08-0.030.12 -$2225-$2955+$742 -0.03

8. US$30 tax per tonne Impacts:  Total carbon emissions, in M tons of C, fall by 13.5%; why? Use of the different energy sources:  Demand for composite non-electric goods (coal + non-coal) Qnel(j,r)1 USA Agriculture-7,26 Coal-28,91 Oil-2,37 Gas-10,48 Oil_Pcts-7,6 Electricity-18,16 En_Int_ind-9,11 Oth_ind_ser-7,24

9.  Especially so for the energy sources that are more carbon emitting (re: Demand for intermediate inputs by sector) qf(i,j,r) Coal Oil_Pcts Electricity En_Int_ind Agriculture-18,84-7,68-2,56 Coal-28,91-7,6-22,3-21,06 Oil-28,91-7,6-11,69-11,21 Gas-28,91-7,6-11,68-11,35 Oil_Pcts-28,91-7,6-8,13-7,64 Electricity-28,91-7,64,08-3,25 En_Int_ind-18,84-7,68-2,56

10. Why the fall in demand?  Prices Average percentage changes in industry prices for composite commodities pf(i,j,r) %age chngs Agriculture0,25 Coal51,69 Oil16,36 Gas16,47 Oil_Pcts12,03 Electricity7,52 En_Int_ind0,75

11. Exports and Imports Agriculture-0,310,16 Coal10,02-27,34 Oil9,96-12,91 Gas5,61-11,92 Oil_Pcts0,9-8,1 Electricity-33,1519,56 En_Int_ind-2,751,05

12. Why?  Prices Border Prices pfob(i,r,s) 1 USA Agriculture0,25 Coal-2,51 Oil-1,65 Gas-1,19 Oil_Pcts-1,07 Electricity7,59 En_Int_ind0,85 Oth_ind_ser0,01

13. This is reflected in the BOT numbers below Balance of Trade DTBALi(i,r) 1 Agriculture-76,78 2 Coal343,25 3 Oil8373,1 4 Gas1001,57 5 Oil_Pcts743,44 6 Electricity-473,8 7 En_Int_ind-3692,89 8 Oth_ind_ser7868,28 Total14086,16

14. Allocation effect decomposition (I) Largest allocation effect for firms Main private household loss from oil products Oil only used for oil products production

15. Allocation effect decomposition (II) Loss of coal tax revenues mainly due to less coal use in electricity production Loss of gas tax revenues more spread Oil products mainly used by oth_ind_ser

16. Terms of trade decomposition Oil prices drop compared to composite world trade price index and US is net importer Export price of En_int_ind rises compared to world price Export price of Oth_ind_ser drops compared to world price

17. Sim 30USD/t on US Impacts:  Total carbon emissions, in M tons of C, fall by 13.5%;  Use of the different energy sources:  Demand for composite non-electric goods (coal + non-coal)

18. New Parameter File ELKEUSAEU JPN ESUBVAMOD USAEUJPN 1 Agriculture0,50 1 Agriculture0,030,150,22 2 Coal1,000,00 2 Coal0,503,994,00 3 Oil1,000,00 3 Oil0,500,390,40 4 Gas1,000,00 4 Gas0,500,351,31 5 Oil_Pcts1,000,00 5 Oil_Pcts0,501,26 6 Electricity1,000,50 6 Electricity0,501,26 7 En_Int_ind1,000,50 7 En_Int_ind0,501,19 8 Oth_ind_ser1,000,50 8 Oth_ind_ser0,501,36 9 CGDS0,00 9 CGDS1,00 Sim 1A. Change Elasticity

19. Main Results EV decomposition welfareUSAEUJPN 2 alloc_A1-3314,4073678,584675,135 6 tot_E13736,0451092,480639,310 7 IS_F1372,773-146,096-148,943 Total794,4114624,9681165,503 Emission Reductions-15,7140,8130,788 Sim 1A. Change Elasticity

20. Sim 1B. 30USD/t on US Fixing the Trade Balance  The trade balance for the regions, except for one are fixed (made exogenous).  The savings slack for the previously omitted region is made exogenous.

21. Sim 1B. 30USD/t on US AllocativeTOTIS_BalTotal USA-2777.412784.82202.91210.33 EU2993.73811.05-86.643718.13 JPN572.37560.90-96.101037.17 Fixing the Trade Balance

22. Sim 1B. 30USD/t on US Fixing the Trade Balance  PExport is the major change in the TOT effect with the largest results coming from Energy-intensive industries Other industries

23. Sim 2. Tax by Regions Impose a USD 30 tax on CO2 emissions in each region (EU, USA, Japan) individually. Each row is a different scenario, with the tax imposed in the country shown in the first column.

24. Sim 2. Tax by Regions Total change in CO2 emissions, M. tons and % in the taxed region - The effect on world CO2 emissions is the greatest with a US tax. Output is already more energy efficient in the EU and Japan.

25. - The per capita effect of the tax on EV is considerably larger in the EU (-30 $) and Japan (-35 $) than in the USA (-8 $). Most of the change in EV arises from allocation (especially in the USA), the rest mainly from TOT (>0 in EU, USA; <0 in Japan). Change in GDP quantity index, % Sim 2. Tax by Regions

26. Change in value added, % - Output of energy commodities declines in the region that introduces the tax. - Generally, labour productivity increases. Exceptions to this are Electricity, En_int_ind and CGDS. Full employment…? Sim 2. Tax by Regions

27. Change in the terms of trade, % - The TOT changes are large in the other five regions. There, change in EV arises more from TOT than from allocation. - Imposing a USD 30 tax in all three regions at the same time, is almost equal to the sum of the above individual results. Sim 2. Tax by Regions

28. Case: Unilateral Carbon Tax in Japan

32. Conclusions  Relationship between the scale of carbon tax and reduction of CO2 emissions in Japan is determined by the following relation: gco2t=-5,23*%change rctax**(-0.09);  Scale of carbon tax and change in value of GDP has almost a linear relationship; Case: Unilateral Carbon Tax in Japan

33. Conclusions - Terms of trade of Japan and net energy exporters (EEx) tend to deteriorate simultaneously at tax rates up to US$30, while it improves in other regions. However, terms of trade tends to deteriorate more for Japan than EEx at higher taxes above US$30 per ton of carbon emission. - As Japan has to reduce its total CO2 emissions by more than 14% by 2012 compared to its 1990 level, it is necessary to introduce at least US$30 per ton of C emissions. Case: Unilateral Carbon Tax in Japan

34. Compare Emission Trading: Carbon Taxes Tax in EU, US and JPN (30USD ) World Emission Trading (4.5%) RCTAX30.00USD7.23USD qgdpEU and JPN suffers the most; China/India gains slightly China/India suffers the most EVDecrease in all regions except China/India ROW Positive in US, EU and JPN qo Coal reductions are large in EU, US and JPN Large coal reductions in China/India

35. Conclusion Our policy instruments are a uniform tax and an emissions trading system. Which is more efficiency?  A worldwide emission trading system would contribute to a reduction in the economic costs for the countries.  We can achieve a larger cut in emissions with a smaller decline in GDP and per capita welfare (EV) by imposing a CO2 tax in the United States than with an equivalent lump-sum tax in either the EU or Japan.

36. Future research section Allowing energy substitution in GTAP is important to reflect agents’ reaction in a context where carbon taxes are used to reduce CO2 emissions. Developing countries may not agree in this approach because it imposes a large constraint on their economy. Future goals for greenhouse gas reductions should therefore vary between the regions, in order to reflect the share of world emissions.