Biomass energy in CGE models

Transcription

1 Biomass energy in CGE models presentation by Peter B. Dixon Centre of Policy Studies, Monash University to the Workshop on modelling bio-energy in agricultural-economic models Bonn, February 27-28,

2 Topics Example of CGE modelling: Biomass application of USAGE for the U.S. Department of Commerce Next steps in the USAGE study General comments on CGE modelling - Strategies in building models - Strategies for analyzing and presenting results 2

3 U.S. Energy Policy President s policy: Use cellulosic ethanol to reduce reliance on imported crude petroleum Simulations with the USAGE model of the effects in

4 The USAGE Model 500-industry, dynamic CGE model of the U.S. developed at the Centre of Policy Studies, Monash University, in collaboration with the U.S. International Trade Commission MONASH-style model, as described in Dixon and Rimmer 2002 Historical, Decomposition, Forecast and Policy simulations 4

5 Methodology DOE reference case used to build benchmark picture of U.S. economy in 2020 i.e. a picture of the US economy in 2020 without the President s energy policies, which involves - subdued growth in consumption - sharp turn-around in trade accounts - increase in crude petroleum prices - reductions in electricity prices - reductions in agricultural prices Then build alternative pictures with energy policies in place. 5

6 Replacing Crude Petroleum with Biomass Basecase Production of Motor fuels in 2020 requires 3.6b barrels of crude and 0 units of biomass Central policy case: 25% replacement by biomass competitive at $40 per barrel Same amount of Motor fuel can be produced in 2020 with 2.7b barrels of crude and X units of biomass where X valued at 2004 prices costs the same as 0.9b barrels of crude at 2004 prices ($40 per barrel) 6

7 Competitive at $40: realistic? What would need to happen to the cost of cellulosic ethanol for it to be competitive with gasoline when crude petroleum costs $40 per barrel? With crude at $40 per barrel, gasoline at the refinery gate costs $1.32 per gallon. For driving a car, one gallon of cellulosic ethanol = 0.73 gallons of gasoline Therefore ethanol is competitive with $40-gasoline when ethanol costs $0.96 per gallon (= 1.32*0.73). Current DOE target is to reduce the cost of cellulosic ethanol to $1.07 per gallon by Thus, $0.96 per gallon by 2020 is optimistic, but not crazy. 7

8 25 percent Biomass Fuel Competitive at $40 per Barrel per cent gain in consumption ($36 billion, $120 per person) per cent gain in post-tax real wages ($206) per cent gain in GDP ($18 billion) 17% reduction in crude petroleum imports (1.7 million barrels per day) Sources of consumption gain 8 (1) Costs-saving substitution between inputs (40% of gain) (2) A reduction in the world price of crude petroleum (15%) (3) An increase in aggregate employment (3%) (4) An increase in export prices (42%)

9 (1) Cost-saving saving substitution between inputs For 2004 to 2020 Increase in price of crude petroleum relative to price of GDP: 24.40% Decrease in price of biomass relative to price of GDP: 14.27% Decrease in price of biomass relative to price of crude : 31.08% In benchmark for 2020 Crude petroleum inputs to refining $ billion Biomass substitution is worth *0.25* = $29.6b in 2020 dollars = $13.3b in 2004 equivalents 9

10 (2) Reduction in the world price of crude petroleum Price index for crude petroleum in benchmark in 2020: Price index for crude petroleum in policy in 2020: Reduction in price: 4.8% Imports of crude in benchmark in 2020: made up of inputs to motor fuels other uses $306.25b $272.57b $33.68b Estimated imports of crude in policy at benchmark prices: $238.11b made up of inputs to motor fuels $204.43b other uses $33.68b 10 Savings = *0.048 = $11.4b in 2020 dollars = $5.1b in 2004 equivalents

11 (3) Increase in aggregate employment 11 35,000 extra jobs in agriculture Half of these are hired workers, half are owner-operators We assume the additional hired workers in agriculture are drawn from other sectors We assume the additional owner-operators in agriculture are not at the expense of alternative employment Net long-run increase in aggregate employment 0.013%=17,500/135m Benchmark wagebill in 2020: $18,577 billion Gain = *18,577 = $2.4b in 2020 dollars = $1.1b in 2004 equivalents

12 (4) An increase in export prices Biomass substitution reduces exports in 2020 by 1.7% Export demand elasticities set at -3 Value of exports in benchmark in 2020: $5,401b Increase in foreign currency export prices = 0.57% = 1.7/3 Gain = *5401 = $30.8b in 2020 prices = $13.8b in 2004 equivalents 12

13 Consumption gain in 2020: $billion (2004( equivalents) Back-of-the-envelope (BOTE) calculation % of BOTE total 1. Substitution between inputs World price of crude Aggregate employment Export prices Total BOTE: USAGE result:

14 Effects on industry outputs in 2020 of replacing 25% of crude petroleum with biomass 14 No. Industry Percentage effect 1 Crop agriculture Industries producing agricultural inputs Motor fuels Foreign holiday Other industries Leather tanning Mining machinery Export tourism Animal agriculture Meat packing plants Oil & gas field machinery Wet corn mills Prepared feeds Crude petroleum and natural gas Maintenance of petroleum and natural gas wells Petroleum & natural gas drilling Petroleum & natural gas exploration Pipelines, crude petroleum Average over all industries 0.21

15 Effects of biomass substitution under different assumptions Biomass competitive at Extent of substitution $40 per barrel $50 per barrel 33.3% requires about 1200 million dry tons of biomass a year 25.0% requires about 900 million dry tons of biomass a year 18.7% requires about 675 million dry tons of biomass a year 8.3% requires about 300 million dry tons of biomass a year Consumption GDP Crude petroleum imports Price of motor fuel Consumption GDP Crude petroleum imports Price of motor fuel Consumption GDP Crude petroleum imports Price of motor fuel Consumption GDP Crude petroleum imports -5-6 Price of motor fuel

16 Next steps Concerns raised by U.S. Departments of Energy and Agriculture Is large-scale ethanol production in the U.S. feasible and what would it do to food prices? We create a new version of USAGE paying particular attention to: technologies for producing ethanol and their demand for agricultural products land use in agricultural industries and supply elasticities Narrow focus: simulate the effects on the U.S. economy of meeting government targets for the production in 2020 of corn ethanol, cellulosic ethanol and alternative ethanol. 16

17 Next steps USE matrix for USAGE-B Inputs aaaindustries Feed grains Switch grass Crop residue Organic by-prods Cellulosic material Corn ethanol Cellulosic ethanol Alternative ethanol Petroleumrefining Ethanol Gasoline/ethanol Other industries Final demands 17 Corn Switch grass Crop residue Cellulosic material Organic by-prods Corn ethanol Cellulosic ethanol Alternative ethanol Crude petroleum Gasoline Diesel Other fuels Gasoline/ethanol Ethanol Fertilizers Other commodities Production tax 0 Labor Capital Land Total inputs

18 Next steps Treatment of land in USAGE-B Land CET, τ 1 Grazing/ Switch grass Crops/ Switch grass CET, τ 2 CET, τ 3 Grazing Switch grass Crops Switch grass CET, τ 4 CET, τ 5 Meat cattle Dairy Other Corn Sorghum Other 18

19 General comments Comments on CGE modelling 1. Model building process needs to be guided by a clear focus on the end point - narrow versus broad better to aim at working out the desirability of achieving a specific bio-fuel target than aiming to build a model for analyzing energy policies - reach results quickly, results will guide the next step 19

20 General comments Comments on CGE modelling In the context of NaRoLa, first objective might be: Quantify the potential role of biomass in world-wide energy generation over the next 15 years. - supply elasticities of output of corn, sugar and other potential inputs to bio-fuels in each region of the world - growth in non-energy demand for agricultural products in each region - projections of the world price of oil or a specification of the supply function for oil - scenarios on technical change in each region, especially in agriculture, bio-fuel production and energy-using sectors - world trade policies 20

21 General comments Comments on CGE modelling 2. To be legitimate and influential CGE results must be explained by back-of-the-envelope calculations - checks the legitimacy of CGE results (4 effects add up 0.34%, USAGE gives 0.36%) - exposes the critical underlying assumptions and data (tech change in agriculture and bio-fuels, technology for making bio-fuels, forecast price of oil, export demand elasticity, supply elasticity for oil, demand for oil, split of oil between motor fuels and other uses) - provides basis for sensitivity analysis - makes results/arguments accessible (send policy maker away with 4 easy ideas) 21