Economy-wide (general equilibrium) analysis of Philippines mitigation potential

Transcription

1 Global Trade Analysis Project Economy-wide (general equilibrium) analysis of Philippines mitigation potential Erwin Corong Center for Global Trade Analysis, Purdue University Crowne Plaza Hotel, Manila 11 January 2016 Center for Global Trade Analysis Department of Agricultural Economics, Purdue University 403 West State Street, West Lafayette, IN USA

2 Presentation outline Introduction and motivation Methodology Business as Usual (BaU) or Baseline scenario Simulation results Insights 2

3 Motivation With energy use (and population) on the rise, increases in carbon emissions are almost inevitable Increasing use of coal to generate electricity Rising demand for transport fuel Investigate the potential economic and distributional impact of low carbon growth strategies in the Philippines Analysis with particular focus on Philippine policy options 3

4 Methodology Partial equilibrium model (e.g. EFFECT) More detailed power/energy sector Impacts limited to one or a few sectors of the economy Cannot account for economy-wide (feedback) effects or trade-offs General equilibrium (CGE) model Encompass the entire economy (disaggregated database with many industries/sectors, labor and households types) Impacts in one sector affects all other sectors of the economy Accounts for country-specific (supply and demand) constraints (i.e., factors are not limitless) Typically less power sector detail Combined use of partial and national models is preferable 4

5 Modeling approach Use EFFECT results CGE baseline uses EFFECT electricity forecasts Macro-micro framework Computable general equilibrium (CGE) model with energy detail CGE model linked to household survey-based micro simulation module for distributional (poverty) analysis Impacts analyzed from macro (GDP, trade) to micro (industries, labor market, household income and poverty) 5

6 Why use a CGE? Economy-wide: Ideal for tracing detailed impacts and identifying transmission channels Policies to reduce carbon footprint will lead to changes in relative energy price then result in changes in the relative prices of goods and services, thus altering the production and economic structure. In turn, the changes in relative prices coupled with changes in economic structure will alter household incomes and consumptions patterns. Downside: Not a bottom-up energy model 6

7 PHILGEM-E model Philippine General Equilibrium model - Energy SAM-based dynamic recursive CGE model of the Philippine economy Extension of PHILGEM model (Corong and Horridge 2012) Facilitates analyses of the possible short- and long-term impacts of policy responses to low carbon growth policies PHILGEM-RD-E explicitly tracks carbon emissions allows for energy substitution among non-energy industries distinguishes electricity generation by technology allows the electricity sector to substitute away from carbon intensive electricity generation technologies towards less carbon-intensive and carbon-free electricity generation technologies 7

8 Production structure Non-energy industries Electricity and energy industries 8

9 Sectors Commodity Description Elements of Set COM Industry Description 1 Paddy rice Paddy 1 Paddy rice 2 Corn Corn 2 Corn 3 Fruits and vegetables FruitsVege 3 Fruits and vegetables 4 Other crops OtherCrops 4 Other crops 5 Livestock and poultry LvstkPoultry 5 Livestock and poultry 6 Other agriculture OtherAgric 6 Other agriculture 7 Mining Mining 7 Mining 8 Coal Coal (Carbon) 8 Coal 9 Crude oil Crude (Carbon) 9 Crude oil and natural gas 10 Natural gas NatGas (Carbon) 11 Processed food ProcFood 10 Processed food 12 Rice, corn, sugar milling Rice 11 Rice, corn, sugar milling 13 Tobacco and alcohol TobacAlchl 12 Tobacco and alcohol 14 Textile, garments and footwear TextGarmFoot 13 Textile, garments and footwear 15 Other manufacturing OtherManuf 14 Other manufacturing 16 Chemicals Chemicals 15 Chemicals 17 Gasoline Gasoline (Carbon) 16 Petroleum refinery 18 Diesel oil DieselOil (Carbon) 19 Fuel oil FuelOil (Carbon) 20 Liquefied petroleum gas LPG (Carbon) 21 Other petroleum products OthPetrol (Carbon) 22 Metal products Metals 17 Metal products 23 Machineries Machines 18 Machineries 24 Electric appliances ElecRelAppli 19 Electric appliances 25 Semi-conductors Semicon 20 Semi-conductors 26 Electricity-oil ElecOil 21 Electricity-oil 27 Electricity-hydro ElecHydro 22 Electricity-hydro 28 Electricity-geothermal ElecGeoth 23 Electricity-geothermal 29 Electricity-coal ElecCoal 24 Electricity-coal 30 Electricity-Natural gas ElecNatGas 25 Electricity-Natural gas 31 Electricity-renewables ElecRenew 26 Electricity-renewables 32 Electricity distribution ElecDist 27 Electricity distribution 33 Utilities Utilities 28 Utilities 34 Retail & wholesale trade Trade (Margin) 29 Retail & wholesale trade 35 Transport Transport (Margin) 30 Transport 36 Communication Communicate 31 Communication 37 Construction Construction 32 Construction 38 Ownership of dwellings Dwellings 33 Ownership of dwellings 39 Public services PublicSrvcs 34 Public services 40 Private services PrivateSrvcs 35 Private services 9

10 Model s database 2010 Social Accounting Matrix Input-Output table updated using 2010 national accounts 2009/2010 Family Income and Expenditure Survey The 35 industries are classified into: 6 agriculture and 3 mining-related industries 3 processed food and beverage industries; 5 manufacturing industries that include petroleum refining 7 electricity industries composed of 6 types of electricity generation technology and an electricity distribution 8 services industries that includes government services. In total, these industries produce 40 commodities. 2 our of 35 industries are multi-product industries CrudeNatGas extraction produces both natural gas and crude oil Petroleum refining industry produces 5 fuel-related commodities such as gasoline, diesel oil, fuel oil, liquefied petroleum gas, and other petroleum products. Households 160 representative household groups classified by the gender of the household head (female and male), by income deciles (deciles 1 to 10), and main source of income (wage earners, entrepreneur, transfer-reliant, and diversified) 160 RHGs mapped to households in the FIES Power generation and carbon emissions data from Department of Energy (DoE) 10

11 Share in CO2 emissions (74.5 million tons, year 2010) LPG 4% Fuel oil 11% Other petrol 2% Coal 37% Energy 1% Others 8% Industry 16% Diesel 24% Transport 32% Gasoline 11% Crude oil 1% Natural gas 10% Electricity 43% Source: Department of Energy 11

12 Electricity generation, by input type (2010) Renewable 90.2 Oil 7,101.0 Renewable 0.1% Oil 10.5% Natural gas 19,517.9 Hydro 7,803.4 Natural gas 28.8% Hydro 11.5% Geothermal 9,929.2 Geothermal 14.7% Coal 23,301.1 Coal 34.4% Generation (in GWh) Shares (in %) Source: Department of Energy 12

13 CGE Baseline Actual 2010 to 2014 GDP growth rates 6% GDP forecast from 2015 to 2050 (shown in Table 3) 1.8% yearly population growth rate 5% yearly depreciation rate Actual electricity generated (in GWh) from 2011 to 2014; and 2015 to 2050 electricity projections (in GWh) from the EFFECT model 13

14 GDP (expenditure-side) 80,000 GDP Consumption Investment Government Exports Imports 60,000 40,000 20, ,000-40,

15 GDP (income-side) 80,000 GDP Land Labour Capital Indirect Tax 60,000 40,000 20,

16 Electricity generation (from EFFECT, in TWh) 400 Coal Oil Natural gas Hydro Geothermal Renewable

17 Electricity generation shares (2030 and 2050) Hydro 6.5% Geothermal 7.3% Renewable 0.3% Natural gas 5.5% Oil 7.2% Hydro 2.4% Geothermal 2.7% Renewable 0.1% Natural gas 15.2% Oil 7.0% Coal 63.7% Coal 82.2% Year 2030 Year

18 CO2 emissions trajectory (in MTCO2-e) 420 Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol

19 CO2 emissions (in % share) 100% Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

20 Renewable Energy (power sector) Policy Scenarios REP Scenario Medium term (relative to 2010) Geothermal: 75% increase (i.e., 16,675 GWh) by 2030 Hydro: 117% increase (i.e., 17,940 GWh) by 2030 Renewable: 100% increase (i.e., 6645) by 2030 In the absence of long term policy, assume by 2050 (relative to 2010) Geothermal: 75% and 150% increase (equivalent to 16,675 and 25,770 GWh) Hydro: 117% and 234% increase (equivalent to and GWh) Renewable: 100% and 200% increase (equivalent to 6645 and 1095 GWh) REP-EFFECT Scenario: Relative to 2016, by 2050 Geothermal: 170% increase (equivalent to 27,863 GWh) Hydro: 765% increase (equivalent to 79,042 GWh) Renewable: 2,502% increase in (equivalent to 9,497 GWh) 20

21 % Change in CO2 emissions (relative to BaU) 0% REP (MT CO2 in %) REP-Effect (MT CO2 in %) -2% -4% -6% -8% -10% -12% -14% -16%

22 CO2 emissions (in MTCO2-e, relative to BaU) 420 REP (in MT CO2-e) REP-Effect (in MT CO2-e) Baseline (in MT CO2-e)

23 CO2 emission reductions (in MTCO2-e relative to BaU) REP (in MT CO2-e) REP-Effect (in MT CO2-e)

24 CO2 emission reductions (in MTCO2-e, by fuel type) REP Scenario (in MTCO2-e) REP-EFFECT Scenario (in MTCO2-e) Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol 24

25 Evolution of CO2 emissions ( ) REP Scenario REP-EFFECT Scenario Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol 25

26 Share in CO2 emissions (by fuel type) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% REP Scenario 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% REP-efficiency Scenario Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol 26

27 Share in CO2 emissions (2030 and 2050) Fuel oil 9% REP Scenarios (2030) LPG 5% Other petrol 2% Coal 32% Fuel oil 9% REP Scenario (2050) LPG 6% Other petrol 3% Coal 27% Diesel 30% Natural gas 6% Gasoline 15% Crude oil refining 1% Diesel 34% Gasoline 17% Crude oil refining 1% Natural gas 3% REP-EFFECT Scenario (2030) Fuel oil 10% LPG 5% Diesel 32% Other petrol 2% Gasoline 16% Coal 27% Crude oil refining 2% Natural gas 6% REP-EFFECT Scenario (2050) Fuel oil 9% LPG 6% Diesel 36% Other petrol 3% Coal 23% Crude oil refining 2% Gasoline 18% Natural gas 3% 27

28 Electricity generation by input type (in TWh) 400 REP Scenario 400 REP-EFFECT Scenario Coal Oil Natural gas Hydro Geothermal Renewable Coal Oil Natural gas Hydro Geothermal Renewable 28

29 Expenditure-side GDP (% change relative to BaU) REP Scenario GDP Government Investment Consumption Exports Imports REP-EFFECT Scenario GDP Government Investment Consumption Exports Imports 29

30 Broad Industry results (in % change) 0.20 REP Scenario Agriculture Manufacturing Serviceis REP-EFFECT Scenario Agriculture Manufacturing Serviceis 30

31 Poverty impacts (in percentage points relative to 2010 index) REP Scenario Poverty Headcount Poverty Gap Poverty Severity REP-EFFECT Scenario Poverty Headcount Poverty Gap Poverty Severity 31

32 Real income effects (in % change relative to BaU) 32

33 Summary and insights Renewable Energy Policy (REP) in the power sector expands GDP Higher investments to sustain increased capital requirements Higher consumption ensues due to higher employment and factor returns that boost household incomes Poverty marginally decreases over time (Income gains among households belonging to middle and higher income deciles) REP in the power sector helps reduce CO2 emissions but needs to be more aggressive to make a dent in future CO2 emission reduction goals of the country 33