Center for Global Trade Analysis
Department of Agricultural Economics, Purdue University
403 West State Street, West Lafayette, IN 47907-2056 USA
http://www.gtap.agecon.purdue.edu
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
• Introduction and motivation
• Methodology
• Business as Usual (BaU) or Baseline scenario
• Simulation results
• Insights
Presentation outline
2
• 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
Motivation
3
• 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
Methodology
4
• 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)
Modeling approach
5
• 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
Why use a CGE?
6
• 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
PHILGEM-E model
7
Production structure
8 Non-energy industries Electricity and energy industries
Sectors
9
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
• 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 38400 households in the FIES
• Power generation and carbon emissions data from Department of Energy (DoE)
Model’s database
10
Share in CO2 emissions (74.5 million tons, year 2010)
11
Coal 37%
Crude oil 1%
Natural gas 10%
Gasoline 11%
Diesel 24%
Fuel oil 11%
LPG 4%
Other petrol 2%
Industry 16%
Electricity 43%
Transport 32%
Energy 1%
Others 8%
Source: Department of Energy
Electricity generation, by input type (2010)
12
Oil 7,101.0
Hydro 7,803.4
Geothermal 9,929.2
Coal 23,301.1
Natural gas 19,517.9
Renewable 90.2
Oil 10.5%
Hydro 11.5%
Geothermal 14.7%
Coal 34.4%
Natural gas 28.8%
Renewable 0.1%
Generation (in GWh) Shares (in %)
Source: Department of Energy
• 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
CGE Baseline
13
GDP (expenditure-side)
14
-40,000
-20,000
0
20,000
40,000
60,000
80,000
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
GDP Consumption Investment Government Exports Imports
GDP (income-side)
15
0
20,000
40,000
60,000
80,000
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
GDP Land Labour Capital Indirect Tax
Electricity generation (from EFFECT, in TWh)
16
0
50
100
150
200
250
300
350
400
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
Coal Oil Natural gas Hydro Geothermal Renewable
Electricity generation shares (2030 and 2050)
17
Coal 63.7% Oil
7.0%
Natural gas 15.2%
Hydro 6.5%
Geothermal 7.3%
Renewable 0.3%
Year 2030
Coal 82.2%
Oil 7.2%
Natural gas 5.5%
Hydro 2.4%
Geothermal 2.7% Renewable
0.1%
Year 2050
CO2 emissions trajectory (in MTCO2-e)
18
0
60
120
180
240
300
360
420
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol
CO2 emissions (in % share)
19
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
Coal Crude oil refining Natural gas Gasoline Diesel Fuel oil LPG Other petrol
• 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 17940 and 30517 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)
Renewable Energy (power sector) Policy Scenarios
20
% Change in CO2 emissions (relative to BaU)
21
-16%
-14%
-12%
-10%
-8%
-6%
-4%
-2%
0%
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP (MT CO2 in %) REP-Effect (MT CO2 in %)
CO2 emissions (in MTCO2-e, relative to BaU)
22
0
60
120
180
240
300
360
420
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP (in MT CO2-e) REP-Effect (in MT CO2-e) Baseline (in MT CO2-e)
CO2 emission reductions (in MTCO2-e relative to BaU)
23
-55.0
-45.0
-35.0
-25.0
-15.0
-5.0
20
16
20
17
20
18
20
19
20
20
20
21
20
22
20
23
20
24
20
25
20
26
20
27
20
28
20
29
20
30
20
31
20
32
20
33
20
34
20
35
20
36
20
37
20
38
20
39
20
40
20
41
20
42
20
43
20
44
20
45
20
46
20
47
20
48
20
49
20
50
REP (in MT CO2-e) REP-Effect (in MT CO2-e)
CO2 emission reductions (in MTCO2-e, by fuel type)
24
-30
-25
-20
-15
-10
-5
0
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP Scenario (in MTCO2-e)
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
-60
-50
-40
-30
-20
-10
0
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP-EFFECT Scenario (in MTCO2-e)
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
Evolution of CO2 emissions (2016-2050)
25
0
60
120
180
240
300
360
420
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP Scenario
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
0
60
120
180
240
300
360
420
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP-EFFECT Scenario
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
Share in CO2 emissions (by fuel type)
26
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20
17
20
19
20
21
20
23
20
25
20
27
20
29
20
31
20
33
20
35
20
37
20
39
20
41
20
43
20
45
20
47
20
49
REP-efficiency Scenario
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20
17
20
19
20
21
20
23
20
25
20
27
20
29
20
31
20
33
20
35
20
37
20
39
20
41
20
43
20
45
20
47
20
49
REP Scenario
Coal Crude oil refining Natural gas
Gasoline Diesel Fuel oil
LPG Other petrol
Share in CO2 emissions (2030 and 2050)
27
Coal32%
Crude oil refining
1%
Natural gas6%
Gasoline15%
Diesel30%
Fuel oil9%
LPG5%
Other petrol2%
REP Scenarios (2030)
Coal27%
Crude oil refining
1%
Natural gas3%
Gasoline17%
Diesel34%
Fuel oil9%
LPG6%
Other petrol3%
REP Scenario (2050)
Coal27%
Crude oil refining
2%
Natural gas6%
Gasoline16%
Diesel32%
Fuel oil10%
LPG5%
Other petrol2%
REP-EFFECT Scenario (2030)
Coal23% Crude oil
refining2%
Natural gas3%
Gasoline18%
Diesel36%
Fuel oil9%
LPG6%
Other petrol3%
REP-EFFECT Scenario (2050)
Electricity generation by input type (in TWh)
28
0
50
100
150
200
250
300
350
400
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP Scenario
Coal Oil Natural gas Hydro Geothermal Renewable
0
50
100
150
200
250
300
350
400
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
REP-EFFECT Scenario
Coal Oil Natural gas Hydro Geothermal Renewable
Expenditure-side GDP (% change relative to BaU)
29
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP Scenario
GDP Government Investment Consumption Exports Imports
-0.2
0
0.2
0.4
0.6
0.8
1
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP-EFFECT Scenario
GDP Government Investment Consumption Exports Imports
Broad Industry results (in % change)
30
-0.05
0.00
0.05
0.10
0.15
0.2020
16
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
REP Scenario
Agriculture Manufacturing Serviceis
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
REP-EFFECT Scenario
Agriculture Manufacturing Serviceis
Poverty impacts (in percentage points relative to 2010 index)
31
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
0.00
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP Scenario
Poverty Headcount Poverty Gap Poverty Severity
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050
REP-EFFECT Scenario
Poverty Headcount Poverty Gap Poverty Severity
Real income effects (in % change relative to BaU)
32
• 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
Summary and insights
33
