meg4c: a computable general equilibrium model for colombia
TRANSCRIPT
MEG4C: A Computable General Equilibrium Model for Colombia
Ana María Loboguerrero Sustainable Environmental Development Deputy Directorate
National Planning Department
LAMP – Second Meeting San José - Costa Rica
October 2 – 4, 2012
CONTENTS
1. MEG4C overview
2. Economics of Climate Change Study for Colombia (impacts and mitigation)
3. Research with LAMP data
The MEG4C Model
• The MEG4C is a recursive dynamic CGEM model based on the OECD GREEN model and built for the assessment of the economic consequences of climate change in Colombia, and the various public policies that can be proposed to face this problem.
• The geographic scope of MEG4C is at the national level, i.e. describing Colombia as a whole country which is interacting with the rest of the world (ROW). Currently a regional version of the model is being developed (department level).
• In the model there are 15 sectors and 4 agents. Sectors are defined by specific aggregations of national accounts that reflect the level of detail needed for the analysis.
SECTORS
Agriculture
Livestock
Fishery
Manufactured foods
Forestry
Fossil fuels
Minerals (Metallic and non-metallic)
Energy
Water and waste services
Industry
Machinery
Construction
Commerce
Transport
Services
INSTITUTIONS
Households
Firms
Government
Rest of the world
The sectors and agents included in MEG4C are:
The MEG4C Model
• Constant returns to scale.
• In the labor market, it is assumed an imperfect substitution between 2 types of labor (skilled and unskilled). It is assumed that demand plus unemployment equals supply by an adjustment of prices, neglecting the possibility of changes in unemployment.
• The ability to substitute or transform domestic goods into exported ones or viceversa is represented by a Constant Elasticity of Transformation (CET) function.
Production
Production Leontief
Intermediate Consumption
Aggregated Value + Energy CES
Labor CES
Capital-Energy Bundle CES
Skilled Unskilled Capital Energy
Good 1 Armington
Domestic
Imported ROW
Good 15 Armington
Domestic
Imported ROW
…
Production
• Homothetic preferences are assumed. • Utility function for households is supposed to be: where µ and θ are ELES parameters, and:
Household Consumption
∑ ⎟⎠
⎞⎜⎝
⎛+−=i
siii PSCU ln)ln( µθµ
icesPSavingsS
nConsumptioC
Pr→
→
→
• The external sector is modeled assuming imperfect substitutability between foreign and domestic goods (for imports the Armington assumption and for exports the Constant Elasticity of Transformation –CET– assumption).
• The decision to produce for the domestic (QD) or the external market (exports, QE) or to demand from the domestic or the external market (imports, QM) is determined by the ratio of the foreign price (PE for exports and PM for imports) to the domestic price (PD). The relevant parameter ruling the substitution possibilities is the elasticity of substitution (εE, εM, both greater than cero).
• If PD increases (for example due to climate change impacts) the domestic producers would prefer to sell in the internal market and therefore will reduce their exports.
External Sector
The dynamics of the model are calibrated according to given rates of population and GDP growth, workforce and labor and capital productivities.
Variable Source
GDP growth rates Data from ECDBC up to 2040 and a growth accounting model from there up to 2100.
Population growth rates DANE data up to 2020 and a model of population growth from there up to 2100.
Labor productivity Calibration for the construction of the baseline GDP
Capital productivity Calibration for the construction of the baseline GDP
Government deficit or surplus and expenditures
Medium-term Fiscal Framework up to 2022 and a constant ratio of GDP from there up to 2100.
Current account deficit or surplus Medium-term Fiscal Framework up to 2022 and a constant ratio of GDP from there up to 2100.
Calibration
Growth Accounting
• Labor (population, labor force, unemployment) • Total Factor Productivity • Investment
GDP Growth
Growth Model
The growth accounting model assumes a Cobb-Douglas production function:
where capital accumulation is achieved through an investment structure described by the following equation:
( )( ) αα KLuAY −−= 11
11)1( −− +−= ttt IKK δ
• A structural unemployment rate u of 7,5% was considered.
• Capital share in output is 40% (this percentage has been obtained from national accounts for the last 20 years).
• The depreciation rate δ is 4,92%.
• Investment I is fixed at 35% of GDP.
• The analysis gives as result an average GDP growth rate of nearly 5% up to 2022, after this, calculations with the Cobb-Douglas model give 3,6%.
• The election of the different parameters was done following Julio (2001) and Arango, Posada and García (2007).
Growth Model
Important Assumptions
Assumptions
Effect on results G o v e r n m e n t s a v i n g i s m o d e l e d exogenously, that is, tax rates adjust endogenously to obtain a specified level of savings.
Insights of the impacts of climate change policies on government revenue are limited.
Savings determine investment, that is, given a savings level for the economy, the investment level is automatically established for each period.
There is no consistent way to modify investment exogenously.
Current account balance is adjusted through the exchange rate to obtain a fixed value.
Insights of the impacts of climate change policies on trade balance, exports and imports are limited.
The elasticities used in the model. These values were obtained from Bourneaux, Nicoletti, & Oliveira-Martins (1992).
Results about the substitution possibilities (between inputs, and between domestic and foreign goods) are sensible to the chosen values.
Baseline dynamics and calibration. Model stability under impacts is sensible to the dynamic parameter specification.
Economics of Climate Change Study using MEG4C
MEG4C can be used to assess the economic costs of climate change and of adaptation measures
Results on Climate Change
In terms of per capita consumption, it is found that it falls 8.01% with respect to the baseline scenario in 2100.
MEG4C is able to provide data about the way climate change impacts spread through out sectors different from the directly impacted ones. For instance, data show that the manufactured food sector suffers a large indirect impact under an A1B scenario.
Mitigation Analysis
Changes in demand parameters and external demand for forest related
goods
CO2eq taxes levied on energy goods consump:on
Analyzed measures: Demand-‐side measures (efficient bulbs, refrigerators and electric vehicles) and supply-‐side measure (forest
planta:ons).
Analyzed measures: Demand-‐side measures, Electricity genera:ons measures
(wind park and geothermal plant) and Transport measures (BRT,SITP,SETP and
truck scrapping) MEG4C
CEDEC Study Cost-‐benefit analysis
MITIGATION ANALYSIS
In the same way, MEG4C gives useful insights about the economic effects of mitigation measures, including taxation policies to curb emissions (green taxes).
Marginal Abatement Cost Curve
CO2eq Taxes Exercise
• Green taxes are levied on households, energy and transport sectors to reach the same emission reductions obtained with cost-benefit analysis.
• It is assumed that tax revenue is used to encourage some behavior in other sectors as would be expected from specific mitigation measures.
• Since CO2eq taxes generate a new revenue source for the government, it is important to analyze different scenarios for the use of this new income (recycling mechanism); the following three were used:
– NR: no specific destination – KCR: the tax revenue subsidizes the capital expenditure – LCR: the tax revenue subsidizes the labor expenditure
.
Cost-benefit analysis change in CO2eq emissions
CO2eq Taxes Exercise
Efficient bulbs and refrigerators (households’ electricity consumption)
Electric vehicles households’ fossil-fuel consumption
Transport sector Energy generation sector
Percental change in national GDP:
RESULTS
CO2eq Taxes Exercise
Percental change in sectoral GDP in each scenario:
RESULTS
It is important to notice the effect that the measures have on the energy sectors. Particularly, although the tax is never imposed to the fossil fuels sector, this is specially affected.
CO2eq Taxes Exercise
The CO2eq emissions reduction is related with the behavior of the GDP
RESULTS
Mitigation measure
Effect on the sector
Effect on other sectors
Sectoral emissions reduction
Indirect emissions change
Variable effect on aggregate emissions
CO2eq Taxes Exercise
Example: Efficient Bulbs
Demand-side measures: Efficient bulbs
Expenditure in electricity
Expenditure in manufactures
Substitution of incandescent bulbs
Substitution of refrigerators
Change in the minimum consumption parameter of the electricity goods and the manufacturing goods
Energy efficiency measures
Since the goods of the CEDEC study are not the same as those from the MEG4C, it is necessary to calculate factors of proportionality. These are calculated using the data from the CEDEC study (expenditure in bulbs) and the data from the SAM.
Sectoral GDP
Decrease electricity GDP
Households Consumption
GDP
Decrease electricity household consumption Increase
disposable income
Increase consumption of other goods
Increase in GDP
Example: Efficient Bulbs
CO2 Tons changes
Supply-side Measures – Forestry Plantations
Forestry Plantations actions
CO2eq emissions reduction by carbon capture
Generate an increase in the forestry sector GDP
Change in the foreign demand for forestry goods
Foreign demand
Sectoral GDP increases 400% in 2040
• Part of the new output of the forestry sector is sold domestically replacing illegal plantations products but the major part of it will be exported.
• Since the model does not contain a land factor market, a ratio of carbon capture to GDP increase is obtained from CEDEC study to calculate the reduction in CO2eq emissions.
Supply-side Measures – Forestry Plantations
Change in GDP Sectoral contribution to the GDP growth
Increase in external demand for forestry goods
Increase in forestry GDP
Increase inputs used in forestry
Increase in household income
Increase consumption for other goods
GDP increases
Research with LAMP Data LAMP database could be an input to MEG4C for:
Option Description 1. Trends for exogenous variables. LAMP database results on trade, capital
flows, international prices, etc., can be used in MEG4C to further specify implications for Colombia of other models’ results.
2. Building new energy-related scenarios. LAMP data can support technological assumptions about energy sectors which can be used in MEG4C to investigate its indirect economic effects in Colombia.
3. Comparison of climate change/related policies’ effects among countries.
Once comparability of data sets is established for models’ results concerning Colombia, insights of relative impacts between Colombia and similar countries could be obtained.
4. Information on variables not specifically modeled by MEG4C.
After appropriate downscaling to Colombia, results on variables not included in MEG4C, such as land use, can be used to refine scenarios until future developments are made in the model.
Research with LAMP Data
In addition to the possibilities shown before, interaction between MEG4C and the other models within the LAMP effort could open up new areas of research in the medium- and long-run:
• A wider framework for analyzing specific mitigation measures additional to the ones considered until now (carbon taxes).
• Perspectives about modeling and implementation of biodiversity, ecosystem services, etc.
• Exchange of modeling experiences, specific details of implementation, solving and analysis.
• Economics of the adoption of new/cleaner energy technologies by Latin American countries, and in particular CCS technologies, in response to climate change or proposed related policies.