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The Economics of Climate Change Study for Colombia –
EIECC
Ana María Loboguerrero Sustainable Environmental Development
Deputy Directory
LAMP – First Meeting Belo Horizonte
January 17 – 19, 2012
Index
1. EIECC
2. PHASE 1
National CGE
3. PHASE 2
SECTORAL AND REGIONAL STUDIES
4. 2012 AGENDA
What is the DNP?
• Is the national authority for public policy, investment budget and monitoring and evaluation of investment projects.
• Is the technical counterpart of all sectoral
ministers and designs inter-sectoral policies.
EIECC Objective
Quantify the economic cost of CC impacts in Colombia and the optimal responses for its economy
Propose public policies in adaptation and mitigation in order to minimize costs.
Prioritize these actions in order to elaborate a short, medium and long run national agenda.
Identification of information gaps for the strengthen of information and data generation in order to follow-up programs and policies related to CC.
National Development Plan 2010 -
2014
National Adaptation
Plan
Disaster Financial Protection Strategy
National Strategy for
REDD+
Colombian Low Carbon
Growth Strategy
CONPES 3700
Institutional Framework
Sustainable Development
ECONOMICS AND POPULATION ECOSYSTEMS CLIMATE CHANGE -‐ CLIMATE
1
ADAPTATION PROCESSES
MITIGATION PROCESSES
CLIMATE IMPACTS ON THE ECONOMY AND POPULATION – ADAPTATION ACTIONS
CLIMATE IMPACTS ON ECOSYSTEMS AND ENVIRONMENTAL GOODS AND SERVICES – ADAPTATION ACTIONS
USAGE OR IMPACT ON ECOSYSTEMS
SECTORIAL AND POPULATION IMPACT ON CLIMATE (MITIGATION)
2
2
3
4
1
2
3
4
Risk Management
5
5 CLIMATE AND MICROCLIMATE REGULATION
EIECC General Structure
National Sub commission of EIECC Coordinator : DNP
Economics and Population (macro and micro studies)
Led by SDAS and DEE
Ecosystems Led by Directory Board IAVH
+ DNP team
Climate Change – Climate
Led by IDEAM + DNP team
Experts: CIAT, IRI, Universidad de Sao Paulo, DANE, BANREP Universities: Andes, Nacional, Valle, Cauca, among others.
Groups: CENICAFE, CENICAÑA, CENIFLORES, among others. Others: CLIMATE NETWORKS, energy sectors, other sectors.
PHASE 1: NATIONAL CGE
Indirect Effects
Backward Linkages (diffusion): Measure the dependence of the domestic production with respect to a specific sector. Forward Linkages (absorption): Measure the dependence of a specific sector with respect to all other sectors.
Some Results 2005
Agricultural producBon in 2005 was approx. : $ 20.200* Taking into account the indirect effects: 1,54 x $ 20.200 = $31.100 Value creaBon: $10.900
Sector Diffusion Absorp?on Food 2,23 1,44 Construc?on 2,07 1,17 Industry 1,95 3,69 Transport 1,92 1,87
Energy 1,87 2,28 Trade 1,78 2,79 Fishery 1,69 1,05
Energy from mining 1,68 1,31 Livestock 1,62 1,45 Water, sewage and wastes services 1,59 1,05 Machinery 1,55 1,65 Forestry 1,55 1,02 Agriculture 1,54 1,25 Minerals 1,46 1,08 Services 1,43 2,83
* in billions of pesos
Agricultural loss was approx. 1.200 billions of pesos*. Considering indirect effects and the structure of the economy in 2005: -‐1,54 x $ 1.200 billions = -‐$1.900 billions Value creaBon: -‐654 billions, represent 2,7% of GDP from agriculture.
GDP Loss: Heavy Rainy Season 2010
*Approx. 5% of GDP from agriculture and 0,44% of 2005 GDP.
Sector Diffusion Absorp?on Food 2,23 1,44 Construc?on 2,07 1,17 Industry 1,95 3,69 Transport 1,92 1,87
Energy 1,87 2,28 Trade 1,78 2,79 Fishery 1,69 1,05 Energy from mining 1,68 1,31 Livestock 1,62 1,45 Water, sewage and wastes services 1,59 1,05 Machinery 1,55 1,65 Forestry 1,55 1,02 Agriculture 1,54 1,25 Minerals 1,46 1,08 Services 1,43 2,83
• Institutions: – Households – Firms – Government – Rest of the world
• Sectors: – Agriculture – Livestock – Fishery – Food – Forestry – Energy from mining (coal, oil, etc.). – Minerals (metallic and non metallic). – Energy – Water, sewage and wastes services – Industry – Machinery – Construction – Trade – Transport – Services
National CGE (GREEN Model)
Production Leontief
Intermediate Consumption
Value Added CES
Labor CES
Capital - Energy Bundle CES
Skilled Unskilled Capital Energy
Good 1 Armington
Domestic
Import ROW
Good 15 Armington
Domestic
Import ROW
…
Production
Model General Methodology
Sectoral studies
Harmed sectors
Inter-sectoral movements and relationships
Damage functions
Microsimulations
Macroeconomic results
Agriculture
Livestock
Fishery
Forestry Water
Infrastructure
Agriculture and livestock annually and department level from AGRONET. Fo res t r y and f i she ry functions form USA study.
Population
0
0,002
0,004
0,006
0,008
0,01
0,012
0,014
0,016
0,018
0,02
0
10
20
30
40
50
60
70
80
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Grow
th rate
Populatio
n and WAP
in millions
Population and Working Age Population
WAP POP WAP GR POP GR
Growth Model: Base Line
Simple accounting model using a constant returns to scale Cobb-Douglas production function:
Capital is accumulated through the common investment structure:
Having as exogenous variables the unemployment rate u, investment rate I, total factor productivity A, capital and labor share on income, capital depreciation δ and population L, that comes from the population model.
( )( ) αα KLuAY −−= 11
11)1( −− +−= ttt IKK δ
Macroeconomic Results
MACROECONOMIC VARIABLES
GDP Percentage Loss (A1B)
MACROECONOMIC VARIABLES
Macroeconomic Results
In terms of per capita consumption at the end of 2040 consumption would have fallen 4,49%. The Balance Growth Equivalent of the discounted consumption path converts to present value the annual loss for an equilibrium trajectory:
Rate 2% 4% 6% 8% 10% Present Value Loss -7,43% -2,76% -1,57% -1,03% -0,72%
Unemployment HH Disposable Income
GDP Loss: Heavy Rainy Season 2010
A reduction of 2,2% in agricultural productivity was estimated. According to the CGE, the effect of this reduction would propagate over time:
-‐0.82%
-‐1.01%
-‐0.62%
-‐1.20%
-‐1.00%
-‐0.80%
-‐0.60%
-‐0.40%
-‐0.20%
0.00% 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039 2041 2043 2045 2047 2049
Pérdida % PIB GDP % LOSS
Microsimulations
• This exercise takes prices and wages until 2100 from the CGE. Using the Life Quality Survey, a goods and services bundle is constructed for the 13611 households and finally the change in the price of this bundle is calculated.
• Using these results is possible to measure the effect of CC (through prices) by income quintiles, Gini coefficients and by changes in population living below the poverty line.
Microsimulations Results
People with lower income use a higher proportion of it to buy food. Food prices grow fast in a CC scenario
Average difference on welfare by quintiles as % of expenditure
Microsimulations Results
0,0%
5,0%
10,0%
15,0%
20,0%
25,0%
30,0%
35,0%
40,0%
45,0%
50,0%
2006 2026 2046 2066 2086
Porc
enta
je d
e la
pob
laci
ón v
ivie
ndo
por d
ebaj
o de
la lí
nea
Pobreza e Indigencia en Colombia según LP y LI, según los escenarios con CC y sin CC
LI, LP con CC LI, LP sin CC
Línea de pobreza
Línea de indigencia
Even though in both scenarios (with and without CC) it is expected that poverty will be reduced, CC could be responsible of a lower impact of social
policies and programs.
0,0%
5,0%
10,0%
15,0%
20,0%
25,0%
30,0%
35,0%
40,0%
45,0%
50,0%
2006 2026 2046 2066 2086
Porc
enta
je d
e la
pob
laci
ón v
ivie
ndo
por d
ebaj
o de
la lí
nea
Pobreza e Indigencia en Colombia según LP y LI, según los escenarios con CC y sin CC
LI, LP con CC LI, LP sin CC
0,0%
5,0%
10,0%
15,0%
20,0%
25,0%
30,0%
35,0%
40,0%
45,0%
50,0%
2006 2026 2046 2066 2086
Porc
enta
je d
e la
pob
laci
ón v
ivie
ndo
por d
ebaj
o de
la lí
nea
Pobreza e Indigencia en Colombia según LP y LI, según los escenarios con CC y sin CC
LI, LP con CC LI, LP sin CC
Poverty Line
Indigence Line
NO CC CC
Policy Recommendations
After finishing the study, the most efficient alternatives for each objective can be implemented in National Development Plans, Policy Documents, etc.
p16eh
US$ 123 Bill
29% BAU
p30eh
US$ 88,5 Bill
21% BAU
p30el 25% BAU
US$ 106 Bill
US$ 135 Bill
32% BAU
Adaptation Savings
SN 0 Bill
0% BAU
Mitigation Commitments
p16el
PHASE 2:
SECTORAL AND REGIONAL STUDIES
The population projections are based on a fertility vs. mortality basic model and were calibrated in order to replicate the regional projections from the IPCC.
IPCC Scenarios – Population
0
10
20
30
40
50
60
70
80
90
100
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2110
Población en Colombia para los escenarios de CC (En millones)
Colombia A1B1 Colombia A2 ColombiaB2A1B1 A2 B2
Population in Colombia for the IPCC scenarios (millions)
IPCC Scenarios - Economy
0
20000
40000
60000
80000
100000
120000
140000
2005 2020 2035 2050 2065 2080 2095
A2
A1B
B2
GDP per capita (in thousands of 2005 pesos)
Growth Accounting
• Labor (population, WAP, unemployment) • Total factor productivity • Investment
GDP Growth
GDP Loss by Scenarios
-‐2.50%
-‐2.00%
-‐1.50%
-‐1.00%
-‐0.50%
0.00%
0.50% 2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
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
A1B A2 B2
Regional CGE
• CC impacts do not affect the country homogenously, on the contrary, each region is affected in a different way. Therefore, analyses should be regional in order to be effective for implementing adaptation and mitigation strategies.
• A regional CGE allows to estimate CC impact by departments given that shocks with different magnitudes can be simulated for each region.
Regional CGE National CGE
-5% -20%
+10%
High levels of WUI
Forecasts of sharp falls on mean stream
flows
High climate change vulnerability
CLIMATE CHANGE – POTABLE WATER PROVISION
RCGE – Efficiency Potable Water Provision
Water Use Index Change in annual mean stream flow
• Water and sewage GDP reduction in Andina and Caribe Region.
• National GDP and regional GDP reduction.
• Dispersion effect on less affected regions due to CC
• Andina and Caribe regions concentrate more than 70% of population and economic activity and are at the same time the most affected.
MACROECONOMIC EFFECTS – REDUCTIONS IN MEAN STREAM FLOW
RCGE – Efficiency Potable Water Provision
Sectoral Studies
REFINE THE DAMAGE FUNCTION FOR DIFFERENT TYPE OF CROPS
Cotton Rice Sugar Cane
Coffee Plantain
Banana Corn
Potato
_ +
Impact Level
¿How do Ecological Niche Models work?
Present
Climate Change Scenario
+ ......
Modeling algorithm
....
..
Potential distribution under present conditions
Potential distribution under new conditions
+ ...... ....
..
Biodiversity and Climate Change
Construct a database of environmental variables (temperature, precipitation, elevation, evapotranspiration, relative humidity, NDVI) for each reported entry.
+ +
60.846 entries
• Clasify the species statistically into clusters based on the environmental variables
We identify 22 independent clusters which are going to be modeled as dicrete units
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des0
500
1000
1500
2000
Cluster Dendrogram
hclust (*, "average")distancia1
Hei
ght
Biodiversity and Climate Change
The actual and future distributions were modeled:
It can be seen how climate change can affect the characteristics for a specie to potentially exist
Biodiversity and Climate Change
Climate Change Scenario Actual
Sectoral Studies:
o Damage functions for livestock, fishery, forestry, transport, water and biodiversity and incorporation into the regional CGE (Technical Cooperation IDB).
o Consolidation of results for agriculture (Aquacrop Project with FAO).
Modeling:
o Introduce land use change issues into the model. o Define a damage function for tourism.
2012 Agenda
SOME PERSPECTVES
RCGE
o Incorporate extreme events impacts into the RCGE (Technical Cooperation IDB).
o Microsimulations at the regional level.
Adaptations Measures:
o Specific adaptation measures according to the analysis of the EIECC. o Cost-benefit analysis of adaptations measures and incorporation in the
CGE as support for the National Adaptation Plan for Climate Change (Technical Cooperation IDB).
2012 Agenda
SOME PERSPECTIVES
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