Based on joint works with - Bioversity International

Introducing Biodiversity issues in a Global
Computable General Equilibrium Model:
the MIRAGE example
DR. DAVID LABORDE D.LABORDE@CGIAR.ORG, IFPRI
BA SE D O N JO I N T WO R KS W I T H :
Anouch Missirian, IFPRI-Columbia University for biodiversity focus
Dr. Lauren Deason, IFPRI for nutrition focus
Prof. Antoine Bouet, IFPRI-University of Bordeaux for Household modeling focus
[…]
Introducing biodiversity in a global CGE
Multi dimensional issues (additivity, separability)
Different scales
Direct and indirect effects
Conceptually: still some challenges
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Biodiversity as a Stock and factor of production
Ecosystem services as a flow
Role of time frame
Role of scale: average vs concentration, average vs marginal
Non linearity, irreversibility
Moving across scale: No Bijection!
Dynamic issues and discount factor!
Quantification: huge challenges, especially when tackling uncertainties properly
Crop genetics,
evolution, traits
Crop varieties,
diversification
Biocontrol /
Pollination
Biodiversity in
Food
Loop
effects
Biodiversity
Long term yield growth, adaptation
capacity
Higher resilience, stress response
Reduced input uses, “higher” yield
Better nutrition
Ecosystem services beyond
agriculture
Total Factor Productivity
(TFP)
Lower yield/TFP volatility, joint
production pattern, constraint
e.g. on mechanization
TFP, land productivity and input
uses, constraint e.g. on human
capital
Nutrition metrics, Labor
productivity
Efficiency of the water system,
Productivity of tourism, Health
Land Use changes - Production Pattern
Inpiut Uses - (flows, accumulation)
Conceptual Framework:
A simplified view on [Ag.] biodiversity from a CGE modeler
MIRAGE-CGE Framework
KEY ELEMENTS
Global dynamic CGE, multi sectoral. Baseyear 2012
Main data sources:
◦ GTAP but a lot of modifications, fixes and updates
◦ Reconstruction of agricultural accounts using FAO, EUROSTAT, USDA,
Bloomberg (consistency between physical and monetary flows)
◦ Trade policy instruments (specific sources)
◦ Foreign Direct Investments
◦ Household surveys
◦ ….
Up to 87 sectors/products and 130 regions. However, most simulations
focus on a 35 x 40 configuration.
Different versions
◦ MIRAGE-CC: Long term, 2050, climate change focus
◦ MIRAGE-HH: Medium term, 2030, Focus on household heterogeneity. Full
bottom up HH modelling.
◦ MIRAGE-Biof: Medium term, 2030, land use focus, different biomass-to-energy
pathways, higher crop disagregation (e.g. 5 oilseed crops)
FRAMEWORK
Remark: CGE are bottom-up models. Should not confuse the level
of aggregation and how entities interact in a model.
Structural model, no reduced forms:
◦ Production function with a inputs and factors
◦ Utility function driven demand function: true welfare
analysis
Prices clear markets for each product, from each origin
 Product differentiation
Factors of production (2 to 10 types of labor, capital,
natural resources, land)
Private and Public income (government finance)
Recursive dynamic
Model focus: Land Markets – at the AEZ Level
In average 200-300 production unit by sector
Wheat
Corn
Infra-country
modelling to capture
land heterogeneity
Oilseeds
CET
Sugar
crops
Substitutable
crops
Other
crops
Vegetables
and fruits
CET
Livestock1
LivestockN
CET
Cropland
Pasture
CET
Managed
forest
Agricultural
land
CET
Unmanaged land
Natural forest - Grasslands
Land extension
Managed land
PAGE 6
Illustration MIRAGE-CC:
Global Land Use Change by 2050:
Cropland expansion. +2.4 Mio Km2 (+20.3%). Pasture will be reduced by 2.07 Mio Km2 (still deforestation)
Africa
America
Asia
CIS
EU27
LAC
Row
Illustration. MIRAGE-CC by 2050. Central Scenario. Laborde 2014
Illustration MIRAGE-Biof:
Differentiated Cropland increase of an increase of the EU
biofuel demand, by region, by trade policy regime
Laborde 2012
Illustration MIRAGE-Biof:
More cropland or More Carbon (Ha by TJ and Tons CO2 eq by Ha of
cropland), by feedstock
Note : The bars (left y-axis) show the amount of additional net cropland by TJ of biofuel produced
for one feedstock. The line (right x-axis) shows the average tons of CO2 equivalent by net Ha of
cropland.
Laborde 2012
Illustration MIRAGE-HH:
Assessment of policy reforms or external shocks at the country
and HH level. Illustration: global trade liberalization
6
One bubble = one household category
Bubble size = Number of people in this household category
5
4
4
2
% Increase in Real Income
% Increase in Real Income
3
2
1
0
2
4
6
2
4
6
-2
8
10
-6
-1
-2
0
-4
0
-2
0
-2
-8
Initial level of Income of the household
Tanzania
Initial level of Income of the household
Brazil
8
10
12
MIRAGE Model outputs
Agricultural production
land use
input uses (chemicals, manure)
agricultural and non agricultural prices
Factor prices (wages, different skills, urban/rural, formal/informal, male/female)
Capital accumulation
income effects, including
Employment
Food consumption
At this stage, no feedback effect from biodiversit
Land Use  Biodiversity.
Top down approach
1. A generic approach to link land use and biodiversity measured as Species richness
Different habitats (model outputs), at an AEZ level
2. A site specific approach: linking CGE output with a local land use model.
Spatial econometric model estimated on detailed grid-information :
◦ for land use
◦ for bird population (STOC data, biodiversity metrics)
Focus: The role of a detailed bilateral trade database on
nutrition contents. 800 products, 220 trading partners
Focus: Food Diversity and concentration
Looking at imports for human consumption only.
Average Number of Products
# Products
Herfindahl-Hirshman Index Product Space
# Exporters
Proteins
Calories
1998-2000
2011-2013
1998-2000
2011-2013
1998-2000
2011-2013
1998-2000
2011-2013
Afghanistan
97
397
1.5
3.7
0.731
0.428
0.516
0.263
Argentina
514
429
5.3
4.8
0.402
0.064
0.201
0.067
Australia
548
546
10.4
15.7
0.129
0.041
0.054
0.021
Brazil
540
502
6.4
7.4
0.338
0.309
0.341
0.262
China
575
558
9.4
14.5
0.371
0.733
0.132
0.270
Ghana
310
491
3.0
7.1
0.234
0.088
0.187
0.093
Guatemala
491
495
3.9
4.7
0.173
0.139
0.134
0.132
Malawi
221
359
1.7
2.2
0.207
0.268
0.160
0.180
Mali
250
309
3.0
3.7
0.137
0.244
0.146
0.187
Paraguay
379
369
3.0
3.7
0.209
0.158
0.135
0.056
United States of America
601
585
20.9
24.9
0.035
0.030
0.026
0.024
Uzbekistan
230
299
2.5
3.2
0.498
0.364
0.370
0.263

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