agriculture, food security and climate change—the...
TRANSCRIPT
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Agriculture, food security and climate change—the global context
Dominique van der Mensbrugghe
Center for Global Trade Analysis (GTAP)
Purdue University
Scaling in global regional and farm models
change the global context
Scaling in global, regional and farm models
Trade M workshop
Vienna, 24 September 2014
Key policy relevant questions
• Long-term evolution of agricultural and food prices, food security and nutrition
• Dual challenge—undernourishment and obesityg y
• Land expansion versus production intensification
• Impact of future climate change on prices, land use, trade, undernourishment
• Potential role of biofuels
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Long-term downward trend in real agricultural prices though-out the 20th century
700
800
900
1000
ic t
on
Rice (Thai)
100
200
300
400
500
600
700
Re
al p
rice
s in
20
10
$U
S p
er
me
tri
Wheat (US HWT)
Maize (US #2)
0
1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
Source: World Bank pink sheet (http://go.worldbank.org/4ROCCIEQ50, accessed 7-Jan-2014) and own calculations
Note: 4-year leading moving average (last year available = 2013).
Large quantity changes for major commodities
5
6
1.000
1.200
1961 2005 Growth (index 1961=1, right-axis)
1
2
3
4
200
400
600
800
Me
tric
to
ns
00
Meats Rice Wheat Coarse grains
Source: FAO.
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Yield improvements account for over 70 percent of production growth
5
6
5.000
6.000
Average cereal yield, 1961 Average cereal yield, 2005 Annual growth, percent
1
2
3
4
1.000
2.000
3.000
4.000
Kilo
gram
pe
r h
ect
are
00
World East Asia South Asia Near East & N. Africa
sub-Saharan Africa
Latin America High-income
Source: FAO.
Global land expansion for crops of around 250 million hectares
2,5
3,0
1.000
1.200
Crop land use, 1961 Crop land use, 2005 Growth (index 1961=1, right-axis)
0,5
1,0
1,5
2,0
200
400
600
800
Mill
ion
he
ctar
es
0,00
World East Asia South Asia Near East & N. Africa
sub-Saharan Africa
Latin America High-income
Source: FAO.
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Radical change in the future?
80
100
120
1960-2010 Trend 2010-2050 w/o climate change 2010-2050 w/ climate change
-60
-40
-20
0
20
40
60
Pe
rce
nt
chan
ge
-80
Wheat Maize Rice
Source: World Bank pink sheet and own calculations for historical series, Nelson et al. (2010) for future price scenarios.
Slowing population growth, however…
8.000
9.000
10.000
HIC ECA EAP LAC MNA SAA SSA
1,120
2,414
Population, SSP2, million
8.000
9.000
10.000
Developing countries
SSP3
SSP2
Population, SSP2 v. SSP3, million
2.000
3.000
4.000
5.000
6.000
7.000
8.000
107
203
241
665
2.000
3.000
4.000
5.000
6.000
7.000
SSP2High-income countries
0
1.000
2010 2050
67
11
Note: 2010-2050 incremental change indicated in 2050 column. High-income (HIC), Europe & Central Asia (ECA), East Asia & Pacific (EAP), Latin America & Caribbean (LAC), Middle East & North Africa (MNA), South Asia (SAA), Sub-Saharan Africa (SSA).
0
1.000
2010 2015 2020 2025 2030 2035 2040 2045 2050
SSP3
g
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GDP per capita under SSP2 and SSP3, $2007
60.000
70.000
2010 2050—SSP2 2050—SSP3
1.3
1.1
10.000
20.000
30.000
40.000
50.000
0.83.6
2 0
4.8
3.25.1
2.8
1.82.1
1.3
2.5
1.2
2.0
0
World Developing East Asia & Pacific
South Asia Europe & Central Asia
Middle East & North Africa
Sub-Saharan Africa
Latin America & Caribbean
High-income
2.03.3
1.63.6
Note: Growth rates, percent per annum, on top of columns.
History vs. projected yield growth, percent per annum
3,5
4,0
4,5
1970/1990 1990/2010 2010/2030 2030/2050
0 0
0,5
1,0
1,5
2,0
2,5
3,0
0,0
World Developing High-income World Developing High-income World Developing High-income
Wheat Rice Maize
Source: 1970/2010 FAOSTAT (accessed 22-Jul-2013), IFPRI’s IPRs and own calculations
Note: Slight differences in regional aggregations between history and projections. Maize yield projections equivalent to coarse grain definition in GTAP.
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IFPRI vs. FAO AT projections
1 4
1,6
1,8
2,0
IFPRI 2010/2030 IFPRI 2030/2050 FAO AT 2050 2006/2030 FAO AT 2050 2030/2050
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
W ld D l i Hi h i W ld D l i Hi h i W ld D l i Hi h iWorld Developing High-income World Developing High-income World Developing High-income
Wheat Rice Maize
Source: IFPRI’s IPRs, Alexandratos and Bruinsma (2012) and own calculations
Note: Slight differences in regional aggregations between IFPRI and FAO projections. Maize yield projections equivalent to coarse grain definition in GTAP.
Agricultural Model Intercomparison and Improvement Project—AgMIP
• Wide range of model results
– Crop and economic models
• Confusing policy advice
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AgMIP and global economic models
• 6 General equilibrium
– AIM (NIES, Japan), ENVISAGE (FAO, Italy), EPPA (MIT, USA), FARM (USDA, USA), GTEM (ABARES, Australia), MAGNET (LEI/Wageningen, Netherlands),
• 4 Partial equilibrium
– GCAM (PNNL, USA), GLOBIOM (IIASA, Austria),GCAM (PNNL, USA), GLOBIOM (IIASA, Austria), IMPACT (IFPRI), MAgPIE (PIK, Germany)
Scenario design
• Harmonization of key exogenous drivers
– Population and GDP (SSP2)
– Exogenous yield growth (IFPRI)
• 3 Optics
– Socio-economic (SSP2 vs. SSP3)
– Climate change (2 crop models x 2 climate models)
– Bio-energy
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Still large differences in long-term price projections, though sharp narrowing after comparison exercise
1,3
1,4
2030 orig.* 2050 orig.*
0,9
1,0
1,1
1,2
Pri
ce in
dex
(2
00
5**
= 1
)
0,8
AIM ENVISAGE EPPA FARM GTEM MAGNET GCAM GLOBIOM IMPACT MAgPIE* original: relative to model-standard numéraire; rebased: relative to the price index for global GDP** trended 2005, i.e. hypothetical in the absence of short-term shocks
Source: von Lampe et al (2014).
2.0
2.5
0 (2
005=
1)
2.0
2.5
Variation of world prices across commodities in 2050
0.5
1.0
1.5
Pri
ce in
dex
in 2
05
0.5
1.0
1.5
AGR WHT RIC CGR CR5
Note: All agriculture (AGR), wheat (WHT), rice (RIC), coarse grains (CGR), index for wheat, rice, coarse grains, oil seeds and sugar (CR5).
Source: AgMIP global economic runs, February 2013 and own calculations.
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Cereal production—all above AT 2050 scenario
3.000
3.500
4.000
ton
s
MAGNET
IMPACT
1.000
1.500
2.000
2.500
Ce
real
pro
du
ctio
n, m
illio
n m
etr
ic t
AT 2050
500
1961 1971 1981 1991 2001 2011 2021 2031 2041
Source: 1961/2005 FAOSTAT (accessed 20-Feb-2014) and model simulations for 2005/2050.
Cropland projections vary significantly across models
1.800
1.900
2.000MAGNET
AIM
ENVISAGEMAgPIE
GCAM
1.200
1.300
1.400
1.500
1.600
1.700
Cro
pla
nd
, mill
ion
he
ctar
e
GCAMGLOBIOMIMPACTEPPA
GTEM
FARM
1.000
1.100
1961 1971 1981 1991 2001 2011 2021 2031 2041
Source: 1961/2005 FAOSTAT (accessed 20-Feb-2014) and model simulations for 2005/2050.
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The climate modeling chain: from biophysical to socioeconomic
Climate Biophysical Economic
General circulation
models (GCMS)
General circulation
models (GCMS)
Global gridded crop
models (GGCMs)
Global gridded crop
models (GGCMs)
Global economic
models
Global economic
models
TempPrecTempPrec
Yield(Biophysical)
Yield(Biophysical)
AreaYieldConsTrade
AreaYieldConsTrade
Farm Farm PP
RCP’sRCP’s practicesCO2
practicesCO2
Pop.GDPPop.GDP
Source: Nelson et al., PNAS (2013).
Four potential yield outcomes for maize in 2045 under RCP 8.5†
Source: Müller and Robertson (2014).† Excludes CO2 effects.
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Simulated impacts for the four climate scenarios: global average for major crops in 2050 wrt reference
0
5
Wheat Rice Coarse grains Oil seeds Sugar CR5
-20
-15
-10
-5
-25
IPSL/LPJ HADGEM2/LPJ IPSL/DSSAT HADGEM2/DSSAT
Source: Shocks from IFPRI as interpreted for use in the ENVISAGE model, Nelson, van der Mensbrugghe et al. (2014).
Climate induced changes in world average producer prices for five main crops (CR5) relative to reference in 2050
60%
70%
80%
enar
io, 2
05
0
IPSL & LPJ HadGEM & LPJ IPSL & DSSAT HadGEM & DSSAT
10%
20%
30%
40%
50%
Pri
ce c
han
ge r
elat
ive
to r
efer
ence
sce
0%
AIM ENVISAGE EPPA FARM GTEM MAGNET GCAM GLOBIOM IMPACT MAgPIE
Source: von Lampe et al. (2014), based on model results as of February 15, 2013.Note: All changes relative to the reference scenario for the same year.
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Take away messages
• Fifty years of substantial progress, but– Significant pockets of poverty and under-
nourishment
– Areas of unsustainable farm practices
• In many aspects, next 50 years appear less daunting– Declining population growth and reaching food saturation thresholds,
– Albeit with continued significant pockets of poverty (SSA and South Asia) and concerns with sustainability—soils, water, etc.
• However, new issues emerge:– Climate change
– Bio-energy
• Quantitative analysis in the future will require more cooperation– Model comparison and validation
– Model integration (climate, crop and economic)
Further reading
• von Lampe, Willenbockel et al., “Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison”
• Robinson, van Meijl, Willenbockel et al., “Comparing supply-side specifications in
Special issue of Agricultural Economics (2014):http://onlinelibrary.wiley.com/doi/10.1111/agec.2014.45.issue-1/issuetoc
Alexandratos, N. & J. Bruinsma (2012), “World Agriculture Towards 2030/2050: The 2012 Revision,”, FAO, Rome. http://www.fao.org/docrep/016/ap106e/ap106e.pdf
models of global agriculture and the food system”
• Valin, Sands, van der Mensbrugghe et al., “The future of food demand: understanding differences in global economic models”
• Schmitz, van Meijl et al., “Land-use change trajectories up to 2050: insights from a global agro-economic model comparison”
• Müller and Robertson, “Projecting future crop productivity for global economic modeling”
• Nelson, van der Mensbrugghe et al., “Agriculture and climate change in global scenarios: why don’t the models agree”
• Lotze-Campen, von Lampe, Kyle et al., “Impacts of increased bioenergy demand on
Special issue
Lotze Campen, von Lampe, Kyle et al., Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison”
Proceedings of the National Academy of Sciences (PNAS) (2013):http://www.pnas.org/content/early/2013/12/12/1222465110.full.pdf+html• Nelson et al., “Climate change effects on agriculture: Economic responses to
biophysical shocks”