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Hunger and Food Security
Major challenges we are facing today
Maximo Torero
Monday 14th March, 12:30 – 14:00
Lunchtime Conference External Cooperation Infopoint
Rue de la Loi 43, Ground floor
Real Price Evolution in US$ 2015
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14
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01
20
15
USD
pe
r M
etr
ic T
on
s
Soybeans (US$/mt)
Maize (US$/mt)
Periods of Excessive Volatility
Note: This figure shows the results of a model of the dynamic evolution of daily returns based on historical data going back to 1954 (known as the Nonparametric Extreme Quantile (NEXQ) Model). This model is then combined with extreme value theory to estimate higher-order quantiles of the return series, allowing for classification of any particular realized return (that is, effective return in the futures market) as extremely high or not. A period of time characterized by extreme price variation (volatility) is a period of time in which we observe a large number of extreme positive returns. An extreme positive return is defined to be a return that exceeds a certain pre-established threshold. This threshold is taken to be a high order (95%) conditional quantile, (i.e. a value of return that is exceeded with low probability: 5 %). One or two such returns do not necessarily indicate a period of excessive volatility. Periods of excessive volatility are identified based a statistical test applied to the number of times the extreme value occurs in a window of consecutive 60 days.
Source: Martins-Filho, Torero, and Yao 2010. See details at http://www.foodsecurityportal.org/soft-wheat-price-volatility-alert-mechanism.
2014
Please note Days of Excessive volatility for 2014 are through March 2014
2015
Different problems but same policies
GLOBAL CHALLENGE
Source: Johan Rockstrom: Let the environment guide our development
Growing
Human
Pressure
Climate change
Ecosystem
decline
Surprise
6
Bigger population in urban areas will demand
more and better food
36%
POPULATION GROWTH
Change in population by
region 2010-2100
(millions)
182 millions
97 millions
-63 millions
2,552 millions
432 millions
29 millions
Africa: Younger
Asia and Europe: Older
Source:UN 2011
Calorie consumption vs total Cereal
Equivalent Consumption
0.5
11
.52
(to
ns/
cap
ita/y
ea
r)
0
50
00
10
00
01
50
00
(kca
l/cap
ita/d
ay)
0 10000 20000 30000 40000 50000Real GDP(PPP) per capita in 2005 int. $ 1980-2009
China Calorie Consumption Fitted Calorie Consumption
China CE Consumption Fitted CE Consumption
Source: Fukase, E. and Martin, W. (2015)
Different types of childhood malnutrition (abstract)
-
200
400
600
800
1,000
1,200
Africa south of the Sahara
South Asia
Developing Countries
Slow decline in malnourishment.
Alarming increase in obesity.
Stunted children (millions)
0
10
20
30
40
50
60
1990 1995 2000 2005 2010 2015 2020
Overweight & obese children (millions)
Source: FAOSTAT3 (http://faostat3.fao.org/download/D/FS/E).
Source: UN in de Onis, M, M. Blössner and E. Borghi. 2010. Global prevalence and
trends of overweight and obesity among preschool children. American Journal of
Clinical Nutrition 92:1257–64.
(http://www.who.int/nutgrowthdb/publications/overweight_obesity/en/).
Undernourished
people (millions)
0
50
100
150
200
250
300
1990 1995 2000 2005 2010 2015 2020
Source: de Onis, M, M. Blössner and E. Borghi. 2011
http://www.who.int/nutgrowthdb/publications/Stunting1990_2011.pdf.
Africa
Asia
Developing Countries
Africa
Asia
Developing Countries
WATER STRESS RISK
2.5
US$9.4 TRILLION
Source: Veolia Water & IFPRI 2011.
BILLION PEOPLE
TODAY Total population living in water scarce areas
Global GDP generated in water scarce regions
US$63 TRILLION
Total population living in water scarce areas
4.7 BILLION PEOPLE
90%
570%
By 2050
Global GDP generated in water scarce regions
52% 49% 45%
36% 39% 22%
population grain production
global GDP
HEAVY TOLL ON RAINFED MAIZE WITH
CLIMATE CHANGE
Global yields projected 30% lower in 2050 compared to no climate change
Source: IFPRI IMPACT simulations. (HadGEM2, RCP 8.5)
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
2010 2015 2020 2025 2030 2035 2040 2045 2050Source: IFPRI IMPACT 3.2 Projections.
FOOD PRICES INCREASE WITHOUT CLIMATE
CHANGE; EVEN HIGHER WITH CLIMATE
CHANGE
No climate change
Average with climate change
With climate change - range across models
(Indexed to 1 in 2010)
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
2010 2015 2020 2025 2030 2035 2040 2045 2050
Cereals Roots/tubers
2010 = 1 2010 = 1
Sources: 1969-71 to 1999-2001 from Alexandratos 2006; 2010-2050 from IFPRI's IMPACT 3.2 Projections.
Per capita food consumption grows.
Africa and South Asia catching up.
0
500
1000
1500
2000
2500
3000
3500
4000
World Industrial countries Developing countries South Asia Africa south of the Sahara
Per capita food consumption (kcal/person/day) 1979/1981 2010 2050
0
100
200
300
400
500
600
700
800
900
2010
2050, No Climate Change
2050, With Climate Change
Source: IFPRI IMPACT 3.2 Projections.
Improved progress on hunger, but too slow.
Climate change increases hunger.
Undernourished people (millions)
Developing countries South Asia Africa south of the Sahara
A continuous trend towards
internationalization of food markets
1975 1985 1995 2005 2015
18.2%
13.9% 12.3%
19.1%
16.1%
Share of produced calories crossing an international border
Globalization and/or Regionalization
-
2,000
4,000
6,000
8,000
10,000
12,000
Average distance (km) travelled by imported calories
1995 2000 2005 2010
Evolution by region of the price support
through border measure
-60.0%
-50.0%
-40.0%
-30.0%
-20.0%
-10.0%
0.0%
10.0%
20.0%
Africa Asia Eastern Europe LAC HIC World
Average Nominal Rates of Assistance (NRA) through Border Measure
1975 1985 1995 2005
Cumulative number of preferential trade
agreements (PTAs) in force
Note: it includes notified and non-notified PTAs by country group
But mega trade deals are becoming strategic
TPP
USA
TTIP
TISA
Vietnam Brunei Singapore Malaysia
Australia Canada Taiwan Japan Chile Mexico Peru South Korea New Zealand
Norway Switzerland Iceland Israel Uruguay Hong Kong Costa Rica Colombia Panama Paraguay Turkey
Austria Bulgaria Belgium France Czech Republic Ireland Denmark
Germany Estonia Portugal Romania Poland Netherlands Lithuania UK
Sweden Luxembourg Slovenia Hungary Slovenia Italy Spain
Greece Finland Malta
Croatia Lativia Cyprus
Economic Slowdown
Comparison of 2012 and 2015 GDP growth
projections for 2017 (selection of countries)
Source: World Economic Outlook (2015 and 2012) - IMF
Economic Slowdown
World Commodity Price Projections (2015)
Source: World Economic Outlook (2015 and 2012) - IMF
40
60
80
100
120
140
2013 2014 2015 2016 2017
Pri
ce In
dex
10
0 =
20
11
Year Crude Oil (petroleum), simple average of three spot prices; Dated Brent, West Texas Intermediate, and the Dubai Fateh, US$ per barrelCommodity Natural Gas Price Index includes European, Japanese, and American Natural Gas Price IndicesCommodity Coal Price Index includes Australian and South African CoalWheat, No.1 Hard Red Winter, ordinary protein, FOB Gulf of Mexico, US$ per metric tonneMaize (corn), U.S. No.2 Yellow, FOB Gulf of Mexico, U.S. price, US$ per metric tonneRice, 5 percent broken milled white rice, Thailand nominal price quote, US$ per metric tonneSoybeans, U.S. soybeans, Chicago Soybean futures contract (first contract forward) No. 2 yellow and par, US$ per metric tonnePalm oil, Malaysia Palm Oil Futures (first contract forward) 4-5 percent FFA, US$ per metric tonneBeef, Australian and New Zealand 85% lean fores, FOB U.S. import price, US cents per poundPoultry (chicken), Whole bird spot price, Georgia docks, US cents per pound
Economic Slowdown
Projections of Effects: Global Poverty
Source: Laborde and Martin (2016)
Economic Slowdown Projections of Effects: Net and gross movements into and out of
poverty, Scenario 1, Percentage points, Total Population.
Source: Laborde and Martin (2016) Note: Poverty is defined by the $1.90 PPP 2011 threshold.
Economic Slowdown Projections of Effects: Net and gross movements into and out of
poverty, Scenario 2, Percentage points, Total Population.
Source: Laborde and Martin (2016) Note: Poverty is defined by the $1.90 PPP 2011 threshold.
Economic Slowdown Projections of Effects: Net and gross movements into and out of
poverty, Scenario 2, Percentage points, Farmer Population.
Source: Laborde and Martin (2016) Note: Poverty is defined by the $1.90 PPP 2011 threshold.
Regional Challenges: Africa South of the
Sahara
Africa in Global Trade After the long decline of the ‘70s-’90s, a reversed trend:
0
100
200
300
400
500
600
700
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Bn
s U
SD
SSA TOTAL TRADE
Agriculture All goods
In 15 years, total trade for SSA has been multiplied by 6, agricultural trade by 4.6. In comparison, global trade multiplied by 3.4 and agricultural trade by 2.9.
0.0%
1.0%
2.0%
3.0%
4.0%1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
SSA SHARE IN GLOBAL TRADE Agriculture All goods
Heterogeneous Performance on Global
Agricultural Markets
-150%
-100%
-50%
0%
50%
100%
150%
200%
250%
% IN
CR
EASE
IN G
LOB
AL
MA
RK
ET S
HA
RE
Decomposition of export performance (selected countries) between 1995 and 2007
Domestic Performance (competitivness) Geographical Specialization Sectoral Specialization
Source: Bouet, Deason and Laborde (2014)
Explaining a country’s performance and defining the right benchmark: • Being specialized in the right
products? • Being specialized in the booming
markets? • Improving its own
competitiveness?
During this period, exports have: • decreased by 20 M USD for C.A.R
(bad performance in absolute and relative terms).
• increased by 150 M USD for Uganda (bad performance in relative terms).
• increased by 88 M USD for Rwanda (good performance in absolute and relative terms).
• Need to differentiate short term variation and medium/long term modification of the trend.
• Different policy responses on both energy and agricultural, and macroeconomic policies.
• In SSA, weak institutions, capital, financial and insurance markets: incremental costs of volatility.
• Energy and food prices: high level of distortions, and huge heterogeneity of policies within the continent.
• From energy to food prices: many links (inputs, fertilizers, transports, biofuels).
Implications of Changing Prices and
Demand for Energy and Food
-5.00
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00Aggregated welfare impact of a world price
shock
AGRI -15% Extraction -15% ExtractionAgri -15%
Looking at the Past
• Increased regional integration, especially when looking at the nutritional contents of trade flows.
African Imports Africa Asia Europe LAC NorthAmerica Oceania
Dollars (value)
1990-1995 6.77% 17.26% 37.90% 9.96% 24.79% 3.31%
2002-2007 12.39% 19.81% 35.23% 15.97% 13.68% 2.93%
kCal
1990-1995 3.09% 14.23% 23.81% 10.44% 44.81% 3.62%
2002-2007 7.05% 20.38% 27.06% 19.45% 21.63% 4.43%
African Exports Africa Asia Europe LAC NorthAmerica Oceania
Dollars (value)
1990-1995 7.99% 16.79% 67.32% 0.61% 6.95% 0.34%
2002-2007 15.15% 14.86% 62.51% 0.53% 6.10% 0.84%
kCal
1990-1995 13.80% 26.20% 49.96% 2.99% 6.59% 0.46%
2002-2007 31.41% 29.21% 34.03% 0.92% 4.19% 0.23%
1/3 of the calories exported by Africa, go to Africa
Role of African intra-trade over the previous decade has more than doubled.
Shift in external suppliers among Americas.
Source: Bouet, Deason and Laborde (2014)
Outlook Modeling and Analysis
Important changes within SSA:
• Potential evolution in agri-food system value-added in Africa: potential increase by about USD 300 million (constant 2007 USD) between 2013 and 2030 (or 85%) in the business as usual scenario.
And beyond:
• SSA share in global food trade will reach 4.3% by 2030 (compared to 3% today, and 2.2% in 2000).
0
10
20
30
40
50
60
70
80
90
20
13
20
14
20
15
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
Bn
s U
SD, c
on
stan
t
SSA Agri-food exports
ECOWAS CEMAC COMESA SACU
0
10
20
30
40
50
60
70
80
90
20
13
20
14
20
15
20
16
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25
20
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20
27
20
28
20
29
20
30
Bn
s U
SD, c
on
stan
t
SSA Agri-food imports
ECOWAS CEMAC COMESA SACU
Source: MIRAGRODEP model simulations, Bouet, Deason and Laborde (2014)
Per Capita Net Agricultural Trade Flows by Region
-150.00
-100.00
-50.00
0.00
50.00
100.00
150.00
2013 2030 2013 2030 2013 2030 2013 2030 2013 2030 2013 2030
AFRICA CEMAC COMESA ECOWAS SACU UMA
USD
pe
r C
apit
a, N
et
trad
e f
low
s
Vegetable Oil Vegetables & FruitsSugar FibersOilseeds Processed FoodCash Crops Meat, whiteMeat, red Fish ProductsDairy Products Cereals
Source: MIRAGRODEP model simulations, Bouet, Deason and Laborde (2014)
• Complementarity in terms of potential and needs at the continental level shows large potential for intra-trade growth; some targeted initiatives may be needed (vegetable oils, food processing).
• The continental agri-business net trade deficit will increase from six dollars per capita to 12 dollars per capita.
How Will Intra-African Trade Perform?
• Under a business as usual scenario? +122% in average
• Which levers could we use to reach the CAADP target (+200% from 2014 to 2025, Malabo Declaration)?
– Addressing trade policy barriers
– Improving infrastructure
Source: MIRAGRODEP model simulations, Bouet, Deason and Laborde (2014)
CEMAC
COMESA
ECOWAS
SACU
0%
50%
100%
150%
200%
SACU ECOWAS COMESA CEMAC
% increase in intra-SSA trade between 2013 and 2030 CEMAC COMESA ECOWAS SACU
CEMAC 67% 148% 80% 88%
COMESA 148% 146% 179% 116%
ECOWAS 80% 179% 136% 137%
SACU 88% 116% 137% 111%
Trade Policy Barriers for Expanding Trade in
Africa
Huge potential for an ambitious trade facilitation agenda:
• Free circulation of goods still not achieved within custom unions (intra-trade still affected by MFN tariffs, double taxation, etc.)
• Numerous fees and bribes
• Administrative burden
• Inefficiency of checkpoints (delays)
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
ECOWAS CEMAC COMESA SACU
Average import tariffs on agri-food imports
Applied to non SSA countries Applied to SSA countries
Despite regional integration, intra-African trade still affected by:
• significant tariffs;
• the need to address between trade barriers between blocs;
• external pressure to liberalize markets with third countries (EPA with the EU: SADC and ECOWAS should sign this year);
• instability/uncertainty regarding some trade policies
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Rice Wheat Yams Beef(carcass)
Chicken(cuts)
Milk Powder
Tariffs on selected products
CEMAC ECOWAS COMESA SACU
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Pow
er
Inte
rnati
onal call
Wate
r
Road f
reig
ht
Inte
rnet
dia
l-up
Mobile t
ele
phone
Rat
io o
f p
rice
s Infrastructure Barriers: Several Times More
Expensive than Elsewhere
Source: AICD – African Infrastructure Country Diagnostic
Challenge 1: Improve
efficiency or shift of
potential frontier
Yields are vey low
Spatial Patterns (annual avg. 2005-07)
Labor Land
Source: Benin, et.al (2011). Trends and Spatial Patterns in Agricultural Productivity in Africa 1961-2010, ReSAKSS.
Intensity of agricultural research spending and capacity, 1981–2008 (E.g. Zambia)
STOCHASTIC PROFIT FRONTIER
C
Production of maize
Production of wheat
Frontier of possibilities of production
Frontier of possibilities of production increases
Challenge 2: We need to
value externalities positive
or negative
Pricing water
A CONTINUOUS TREND TOWARDS INTERNATIONALIZATION OF FOOD MARKETS
1975 1985 1995 2005 2015
18.2%
13.9% 12.3%
19.1%
16.1%
Share of produced calories crossing an international border
Are we pricing the water?
We need to recognize carbon as a global externality and value carbon through carbon trade
Challenge 3: We need to
be resilient to climate
change and weather
shocks
https://www.climate.gov/news-features/blogs/enso/november-el-ni%C3%B1o-update-it%E2%80%99s-small-world
Ranking of August-October El Niño episodes (ONI) since 1950
El Niño Risks
El Niño Risks: January to March 2015
El Niño Risks: October – December 2015
Cereal Production in selected regions (million tons)
2012/13 2013/14 2014/15 2015/16*
2015 / Average 2012-2014 (% change)
World 2,267.0 2,474.9 2,501.1 2,467.5 2.2 SSA 121.4 123.1 124.9 117.2 -4.8 Central Africa 7.5 6.7 6.7 6.9 -1.4 East Africa 38.1 38.9 42.1 40.0 0.8 Southern Africa 28.5 31.1 29.5 23.7 -20.2 West Africa 47.3 46.4 46.5 46.6 -0.4 North Africa 32.2 36.2 32.6 36.5 8.6 East Asia 495.0 508.9 512.3 526.2 4.1 South Asia 324.7 332.4 333.4 318.8 -3.4 Southeast Asia 144.8 148.0 146.5 145.2 -0.8 Europe 292.0 318.3 343.6 323.2 1.7 Central America & Caribbean 6.5 6.8 6.3 6.5 -0.7 Middle East 57.9 65.9 55.5 66.0 10.5 North America 436.9 533.1 527.2 517.3 3.7 South America 169.9 168.0 173.9 167.5 -1.8 Others 185.8 234.2 244.9 242.9 9.6
Source: USDA, *= forecasted estimates
Maize and wheat price data in selected markets
Region Market Current Price ($/KG)
Current price compared to 2012-14 average (% change)
East Africa
Ethiopia, Addis Ababa, Wheat 0.465 15.3%
Ethiopia, Addis Ababa 0.217 -25.6%
Uganda, Kampala 0.240 -4.4%
LAC
El Salvador, San Salvador 0.413 22.8%
Guatemala, Guatemala City 0.350 4.3%
Honduras, National Average 0.430 38.2%
Nicaragua, National Average 0.400 29.5%
Southern Africa
Malawi, National Average 0.253 6.5%
Mozambique, Maputo 0.300 -30.1%
South Africa, Randfontein 0.223 -4.7%
Zimbabwe, Harare 0.565 -32.6% Source: Authors’ calculation based on FAO GIEWS data Notes: All prices for maize unless otherwise indicated. Real prices using IMF CPI deflator, prices are averages for the period October to December for all years presented.
Challenge 4: Is not only
supply!
ADDITIONAL DEMAND FOR BIOMASS
Growing population
Growing income
Need for alternative to fossil carbon chains
Increased production
Reduced supply for final consumers
Reduced supply for
intermediate consumers
New Demand for crops
Increase in yield and
area, extension of
cropland, and reduction
of other crops
GROWING DEMAND
Additional food demand
Additional Bioenergy demand
Additional industrial
Hunger?
Substitution effects
Feed
Other sectors (agrifood,
cosmetics)
Substitution effects Biomass demand
OVERALL IMPACT
By 2020: illustration with biofuels 1st generation
23.2%
22.1%
2.7%
10.0%
43.3%
15.7%
15.0%
10.1%
2.0%
13.9%
1.4%
2.4%
7.7%
1.7%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0%
MAIZE
SUGAR CROPS
WHEAT
PALM OIL
RAPESEED OIL
SOYBEAN OIL
SUNFLOWER OIL
Share of the crop (all use) in totalHARVESTED cropland
Production devoted to biofuels
Source: Laborde, 2011 But only 16% of world area devoted to biofuels
SUPPLY AND DEMAN
SUPPLY AND DEMAND
• Huge opportunity for smallholders
• Huge potential for contract farming
• But we need an appropriate regulation framework
Challenge 5: Economic
Growth is not enough
Prevalence of Undernourishment
Economic Growth is not enough
A 10% increase in GDP/PC
leads to a 6% reduction in
stunting
Source: Ruel and Alderman, 2013
Income Growth Can Have Unintended
Consequences of Increasing Risks of Overweight
and Obesity
A 10% increase in GDP/PC
leads to a 7% increase in
overweight and obesity in women
Source: Ruel and Alderman, 2013
Final Remarks
Agriculture is critical for
Employment
Economic development
Food Security
Important changes in key drivers
Demand drivers changing rapidly
Land constraints
Water constrains
Climate change
Huge opportunity
But we need proper regulatory
environment
Gains in efficiency and potential
Increase value added
SAI
Needs to be inclusive
63
Features
SSA.foodsecurityportal.org
Thanks!