SlideShare a Scribd company logo
1 of 43
Jim Hansen, Syd Cochrane, Getachew Nigatu
Agricultural Economist
USDA, Economic Research Service
June 27, 28, 29 2016
Long-term Projections
of International Agricultural Trade,
ECOWAS Agriculture to 2025 and Model
Presentation Outline
• Description of USDA 10 Year Commodity Projections
• Macroeconomics, population, and energy
• ECOWAS Model
• US commodities and International trade
• ECOWAS agricultural projections
• Conclusion
USDA’s Agricultural Projections
• 10-year projection of major commodities
- Supply, demand, trade, and prices.
- Based on November 2015 market conditions. Released Feb 2016
• Assumptions:
- Continuation of current U.S. law
- Continuation of existing international trade agreements
- Population growth slows, strongest in developing countries
- Macroeconomic growth – strongest in emerging markets
• Composite of Model Results and Analysts Judgment
- Modeling system: dynamic partial equilibrium trade
- 40 countries/regions,
- 24 commodity markets
• Equilibrates: (Supply = Demand) & (Imports = Exports)
Solves for prices and trade, clear world and country markets
Demand Structure:
•Per Capita GDP growth
- Population growth
- GDP growth
•Own and Substitute Prices
•Rural and Urban for some countries
•Diet Diversification in developing countries
 GDP/Capita Growth
 Urbanization
 Income distribution equality
 Food away from home
Changes in Food Consumption:
• Greater consumption of:
- Fruits & Vegetables
- Vegetable Oils
- Processed Cereal Products
- Meats & Dairy Products
Feed Demand Increases
 Import demand for Feed grains
• Less consumption of:
- Staple grains - rice in Asia, corn in Indonesia and Mexico
- Low-quality grain varieties and switching to high-quality
(high-quality varieties may lower yields)
- Roots & tubers
ERS ECOWAS Model
Commodities in ERS ECOWAS Model
• Livestock: (3 sectors)
– Beef, Pork, and Poultry
• Crops: (9 sectors)
– Wheat, Rice
– Corn, Sorghum, Other-Coarse-Gr (mostly millet)
– Other seeds (mostly peanuts), meal and oil
– Cotton, sugar, cocoa
– Blank sections no data – barley, soybeans meal oil,
• Elasticity Partial Equilibrium model
• Model in Excel Spread sheet - 3 main sheets
Commodity models (Forecast)
Parameters,
Base-Scenario (table)
• Data Requirement for Model
– Macroeconomic variables
– Agriculture data (aggregate) –
• USDA Production, supply and Disappearance and FAO
– Prices and Policies
Modeling the Agriculture Economy:
• Production & consumption
– Crops: area, yield, consumption, stocks and trade
– Livestock: animals inventory, production, consumption,
trade, stocks
• Model as a System
– Accounting (0 = PROD+BSTK+IM-TCON-EX-ESTK)
– Number of different identities must hold
– Stock issue, government, farm household
Modeling Production:
• Production
Gross return = lagged prices x expected yield
Yield = f(gross return, technology time trend)
Area = f(gross return, alternative crops GR, tech)
Production = Yield x Area
Total Supply = Production + Imports + Beg Stocks
Modeling Consumption:
• Consumption
Per capita cons = f(own price, sub prices, income)
Food cons = per capita cons x population
Total cons = food cons + feed cons + waste + industry use
Total Disappearance = Total cons + exports + end stocks
Modeling Stocks & Trade:
• Ending and beginning stocks
Beginning stocks = lagged(Ending stocks)
Ending stocks = f(production or consumption, trend)
Exports = f(consumer price, export price, trend)
Imports = f(producer price, export price, trend)
Imports and exports are also identities for some commodities
Imports = Cons + endstocks – production – exports-begstocks
Closing the Model:
• Domestic prices solved in the model for some
commodities
Total Disappearance = Total cons + exports + end stocks
Total Supply = Production + Imports + Beg Stocks
Prices solved in the model until supply = demand
0 = Total Supply - Total Disappearance
ECOWAS Commodity Projections
0
2
4
6
8
10
12
14
16
18
77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Oth-CoarseGrn Sorghum Corn Oth-Oilseed Rice
ECOWAS Area Harvested (million ha)
Million hectares
Corn
Oth-oil
seed
Rice
Sorghum
Other coarse grain
0
10
20
30
40
50
60
77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Oth-CoarseGrn Sorghum Corn Oth-Oilseed Rice
ECOWAS Area Harvested (million ha)
Million hectares
Corn
Oth-oil seed
Rice
Sorghum
Other coarse grain
(Millet)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
2.00
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Corn Rice
ECOWAS Yields: (mt/ha)
Metric tons per hectares
Corn
Rice
Are the recent yield data correct?
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Sorghum Other Coarse Grain Oth-Oilseed
ECOWAS Yields: (mt/ha)
Metric tons per hectares
Other oil seed
Sorghum
Other coarse grain
0
2
4
6
8
10
12
14
16
18
20
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Consumption Feed Food seed waste
ECOWAS Corn Production,
and Consumption (million mt)
Million metric tons
Feed
Food
Total Consumption
Production
0
100
200
300
400
500
600
700
800
900
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Imports Exports
ECOWAS Corn
Imports and Exports (1,000 mt)
Thousand metric tons
Exports
Imports
0
2
4
6
8
10
12
14
16
18
83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Feed Food seed waste
ECOWAS Sorghum Production,
Food, and Feed Consumption (million mt)
Million metric tons
Feed
Food
Production
0
50
100
150
200
250
300
83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Imports Exports
ECOWAS Sorghum
Imports and Exports (1,000 mt)
Thousand metric tons
Imports
Exports
0
2
4
6
8
10
12
14
16
71 74 77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
P ro ductio n C o nsumptio n
ECOWAS Other Coarse Grain (Millet)
Production and Consumption (million mt)
Million metric tons
0
2
4
6
8
10
12
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Imports Exports Consumption
ECOWAS Wheat Imports, Consumption,
Exports and Production (million mt)
Million metric tons
Exports
Consumption
Imports
0
5
10
15
20
25
83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Imports Consumption
ECOWAS Rice Total Consumption,
Production and Imports (million mt)
Million metric tons
Production
Total
Consumption
Imports
0
2
4
6
8
10
12
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production T otal Consumption Feed seed waste Food Crush
ECOWAS Other Oilseeds (Peanuts)
Production, Exports, and Consumption (million mt)
Million metric tons
Crush
Total Consumption
Production
Food
Feed, seed & waste
0
2
4
6
8
10
12
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Feed seed waste Food Crush
ECOWAS Other Oilseeds (Peanuts) : Crush, Food,
and Feed, seed & waste (million mt)
Million metric tons
Crush
Total Consumption
Food
Feed, seed & waste
Consumption
0
5
10
15
20
25
30
35
40
45
50
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Corn W heat Rice
ECOWAS Food
Per Capita Consumption (kg/capita)
Kilograms/person per year
Corn
Rice
Wheat
0
10
20
30
40
50
60
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Sorghum Other Coarse Grain
ECOWAS Food
Per Capita Consumption (kg/capita)
Kilograms/person per year
Sorghum
Other Coarse Grain
Millet
0
2
4
6
8
10
12
14
16
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Seeds Other-Oilseed Peanuts Oil - Other Oil Peanuts
ECOWAS Food
Per Capita Consumption (kg/capita)
Kilograms/person per year
Peanuts
Other Oilseeds
Peanut Oil
Pork, Poultry, and Beef Production
and Feed Demand
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
89 92 95 98 01 04 07 10 13 16 19 22 25
Production Imports T otal Consumption
ECOWAS Beef
Production, Consumption and Imports (million mt)
Million metric tons
Consumption
Production
Imports
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Imports T otal Consumption
ECOWAS Pork
Production, Consumption and Imports (million mt)
Million metric tons
Consumption
Production
Imports
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
86 89 92 95 98 01 04 07 10 13 16 19 22 25
Production Imports T otal Consumption
ECOWAS Poultry
Production, Consumption and Imports (million mt)
Million metric tons
Consumption
Production
Imports
0.0
0.5
1.0
1.5
2.0
2.5
3.0
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Pork Poultry Beef
ECOWAS Meat Production:
Beef, Poultry and Pork (million mt)
Million metric tons
Beef
Pork
Poultry
Feed Demand
0
1
2
3
4
5
6
7
8
80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25
Sorghum Other-Oilseed-Peanuts Other-Meal-Peanuts Corn
ECOWAS Feed Demand:
Corn, Peanut-Meal, Peanuts, and Sorghum (million mt)
Million metric tons
Corn
Other-Oilseeds Peanut
Other-Meal
Peanut
Sorghum
Corn Increase
1980-2003 flat
2003-2016 + 2.4 mmt, Projection little growth
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
70 73 76 79 82 85 88 91 94 97 00 03 06 09 12 15 18 21 24
Production Exports Consumption
ECOWAS Cotton
Production, Exports, and Consumption (million mt)
Million metric tons
Exports
Total Consumption
Production
80
100
120
140
160
180
200
220
240
260
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
80
100
120
140
160
180
200
220
240
260
Total world grain & oilseeds1
Production, yield, area harvested, population & per cap production
Index: 1970 = 100
1/Oilseeds = soybeans + rapeseed + sunflowers.
Source: Compiled from USDA’s PS&D Database & Baseline Projections
Growth rates: Exponential Trend (%/year)
1970-1990 1990- 2009 2010- 2019
Production 2.4 % 1.54 1.27
Yields 1.9 1.21 0.70
Area 0.50 0.33 0.57
80
100
120
140
160
180
200
220
240
260
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
80
100
120
140
160
180
200
220
240
260
Total world grain & oilseeds1
Production, yield, area harvested, population & per cap production
Index: 1970 = 100
1/Oilseeds = soybeans + rapeseed + sunflowers.
Source: Compiled from USDA’s PS&D Database & Baseline Projections
Per Capita/Production
Growth rates: Exponential Trend
1970 - 90 1990 - 09 2010 - 19
Production 2.4 1.54 1.27
Yields 1.9 1.21 0.70
Population 1.7 1.30 1.06
Area 0.50 0.33 0.57
Capita/Pro 0.61 0.28 0.20
Conclusions and Summary:
• Strong global trade growth in most agriculture commodities,
without significant increases in real world commodity prices.
• Strong income growth in developing countries and urbanization
lead to increased import demand for grains, High Value Products
• Trade to remain very competitive
Expanding production potential in Brazil & Argentina, FSU, EU
Indonesia expands palm oil production.
• Uncertainties, Ethanol and trade, Bio-energy policies,
BSE, Avian influenza, food safety, China and Brazil,
natural resource constraints – water, changing demographics and
effect on food demand
Thank you
USDA-ERS Long-Term Projections
briefing room
http://www.ers.usda.gov/briefing/baseline

More Related Content

Similar to ECOWAS-Agriculture-to-2025-and-Model_USDA-Juin-2016.pptx

Implications of Price and Production Shocks on Food Security in Ethiopia: A G...
Implications of Price and Production Shocks on Food Security in Ethiopia: A G...Implications of Price and Production Shocks on Food Security in Ethiopia: A G...
Implications of Price and Production Shocks on Food Security in Ethiopia: A G...essp2
 
The rapid - but from a low base - uptake of agricultural mechanization in Eth...
The rapid - but from a low base - uptake of agricultural mechanization in Eth...The rapid - but from a low base - uptake of agricultural mechanization in Eth...
The rapid - but from a low base - uptake of agricultural mechanization in Eth...essp2
 
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...Brad Jordahl Redlin
 
Agricultue issue Pakistan new
Agricultue issue Pakistan newAgricultue issue Pakistan new
Agricultue issue Pakistan newUltraspectra
 
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sector
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy SectorTransforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sector
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sectoressp2
 
Agree.cluture growth in india 2022-2023pptx
Agree.cluture growth in india 2022-2023pptxAgree.cluture growth in india 2022-2023pptx
Agree.cluture growth in india 2022-2023pptxSourabhKalolikar
 
Why isn´t Colombia the LAC version of Thailand for the cassava crop?
Why isn´t Colombia the LAC version  of Thailand for the cassava crop?Why isn´t Colombia the LAC version  of Thailand for the cassava crop?
Why isn´t Colombia the LAC version of Thailand for the cassava crop?CIAT
 
CIAT cassava program in Asia
CIAT cassava program in AsiaCIAT cassava program in Asia
CIAT cassava program in AsiaJonathan Newby
 
Agricultural index
Agricultural indexAgricultural index
Agricultural indexHiral Anghan
 
How big are post-harvest losses in Ethiopia? The case of teff
How big are post-harvest losses in Ethiopia? The case of teffHow big are post-harvest losses in Ethiopia? The case of teff
How big are post-harvest losses in Ethiopia? The case of teffessp2
 
Food processing, transformation and job creation: The case of ready-to-eat st...
Food processing, transformation and job creation: The case of ready-to-eat st...Food processing, transformation and job creation: The case of ready-to-eat st...
Food processing, transformation and job creation: The case of ready-to-eat st...essp2
 
Transforming Agri-food Systems in Ethiopia: Evidence from the Downstream and...
Transforming Agri-food Systems in Ethiopia:  Evidence from the Downstream and...Transforming Agri-food Systems in Ethiopia:  Evidence from the Downstream and...
Transforming Agri-food Systems in Ethiopia: Evidence from the Downstream and...essp2
 
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURE
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURECHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURE
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTUREAnjum Ali Buttar
 
Research advances of HarvestPlus socioeconomic studies in LAC
Research advances of HarvestPlus socioeconomic studies in LACResearch advances of HarvestPlus socioeconomic studies in LAC
Research advances of HarvestPlus socioeconomic studies in LAC CIAT
 
Ethiopian Common Bean Seed Roadmap_TL III Annual Meet
Ethiopian Common Bean Seed Roadmap_TL III Annual MeetEthiopian Common Bean Seed Roadmap_TL III Annual Meet
Ethiopian Common Bean Seed Roadmap_TL III Annual MeetTropical Legumes III
 

Similar to ECOWAS-Agriculture-to-2025-and-Model_USDA-Juin-2016.pptx (20)

Implications of Price and Production Shocks on Food Security in Ethiopia: A G...
Implications of Price and Production Shocks on Food Security in Ethiopia: A G...Implications of Price and Production Shocks on Food Security in Ethiopia: A G...
Implications of Price and Production Shocks on Food Security in Ethiopia: A G...
 
The rapid - but from a low base - uptake of agricultural mechanization in Eth...
The rapid - but from a low base - uptake of agricultural mechanization in Eth...The rapid - but from a low base - uptake of agricultural mechanization in Eth...
The rapid - but from a low base - uptake of agricultural mechanization in Eth...
 
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...
2018 Farm Bill: Context and Policies. University of Minnesota, Colloquium in ...
 
Agricultue issue Pakistan new
Agricultue issue Pakistan newAgricultue issue Pakistan new
Agricultue issue Pakistan new
 
Seed systems and rice seed capital in Africa
Seed systems and rice seed capital in AfricaSeed systems and rice seed capital in Africa
Seed systems and rice seed capital in Africa
 
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sector
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy SectorTransforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sector
Transforming Agri-food Systems in Ethiopia: Evidence from the Dairy Sector
 
Agree.cluture growth in india 2022-2023pptx
Agree.cluture growth in india 2022-2023pptxAgree.cluture growth in india 2022-2023pptx
Agree.cluture growth in india 2022-2023pptx
 
Why isn´t Colombia the LAC version of Thailand for the cassava crop?
Why isn´t Colombia the LAC version  of Thailand for the cassava crop?Why isn´t Colombia the LAC version  of Thailand for the cassava crop?
Why isn´t Colombia the LAC version of Thailand for the cassava crop?
 
2015 ReSAKSS Conference – Day 1 - Sam Benin
2015 ReSAKSS Conference – Day 1 - Sam Benin2015 ReSAKSS Conference – Day 1 - Sam Benin
2015 ReSAKSS Conference – Day 1 - Sam Benin
 
CIAT cassava program in Asia
CIAT cassava program in AsiaCIAT cassava program in Asia
CIAT cassava program in Asia
 
Lloyd's extreme event scenarios (feb 2015)
Lloyd's extreme event scenarios (feb 2015)Lloyd's extreme event scenarios (feb 2015)
Lloyd's extreme event scenarios (feb 2015)
 
1 Rosegrant- IMPACT Model, Baseline, and Scenarios: New Developments
1 Rosegrant- IMPACT Model, Baseline, and Scenarios: New Developments1 Rosegrant- IMPACT Model, Baseline, and Scenarios: New Developments
1 Rosegrant- IMPACT Model, Baseline, and Scenarios: New Developments
 
Bart Minten Value Chains
Bart Minten Value ChainsBart Minten Value Chains
Bart Minten Value Chains
 
Agricultural index
Agricultural indexAgricultural index
Agricultural index
 
How big are post-harvest losses in Ethiopia? The case of teff
How big are post-harvest losses in Ethiopia? The case of teffHow big are post-harvest losses in Ethiopia? The case of teff
How big are post-harvest losses in Ethiopia? The case of teff
 
Food processing, transformation and job creation: The case of ready-to-eat st...
Food processing, transformation and job creation: The case of ready-to-eat st...Food processing, transformation and job creation: The case of ready-to-eat st...
Food processing, transformation and job creation: The case of ready-to-eat st...
 
Transforming Agri-food Systems in Ethiopia: Evidence from the Downstream and...
Transforming Agri-food Systems in Ethiopia:  Evidence from the Downstream and...Transforming Agri-food Systems in Ethiopia:  Evidence from the Downstream and...
Transforming Agri-food Systems in Ethiopia: Evidence from the Downstream and...
 
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURE
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURECHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURE
CHALLENGES IN PUNJAB AND PAKISTAN AGRICULTURE
 
Research advances of HarvestPlus socioeconomic studies in LAC
Research advances of HarvestPlus socioeconomic studies in LACResearch advances of HarvestPlus socioeconomic studies in LAC
Research advances of HarvestPlus socioeconomic studies in LAC
 
Ethiopian Common Bean Seed Roadmap_TL III Annual Meet
Ethiopian Common Bean Seed Roadmap_TL III Annual MeetEthiopian Common Bean Seed Roadmap_TL III Annual Meet
Ethiopian Common Bean Seed Roadmap_TL III Annual Meet
 

More from constantino34

Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptx
Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptxPresentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptx
Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptxconstantino34
 
Presentation-PROACT_atelier-partage_28-Sept-2016.pptx
Presentation-PROACT_atelier-partage_28-Sept-2016.pptxPresentation-PROACT_atelier-partage_28-Sept-2016.pptx
Presentation-PROACT_atelier-partage_28-Sept-2016.pptxconstantino34
 
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptx
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptxGénéralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptx
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptxconstantino34
 
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptx
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptxAgrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptx
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptxconstantino34
 
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptx
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptxintro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptx
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptxconstantino34
 
melwebinaragrometeorologicalindicators20190529.pptx
melwebinaragrometeorologicalindicators20190529.pptxmelwebinaragrometeorologicalindicators20190529.pptx
melwebinaragrometeorologicalindicators20190529.pptxconstantino34
 
ftf_mel_webinar_series_application_technologies_06132018_final.pptx
ftf_mel_webinar_series_application_technologies_06132018_final.pptxftf_mel_webinar_series_application_technologies_06132018_final.pptx
ftf_mel_webinar_series_application_technologies_06132018_final.pptxconstantino34
 
5B. Collaborating, Learning and Adapting Workshop Template.pptx
5B. Collaborating, Learning and Adapting Workshop Template.pptx5B. Collaborating, Learning and Adapting Workshop Template.pptx
5B. Collaborating, Learning and Adapting Workshop Template.pptxconstantino34
 
4A. Data Collection Preparation Workshop Template.pptx
4A. Data Collection Preparation Workshop Template.pptx4A. Data Collection Preparation Workshop Template.pptx
4A. Data Collection Preparation Workshop Template.pptxconstantino34
 
5A. Validation Workshop Template.pptx
5A. Validation Workshop Template.pptx5A. Validation Workshop Template.pptx
5A. Validation Workshop Template.pptxconstantino34
 
Processus dÔÇÖ+®laboration des politiques agricoles.ppt
Processus dÔÇÖ+®laboration des politiques agricoles.pptProcessus dÔÇÖ+®laboration des politiques agricoles.ppt
Processus dÔÇÖ+®laboration des politiques agricoles.pptconstantino34
 

More from constantino34 (11)

Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptx
Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptxPresentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptx
Presentation-outil-danalyse-SAPAA_atelier-partage_28sept_final.pptx
 
Presentation-PROACT_atelier-partage_28-Sept-2016.pptx
Presentation-PROACT_atelier-partage_28-Sept-2016.pptxPresentation-PROACT_atelier-partage_28-Sept-2016.pptx
Presentation-PROACT_atelier-partage_28-Sept-2016.pptx
 
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptx
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptxGénéralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptx
Généralités-et-Approche-Chaine-de-Valeur_IFPRI-PAPAFevrier-2016.pptx
 
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptx
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptxAgrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptx
Agrifood-Value-Chains-overview_MSU-PAPA_Janvier-2016.pptx
 
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptx
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptxintro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptx
intro_to_the_revised_ftf_mel_system_webinar_2018-04-19.pptx
 
melwebinaragrometeorologicalindicators20190529.pptx
melwebinaragrometeorologicalindicators20190529.pptxmelwebinaragrometeorologicalindicators20190529.pptx
melwebinaragrometeorologicalindicators20190529.pptx
 
ftf_mel_webinar_series_application_technologies_06132018_final.pptx
ftf_mel_webinar_series_application_technologies_06132018_final.pptxftf_mel_webinar_series_application_technologies_06132018_final.pptx
ftf_mel_webinar_series_application_technologies_06132018_final.pptx
 
5B. Collaborating, Learning and Adapting Workshop Template.pptx
5B. Collaborating, Learning and Adapting Workshop Template.pptx5B. Collaborating, Learning and Adapting Workshop Template.pptx
5B. Collaborating, Learning and Adapting Workshop Template.pptx
 
4A. Data Collection Preparation Workshop Template.pptx
4A. Data Collection Preparation Workshop Template.pptx4A. Data Collection Preparation Workshop Template.pptx
4A. Data Collection Preparation Workshop Template.pptx
 
5A. Validation Workshop Template.pptx
5A. Validation Workshop Template.pptx5A. Validation Workshop Template.pptx
5A. Validation Workshop Template.pptx
 
Processus dÔÇÖ+®laboration des politiques agricoles.ppt
Processus dÔÇÖ+®laboration des politiques agricoles.pptProcessus dÔÇÖ+®laboration des politiques agricoles.ppt
Processus dÔÇÖ+®laboration des politiques agricoles.ppt
 

Recently uploaded

Booking open Available Pune Call Girls Sanaswadi 6297143586 Call Hot Indian ...
Booking open Available Pune Call Girls Sanaswadi  6297143586 Call Hot Indian ...Booking open Available Pune Call Girls Sanaswadi  6297143586 Call Hot Indian ...
Booking open Available Pune Call Girls Sanaswadi 6297143586 Call Hot Indian ...Call Girls in Nagpur High Profile
 
Top Rated Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...
Top Rated  Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...Top Rated  Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...
Top Rated Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...Call Girls in Nagpur High Profile
 
Top Rated Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...
Top Rated  Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...Top Rated  Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...
Top Rated Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...Call Girls in Nagpur High Profile
 
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Serviceranjana rawat
 
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...Call Girls in Nagpur High Profile
 
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...ranjana rawat
 
Top Rated Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated  Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...Top Rated  Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...Call Girls in Nagpur High Profile
 
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Serviceranjana rawat
 
Grade Eight Quarter 4_Week 6_Cookery.pptx
Grade Eight Quarter 4_Week 6_Cookery.pptxGrade Eight Quarter 4_Week 6_Cookery.pptx
Grade Eight Quarter 4_Week 6_Cookery.pptxKurtGardy
 
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdf
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdfTech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdf
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdfAlessandroMartins454470
 
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...Pooja Nehwal
 
Katraj ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...
Katraj ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...Katraj ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...
Katraj ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...tanu pandey
 
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...Suhani Kapoor
 
Pesticide Calculation Review 2013 post.pptx
Pesticide Calculation Review 2013 post.pptxPesticide Calculation Review 2013 post.pptx
Pesticide Calculation Review 2013 post.pptxalfordglenn
 
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Bookingroncy bisnoi
 
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service Bikaner
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service BikanerVIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service Bikaner
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service BikanerSuhani Kapoor
 
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDY
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDYTHE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDY
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDYHumphrey A Beña
 
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escortsranjana rawat
 

Recently uploaded (20)

Booking open Available Pune Call Girls Sanaswadi 6297143586 Call Hot Indian ...
Booking open Available Pune Call Girls Sanaswadi  6297143586 Call Hot Indian ...Booking open Available Pune Call Girls Sanaswadi  6297143586 Call Hot Indian ...
Booking open Available Pune Call Girls Sanaswadi 6297143586 Call Hot Indian ...
 
Top Rated Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...
Top Rated  Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...Top Rated  Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...
Top Rated Pune Call Girls JM road ⟟ 6297143586 ⟟ Call Me For Genuine Sex Ser...
 
Top Rated Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...
Top Rated  Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...Top Rated  Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...
Top Rated Pune Call Girls Baner ⟟ 6297143586 ⟟ Call Me For Genuine Sex Servi...
 
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service
(SUNAINA) Call Girls Alandi Road ( 7001035870 ) HI-Fi Pune Escorts Service
 
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Sinhagad Road (7001035870) Pune Escorts Nearby with Comp...
 
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...
Book Paid Chakan Call Girls Pune 8250192130Low Budget Full Independent High P...
 
Top Rated Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated  Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...Top Rated  Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated Pune Call Girls Yashwant Nagar ⟟ 6297143586 ⟟ Call Me For Genuine ...
 
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service
(ISHITA) Call Girls Manchar ( 7001035870 ) HI-Fi Pune Escorts Service
 
Grade Eight Quarter 4_Week 6_Cookery.pptx
Grade Eight Quarter 4_Week 6_Cookery.pptxGrade Eight Quarter 4_Week 6_Cookery.pptx
Grade Eight Quarter 4_Week 6_Cookery.pptx
 
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdf
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdfTech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdf
Tech Social Sharing Space 4.0_Donation_System_April_26_2024_Rev70.pdf
 
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...
Ho Sexy Call Girl in Mira Road Bhayandar | ₹,7500 With Free Delivery, Kashimi...
 
Katraj ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...
Katraj ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...Katraj ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...
Katraj ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...
 
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...
VIP Russian Call Girls in Noida Deepika 8250192130 Independent Escort Service...
 
Call Girls In Tilak Nagar꧁❤ 🔝 9953056974🔝❤꧂ Escort ServiCe
Call Girls In  Tilak Nagar꧁❤ 🔝 9953056974🔝❤꧂ Escort ServiCeCall Girls In  Tilak Nagar꧁❤ 🔝 9953056974🔝❤꧂ Escort ServiCe
Call Girls In Tilak Nagar꧁❤ 🔝 9953056974🔝❤꧂ Escort ServiCe
 
Pesticide Calculation Review 2013 post.pptx
Pesticide Calculation Review 2013 post.pptxPesticide Calculation Review 2013 post.pptx
Pesticide Calculation Review 2013 post.pptx
 
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sb Road Call Me 7737669865 Budget Friendly No Advance Booking
 
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service Bikaner
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service BikanerVIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service Bikaner
VIP Call Girl Bikaner Aashi 8250192130 Independent Escort Service Bikaner
 
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDY
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDYTHE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDY
THE ARTISANAL SALT OF SAN VICENTE, ILOCOS SUR: A CASE STUDY
 
young Whatsapp Call Girls in Jamuna Vihar 🔝 9953056974 🔝 escort service
young Whatsapp Call Girls in Jamuna Vihar 🔝 9953056974 🔝 escort serviceyoung Whatsapp Call Girls in Jamuna Vihar 🔝 9953056974 🔝 escort service
young Whatsapp Call Girls in Jamuna Vihar 🔝 9953056974 🔝 escort service
 
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MAYA) Baner Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
 

ECOWAS-Agriculture-to-2025-and-Model_USDA-Juin-2016.pptx

  • 1. Jim Hansen, Syd Cochrane, Getachew Nigatu Agricultural Economist USDA, Economic Research Service June 27, 28, 29 2016 Long-term Projections of International Agricultural Trade, ECOWAS Agriculture to 2025 and Model
  • 2. Presentation Outline • Description of USDA 10 Year Commodity Projections • Macroeconomics, population, and energy • ECOWAS Model • US commodities and International trade • ECOWAS agricultural projections • Conclusion
  • 3. USDA’s Agricultural Projections • 10-year projection of major commodities - Supply, demand, trade, and prices. - Based on November 2015 market conditions. Released Feb 2016 • Assumptions: - Continuation of current U.S. law - Continuation of existing international trade agreements - Population growth slows, strongest in developing countries - Macroeconomic growth – strongest in emerging markets • Composite of Model Results and Analysts Judgment - Modeling system: dynamic partial equilibrium trade - 40 countries/regions, - 24 commodity markets • Equilibrates: (Supply = Demand) & (Imports = Exports) Solves for prices and trade, clear world and country markets
  • 4. Demand Structure: •Per Capita GDP growth - Population growth - GDP growth •Own and Substitute Prices •Rural and Urban for some countries •Diet Diversification in developing countries  GDP/Capita Growth  Urbanization  Income distribution equality  Food away from home
  • 5. Changes in Food Consumption: • Greater consumption of: - Fruits & Vegetables - Vegetable Oils - Processed Cereal Products - Meats & Dairy Products Feed Demand Increases  Import demand for Feed grains • Less consumption of: - Staple grains - rice in Asia, corn in Indonesia and Mexico - Low-quality grain varieties and switching to high-quality (high-quality varieties may lower yields) - Roots & tubers
  • 7. Commodities in ERS ECOWAS Model • Livestock: (3 sectors) – Beef, Pork, and Poultry • Crops: (9 sectors) – Wheat, Rice – Corn, Sorghum, Other-Coarse-Gr (mostly millet) – Other seeds (mostly peanuts), meal and oil – Cotton, sugar, cocoa – Blank sections no data – barley, soybeans meal oil,
  • 8. • Elasticity Partial Equilibrium model • Model in Excel Spread sheet - 3 main sheets Commodity models (Forecast) Parameters, Base-Scenario (table) • Data Requirement for Model – Macroeconomic variables – Agriculture data (aggregate) – • USDA Production, supply and Disappearance and FAO – Prices and Policies
  • 9. Modeling the Agriculture Economy: • Production & consumption – Crops: area, yield, consumption, stocks and trade – Livestock: animals inventory, production, consumption, trade, stocks • Model as a System – Accounting (0 = PROD+BSTK+IM-TCON-EX-ESTK) – Number of different identities must hold – Stock issue, government, farm household
  • 10. Modeling Production: • Production Gross return = lagged prices x expected yield Yield = f(gross return, technology time trend) Area = f(gross return, alternative crops GR, tech) Production = Yield x Area Total Supply = Production + Imports + Beg Stocks
  • 11. Modeling Consumption: • Consumption Per capita cons = f(own price, sub prices, income) Food cons = per capita cons x population Total cons = food cons + feed cons + waste + industry use Total Disappearance = Total cons + exports + end stocks
  • 12. Modeling Stocks & Trade: • Ending and beginning stocks Beginning stocks = lagged(Ending stocks) Ending stocks = f(production or consumption, trend) Exports = f(consumer price, export price, trend) Imports = f(producer price, export price, trend) Imports and exports are also identities for some commodities Imports = Cons + endstocks – production – exports-begstocks
  • 13. Closing the Model: • Domestic prices solved in the model for some commodities Total Disappearance = Total cons + exports + end stocks Total Supply = Production + Imports + Beg Stocks Prices solved in the model until supply = demand 0 = Total Supply - Total Disappearance
  • 15. 0 2 4 6 8 10 12 14 16 18 77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Oth-CoarseGrn Sorghum Corn Oth-Oilseed Rice ECOWAS Area Harvested (million ha) Million hectares Corn Oth-oil seed Rice Sorghum Other coarse grain
  • 16. 0 10 20 30 40 50 60 77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Oth-CoarseGrn Sorghum Corn Oth-Oilseed Rice ECOWAS Area Harvested (million ha) Million hectares Corn Oth-oil seed Rice Sorghum Other coarse grain (Millet)
  • 17. 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Corn Rice ECOWAS Yields: (mt/ha) Metric tons per hectares Corn Rice Are the recent yield data correct?
  • 18. 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Sorghum Other Coarse Grain Oth-Oilseed ECOWAS Yields: (mt/ha) Metric tons per hectares Other oil seed Sorghum Other coarse grain
  • 19. 0 2 4 6 8 10 12 14 16 18 20 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Consumption Feed Food seed waste ECOWAS Corn Production, and Consumption (million mt) Million metric tons Feed Food Total Consumption Production
  • 20. 0 100 200 300 400 500 600 700 800 900 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Imports Exports ECOWAS Corn Imports and Exports (1,000 mt) Thousand metric tons Exports Imports
  • 21. 0 2 4 6 8 10 12 14 16 18 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Feed Food seed waste ECOWAS Sorghum Production, Food, and Feed Consumption (million mt) Million metric tons Feed Food Production
  • 22. 0 50 100 150 200 250 300 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Imports Exports ECOWAS Sorghum Imports and Exports (1,000 mt) Thousand metric tons Imports Exports
  • 23. 0 2 4 6 8 10 12 14 16 71 74 77 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 P ro ductio n C o nsumptio n ECOWAS Other Coarse Grain (Millet) Production and Consumption (million mt) Million metric tons
  • 24. 0 2 4 6 8 10 12 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Imports Exports Consumption ECOWAS Wheat Imports, Consumption, Exports and Production (million mt) Million metric tons Exports Consumption Imports
  • 25. 0 5 10 15 20 25 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Imports Consumption ECOWAS Rice Total Consumption, Production and Imports (million mt) Million metric tons Production Total Consumption Imports
  • 26. 0 2 4 6 8 10 12 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production T otal Consumption Feed seed waste Food Crush ECOWAS Other Oilseeds (Peanuts) Production, Exports, and Consumption (million mt) Million metric tons Crush Total Consumption Production Food Feed, seed & waste
  • 27. 0 2 4 6 8 10 12 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Feed seed waste Food Crush ECOWAS Other Oilseeds (Peanuts) : Crush, Food, and Feed, seed & waste (million mt) Million metric tons Crush Total Consumption Food Feed, seed & waste
  • 29. 0 5 10 15 20 25 30 35 40 45 50 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Corn W heat Rice ECOWAS Food Per Capita Consumption (kg/capita) Kilograms/person per year Corn Rice Wheat
  • 30. 0 10 20 30 40 50 60 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Sorghum Other Coarse Grain ECOWAS Food Per Capita Consumption (kg/capita) Kilograms/person per year Sorghum Other Coarse Grain Millet
  • 31. 0 2 4 6 8 10 12 14 16 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Seeds Other-Oilseed Peanuts Oil - Other Oil Peanuts ECOWAS Food Per Capita Consumption (kg/capita) Kilograms/person per year Peanuts Other Oilseeds Peanut Oil
  • 32. Pork, Poultry, and Beef Production and Feed Demand
  • 33. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Imports T otal Consumption ECOWAS Beef Production, Consumption and Imports (million mt) Million metric tons Consumption Production Imports
  • 34. 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Imports T otal Consumption ECOWAS Pork Production, Consumption and Imports (million mt) Million metric tons Consumption Production Imports
  • 35. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Production Imports T otal Consumption ECOWAS Poultry Production, Consumption and Imports (million mt) Million metric tons Consumption Production Imports
  • 36. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Pork Poultry Beef ECOWAS Meat Production: Beef, Poultry and Pork (million mt) Million metric tons Beef Pork Poultry
  • 38. 0 1 2 3 4 5 6 7 8 80 83 86 89 92 95 98 01 04 07 10 13 16 19 22 25 Sorghum Other-Oilseed-Peanuts Other-Meal-Peanuts Corn ECOWAS Feed Demand: Corn, Peanut-Meal, Peanuts, and Sorghum (million mt) Million metric tons Corn Other-Oilseeds Peanut Other-Meal Peanut Sorghum Corn Increase 1980-2003 flat 2003-2016 + 2.4 mmt, Projection little growth
  • 39. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 70 73 76 79 82 85 88 91 94 97 00 03 06 09 12 15 18 21 24 Production Exports Consumption ECOWAS Cotton Production, Exports, and Consumption (million mt) Million metric tons Exports Total Consumption Production
  • 40. 80 100 120 140 160 180 200 220 240 260 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 80 100 120 140 160 180 200 220 240 260 Total world grain & oilseeds1 Production, yield, area harvested, population & per cap production Index: 1970 = 100 1/Oilseeds = soybeans + rapeseed + sunflowers. Source: Compiled from USDA’s PS&D Database & Baseline Projections Growth rates: Exponential Trend (%/year) 1970-1990 1990- 2009 2010- 2019 Production 2.4 % 1.54 1.27 Yields 1.9 1.21 0.70 Area 0.50 0.33 0.57
  • 41. 80 100 120 140 160 180 200 220 240 260 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 80 100 120 140 160 180 200 220 240 260 Total world grain & oilseeds1 Production, yield, area harvested, population & per cap production Index: 1970 = 100 1/Oilseeds = soybeans + rapeseed + sunflowers. Source: Compiled from USDA’s PS&D Database & Baseline Projections Per Capita/Production Growth rates: Exponential Trend 1970 - 90 1990 - 09 2010 - 19 Production 2.4 1.54 1.27 Yields 1.9 1.21 0.70 Population 1.7 1.30 1.06 Area 0.50 0.33 0.57 Capita/Pro 0.61 0.28 0.20
  • 42. Conclusions and Summary: • Strong global trade growth in most agriculture commodities, without significant increases in real world commodity prices. • Strong income growth in developing countries and urbanization lead to increased import demand for grains, High Value Products • Trade to remain very competitive Expanding production potential in Brazil & Argentina, FSU, EU Indonesia expands palm oil production. • Uncertainties, Ethanol and trade, Bio-energy policies, BSE, Avian influenza, food safety, China and Brazil, natural resource constraints – water, changing demographics and effect on food demand
  • 43. Thank you USDA-ERS Long-Term Projections briefing room http://www.ers.usda.gov/briefing/baseline