Vergara Air CIRAD 2010

Information Needs for Agricultural Risk M t i D l i C t iManagement in Developing Countries

Agricultural Market Information Systems in Africa:

Oscar Vergara

Agricultural Market Information Systems in Africa: Renewal and ImpactMontpellier, FranceMarch 29-31, 2010

2010 AIR WORLDWIDE CORPORATION AGRICULTURAL MARKET INFORMATION SYSTEMS IN AFRICA WORKSHOP 1

,

Overview of the MPCI Program: Corn, Soybean and Wheat Dominate the US Crop Riskand Wheat Dominate the US Crop Risk


Source: Risk Management Agency 2009

Weather Is the Key Source of Uncertainty Affecting Yields

% Crop Loss

Drought & Heat 37%Drought & Heat 37%Excess Moisture 33%Hail 13%Cold, Frost & Freeze 5%Flood 1%Wind, Hurricane 4%

Subtotal – Directly related to weather 93%Disease 5%Insects & Wildlife 1%Insects & Wildlife 1%Other 1%

Subtotal – Other perils 7%


Total 100%

Still … Every Billion Dollar Weather Disaster Came as a Surprisep

---- 1988 ----

D h /H W S 1988 1988 d h i lDrought/Heat Wave Summer 1988. 1988 drought in central and eastern U.S. with very severe losses to agriculture and

related industries; estimated $40.0 (71.2) billion damage/costs; estimated 5,000 to 10,000 deaths (includes

heat stress-related).

Midwest Flooding Summer 1993. Severe, widespread flooding in central U.S. due to persistent heavy rains and

thunderstorms; approximately $21.0 (30.2) billion

---- 1993 ----

thunderstorms; approximately $21.0 (30.2) billion damage/costs; 48 deaths.


The 2008 Iowa Flood Event


Traditional Approach for Estimating Crop Losses

Observed Corn Yields

100

120

140

Statistical

lity Expected Yield

Yield Distribution

0

20

40

60

80

70 73 76 79 82 85 88 91 94 97 00 03

Yiel

d

Yield – bushels/acre

Prob

abil

197

197

197

197

198

198

198

199

199

199

200

200

Year

Market information

• Significant weaknesses with traditional approach that inaccurately accounts for ty

Loss Distribution

accounts for– Changes in technology– Changes in market information– Weather variability

Prob

abili

t


– Weather variabilityLoss distribution

Probabilistic Agricultural Model Components

YIELD / PRICEHAZARD

Price ModelDetrended Yield

Distribution

AWI Calculation

Exposure Information

Event Yield Generation

FINANCIAL

Gross Loss

Market Information

Gross Loss Calculations

Government Donor

Interventions

Net Loss Calculations


Subsidies

AWI (Agricultural Weather Index) is a Measure of Yield Variability Due To Weather

Temperature Precipitation

County-Specific AWI

IndexAvailable Water Capacity

(Soil)Crop Specific Data

Index


County Specific AWI Index


AWI Removes Weather Variability from the Historic Yields to Reveal True Technology Trend

000

Yield Time Series

180

2018

020

180

20

17 Bushels

re

140

160

y

140

160

y

140

160

y

True Technology Trend with Weather Variability -B

ushe

ls/A

cr

0012

0

y

0012

0

y

0012

0

y yRemoved

Yiel

d

8010

8010

8010

Trend Line Influenced by Weather Variability


1990 1995 2000 2005 2010

x

20081990 1995 2000 2005 2010

x

20081990 1995 2000 2005 2010

x

2008

The Choice of Methodology Can Have a Large Impact on Insurance Contracts

Probability Density Function of Detrended Yield Time Series

0.01

5

Without AWIWith AWI

0.01

50.

015

0.01

5

Yield Guarantee

0.01

0

Without AWI

0.01

00.

010

0.01

0

Prob

abili

ty

0.00

50.

005

0.00

50.

005

100 150 200 250

0.00

0

100 150 200 250

0.00

0

100 150 200 250

0.00

0

100 150 200 250

0.00

0

Yield – Bushels/Acre

100 150 200 250



YIELD / PRICEHAZARD


Distribution

AWI Calculation



FINANCIAL

Gross Loss

Market Information


Government Donor

Interventions



Subsidies

Corn Price Volatility During 2008

2008 Price Volatility for Corn2008 Price Volatility for Corn

(CME December Corn Contract)

Planting Price

Harvest Price


Corn Price Model

180%e)

Corn

ntin

g Pr

ic(%

of P

lan

vest

Pric

e

Historical Values

2008 Example of

0%60% 80% 100% 120%

Harv Example of

a yield scenario


Event Yield (Percent of Normal)


YIELD / PRICEHAZARD


Distribution

AWI Calculation



FINANCIAL

Gross Loss

Market Information


Government Donor

Interventions



Subsidies

County Loss Distributions Form Basis of Event Catalog

• 10,000 outcomes based on variation from historical dataC t t h l l l d• Current technology level and spatial correlations

• Current market information• Not biased by recent years• Not biased by recent years



YIELD / PRICEHAZARD


Distribution

AWI Calculation



FINANCIAL

Gross Loss

Market Information


Government Donor

Interventions



Subsidies

Different Applications of the Agricultural Risk Model

Household Risk

ManagementManagement

Planting and Harvesting D i i

Financial Planning

Agricultural Risk Model

f C

DecisionsPlanning

for Crop Producers

Input Risk pPurchases

Sales

Transfers


Sales Planning

AIR Crop Model Clients


Expected Yields (Corn) – RMA and AWIIS

ILLI

NO

II


Iowa Corn GRIP (Harvest Revenue Option) 90% Coverage

Probability of Loss

2008 2009


Real-Time MonitoringMaximum Temperature Weekly Accumulated TemperatureMinimum Temperature

Growing Degree Days Surface Moisture LevelGrowing Degree Days Surface Moisture LevelCrop Moisture Index

AWI C t Yi ld Di t ib ti AWI – County-Specific IndexSt d di d P i it ti AWI – County Yield Distribution AWI County Specific IndexStandardized Precipitation


CropAlert: Real-Time Crop Yield and Weather Forecast Information Service


USDA - NASS Crop Production 2009 Summary


AIR Proven Technology: USDA Validation and Commodity Trading Simulation Awardsy g


Summary

• Traditional approaches for estimating crop losses need toaccount for changes in technology, price volatilities, marketaccou t o c a ges tec o ogy, p ce o at t es, a etinformation changes and, most significantly, the effect of weather

• A weather-based agricultural risk model based on a fullyprobabilistic yield and price catalog can take into account thep y p gspatial and temporal correlations of crop losses

• Extension agents, agricultural educators and donors shouldcouple their marketing information systems with agricultural riskp g y gmodels that can better quantify the potential crop portfolio riskunder future adverse weather conditions and improve the type ofinformation that producers receive for risk management


Data Requirements for Agricultural Risk Modeling


Modeling Agricultural Perils in Developing Countries: What is Needed?

Validation

Calibration

ModelsData

Calibration


Sources of Information for Agricultural Risk Modeling in the United States

Weather InformationNational Oceanographic and Atmospheric Administration (NOAA)National Weather Service (NWS) Climate Prediction Center (CPC)

Soil InformationUnited States Geological Survey (USGS)United States Forest Service (USFS)

Crop and Livestock InformationCooperative Research, Education and Extension Service (CREES)Cooperative Research, Education and Extension Service (CREES)Agricultural Research Service (ARS)

Price and Yield InformationNational Agricultural Statistics Service (NASS)National Agricultural Statistics Service (NASS)Economic Research Service (ERS)

Historical Loss InformationRi k M t A (RMA)


Risk Management Agency (RMA)

Sources of Information for Agricultural Risk Modeling in Developing Countries

Weather InformationProduction Estimates Crop Assessment Division (PECAD-FAS)

g p g

Food and Agriculture Organization (FAO-METART ARTEMIS)Soil Information

Famine Early Warning System Network (FEWS-NET)Food and Agriculture Organization (FAO-METART ARTEMIS)

Crop and Livestock InformationGlobal Information and Early Warning System (FAO-GIEWS)Global Information and Early Warning System (FAO GIEWS)Agricultural Ministries, Educational Institutions

Price and Yield InformationAgricultural Ministries Trade AssociationsAgricultural Ministries, Trade AssociationsFood and Agriculture Organization Statistical Database (FAOSTAT)

Historical Loss InformationA i lt l L d P d A i ti


Agricultural Lenders, Producer Associations

Number of Weather Stations in Central America

Honduras

52 weather

t ti

Guatemala

102 weather stationsstations stations

Ni El SalvadorNicaragua

31 weather

stations

El Salvador

30 weather

stations


Source: World Meteorological Organization, 2009

Coverage of Weather Data in the United States

United States

9,000+,

weather

stations


Source: National Oceanographic and Atmospheric Administration, 2009

In Crop Production, Every Growing Season is Different

Agricultural production is very risky due to weather uncertaintiesWeather experienced by crops at different stages of development will have anWeather experienced by crops at different stages of development will have an impact on harvest outcome

Seedling Stages

adequate soil moisture

and temperature

needed for germination

Pod Filling Stages

adequate soil

moisture needed forVegetative Stages moisture needed for

grain filling

g g

more resistant to

environmental stress


Global Perspective on Enhanced Vegetation Index (EVI)

Global tropical cyclone tracks, 1985 - 2009


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Vergara Air CIRAD 2010

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