USDA’s Economic Research Service and Use of

Weather Data

Ed AllenCross Commodity Analyst for Field Crops

Market and Trade Economics DivisionMarch 31, 2010

ERS mission

The mission of ERS is to inform and enhance The mission of ERS is to inform and enhance public and private decision-making on public and private decision-making on economic and policy issues related to economic and policy issues related to agriculture, food, natural resources, and rural agriculture, food, natural resources, and rural development. development.

ERS Functions

Research Market analysis and forecasting Database development Short term policy analysis

Resource & Rural Economics

Agricultural Structure & Productivity

Farm & Rural House-hold Well-Being

Farm & Rural Business

Production Economics & Technology

Resources, Environmental & Science Policy

Markets & Trade Economics

Food & Specialty Crops

Agricultural Policy and Models

Field Crops

International Demand & Trade

Animal Products

ERS research programs areas

Diet, Safety & Health

Food Economics

Food Assistance

Food Markets

Food Security & Development

Commodity Market Analysis at the Economic Research Service

Purpose: Timely, reliable, and objective information is essential if a market economy is to operate efficiently

Analyze and explain Current market situation Short term forecast of supply,

demand and prices

ERS market analysis covers a wide range of commodities, countries, and topics

Wheat Rice Corn and other feed

crops Oil crops Cotton and wool Fruit and tree nuts Aquaculture Sugar and sweeteners

Livestock, dairy & poultry

Vegetables, fruits, tree nuts & specialties

Agricultural Trade Reports—Europe, China, Brazil, India, Transition economies, etc.

Food Security Assessment

Agricultural income and finance

What makes a commodity market reporting program effective?

Information needs to be timely and available to everyone

Information must be regarded as objective

Analysts need to become specialists Good commodity analysts are good

economists The successful analyst understands the

commodity market

Quality assurance Quality assurance is an essential part of an

effective outlook program. The Department speaks with one voice Interagency committees are involved in all

estimates and review of all market outlook publications released by USDA.

World Agricultural Outlook Board approves all forecasts

Forecasts must be free from political bias so political appointees do not dictate forecasts or conclusions.

How the short-term forecasting process works...

USDA Interagency Commodity Estimates Committee Process

Data:- International

- Domestic

Information:

Commodity Forecasts Appear in:WASDE

Newsletters Circulars

Other Forecasts:- Farm Income- Food Prices

- Trade

Policy Decisions:

- Attaché reports- Wire service stories

--Short term--Long term

The supply and use table: the basic tool for analysis

The supply and use table has three main components: SUPPLY USE PRICE

Describes the marketing year outcome for a single commodity

Summarizes market behavior of all buyers and sellers

Organizes information about a crop Provides framework for analysis

Some words about forecasting

Forecasting is an essential part of our analysis But forecasts have limits

The basic tool is a model A way of organizing and elaborating the

relationships Based on assumptions

Forecasts can be wrong Mistaken assumptions Wrong information Poor model specification

Weather Is a Key Variable Production

Yield fluctuates mostly with weather (but also economic variables like fertilizer use)

Area planted and abandonment are often influenced by weather (i.e. freezes or floods)

Domestic use and trade Occasionally influenced by weather

Some Uses of Weather Data Past

ERS used very disaggregated daily temperature and precipitation data to model crop yields for the Risk Management Agency (crop insurance)

In 1989, yield models for wheat, corn, soybeans, sorghum, barley, and oats, by state, using monthly average temperature and precipitation

Some Uses of Weather Data

Present Corn yield model using weekly and monthly

temperature and precipitation for June, July, and August in key corn belt states

Soybean yields using monthly averages for top 19 states

Rainfall in West Texas and California for cotton yields

U.S. drought areas overlap with hay and beef cattle pasture

Argentina’s precipitation data to compare soybean yields and drought

Australian drought variable to forecast cotton yield

Some Uses of Weather Data

Future Climate change using regional crop

yield, pest distribution and water availability weather variables

An Example of Policy Oriented Research A project studying how conservation

programs function as a means of drought adaptation uses Measures of drought such as the

Standardized Precipitation Index and Palmer Modified Drought Index (station level from NOAA)

County-level monthly precipitation and temperature (average min, max) data derived from PRISM Climate Group data.

Long-run station-level precipitation data from the U.S. Historical Climate Network to estimate regional differences in drought risk.

An Example of Policy Oriented Research ERS’s biggest obstacle is getting

weather data to the county level Much data on conservation program

participation, crop yields, and other variables are at the county level

Access to daily station-level data and interpolating it to the county level is needed measures of heating degree days, cooling

degree days measures of exposure to precipitation

events of different intensities.

Historical Data Used More than Weather Forecasts

USDA commodity forecasts officially assume “normal” weather.

Subjective evaluation based on weekly weather briefings is used to judge satellite imagery and anecdotal reports.

Weather forecasts are sometimes used to “fill in” for a variable in a model.

Weather forecasts can influence how aggressive the committee is at making a change.

Potential Collaboration Between CPC, FAS, WAOB, and ERS

WAOB has Major World Crop Areas and Climatic Profiles (2006) on their website Mix of atlas, crop data, calendars, and weather

data A web product could showcase key

production/yield analysis. For example: Drilling down from a map (i.e. Brazil) to a more

detailed crucial map (such as Mato Grosso) Include more useful details about cropping patterns Show results from models relating weather and yield

that have been developed but never published Analysts from different agencies could get

credit for work already done Analysts from different agencies could be

encouraged to collaborate

Useful websites ERS Website www.ers.usda.gov

WAOB Weather www.usda.gov/oce/weather/pubs