James Richardson, Texas A M University

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How Agricultural and Resource
Management Survey (ARMS) Data Have
Been Used by AFPC
Dr. James W. Richardson
Co-Director Agricultural and Food Policy Center
Regents Professor and TAES Faculty Fellow
Data to Serve 21st Century Agriculture:
Expanding ARMS
December 1, 2003
AFPC’s Use of ARMS Data Base
• AFPC has benefited from the ARMS data
base for more than a dozen years
• ARMS data base has been used to
– Validate representative farms
– Obtain information we do not ask our producer
panels
– Obtain information on structural differences
across farms
– Obtain information for average farms in new
regions
AFPC’s Representative Farms
Data Base
• AFPC develops data to simulate representative
farms through panel interviews
• Information obtained are:
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Farm size, tenure, and rental arrangements
Crop mix & yield history
Herd size & productivity
Farm program participation history
Production costs by enterprise
Fixed costs, by category for the whole farm
Asset values
Machinery complement and replacement details
Representative Farms and Ranches
Dairy
Wheat
Dairy
Wheat
Cattle
Cattle
Dairy
Dairy
Dairy
Dairy
Feed Grain
Hog
Cattle
Rice
Cattle
Feed
Grain
Wheat
Wheat
Cotton
Dairy
Hog
Hog
Feed Grain
Feed Grain
Cattle
Wheat
Cattle
Cattle
Dairy
Feed
Grain
Dairy
Cotton
Cotton
Dairy
Feed Grain
Cotton
Rice
Cotton
Cotton
Rice
Rice
Cotton
Hog
Feed Grain
Cotton
Rice
Rice
Cotton
Rice
Dairy
Dairy
Rice
Rice
Feed
Grain
Cotton
Dairy
Cattle
Cotton
Dairy
AFPC’s Representative
Farms Data Base
• Panel farms located in major production regions
• Locations of panel farms specified by economists
on House and Senate Ag Committees
• Panel farms used to “represent” farms for a
region of importance to Congress
• Representative farms simulated with FLIPSIM to
analyze likely consequences of alternative policies
• Costly to develop and maintain farm level data
base
Validation of AFPC’s
Representative Farms
• Questions are always:
How representative are the farms?
Are the data from a small panel interview accurate?
• ARMS data base used to address these questions,
and more
• ARMS data is sampled to develop a sub-sample of
survey farms that matches a representative farm
– Range of acres (600 to 1400 if AFPC farm is 1000
acres) or range for the number of cows (or sows)
– Crops produced (e.g.., corn and soybeans)
• Start with one crop reporting district and then add
CRDs to gain adequate sample size
Validation of AFPC’s
Representative Farms
• After a sub-sample is identified that has the
same average acres of cropland or number
of head
– Calculate averages for 50+ variables used to
validate our farms, such as:
• Acres of each crop, total costs of production for
crops and livestock, fixed costs by category, asset
values, milk production, receipts from crops and
livestock, government payments
– Results are very good, usually within 5% of
each other
AFPC and the ARMS Data Base
• Information that can be obtained from ARMS that
panels do not provide:
– Debt levels, off-farm income, family living expenses
• Data in ARMS sub-sample used to calculate
average debt to asset ratios for long- and
intermediate-term assets
• Added benefit, the ARMS data matches with Ag
Census so
– Calculate the portion of farms in a region represented
by AFPC farms, e.g., Iowa grain farm represents 26%
of farms in the sub-sample region
AFPC and the ARMS Data Base
• ARMS used for farm structure research
• Debt to asset ratios calculated for different
size farms, by:
– Type of debt (long- and intermediate-term),
– Enterprise (crop or livestock farms), and
– Regions that often combine CRDs and cross
state lines and in Texas go to sub-state level
– Production practice (e.g., irrigation)
• Cost of production and off-farm income
across farm sizes
AFPC and the ARMS Data Base
• Access to ARMS data base makes our jobs easier;
we are more confident our farms are
“representative”
• We still need contacts with actual producers in
the different regions for:
– Local production risk information
– Details on rental arrangements (cash vs. share)
– Details on machinery complements and replacement
schedules
– Technology adoption and changes in production
practices
– Changes in crop mixes in response to cost and policy
changes
AFPC and the ARMS Data Base
• Thanks to ERS and NASS for developing
ARMS and making it available
• Special thanks go to Jim Johnson and Mitch
Morehart for their help in using the ARMS
data base
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