The Food Availability Data System (FADS) provides estimates of aggregate food demand in the United States by tracking production, trade, processing, and stocks of foods. FADS data is uniquely suited for understanding population-level food demand and the links between supply and demand. It has been widely used by researchers in fields like agriculture economics, public health, nutrition, and environmental science to study trends in the U.S. food system and impacts of factors like commodity prices, dietary guidance, food safety incidents, and climate change. While limited in providing data on specific foods or households, FADS remains a key resource for answering important questions about U.S. food system performance.

1. The Food Availability Data System:
Importance for Research
Laurian Unnevehr
Professor Emerita, University of Illinois
Presentation to the National Academies Workshop:
Data and Research to to Improve the U.S. Food Availability
Data System
April 8, 2014

2. Introduction
• FADS grew out of ag statistical system focused
on production estimates
• Provides estimates of aggregate demand
(Disappearance) that reflect basic components
of supply: Production, Trade, Processing,
Stocks
• Data are uniquely suited for understanding:
– Demand at the aggregate or population level
– How supply and demand are linked

3. FADS Shows Food System Trends
• What share of the food supply is imported?
• Which meat (or fruit, vegetable, dairy
product) is the most consumed?
• What is the trend in total calories per capita?
• What share of the food supply is lost or
wasted?
• How does the U.S. food system compare with
other countries?

4. FADS Use in Research
• Aggregate demand response to changes in
supply, market shocks, advertising
• Forecasts of demand, supply, and prices
• How well aggregate demand reflects dietary
guidance
• Environmental impact of food demand

5. Research Stakeholders Have Expanded
• Agricultural economists
– Less important over time as research focus shifted with
changes in consumer behavior
• Public health and nutrition
– Widespread use since development of nutrient and serving
data within FADS
• Industrial ecology, life cycle, environmental systems
– Most recent and growing use in these fields
Tracking use of the data in research would provide
guidance about its value to research stakeholders.

6. FADS Is One Source of Food
Consumption Data
Source: Morrison, Smith, and Lin. Amber Waves. March 2009

7. Questions FADS Cannot Answer
• What is the demand for specific food products
(within a commodity aggregate)?
• How does food demand vary with household
demographic characteristics? With SNAP
benefits?
• What is the demand for differentiated food
products and/or for quality attributes of food?
• What is the demand for FAFH and how does it
differ from demand for FAH?

8. Research Example:
Market Forecasts
• How are commodity prices expected to
change in the future? (ERS Baseline Model)
– Uses per capita consumption of foods from major
commodities as part of model
– Population growth, income lead to growth in total
demand
– Changes in supply intersect with demand to give
new equilibrium prices
– Used for a wide variety of policy questions

9. Research Example:
Changes in Food Preferences
• Was there structural change in U.S. meat
demand in the 1980s?
– Rapid increase in chicken consumption relative to
beef led to question of whether driven by relative
prices or preferences
– Many studies in the 1980s used FADS data to
estimate U.S. meat demand and to test for a
change in preferences
– Most recent was McGuirk et al., JARE, 1995

10. Research Example:
Generic Advertising Impact
• What is the impact of generic advertising on
commodity demand? (eg. Zheng, Kinnucan,
Kaiser, Applied Economics, 2010)
– Non-alcoholic beverage data 1970-2004 from
FADS
– Estimated how advertising expenditures rotate
demand curves with special interest in how
generic dairy advertising influences milk demand

11. Research Example:
Media Impact on Markets
• How did meat demand respond to food safety
media coverage? (Piggott and Marsh, AJAE, 2004)
– Use quarterly data combined with index of media
coverage
– Found short-lived effects of significant media events
• Most studies of food safety incidents have used
scanner data (eg. Arnade et al., AEPP, 2009)
– Reasons include time and product specificity needed
to tease out market impacts

12. Research Example:
Nutritional Epidemiology
• How do different patterns of food
consumption correlate with the incidence of
disease? (Willett, Nutritional Epidemiology,
2012)
– Shows example of meat consumption in different
countries correlated with incidence of colon
cancer
– Recognizes limitations of such studies but also
their use in setting up hypotheses for controlled
investigation

13. Research Example:
Food Safety Epidemiology
• How is the incidence of pathogens related to
food commodity sources? (Guo et al.,
Foodborne Pathogens and Disease, 2011)
– FADS data used to represent consumption within
larger risk assessment model for Salmonella
– Find that chicken, ground beef, and turkey are
three most important sources of foodborne
Salmonella

14. Research Example:
Production Needed for Improved Diets
• How would U.S. food production change if
diets matched guidelines? (Young and Kantor,
1999; Buzby, Wells, and Vocke, 2006 )
– Show how crop acreage would need to shift for
production to meet demand that follows dietary
guidance
– Renewed interest in this question as shown by
recent citations in articles regarding local foods
and sustainable food supply

15. Research Example:
Climate Change and Food Losses
• How much do food losses contribute to
greenhouse gas emissions? (Venkat, Intl J.
Food System Dynamics, 2011)
– Uses FADS estimates of losses for 134
commodities
– Estimates that “avoidable” food loss (at consumer
level) accounts for 2% of U.S. greenhouse
emissions

16. Research Example:
Food Miles
• How does food transportation contribute to
greenhouse gas emissions? (Weber and
Matthews, Env. Sci. Tech., 2008)
– Use FADS and Commodity Flow Survey to examine
relative impacts of transportation versus dietary
patterns to greenhouse gas emissions
– Find that transportation is much smaller
contributor than production and changes in diets
would reduce emissions more than “eating local”

17. Concluding Comments
• How well our food system meets a variety of
demands– economic, social, environmental is of
continuing interest
• FADS will remain key to answering many
questions about food system performance
• Loss estimates critical to both better
characterization of demand and understanding
environmental impacts
• How can improvements to the data support more
definitive answers to important questions?