Understanding Demand Shifts for Grain-Based Foods

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Understanding Demand Shifts for Grain-Based
Foods
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Consumer Demand and Market Trends What do
the Data Tell Us and Where are the Knowledge
Gaps?Part II
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DiscussionOral Capps, Jr.Texas AM
UniversitySeptember 28, 2004
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• Background
• The availability, accessibility, and choice of
  foods to meet an adequate and safe diet and to
  promote health and nutrition are fundamental
  challenges facing the US food distribution
  system.
• Understanding factors influencing food choices is
  needed to better understand the mechanisms by
  which individuals select and consume foods.

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• Discussion of Presentations
• Goergen
• Provides trends and insights from grain-based
  categories using weekly scanner data from
  ACNielsen.
• RTE cereal, bread and bakery goods, pasta, and
  crackers have experienced declines in grain-based
  categories.

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• Discussion of Presentations (cont)
• Eales
• Examines RTE cereal consumption trends in the
  1990s by region and by nutritional content
  (protein, fat, fiber, sugar, sodium.)
• Use of grocery marketing data (SAMI) for 1990.
• Use of ACNielsen HomeScan data for 1999.

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• Commentary
• The trends described by Goergen and Eales,
  although useful, are not sufficient for marketing
  strategies.
• Several questions are begged in the discourse of
  the aforementioned trends associated with the
  consumption of grain-based foods.

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• Which demographic segments of the U.S. population
  are most likely to consume grain-based foods?

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1. Which demographic segments of the U.S. population
   are most likely to consume grain-based foods?
2. Do differences exist between low-income and
   non-poverty segments of the U.S. population in
   the consumption of grain-based foods? What about
   differences among race region ethnicity and
   age?

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1. Which demographic segments of the U.S. population
   are most likely to consume grain-based foods?
2. Do differences exist between low-income and
   non-poverty segments of the U.S. population in
   the consumption of grain-based foods? What about
   differences among race region ethnicity and
   age?
3. What are the driving forces behind the demand for
   grain-based foods? Specifically, what roles do
   traditional economic factors such as prices and
   income play?

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• Which demographic segments of the U.S. population
  are most likely to consume grain-based foods?
• Do differences exist between low-income and
  non-poverty segments of the U.S. population in
  the consumption of grain-based foods? What about
  differences among race region ethnicity and
  age?
• What are the driving forces behind the demand for
  grain-based foods? Specifically, what roles do
  traditional economic factors such as prices and
  income play?
• To what degree have health and nutrition issues
  (e.g. low-carb diets) influenced the demand for
  grain-based foods?

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• Commentary
• To address these issues, it is necessary to
  develop econometric (structural) models with
  appropriate data.
• Currently, ACNielsen HomeScan Panel data are
  available from the ERS for 1998, 1999, 2000, and
  2001 presumably these data also are available
  for 2002, 2003, and 2004.

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• Commentary (Cont)
• The use of the HomeScan Panel data from 1998 to
  present permits a perspective by household,
  fine-tuning the trends previously discussed.
• Obtain a micro-perspective in lieu of a macro
  perspective.
• Marketing strategists require this micro
  orientation.

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• Commentary (Cont)
• Consumers today are offered an ever-increasing
  number of choices within the category of
  grain-based foods.
• ACNielsen HomeScan Panel data allow for detailed
  analyses not only by household, but also by type
  of grain-based foods.

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• Commentary
• Probit models/analysis
• Demand models/analysis
• Who is most likely to purchase (or not to
  purchase) grain-based foods? By addressing this
  issue, market strategists may target population
  groups to increase consumption of grain-based
  foods.
• Single-equation Heckman or Double-Hurdle models
  multi-equation demand system models.

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• Commentary (Cont)
• Provide an understanding of the demographic
  factors associated with the level of consumption
  of grain-based foods.
• Obtain own-price, cross-price, and income
  elasticities of demand for grain-based products
  measures of sensitivity on the part of consumers
  to changes in prices and to changes in income.

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• Commentary (Cont)
• A by-product of demand systems analysis--
  ascertain whether goods are complements,
  substitutes, or independent
• Develop alternative measures for ranking
  substitutes.
• Use of diversion ratios
• Allows market analysis to determine if, for
  example, sales of white bread decrease, which
  sales of other products are positively impacted?

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Alternative Measures for Ranking Substitutes, j,
of Base Product i.
We use the unit diversion ratio which is
tantamount to
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• Commentary
• Given the widespread attention on health and
  nutrition issues from the news media, food
  product labels, and from medical personnel, it is
  important for market analysis to identify and
  assess the impacts of this information on the
  demand for grain-based foods.
• As one illustration, using ACNielsen HomeScan
  panel data from 1998 to present, we are in
  position to examine consumption patterns of
  grain-based foods before the low-carb diet
  phenomenon during the height of the low-carb
  diet phenomenon and in the twilight of the
  phenomenon.

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• Data Gaps
• Current data available to the USDA/Economic
  Research Service
• Time-series data (1) consumption of flour and
  cereal products, by type of grain, on a pounds
  per capita basis from 1967 to 2002 (2) per
  capita consumption of breakfast cereals from 1970.

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• Data Gaps (Cont)
• Positive feature of time-series data
• Disappearance data, both at-home and
  away-from-home markets.
• Negative features of time-series data
• Typically not specific enough to address market
  issues
• Do not reflect current market conditions.
• Frequency is annual.

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• Data Gaps
• Current data available to the USDA/Economic
  Research Service
• Cross-sectional data (1) ACNielsen HomeScan
  Panel (2) Continuing Survey of Food Intakes for
  Individuals (CSFII.)
• But these data say nothing, however, about
  purchases/consumption in the away-from-home
  market, institutional, or convenience-store
  channels.

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• Data Gaps (Cont)
• One may employ National Panel Diary data to say
  something about the away-from-home market.
• What about getting information from mass
  merchandisers like Wal-Mart?
• To be sure, then, data gaps exist.

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• Concluding Remarks
• In order to better understand demands for
  grain-based foods, it is necessary to develop and
  estimate formal structural models with
  appropriate data.
• Currently we have the ability to assess
  consumption patterns in the at-home market with
  scanner data.

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• Concluding Remarks (Cont)
• However, data from mass merchandisers typically
  are not available so at-home consumption of
  grain-baesd foods is likely to be understated.
• To assess away-from-home consumption or
  consumption from the convenience channel, data
  typically are lacking.