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Understanding Demand Shifts for Grain-Based Foods. Consumer Demand and Market Trends: What do the Data Tell Us and Where are the Knowledge Gaps? Part II. Discussion Oral Capps, Jr. Texas A&M University September 28, 2004. Background

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consumer demand and market trends what do the data tell us and where are the knowledge gaps part ii
Consumer Demand and Market Trends:What do the Data Tell Us and Where are the Knowledge Gaps?Part II
slide4

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.
slide5

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.
slide6

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.
slide7

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.
slide9

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?

slide10

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?

slide11

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?
slide12

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.
slide13

Commentary (Con’t)

  • 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.
slide14

Commentary (Con’t)

  • 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.
slide16

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.

slide17

Commentary (Con’t)

  • 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.
slide18

Commentary (Con’t)

  • 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?
slide19

Alternative Measures for Ranking Substitutes, j, of Base Product i.

We use the unit diversion ratio which is tantamount to

slide20

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.
slide21

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.
slide22

Data Gaps (Con’t)

  • 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.

slide24

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.
slide25

Data Gaps (Con’t)

  • 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.
slide26

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.
slide27

Concluding Remarks (Con’t)

  • 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.
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