Blog

Food Sector Linkages

Parke Wilde at Tufts University mentioned a new project he spearheaded in a recent blog post.  Parke and colleagues have crated a tool that lets the user visualize the input-output data provided by the Bureau of Economic Analysis.   

I've looked at these sorts of tables before, but I've always found it is a bit hard to distill insights from them.  This tool provides an easy way to ​visualize the flows between different food sectors.  Great idea!  

Below is a video of Parke describing the tool:​

The Food Demand Survey (FooDS)

For a number of years, I've thought about creating a monthly survey to track consumer knowledge, concerns, and preferences for various food-related issues.  After no small amount of effort, and thanks to the funding from the Willard Sparks Endowment and DASNR and the assistance of Susan Murray, that vision has now become a reality.  

The inaugural issue is now up online, and we will to follow with regular monthly releases.

Of course, this initial issue can't report changes , but that information will come.

For those who might be interested, the purpose of the project is to provide timely information on:

  • Indices of consumer sentiments on (or beliefs about) the safety, quality, and price of food consumed at home and away from home.
  • Indices of consumers' anticipated demand for various meat products consumed at home and away from home.
  • Awareness of food-related issues or events that could affect demand.
  • Emerging policy or marketing issues.

It is envisioned that such data could be used by analysts to:

  • Construct and analyze trends in beliefs, demand, and awareness
  • Forecast changes in consumption
  • Compliment (i.e., merge with) existing sources of secondary data (e.g., USDA disappearance or scanner data) in food demand analysis

Some of the motivations for starting the project include the following.

  • Although scanner data is available to analyze immediate past behaviors, it is inherently backward-looking.  A consumer survey can be devised to be forward looking, potentially providing better forecasts.  Moreover, analyzing demand using scanner data is tricky due to issues of supply shifts, endogeneity, unobserved quality variation, promotions, etc that can be overcome with a well-designed survey.
  • Current meat demand indices are aggregate, quarterly, assume a constant demand elasticity, and attribute all price/quantity changes to shifts in demand; a survey is more rapid and can better isolate demand-side issues.
  • Existing surveys of consumers (i.e., panel diaries or home scanning data) only focuses on at-home food consumption; away from home food consumption now accounts for just under half of all food expenditures.
  • Although some marketing companies routinely track eating intentions and awareness of food issues, the data is proprietary and is not publically released in any uniform fashion.  Moreover, their survey questions are not always designed using state-of-the-art techniques in consumer research.


  

 

Why I'm an Economist and Not a Psychologist

​This quote from Michael Moss's book Salt, Sugar, Fat accurately sums up one of the main reasons I see economic analysis as preferable to psychological explanations (and it is one of the main reasons I often prefer non-hypothetical economic experiments to hypothetical surveys).

Pg. 150: “There is not a lot to be gained from asking people why they like something because they don’t bloody know.”  - Fancis McGlone, former Unilever scientist

Oxford Handbook of the Economics of Food Consumption and Policy

Good news.  The Oxford Handbook of the Economics of Food Consumption and Policy, which I co-edited, is now out in electronic version, and each chapter can be individually downloaded.​

This is a text designed for graduate-students and faculty interested in learning the "state of the art" in the methods and analysis of the food consumer.​

Click here to access the electronic version.​

A Vote-Buy Behavior Gap

Glynn Tonsor at Kansas State University has created a great resource for the readers of Feedstuff magazine.  Glynn writes a periodic column where he takes recent research from the academic literature and boils it down to a layman's perspective.  I was pleased to see he featured some work by Kate Brooks at the University of Nebraska and myself in his most recent column.  Here were the implications Glynn took from our research:

Implications: This study highlights the potential pitfalls of inferring public preferences from private choices. In this particular study private choices suggested stronger preferences than were reflected in public preferences for a ban restricting production practice options. Conversely, in other settings the opposite behavioral differences are observed. One of the clearest examples is the approximate 5% market share held by cage-free eggs (revealing that the majority of egg consumers are not willing to pay cage-free market premiums) and majority of residents expressing support in ballot settings for bans on laying hen cages. There are several reasons researchers may find the same individual to behave differently when making decisions as a food purchasing consumer than when making decisions as a voting resident. Identification of these reasons and the economic implications of these behavioral patterns are an area in need of additional research as there is a growing list of parallel examples that present complex dilemmas for livestock producers.