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Food Demand Survey (FooDS) Finale - at least for now

Five years ago in May 2013, I put out the first issue of the Food Demand Survey (FooDS).  Every month since that time, a survey of over 1,000 food consumers (a different 1,000 each month), has been conducted where we've tracked concerns, attitudes, and preferences for various food issues over time.  This has been a really fun project.  Alas, all good things must come to an end and the May 2018 edition of FooDS will be the last - at least in its current incarnation.  

Here I wanted to highlight some of the findings we've generated and provide some graphs showing the trends we've observed over the past five years (every issue of FooDS and all the underlying data is available here).  At the end, I'll give a few "thanks" and give insights on where the project may be heading next.  

Some highlights.

Now for some trends (note: each of the graphs below shows data from at least 1,000 consumers surveyed each month for 5 years for a total of more than 60,000 observations).  Because I've discussed these results many times in the past, I'm going to let these graphs "stand on their own" without interpretation or description of how the data are collected or analyzed.

FooDS_1.JPG
 note: "average" is the average of about 16 other issues tracked in the survey

note: "average" is the average of about 16 other issues tracked in the survey

 note: "average" is the average of about 16 other issues tracked in the survey

note: "average" is the average of about 16 other issues tracked in the survey

 Food Values over Time

Food Values over Time

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Finally, I want to say thanks to Susan Murray who did the heavy lifting every month, Bailey Norwood who helped me conceptualize the project and kept it running for the last year, Glynn Tonsor who provided intellectual capital over the course of the project, and many graduate students who provided great ideas and analysis.  Early on, funding support for the project came from the Willard Sparks Endowed Chair.  Later, the Division of Agriculture and Natural Resources at Oklahoma State pitched in.  For the past several years, funding support came from a USDA-AFRI-NIFA grant.  I've had numerous conversations with Bailey (at Oklahoma State), Glynn (at Kansas State), and Trey (at Michigan State) about the future of the project, where it might "reside", and how it should change to be even more informative.  All the details are yet to be worked out, but I think there is a good chance FooDS will re-emerge in the next several months with a new "home" and focus.  

Blockchain - from Bitcoin to Bacon

It was probably about a year ago I started hearing some rumblings about blockchain technology be of use in tracking agricultural products.  I was familiar with bitcoin so I had a vague sense of how the technology could be used in a traceability system.  But, until a few months ago, it wasn't so obvious to me how it could also be used to increase transparency and even help with contract fulfillment.

Fortunately, the latest issue of Meatingplace Magazine has a great article by Julie Larson Bricher that provides an easy to read primer on blockchain technology - what it is and how it's starting to be used in the food industry.  

Here's one excerpt:

So, what is blockchain? It’s a type of digital distributed leger, or shared database, in which transactions from multiple computers are security recorded into “blocks” of verified data entries in real time. These time-stamped blocks of data are linked together in a sequential chain, which means that the leger cannot be modified or changed.

The distinctive feature of the blockchain is its assurance of data integrity, which makes the records trustworthy – and this is what makes it so attractive to food supply chain companies. In a blockchain, the data can be trusted because all members in a network must agree to each new record is added to the ledger …

Numerous examples of the blockchain being tested in the food supply chain are given, including Cargill's traceable turkeys (where people could text or enter an on-package code to "access the farm's location ..., view the family farm story, see photos and read a message from the farmer."  Other firms mentioned as testing the technology include Tyson, Walmart, IBM, and Carrefour.  

To imagine how the technology might ultimately influence the industry, the piece included the following graphic that showed the types of information that could be included in a blockchain for poultry.  

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I'll end with this final quote on how blockchain could facilitate contracts:

Blockchain also enables the use of “smart contracts,’ which means that previously agreed terms, conditions or business protocols are built into the digital ledger and automatically triggered and enforced as the terms of agreement are met... By programming contract conditions and terms into the blockchain, contracts are executed by the system itself and not middlemen, which translates into time- and cost-saving business transaction efficiencies.

It will be interesting to see how this technology transforms the food supply chain and what information we consumers may have one day simply by scanning a bar code at the grocery store.

The New GMO Labeling Law

Last week, the USDA finally released its proposed rule outlining the ways in which it may implement the National Bioengineered Food Disclosure Standard (NBFDS) (i.e., the a mandatory labeling law for GMOs) that was passed by the US Congress and signed into law back in the summer of 2016.  At the point, this is still a proposed rule: public comments are still being accepted until July 3, 2018.  

As I wrote at the time of its passage, the mandatory labeling bill was not particularly popular with the "anti" or "pro" GMO crowds.  I won't rehash all the issues involved or re-cover all the arguments for and against mandatory labeling (as an aside, I am amazed at how often I still see people citing my result on consumer preferences for DNA labels; I suppose that's a least one mark of success when people unknowingly cite your own research results to you as something you need to know!).  Here, I want to point out a few things that were news (at least to me) in the proposed rule.

  • One of the controversial facets of the original bill was that it allowed for disclosure of genetically engineered ingredients via a QR code (this is an issue we have researched - e.g., see here).  In addition to the QR code or a text disclosure, it appears companies might be able to also use one of several different types of labels (I am not aware of any publicly available research on consumer perception of these labels).  Here are some of the examples proposed:
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  • It also appears that a food may only have to be labeled if it actually contains genetically engineered (or shall i now say "bioengineered") ingredients that contain recombinant DNA.  Why does this matter?
    • Sugar and oil don't contain DNA.  Tests for recominant DNA are likely to come back negative even if applied to oil from derived from bioengineered corn or soy or if applied to sugar from bioengineered sugar beets.  As such, foods using oil or sugar derived from GE crops  may not ultimately be subject to the mandatory disclosure.
    • Other biotechnologies, such as gene editing, don't utilize recombinant DNA, and as such may not ultimately fall under this mandatory labeling law.
  • What will be the tolerances or thresholds that would trigger mandatory labeling?  The proposed rule didn't say for sure but offered several options:
    • A) disclosure is required if more than 5% of any ingredient (by weight) is bioengineered; 
    • B) disclosure is required if more than 0.9% of any ingredient (by weight) is bioengineered; 
    • C) disclosure is required if more than 5% of the entire product (by weight) is bioengineered.
    • It should be noted that these different thresholds are likely to imply VERY different costs of compliance; a 0.9% threshold is likely to be more than 5x more costly than a 5% threshold, and individual ingredient thresholds will be much more costly than total product thresholds.  
  • There are many exceptions, for examples for small manufacturer, for certain enzymes,  and for animal products derived from animals fed bioengineered feed.

Pork: The Other Red Meat

Remember the long running campaign by the Pork Board?

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The campaign pitching pork as the other white meat made sense at a time when there was rising concern about fat content and red meat consumption and increased competition from chicken.  But, times have changed.

One of the changes has come about from scientific developments.  As it turns out, pork color is a good indicator of eating quality, and in blind taste tests, consumers prefer redder pork to whiter pork.  Do consumers know this?  Could a quality labeling system help coordinate the pork supply chain and better align production with consumers' eating expectations?

These were the questions that led to this paper just released by the journal Food Policy that I co-authored with Glynn Tonsor, Ted Schroeder, and Dermot Hayes with funding by the National Pork Board (a longer report of the results is here).

We surveyed about 2,000 consumers for the analysis reported in the Food Policy paper.  We were mainly interested in how consumers' choices between pork (and other meat) products varied with the color of the pork and whether and which kinds of labels were present.  Consumers were randomly assigned to a control (with no labels) or one of several treatment groups that utilized different labeling systems.  Below shows a particular choice question used in the various treatments.  

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We use the choices consumers made in these treatments to back out consumers' willingness-to-pay, but even more importantly, the probability a consumer buys any type of pork and the expected revenue from pork.  For the economists out there, I'll note that we also have some methodological innovation.  Rather than just looking at the probability of buying a type of pork at a given set of prices, we also invert the equations to look at the equilibrium price of pork at a given quantity of different types of pork (this is important because in the short run, pork producers can't easily produce a larger amount of higher quality pork).

So, what did we find?

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We find: 

In the absence of a cue in the “no labels” control, on average, participants do not differentiate among the three quality levels [or pork colors]. There is no significant difference in average WTP [willingness-to-pay] for the three different colored chops. This is consistent with industry interest in adding quality labels to facilitate further separation of pork quality by consumers. The introduction of a single Prime label for the highest quality chop in Treatment 1 results in a significant increase in the WTP for the chop that would carry the highest quality grade; however, there is a significant reduction in WTP for the lower quality chops that did not carry labels in this treatment.  ... When all pork products have grade labels, there is a significant premium for higher vs. lower quality pork and total pork sales rise, as do expected revenues. This can be seen in [the figure] as the mean WTP estimates for all pork qualities lie above those in the control condition with no labels.

We go on to show there is significant heterogeneity in consumer preferences.  We find that 28% to 40%, depending on the labeling condition, of consumers prefer white pork to red pork.  

From the conclusions: 

The choice experiment data analysis suggests that a USDA grade using Prime, Choice, and Select or Good, Better, Best labels would be most likely to increase expected pork revenue and the probability of purchasing pork. Additional important opportunities are present within this strategy. Foremost is that even with quality labels on the pork chops, a significant fraction of consumers preferred lower quality than Prime even when the three quality products were priced the same. Such consumers either do not understand the quality grade rankings of Prime, Choice, and Select (though results were similar for Best, Better, Good, which should be less prone to confusion), or this group of consumers were ignoring the quality grade labels and relying on product color to influence their choices. A possible response would be to segment consumers and to use the grading system only on those consumers who prefer red chops. Segmentation could be done by exploring preferences across states, institutions, income categories, ethnicity, and by export market. Despite the possibility for segmentation, however, we show, that if all qualities are present, only labeling the highest quality is likely to reduce total pork sales and revenue

As this piece in the Federal Register indicates, the USDA Agricultural Marketing Service is seeking public comment on the usefulness of such a labeling system.  Maybe one day in the future you will see new pork quality grade labels in the grocery store.