Factors Affecting Beef Demand

Glynn Tonsor, Ted Schroeder, and I recent completed a report for the Cattlemen's Beef Board on the factors influencing beef demand.  

One of the key factors that emerges from the analysis of the USDA price/quantity data is that beef demand appears to have become less sensitive to price-related factors.  In econ-lingo, beef demand has become more inelastic.  Moreover, changes in pork and poultry prices have fairly small impacts on beef demand.

As a result, we focused on several potential non-price demand determinants.  We find that emerging stories about climate change have adversely affected beef demand, but at the same time increased media focus on taste and flavor have more than compensated for those effects, pulling up demand since 2012.  

We also look at trends from the Food Demand Survey (FooDS) and how they relate to consumers' preferences and beliefs.  Here are some graphs on the relationship between a variety of factors and steak demand.

Here is the same but for ground beef demand.

Increases in income clearly increase steak demand, but ground beef is demanded similarly by all income categories.  Some of the biggest determinants of beef demand are "food values".  Here's what we have to say about how to interpret those results.

“While it may not be initially obvious, results in figure 4.5 [showing the relationship between steak demand and food values] can be interpreted as providing evidence about people’s beliefs about (or perceptions of) steak. Suppose an individual highly values taste. Figure 4.5 shows that such an individual will tend to choose more steak. As a result, it must be that steak is perceived to be highly tasty. By this line of reasoning, figure 4.5 suggests that consumers, on average, perceive steak to be convenient, tasty, attractive, and novel but they also perceive steak to be poor for animal welfare, nutrition, and environment while also being expensive. ”

There's a lot more in the report.

Disruptive Trends in Food and Agriculture

In the past couple weeks, I've had several opportunities to engage with some forward looking farmers and agribusiness executives, and a common theme seems to have emerged around many of the conversations: what are the issues or food and agricultural technologies on the horizon that could be potentially disruptive for the current incumbents?  

1) Block chain technology.  This isn't bitcoin, but rather the underlying technology that facilitates bitcoin trades, which could be applied to many other industries.  This Reuters article from earlier in the week, for example, indicates, "A cargo of U.S. soybeans shipped to China has become the first fully-fledged agricultural trade conducted using blockchain."  The thought is that blockchain technology might prove to be a mechanism that can more rapidly disseminate many types of information about trades (the Reuters article mentions the "sales contract, letter of credit and certificates") more widely and rapidly.  Big players like Walmart and IBM are also talking about using blockchain to improve traceability and food safety.

2) Plant-based and cellular-based protein.  This is a topic I've written about many times in the past (e.g., here or here).  What's changed is the high level of investment flowing into this space, including by companies like Tyson and Cargill.  Moreover, there are now products from companies like Impossible Foods, Beyond Meat, JUST, and others that are actually in the market.  If sales ramp up, what are the impacts on producers of current animal feeds (primarily corn and soy)?  What are the new agricultural inputs for these plant-based meat/egg/dairy alternatives? 

3) CRISPR.  Again, the basic science isn't necessarily new,  but there are new applications coming on board (non-browning apples, hornless Holsteins, etc.) and potential changes in the regulatory landscape that could accelerate (or decelerate) adoption and consumer acceptance.

4) Agricultural analytics.  This includes precision agriculture, sensing, big data, drones, modeling, etc.  Yes, these have been around for a while and there have been many discussions about data ownership and rights, but there is a sense that the data and technology have moved to a point where some adopters may be able to start gaining a competitive advantage. 

5) Online food buying.  Will Amazon do to the food supply chain what they've done in other industries?  Walmart is also making big moves into this space.  What are the implications for traceability, tracking, and vertical market coordination?

6) Trade.  Agricultural trade has a big impact on US agriculture, and it appears there may be changes in trade policy on the horizon. 

What have I missed?

Don't Want to Eat Pink Slime? Would You Even Know?

It's hard to believe it's been almost five years since the finely textured beef (aka "pink slime")  scandal broke.  To briefly re-cap, by 2012 it had become an industry standard to include finely textured beef with other beef trimmings to make ground beef.  The process enabled food processors to add value, cut down on waste, and increased the leanness of ground beef in an affordable manner.  But, a series of news stories broke, which caused public backlash against the process, and ultimately led to the closure of several plants that produced finely textured beef.  In 2013, I wrote about my visit to BPI, one of the largest producers of lean finely textured beef (this summer, ABC settled a multi-million dollar lawsuit brought by BPI regarding ABC's coverage of the issue).  I devoted a whole chapter of my 2016 book, Unnaturally Delicious, to the issue.  I'll also note, for some aspiring journalist out there,  that I can imagine a highly compelling a book-length treatment of the saga.

Back to the heart of the story, must of the public backlash presumably came about because the public was worried about taste or safety of ground beef made with finely textured beef.  In the monthly Food Demand Survey (FooDS), we've been running for almost five years, we ask about perceptions of the safety of "pink slime" and of "lean finely textured beef".  The data suggests neither are top safety concerns.  The most common answer is that people are "neither concerned nor unconcerned" about the safety of these issues (for lean finely textured beef, the average response is actually in the direction of "somewhat unconcerned").

Well, what about taste?  People may think "pink slime" tastes bad, but what would happen in a blind taste test?  Along with several of my former econ and meat science colleagues at Oklahoma State University (Molly Depue, Morgan Neilson, Gretchen Mafi, Bailey Norwood, Ranjith Ramanathan, and Deb VanOverbek), we conducted a study to find out.  The results were just published in PLoS ONE.  Here's what we found.

“Over 200 untrained subjects participated in a sensory analysis in which they tasted one ground beef sample with no finely textured beef, another with 15% finely textured beef (by weight), and another with more than 15%. Beef with 15% finely textured beef has an improved juiciness (p < 0.01) and tenderness (p < 0.01) quality. However, subjects rate the flavor-liking and overall likeability the same regardless of the finely textured beef content. Moreover, when the three beef types are consumed as part of a slider (small hamburger), subjects are indifferent to the level of finely textured beef.”

So, a burger made with 15% finely textured beef is as tasty or tastier than a burger without finely textured beef.  If people knew this, would it have changed their reaction to the Jamie Oliver show or the 2012 ABC News stories?   

How Innovative are Food Sellers?

I tend to think of the food and grocery business as hyper-competitive with many new product introductions and failures.  For example, data from the USDA ERS suggests roughly 20,000 new food and beverage products come on the market each year.  That seems like a lot.  But, compared to what?

I ran across a presentation that Austan Goolsbee and Pete Klenow recently gave at the ASSA conference in Philadelphia.  They use online price and quantity data collected by Adobe Analytics.  Their main objective was to construct price indices to compare against the official government consumer price index measures.  Those results are interesting, but I was intrigued by some of their other findings regarding new product introductions and exits.

Below are two slides they created that challenged my prior beliefs about the food and beverage category.  

If I'm understanding this correctly (and I may not be), I think the data below suggests that 69.8% of the total sales in the apparel category come from newly entering products.  Moreover, 29.5% of total sales in the the apparel category come from products that are soon to exist the market.  Other categories with high levels of "churn" and new product introductions are "other goods and services", ICT (which I believe is information and communications technology), and recreational goods.  For food and beverages, "only" 19.5% of sales are by new entrants, and 8.5% of sales are by soon-to-be-gone products. By this measure, the food sector seems less dynamic than others. 

Their next slide conveys the same information in a different way - by measuring the percent growth in sales-weighted variety.  By this measure, variety in food and beverages has only grown by an average of 1.2% per year, and the only category with a smaller growth in variety is medicines and medical supplies. By contrast, there is an average 18.3% growth in vareity in the aparel cateogory.  

One downside to these data is that they only reflect online sales.  Perhaps there is more "churn" and new product introduction in brick-and-mortar grocery stores than online?  Either way, this is interesting food for thought. 

Taste elasticities?

Economists are accustomed to reporting price elasticities, which indicate the percentage reduction in quantity of a product that will be demanded when the price of a product increases by 1%.  The focus on price elasticities might suggest that changes in prices are more important demand determinants than changes in other variables.  Another possibility is that prices are observable.  That is, we focus on price changes because we can see and measure them.

This new paper, published in Managerial and Decision Economics with Trey Malone, suggests other factors that are highly influential demand determinants.  In particular, Trey designed a survey to measure preferences (and demand) for different beer brands at various prices.  He asked people to answer choice questions like the one below.

The only difference across the choice questions were the prices assigned to brands.  It is straightforward to calculate the typical own-price demand elasticities from these data - one simply has to observe how the frequency with which a brand is chosen changes when its price changes.  

In addition to these standard questions, Trey and I also asked questions about consumer perceptions of each brand.  Here is a partial screen shot of the question we asked on taste (a similar question was asked about familiarity).  

Merging these data with the choice data, then, allows us to see how a change in perceived taste (or familiarity) affects choice.  

One of the key challenges with this sort of analysis is that taste/familiarity perceptions might be endogenously determined with other variables, such that we don't really know whether we're measuring mere correlations or the causal impact of taste changes on choice.  Our paper suggests a way to deal with this challenge.  In short, it involves using perceptions for other brands as instruments for perceptions of another brand.  I won't go into the details here, but we show the approach has a substantive effect on the results.  

So, what did we find?  Not surprisingly, taste and familiarity matter.  But by how much?  Here is a table of elasticities (not price elasticities, mind you, but taste elasticities). 

We write:

“Changes in perceived taste matter much more for the craft options (Marshall and Oskar Blues) than do changes in the perceived taste of the premium and macro options. For example, a 1% increase in the perceived taste of the Oskar Blues option leads to a 6.753% increase in the quantity demanded of that beer, whereas the same increase in the perceived taste of Corona leads to a 4.891% increase in its quantity demanded. Similar to the own-taste elasticities, relative to the familiarity elasticities, cross-taste elasticities are much larger. According to the model estimated via the control function approach, the perceived taste of Samuel Adams is the option most dependent on the perceived taste of the other beers. Specifically, the 1% increase in Corona’s perceived taste would also lead to a 1.339% reduction in the probability a Samuel Adams was selected, and the 1% increase in Oskar Blues’ perceived taste would create a corresponding 1.991% reduction in Samuel Adams’ quantity demanded.”

Another result that probably won't be too surprising to many craft beer drinkers:

“Once we control for endogeneity, our estimates indicate that some participants actually prefer an unfamiliar beer (i.e., they are variety seekers)”