Is bigger safer?

The answer to the question in the title, at least in the context of consolidation and food safety, seems to be "no" according to this article by Anne Kim in Washington Monthly.

The subtitle of the article indicates:

“A consolidated food industry brings you salad and chicken nuggets cheaper—and spreads deadly food-borne pathogens farther.”

And later in the article:

“In other words, the same hyperefficient distribution system that brings you convenient and affordable salad greens and all the chicken nuggets you can eat can just as efficiently deliver E. coli, salmonella, and other dangerous bugs to your plate. Moreover, today’s industrialized food production processes carry other public health risks. ”

The article contains several interesting stories and interviews, but lacks solid evidence supporting the article's main premise that a less consolidated food system would be a safer one.  Yes, there has been consolidation in agriculture.  Yes, when a large firm has a food safety event, it affects more people.  But, what we don't know is whether, overall, a food system with many smaller firms is safer than one with fewer larger firms.  Indeed, the author even acknowledges the following:

“According to the CDC, no evidence suggests that smaller or larger producers have an inherent advantage on food safety. “It has to do more with your practices than your size,” says the CDC’s Matthew Wise. ”

What is not mentioned is that large size can sometimes lower the average (or per unit) cost of investing in certain food safety technologies.  

I touched on this issue in my book, Unnaturally Delicious, when talking to Frank Yiannas, the Vice President of food safety at Walmart.  Here's an excerpt:

“More than 120 million Americans (more than a third of the U.S. population) shop at Walmart every week. Does the sheer scale of the operation make the U.S. food system riskier? If Walmart has an outbreak, multitudes would be sickened. Yiannas replied: “One out of every four dollars spent on food are spent at a Walmart. We can make a big difference. Large organizations like Walmart result in a safer food system.” He points out that when Walmart makes a change, it affects the whole system. Sure, smaller companies might have outbreaks that affect fewer people, but when lots of small companies are having lots of small outbreaks, the problem is more widespread. A downside to small companies, said Yiannas, is that they can’t easily invest in improving the system as a whole. While Walmart often attracts negative attention because of its size and scale (e.g., Do they pay workers fairly? Do they hurt local mom-and-pop businesses?), at least in the world of food safety, their size has significant benefits for its customers, and as I’ll soon discuss, even for non-customers. ”

Yiannas went on to talk about the value of protecting Walmart's brand, the fact that their internal safety standards far exceed government minimums, and he presented evidence that the food safety initiatives that they've implemented have improved safety for the whole country (because of their size). You'll have to read the book for all the details.  

I'll also point out research by Marc Bellemare (here's his piece on the topic in the New York Times) showing a relationship between food safety outbreaks and the prevalence of farmers markets (you know, those places with many small farms and processors).  

I'm not saying that larger IS unilaterally safer, but I am saying there is no solid evidence to support the broad premise behind the Washington Monthly article.  There are a lot things to like about small producers and we ought to think about ways of lowering barriers to entry that are sometimes created by food safety regulations, but doesn't mean we should cast undue fear about our present food system, which is among the safest in the world.  

Food Demand Survey (FooDS) - January 2017

The January 2017 edition of the Food Demand Survey (FooDS) is now out.

After reporting a decline in willingness-to-pay (WTP) for virtually all food products last month, WTP increased for all food products rebounded, with all food products experiencing gains of at least 7%. Steak, deli ham, and chicken wings experienced the largest percent increase in WTP. WTP for both beef products is higher than one year ago, but the opposite was the case for both pork products.

There was a bit of an uptick in reported spending on food away from home, and consumers report expecting higher meat prices in coming weeks relative to last month.  

An ad hoc question was added this month on food waste.  Subjects were shown the following question, which was loosely based on the questions posed by Violeta Stancu and colleagues in this paper published in 2016 in the journal Appetite.  (Note that the order of items was randomized across respondents).  

The most common answer for each item was “hardly any”.

Models were used to estimate the percent of food thrown away each week for each product category. On average, more fresh fruits and vegetables were said to be thrown away than compared to  the other food categories, with 12.7% of this type of food being thrown away. Meat and fish was ranked as the least likely to throw away, with respondents stating only 9.8% of all meat and fish bought was thrown away.

Analysis of demographic data shows (averaged across all food categories), females report about 3 percentage points more food thrown away than men; younger individuals about 10 percentage points more than older consumers; people on SNAP (aka “food stamps”) about 6 percentage points more food is thrown away than by than people not on SNAP; and higher income individuals say they throw away about 5 percentage points more food than lower income individuals.

One of the issues we aim to explore with additional analysis is the extent to which stated food waste behavior is related to risk and time preferences.  

Humpty Dumpty had a great fall

Unless you happen to be relatively low income or one of the few commercial growers, a big change in the grocery store might have gone unnoticed.  Humpty Dumpty didn't exactly fall, but the price of eggs has plunged in recent months.  Here is a recent graph of national retail egg prices (grade A, $/dozen) from the Bureau of Labor Statistics (November 2016 is the last data they report). 

After hovering around $2/dozen for nearly two years, in mid 2015, prices began to rise dramatically, reaching almost $3/dozen in August and September 2015 (a 50% increase).  Then, around the first of 2016, prices began falling.  The fall was even more dramatic than the price increase.  As of November 2016, egg prices were sitting at $1.32/dozen, less than half of what they were a year earlier.

For more perspective, here's the same price data going all the way back to 1980 (this time prices have been adjusted for inflation and are in current dollars).

The above graph illustrates how dramatic the recent swing in egg prices has been in a historical context.  The last time egg prices were as high as the were in September 2015 was 30 years ago in the early 1980s.  And, the last time egg prices were as low as the are today was about 16 years ago in the early 2000s.  

Aside from thinking now  might be a good time to eat an omelet, one might wonder about the causes of recent volatility in egg prices.  While there are no doubt a variety of contributing factors, the main cause has a fairly simple explanation: bird flu.  Back in May 2015, I was writing about the possible impacts of having to kill off almost 40 million hens because of avian influenza.  In fact, looking back on it now, the data show the dramatic impact of the epidemic on the number of table egg laying hens in this country.  

According to USDA data, there were over 313 million hens laying table eggs in December 2014.  Just six months later, there 38.8 million fewer hens, down to 274 million.  Fast forward to today (or at least November 2016, which is the  last reported data), and we're now back up to 309 million hens.  

The change in laying hen inventory over the past couple of years roughly mirrors the changes in egg prices over the same time period, and it is a great example of the economic forces at play.  The bird flu caused a shift in supply (the supply curve shifted up and to the left).  Demand was relatively unchanged, so consumers were left to scramble (sorry I couldn't help myself) over the fewer eggs that remained, bidding up prices.  Because research suggests egg demand is relatively inelastic (i.e., consumers are not very price sensitive when it comes to eggs), a small change in supply can induce much larger proportional change in price.  When the outbreak subsided and producers were able to add back inventory, the same story played out, but this time in reverse.  

It's too soon to tell whether the roller-coaster ride for egg buyers and sellers is over.  

What do school children want to eat?

In the past I have, at times, been somewhat critical of the National School Lunch Program (NSLP) guidelines destined to make school lunches healthier by reducing calories, sodium content, saturated fat, etc.  It's not not that I'm against healthy kids!  Rather, I bristled at the idea of a bunch of nutritionists, policy makers, etc. setting rules and guidelines for how they think kids should eat without considering how the children would respond to the rules.  Nutritional content is but one of the components we care about when eating - don't we also care about how the food tastes, how much it costs, whether it leaves feeling full, whether it is safe to eat, etc. etc.  In short, the guidelines were established with limited understanding of what children want to eat, and as such we knew very little about whether the rules might increase food waste, increase the frequency of home lunches, cause unintended substitution patterns, and so on.  

In an interesting paper in the most recent edition of the American Journal of Agricultural Economics, a team of six researchers sought to do what should have been done prior to implementing nutritional guidelines.  In particular, the authors studied almost 280,000 school lunch choices of about 5,500 elementary age children in a suburban South Carolina school district.  The authors know the precise foods available at each lunch offering, the nutritional characteristics of the foods, which foods the child selected (or whether the child brought a lunch from home - note that lunch menus were published well in advance), and some of the characteristics of the child who made the choice such as their grade, gender, race, and whether they received free or reduced price lunch.

The authors are able to take all this data to estimate demand curves associated with different food offerings.  Their demand models let them answer questions like the following:

• If the sodium content of a pizza offering were lowered, how would that change the number of children who select it?  
• If a low fat pizza is paired with a peanut butter sandwich, which would most people choose?
• If the caloric content were unilaterally lowered on all offerings, how many more children would bring their lunches from home?       

Here's what the authors find:

“If the protein content of Entrée 1 is increased by 3.2grams (one standard deviation of all entree offerings over the course of study), students are, on average, 2.8 percentage points more likely to select that offering. Increasing the fat content of Entrée 1 by one standard deviation (3.9grams) has a similar effect, though smaller in magnitude; students are only 0.2 percentage points more likely to select Entrée 1 because of this increase in its fat content. Increasing the carbohydrate content has the opposite effect; the average probability of choosing Entrée 1 over the alternatives decreases by 3 percentage points if the carbohydrate content increased by 6.8grams (one standard deviation). Thus, the first row of table 3 reveals that students prefer more fat and protein but dislike additional carbohydrates. While the results for sodium are positive, the effect is not statistically significant.”

There are important differences across children:

“While an increase in the fat content of Entrée 1 increases the average probability that a student receiving free lunch will select it, the same increase in fat reduces the likelihood a student who pays full-price will select Entrée 1. The results also suggest that students who pay full-price are more likely to select offerings with more protein than students receiving free or reduced-price lunches (Bonferroni p-value <0.0001), and those who received free lunches are more likely to reject entrées with additional sodium relative to students who pay full-price or students who received reduced-price lunches (Bonferroni p-value =0.0044).”

The authors use their results to suggest how "schools can increase the healthfulness of their students’ meals by replacing unhealthy options with relatively healthy options that are already popular amongst the students."  One things the authors didn't do (but which is possible given their estimates) is to ask: are the children better or worse off (at least as measured by their own preferences revealed by their short run choice behavior) with the new nutritional standards?  Which types of children are now happier or sadder?  Because there is no price variation in the dataset, the authors can't provide a monetary measure of the loss (or gain) in student happiness, but they could covert it to some other unit they measure - such as grams of protein or calories.  

Nonetheless, this is a really interesting study, and it has a number of important findings.  Here's some from the conclusions:

“Nationwide between school year 2010–11 and 2012–13, the number of students receiving free lunches increased while the number of students purchasing full-price lunches decreased, leading to an overall reduction in participation by 3.7% (Government Accounting Office 2014). The results of our analyses suggest that the underlying preferences for offerings with higher levels of fat and lower levels of carbohydrates may be driving the decline in NSLP participation. Full-price participants are most likely to respond to changes in the nutritional content of the offered entrées by opting out of purchasing a school lunch altogether. Our findings have particularly important implications for the NSLP’s stated goal of reducing childhood obesity as they indicate that children are likely to reject those entrées that are most compatible with this particular aim. However, our results do suggest that the future guidelines reducing sodium levels may not trigger additional participation declines.”

2016 Review

2016 has been a busy year.  I've had the pleasure to serve as president of the Agricultural and Applied Economics Association (AAEA), continue the Food Demand Survey (FooDS), travel to Australia, Alabama, Montana, California, DC, Massachusetts, Minnesota, Georgia, and New York just to name a few, advise several graduate students who graduated, keep up a regular stream of research with 11 articles published in peer reviewed journals (and 10 more already forthcoming for 2017), publish articles in the Wall Street Journal and New York Times, and give several radio and podcast interviews (including on one of my favorites - Econ Talk). My latest book Unnaturally Delicious was also released this year. 

Here on the blog, there were about 150 posts this year garnering about 82,000 page views in 2016.  Here are a few of the most viewed posts of the year.

• Real world demand curves (in which I take issue with the claim in a Freakonomics podcasts that economists have never observed a "real world" demand curve)
• New York Times on GMOs (critiques an article by Danny Hakim in the New York Times on effects of GMOs) 
• Country of Origin Labeling and cattle prices (this post analyzes the claim that the repeal of mandatory country of origin labeling caused a big drop in cattle prices)
• 11 things to know about GMOs (points to a short OSU facts sheet I wrote with Eric and Cheryl Devuyst answering some commonly asked questions about GMOs)
• What do cows want? (this post applies the economic concept of "revealed preferences" to the study of animal welfare)
• Changes in meat consumption (proves some economic explanations for recent changes in meat consumption)
• New research on the Berkeley soda tax (this post discusses some research on the effects of the soda tax in Berkeley suggesting consumption changes may not have resulted from the effects of a price change per se; see also this previous post)
• False beliefs about food stamps (in this post, I covered a paper by Craig Gundersen which debunks several widely held beliefs about the effects of SNAP)
• What is going on in your brain? (here I review the findings of a paper I co-authored on neuro-economics and food choice forthcoming in the Journal of Economic Behavior and Organization)
• Trade matters (highlights the importance of trade for U.S. agriculture)
• Evolution of American agriculture (provides statistics on changes in US agriculture over time and introduces a paper about the USDA I wrote for the Mercatus center)

Thanks for tuning in!