Economics of Food Waste

There seems to be a lot of angst these days about food waste.  Last month, National Geographic focused a whole issue on the topic.  While there has been a fair amount of academic research on the topic, there has been comparatively little on the economics of food waste.  Brenna Ellison from the University of Illinois and I just finished up a new paper to help fill that void.

Here's the core motivation.

“Despite growing concern about food waste, there is no consensus on the causes of the phenomenon or solutions to reduce waste. In fact, many analyses of food waste seem to conceptualize food waste as a mistake or inefficiency, and in some popular writing a sinful behavior, rather than an economic phenomenon that arises from preferences, incentives, and constraints. In reality consumers and producers have time and other resource constraints which implies that it simply will not be worth it to rescue ever last morsel of food in every instance, nor should it be expected that consumers with different opportunity costs of time or risk preferences will arrive at the same decisions on whether to discard food”

So, what do we do?

First, we create a conceptual model based on Becker's model of household production to show that waste is indeed "rational" and responds to various economic incentives like time constraints, wages, and prices.  

We use some of these insights to design a couple empirical studies.  One problem is that it is really tough to measure waste.  And, people aren't likely to be very accurate at telling you, on a survey, how much food they waste.  Thus, we got a bit creative and came up with a couple vignette designs that focused on very specific situations.  

In the first study, respondents were shown the following verbiage.  The variables that were experimentally varied across people are in brackets (each person only saw one version).  

“Imagine this evening you go to the refrigerator to pour a glass of milk. While taking out the carton of milk, which is [one quarter; three quarters] full, you notice that it is one day past the expiration date. You open the carton and the milk smells [fine; slightly sour]. [There is another unopened carton of milk in your refrigerator that has not expired; no statement about replacement]. Assuming the price of a half-gallon carton of milk at stores in your area is [$2.50; $5.00], what would you do?”

More than 1,000 people responded to versions of this question with either "pour the expired milk down the drain" or "go ahead and drink the expired milk."  

Overall, depending on the vignette seen, the percentage of people throwing milk down the drain ranged from 41% to 86%.

Here are how the decision to waste varied with changes in the vignette variables.

The only change that had much impact on food waste was food safety concern.  The percentage of people who said they'd discard the milk fell by 38.5 percentage points, on average, when the milk smelled fine vs. sour.  The paper also reports how these results vary across people with different demographics like age income, etc.

We conducted a separate study (with another 1,000 people) where we changed the context from milk to a meal left-over.  Each person was randomly assigned to a group (or vignette), where they saw the following (experimentally manipulated variables are in brackets).

“Imagine you just finished eating dinner [at home; out at a restaurant]. The meal cost about [$8; $25] per person. You’re full, but there is still food left on the table – enough for [a whole; half a] lunch tomorrow. Assuming you [don’t; already] have meals planned for lunch and dinner tomorrow, what would you do?”

People had two response options: “Throw away the remaining dinner” or “Save the leftovers to eat tomorrow”.

Across all the vignettes, the percent throwing away the remaining dinner ranged from 7.1% to 19.5%.  

Here are how the results varied with changes in the experimental variables.

Meal cost had the biggest effect.  Eating a meal that cost $25/person instead of one that cost only $8/person reduced the percentage of people discarding the meal by an average of 5.8 percentage points.  People were also less likely to throw away home cooked meals than restaurant meals.  

There's a lot more in the paper if you're interested.

Food Demand Survey (FooDS) - Third Year Review

It's hard to believe, but the Food Demand Survey (FooDS) has been conducted every month now for three years.  I've been fortunate to have Susan Murray working with me to make it happen every month and to have funding support from DASNR, the Willard Sparks Endowment, and the USDA NIFA competitive grant program, AFRI.  

We've pulled together a summary of trends in key survey question we've asked for the past three years.

Overall, willingness-to-pay (WTP) for most meat products has been down this year compared to last year, partly reflecting (I suspect) lower overall meat prices.  Here are relative changes in WTP where May 2013=100 for steak, chicken breast, and pork chops.    

Steak WTP

Chicken breast WTP

Pork chop WTP

We also ask people their expectations about increases in prices of beef, pork, and chicken. Here is the trend in future price expectations for beef.  Except for last month, expectations have been lower this year compared to last  (consistent with the fact that retail prices have declined).

Expectations of Future Beef Price Increases

Here is the trend in awareness and concern for the four top concern issues tracked in our survey (May 2015=100).  There was a big spike in awareness of E. Coli in the news in November and December, which coincided with the Chipotle outbreak.  Pay attention to the units on the vertical axes.  As might be expected, awareness of these four items in the news is much more volatile than is concern.

Awareness in the News

Concern

Finally, here are the % of respondents each month who say they are on food stamps, are vegetarian, or say they had food poisoning in the past month.  For comparison purposes, note that USDA data suggests 22.3 million households are on food stamps, and the Census Bureau indicates there are roughly 116 million households in the US, which implies about 19% of households are on food stamps.  

If you want to compare to previous years, check out the First Year and Second Year reviews.

Hand seeding innovation

I my conversation with agronomy professor Bill Raun while doing interviews for Unnaturally Delicious, he informed me of a major agricultural problem which I'd never before heard about.

“He estimates that 60 percent of maize in the developing world is planted by hand. That’s more than seventy one million acres on Earth where poor, often subsistence, farmers use long sticks to poke a hole in the ground and drop in three or four kernels of corn before moving a foot or so and repeating the process again—and again and again. This is imprecise, backbreaking work, and potentially deadly.

According to Raun, many of these rural farmers have access to high-quality hybrid seeds, but the seeds have been pretreated with fungicides and insecticides. The treatments protect the vulnerable seedlings from insects and disease, but chemically treated seeds weren’t meant to be routinely handled by the farmer.”

Here are a few photos he took of hand-seeding in action.

Fortunately, he's got a potential technological solution (see also his web page)

“Raun again teamed up with engineers to create what he calls a GreenSeeder—a handheld device that can be loaded with seed and reliably deliver a single seed with each poke in the ground. Raun optimistically estimates the device could boost yields by 25 percent, resulting in $2 billion of extra revenue to the developing world if farmers abandoned their wooden sticks in favor of his mechanical poles.”

Precision Agriculture

Chapters 6 and 8 in Unnaturally Delicious were two of the most enjoyable to write because I got to learn about some of the amazing things going on in my own town and university.  

Chapter 6 focuses on the story of David Waits, who created SST Software, a company focused on data management solutions for farmers, particularly geo-spatial information.  While most farmers are today accustomed to seeing colorful yield maps showing which areas of the field are providing more and less grain, most food consumers have no idea of how much information and complexity goes into running a modern farm.

They key for farmers is to combine yield information with spatially-lined information on varieties planted, soil characteristics, etc. so that more precise decisions can made, for example, on fertilizer applications (to help prevent nitrogen runoff and increase yields).  

I write:

“Today SST Software is one of the leading agricultural suppliers of geographic decision support tools in the world. SST houses data on more than 100 million acres of farmland in twenty-three countries from Australia to Africa. At the heart of the operation is software that consists of relational databases that link information about the use of farm inputs to geographic identifiers and to site-specific information about soils, moisture, and much more. Some farmers can use SST’s software directly themselves, but given the size and complexity of today’s farms, the rapid pace of technological change, and the expertise needed in entomology, agronomy, and economics, many farmers rely on consultants to help make management decisions. As a result, SST’s biggest clients are crop consulting companies like Crop Quest and Servi-Tech and seed and chemical suppliers like Monsanto and Helena Chemical. These companies often work with farmers to send to SST information on soil samples, pesticide and fertilizer applications, yields, insect scouting reports, and seed varieties planted. The companies use these data to make site-specific fertilizer or planting recommendations. For example, based on his company’s agronomic models, an adviser might use SST software to identify which areas of a field should receive which kinds of fertilizer and in which amounts—a recommendation that can be sent electronically to a variable rate spreader that communicates with satellites to determine when and where to apply which mix of fertilizers. Given the high cost of seed, new variable-rate planters are also coming on the market. A thumb drive loaded with a recommendation from SST can be plugged into a planter, which can plant two different corn hybrids at different seeding rates and at different depths throughout the field. SST doesn’t make recommendations; it provides the mechanism for translating an agronomist’s recommendation into an action plan.”

I had the chance to play around with their software a bit myself, and it is truly amazing how many possible decisions a modern commercial farmer today has to make - something many critics of modern agriculture scarcely comprehend.  Here's what I had to say after talking about different decisions on seed choice and fertilizer choice:

“Each field might have 100,000 possible items of information linked to it in a given year, and that doesn’t begin to count the combinations of management decisions the farmer might have to make when mixing a particular type of seed with a particular soil type and a particular fungicide.”

Later in Chapter 8, I also talked about Bill Raun, an agronomy professor at Oklahoma State University (more on him later) who is also working on precision agriculture applications.  Along with some engineers he created the GreenSeeker, which is:

“is a handheld device that senses the color of the plants’ leaves and, along with other information—such as the date the crop was planted—provides a recommendation of how much nitrogen to apply to satisfy the plants’ needs. The sensors can also be placed atop a tractor or fertilizer applicator so that, as a farmer drives through a corn or wheat field, the amount of nitrogen applied changes in response to what the GreenSeeker is “seeing.” Today several companies make the GreenSeeker and related technologies commercially available to farmers all over the world. Adoption has been limited by the cost of the technology, lack of precision, and the low cost of alternatives, like simply applying a uniform rate of nitrogen throughout portions of the field before planting.”

Bill has a lot of amazing pictures at his website, here is one with several GreenSeeker's attached to a fertilizer applicator.

How bad, really, is meat eating?

Last week, Scientific American published a piece on how to get people to eat less meat.  Apparently, the science is settled and we now only need to come up  with the right "messages." 

There are an awful lot of apocalyptic pronouncements about the adverse effects of meat eating on the environment.  In a widely viewed TED talk, Mark Bittman likens meat production to a nuclear explosion and says it is leading to a "holocaust of a different kind," pointing directly to impacts on climate change.  As another example, Bill Maher, comedian and host of an HBO talk show, has written, “But when it comes to bad for the environment, nothing—literally—compares with eating meat. . . . If you care about the planet, it’s actually better to eat a salad in a Hummer than a cheeseburger in a Prius.”   I could, quite literally, provide dozens of these sorts of quotes from well known journals, writers, actors, etc, but I think you get the point.  The overall message is pretty clear: we should become increasingly more vegetarian.  

Let's take a look at one of the outcomes people are most worried about and where externality is relatively clear: climate change.   I went to the EPA's calculations, and surmise the following carbon equivalent impacts for the US attributable to beef cattle, swine, and poultry production during the year 2014 (MMT is million metric tons):

• beef cattle: 116.7 MMT C02 (from digestion) + 4 MMT C02 (from waste management) = 119.7 MMT C02;
• swine: 1 MMT C02 (from digestion) + 22.4 MMT C02 (from waste management) = 23.4 MMT C02; and
• poultry: 0 MMT C02 (from digestion) + 3.2 MMT C02 (from waste management) = 3.2 MMT C02.

Elsewhere, the EPA suggests using using a social cost of carbon of $36/metric ton of C02 (assuming a discount rate of 3%) for cost benefit analysis and rule making.  Multiplying the C02 impacts above by the price tag of $36 implies the following total carbon costs in 2014.

• beef cattle: $4.3 billion;
• swine: $842 million; and
• poultry: $115 million.

That seem like a lot, but keep in mind that we also eat a lot of meat.  Data from the USDA suggests that in 2014, farmers/ranchers in the US produced 24.32 billion pounds of beef, 22.86 billion lbs of pork, and 44.98 billion lbs of poultry.  Putting the carbon costs on a per-pound basis (i.e., dividing total carbon cost by pounds produced), suggests the following.

• beef: $0.177/lb;
• pork: $0.037/lb; and
• poultry: $0.002/lb.

I don't know about you, but those don't seem like enormous costs.  Let's think about it a different way.  Suppose you wanted to "internalize" the the impacts you're having on climate change by altering how much beef, pork, and poultry you buy.  To do this, take the price you see at the grocery store and add about $0.18/lb to the price of beef, $0.04/lb to the price of pork, and less than a penny to the price of poultry, and act as if these were the prices actually being charged.  Would you change your behavior much based on such price increase?  If not, we'd could say the climate impacts are relatively small.

I saw the following from the economist Bob Lawson on twitter this weekend.

If you have ever said "externality" but don't understand that the optimal amount of pollution >0, then you're doing it wrong.

— Bob Lawson (@doclawson12) April 17, 2016

The key isn't to have zero greenhouse gas impacts, but rather to to make sure you're taking into account the cost of those impacts.  For the case of beef, that means acting as if the price were about $0.17/lb higher.  Do that and you can shop away, guilt free (well, at least the guilt of carbon impacts).

P.S.  USDA data suggests the retail price of beef in 2014 was around $5.60/lb.  An $0.18/lb price increase would represent about a 3% increase in the price of beef.  Assuming the own-price elasticity of demand is, say, -0.6, this price increase would lead to a 1.9% reduction in the quantity of beef demanded. So, to internalize the carbon impacts of beef eating, Americans would reduce beef consumption by 1.9%.   It's not zero but its a far cry from vegetarianism.