Free Markets in Donated Food

“Imagine that someone gave you 300 million pounds of food and asked you to distribute it to the poor—through food banks—all across the United States. The nonprofit Feeding America faces this problem every year. The food in question is donated to Feeding America by manufacturers and distributors across the United States. As an example, a Walmart in Georgia could have 25,000 pounds of excess tinned fruit at one of its warehouses and give it to Feeding America to distribute to one of 210 regional food banks. How should this be accomplished [when the food cannot be sold to food banks]? ”

That's the opening paragraph of an article in the latest issue of the Journal of Economic Perspectives by Candice Prendergast.  His answer to the question was to create a market to allocate the food while attempting to feed the most people and have some equity across food banks.  He shows that there were myriad details and market design issues that had to be overcome, but the ultimate outcome appears to be wildly successful.  He writes: 

“Feeding America knew that its previous system of offering the same amount, and kind of food, to food bank clients might not be optimal, but it did not have the hard information to design a better system. Indeed, given the information that Feeding America had available with the queuing system, it is likely that offering everyone the same thing was close to the best option. The Choice System has allowed the participants to match outcomes to their preferences more effectively. Auctions have revealed willingness to pay for different kinds of food (who would have guessed that one pound of cereal was worth almost 50 pounds of produce?), which has allowed food banks to sort more efficiently on the quality–quantity dimension. In this way, the market system has allowed gains not possible with centralized assignment.”

For those wanting to learn more, a couple years ago, Prendergast was on the Econ Talk podcast with Russ Roberts discussing these markets.

How Much Does Your State Rely on Other States for Food?

With all the ongoing discussion of benefits and costs of trade and NAFTA, I thought it might be useful to look at some agricultural trade within the United States.  We don't usually think of sending corn from Iowa to Louisiana as "trade" but it's hard to see how it is much different than sending corn, for example, from Iowa to Alberta, except of course for crossing national rather than state boarders.  These sorts of discussions also relate to efforts to move toward local and regional food systems.  How feasible is it, really, for a state to "feed itself"?  

Unfortunately, there simply isn't good data on how much states trade with each other. Thus, I thought I'd make some very crude calculations based on a variety of tenuous assumptions.  First, I'll report what I found and then discuss the details and assumptions I had to make below.  

The table above shows my crude calculation of how much a state imports or exports for various food products on a per-capita basis.  For example, for every Iowan, 3,896 lbs of hogs leave the state for every pound that comes in.  Iowa is thus a net exporter of hogs/pork.  By contrast, for every New Jerseyan, 111 lbs of hogs enter the state for every lb that leaves New Jersey.  New Jersey is a net importer of hogs.  By these calculations, 11 states "feed" the other 39 states pork. 

For eggs (this includes both table eggs and hatching eggs because these were the most complete data available at the state level), in Iowa, 3,747 eggs per person leave the state for every egg that enters the state.  These calculations suggest Massachusetts and the District of Columbia are the largest net importers of eggs with more than 300 eggs entering the state/district per person for every egg that leaves.     

For cattle, 18 states "export" lbs of cattle on a per capita basis and the other 32 states import lbs of cattle.  Rice is the most extreme case shown.  Only six US states produce meaningful quantities of rice according to USDA; people in the rest of the US have to import from these locations.

A state like Massachusetts, for example, heavily relies on other states for these four agricultural products.  The average Bostonian imports 110 lbs of hogs, 302 eggs, 130 lbs of cattle, and 62 lbs of rice from other states.  California is a big producer of agricultural products, but it is also a populous state, and as a result, it is also a net importer of hogs, eggs, and cattle.  

***

On the details of the calculations -  I'll admit up front that the figures in the above table leave a lot to be desired.  I'll describe what I've done and leave it to the reader to decide whether there is more information than noise.  

I went to USDA-NASS data and obtained production by state. The USDA doesn't always report production for all states, and in many cases, it withholds reporting for some states due to confidentiality issues.  In these cases, I "fudged" and simply divided the total production that was unaccounted for equally among states for which the USDA did not report data.  

These USDA data yield crude estimates of production by state.  We do NOT have good data on consumption by state, but we do have data on population by state.  Making the assumption that per-capita consumption of various food products is the same in every state, we can then make an inference as to how much of any food product is consumed in a state.  It is simply the share of the US population in a given state multiplied by the total US production of a given agricultural commodity.  The difference in the state production and the inferred state consumption is a crude estimate of net exports/imports into a state.  I then divided the total pounds (or eggs) of net exports/imports by a state's population to put the figures in per capita terms.  

There are some shortcomings with these calculations.  First, I've ignored trade with other countries.  For example, if eggs leave Iowa for Mexico, then the above figures over-state how many eggs are consumed within a given state in the US.  I similarly ignore imports, which will instead under-state how much is imported into certain states.  Also, the figures above suggest per-capita consumption numbers that are substantially higher than that reported by the USDA-Economic Research Service.  The main reason, for beef and pork, is that the USDA production data report farm-level lbs produced by a state not the amount of retail meat lbs.  There is some double counting in these figures.  If an Indiana farmer raises a hog to 20 lbs and then sells it to a finishing operation in Illinois that raises the hog to 200 lbs, then the USDA statistics will say Indian had 20 lbs of production and Illinois had 200 lbs of production, which added together is 220 lbs.  But, there aren't 220 lbs of pork, only 220. The way around this would be to only count retail lbs produced, but the USDA doesn't report this on a state level for pork or beef.  Also, there are a lot of other foods, like vegetables or table eggs, that we might desire to create statistics like those in the above table; however, there is very sparse reporting at the state-level by the USDA, and often the "other states" category has more quantity produced than the total of the quantity specified for named states.   

Hierarchy of Food Needs

“How would it look to apply the principles of Maslow’s Hierarchy of Needs to food management?”

That's the opening sentence by Ellyn Satter in a 2007 article in the Journal of Nutrition Education and Behavior.  She writes:

“Abraham Maslow arranged basic needs in order of sequential importance to the individual and taught that needs at each level must be satisfied before the individual can become aware of and address the next level of need. From the foundation through the apex on Maslow’s pyramid-shaped Hierarchy of Needs, they are: (1) physiological needs: air, water, food, shelter, sleep, sex; (2) safety, security and order; (3) social affection: love and belongingness; (4) esteem, status: self-esteem and esteem by others; and (5) self-actualization: being all the individual can be.”

She then proposes (without any data or evidence I might add), the following hierarchy of food needs.

Satter argues this hierarchy is important to understand for nutrition educators who should: 

“join with individuals right where they are. For those whose most pressing concern is getting
enough to eat, help them choose dependably filling and satisfying food. Address energy inadequacy by endorsing adding fat—butter, oil, or salad dressing—to vegetables and grains and using whole milk. Point out the nutritional value of preferred food items, and suggest additional low-cost food items that are both energy dense and nutritious. But avoid prioritizing food selection based nutritional considerations alone. Doing so is realistic only for people who are functioning at the apex of Satter’s Hierarchy of Food Needs.”

To what extent is this "model" true?  A few weeks ago, I compared the food values for the rich and poor, which provided some support.  But, even that data suggests taste, safety, price, and nutrition are top four food values (out of 12 total values) for both low and high income.  The ranking for high income is taste, nutrition, safety, and price and for low income is price, taste, safety, and nutrition; factors like fairness, novelty, and origin were ranked last for both high and low income groups.  It would be interesting to see studies comparing income elasticities of demand for foods that fit the above criteria.  However, the above model doesn't necessarily suggest income is the main driver - only that one has to meet a "lower" need, via whatever means, before another "higher" need is met.    

Akin Adesina

One of the pleasures of being a department head is getting to celebrate the successes and accomplishments of students, faculty, and alumni.  Last week, Akinwumi (Akin) Adesina, an MS and PhD graduate of the Department of Agricultural Economics at Purdue University, was awarded the World Food Prize, and I had the opportunity to engage with him a bit at events prior to the ceremony and yesterday when he returned to campus for a visit.  

To say I was impressed by Akin would be an understatement.  He is smart, passionate, and gregarious, which helps explain how he became president of the African Development bank after previously serving as Nigerian Agriculture Minister.  In, 2013 he was Forbes man of the year in Africa, and probably more telling than anything else, he’s giving away the $250,000 prize money from the World Food Prize to create a fund to promote African youth in agriculture.

Akin's visit caused me to reflect on the ability of good economic work to substantially impact people's lives and on the state of the academic economics profession generally.  He told a story about how, early on in his career, after witnessing grain bins in a farm village overflowing with a new, high yielding sorghum variety, he realized that food security was more than just agronomy: without developing markets to sell higher-yielding crops varieties, the benefits would not be widely distributed and enjoyed.  The market and economic approach to helping solve African food security and poverty problems have become signatures of Akin's career.  Among Akin's many accomplishments that rely on this economic-based approach, I'll mention two (see here for more details). 

First, he noticed that several promising technologies and crop varieties already existed but were not being adopted because farmers lacked the resources to acquire the new technologies that could substantially increase yield.  By promising to partially backstop loans (initially via a fund from the Rockefeller Foundation), he encouraged banks to make capital available to farmers.  Despite banks' initial reluctance to loan to farmers, there were very low loan failure rates, and the program was successful and was scaled up, eventually leveraging hundreds of millions of dollars that flowed to the African agricultural sector to increase agricultural productivity.  This is one of several efforts he and his team are working on to reduce the risk of investing in African agriculture.

Second, as Minster of Agriculture in Nigeria, he aimed to tackle the problem under-use of fertilizer in the country.  Yes, in many parts of the developed world, there are problems associated with over-use of fertilizer, but in Africa the problem is just the reverse.  The problem is that for decades fertilizer had been purchased by the government and then was distributed to farmers.  The program was rife with corruption and only well-connected farmers had access to fertilizer.  Akin initiated a disruptive technological solution to the problem: fertilizer subsidies were instead directly distributed to farmers via their mobile phones.  Within a few months, decades of corruption were overturned and fertilizer became much more accessible.  As a result, crop yields increased significantly.  His efforts earned him the nickname: "the farmers' minister."  

One of the things Akin mentioned several times over the past few days is that he aims for Africans to see farming as a business.  This runs so counter to our developed-world pastoral ideals about what farming should be.  Yet, we can afford to harbor these romantic notions precisely because the farmers in the US became much more business-like over the past century.  Another of Akin's goals is, in his words, to make agriculture sexy.  Through a variety of efforts, he's encouraging what he calls "agri-preneurs", to prompt investment in agriculture.

It is useful to contrast this body of work with what we typically do in academics.  In academic economics, focus has shifted in recent decades toward research problems where there can be strong credible claims about identification and causal relationships (i.e., are we sure X is causing Y or are the two just correlated?).  In development economics, the shift has led to more randomized controlled trials (RCTs) to evaluate effectiveness of interventions. These changes have been good for the profession and I fully support the shift.  However, Akin’s visit also made me a bit more sympathetic to some of the critics (including prominent figures such as Angus Deaton and James Heckman) of these methodological changes.  The concern is that the “randomistas”, as they are sometimes derogatorily called, miss the “big questions” and the “important issues”, focusing instead only on those problems and data sets that lend themselves to making strong causal claims that can be published in top academic journals.  My view is that the economics profession is big enough to do both: we can pursue the big questions while simultaneously thinking about creative ways to uncover causal mechanisms.  Akin’s work is really inspirational in showing how good economic policy based on solid economic theory (i.e. the presumed causal mechanisms) can help improve the lives of millions of people. 

Agricultural Productivity and Food Security

There are two competing narratives about the future of food.  One is that the world population is growing and we need to increase agricultural productivity to "feed the world".  The other argument is that we don't need to produce more food - we already produce enough food to feed the world and our problems are really more about distribution than production.  Folks in the later camp often advocate for lower-productivity forms of agriculture that they perceive to have health or environmental benefits.  Like most arguments, there are elements of truth to both sides.  

As a proponent of improved agricultural productivity (which, I've argued is the key metric to improved sustainability), it bears asking: if a country's agriculture is more productive are it's people better fed?  

To delve into this question, I combined two data sets.  The first is a measure of a country's agricultural productivity from the World Bank in the year 2015.  In particular, they calculate for a large number of countries, the agricultural value added per worker.  In their words:

“Agriculture value added per worker is a measure of agricultural productivity. Value added in agriculture measures the output of the agricultural sector (ISIC divisions 1-5) less the value of intermediate inputs. Agriculture comprises value added from forestry, hunting, and fishing as well as cultivation of crops and livestock production. Data are in constant 2010 U.S. dollars.”

By this measure, the most productive countries are Slovenia, Singapore, Norway, France, Lebanon, Canada, New Zealand, Finland, and the United States, each of which produced more than $80,000 in agricultural value per worker in 2015 (measured in 2010 dollars).  Places like Malawi, Congo, Mozambique, Gambia, and Madagascar had some of the lowest productivity, with agricultural value added at around $400/worker or less.

Secondly, I collected data from the Global Food Security Index, a project ran by The Economist and supported by DuPont.  In their words:

“The Global Food Security Index considers the core issues of affordability, availability, and quality across a set of 113 countries. The index is a dynamic quantitative and qualitative benchmarking model, constructed from 28 unique indicators, that measures these drivers of food security across both developing and developed countries.

This index is the first to examine food security comprehensively across the three internationally established dimensions. Moreover, the study looks beyond hunger to the underlying factors affecting food insecurity. This year the GFSI includes an adjustment factor on natural resources and resilience. This new category assesses a country’s exposure to the impacts of a changing climate; its susceptibility to natural resource risks; and how the country is adapting to these risks.”

From this project, I pulled each country's overall food insecurity score (calculated in September 2017), which took on the values of around 30 for countries like the Congo, Madagascar, Chad, and Malawi, and was above 80 for countries like the U.S., the U.K., Ireland, and France.  Although they call this a measure of food insecurity, a higher score actually means a country is more food secure.   

So, what did I find?

There is a strong positive relationship between a country's agricultural productivity and how well it's people are fed and how food secure they are.  Fitting a logarithmic relationship between the two variables suggests that 82% of the variation in the food security scores across countries is explained by differences in agricultural productivity.  

Now, there are a lot of other things going on here as agricultural productivity is likely correlated with and affected by other factors affecting a country's general productivity and development, but the above figure might give pause to those arguing for lower productivity forms of agriculture. 

At the top end, the curve suggests one can sacrifice some productivity with only a small reduction in food security (going from $80,000/worker to $40,000/worker) reduces the food security scale from about 80 to 75.  But, at the lower end, going from, say, $20,000 in agricultural output per worker to $10,000/worker reduces the food security scale from about 70 to 60, and reducing productivity another $10,000 lowers the food security scale down to the 30s.