Breakfast Cereal Economics 101

Yesterday evening I happened to be in the gym while the NBC nightly news was playing on a  screen above my treadmill.  A video of the segment is embedded below.

The premise of the story is that the price of breakfast cereal is on the rise.  As the reporter put it, "sticker shock in the cereal aisle.  The morning staple is getting more expensive."

The story reported that over the past five years, the price of a pound of cereal has increased $0.20 to $3.09.  That doesn't seem like an enormous increase to me.  That works out to a 6.9% price increase over 5 years - or just a 1.4% increase per year (if the price of cereal rose at the same pace as the overall rate of inflation, we'd expect it to have risen by roughly the same amount as it actually has over the past five years).  But, let's leave that aside for now.  I want to focus on the economic arguments made in the piece.

The story says that consumption is down 7% over the same time period.  So far so good.  Prices rise, consumption falls, showing the demand curve is downward sloping.  In econ-speak, we'd say there was a movement along the demand curve.

Where the story runs off the rails is when trying to discuss the causes of the price "spike".  They say "shoppers are looking for healthier and faster food.  They've gone to Greek yogurt, they've gone to power bars, . . ."  The story talks about cereal brands trying to become healthier by adding fiber and cutting sugar.  Then the key phrase at the 1:33 mark:

“As the demand for cereal falls . . . ”

Here's the problem: as we teach in Econ 101, if the demand curve falls (or shifts inward) because of health concerns or change in the price of substitutes then the price will also fall.  But, the whole NBC story was motivated by the fact that cereal prices are rising not falling.

Unless something is happening on the supply-side, falling demand cannot occur at the same time as rising prices.  Either NBC got the facts wrong (cereal prices aren't falling in real terms) or they got the explanation wrong (cereal demand isn't falling but rather the supply curve was shifting).  I suspect the they also did what a lot of students in our intro classes do: they confused a movement along the demand curve for a shift in the demand curve.   

Consider this a friendly lesson in cereal economics 101.

Local foods and seasonal price swings

In the Food Police, I wrote the following about local foods when critiquing the argument that a larger local food system would be better for the environment and for food security:

“Because of common weather and temperature, all farms within a region are likely to have their produce come to market around the same time. In a world with regional and international trade, that isn’t a big deal as the surplus can be shipped out to other locations. But, in the locavore’s world, the result is inevitable: spoilage and waste.

...

It would be foolish to invest all your retirement savings in a single stock. The financial experts tell us to diversify. And if we shouldn’t keep all our financial eggs in one basket, the same goes for the real ones. One of the things that makes farming unique compared to other businesses is its unusually large reliance on the weather. An unexpected drought, a rain at the wrong time, an early freeze, or a hail storm can devastate a whole farming community or even an entire region. While farmers protect themselves financially against these kinds of risk by buying crop insurance, what about the food consumer? ”

This new paper in the Journal of Agriculture and Applied Economics by some Hawaiian researchers provides some empirical evidence of the price volatility I mention surrounding local foods.  Here's a graph from their paper showing production and prices of local tomatoes over 12 months of the year

There is a very clear negative correlation between production and price.  When tomatoes are "in season" and local producers have a lot to sell, prices are low, and vice versa.

Of course, that inverse relationship is true for most of agricultural production.  But, here's the difference for a lot of local food production: A) with grains you can store the commodity to help smooth out prices over time (something much harder with perishable fruits and vegetables) and B) with trade you can ship to locations with different seasons (where there is less supply and therefore higher prices).

In short, by limiting sales to local consumers, producers are opening themselves up to a lot of potential price volatility, and to lower prices at the exact time they have produce ready to sell.  How can the producers partially mitigate such effects?  Find people in other locations with different seasons with whom to trade.  

The authors write:

“It can be seen that local price premiums/discounts vary depending on product type and season. For grape and cherry tomatoes, there is an 18.18% local premium during season 1 (before the peak season). However, starting from season 2 (local peak season), price difference declines and becomes insignificant. On the other hand, there are constant local discounts for other tomatoes throughout the year, although prices are considerably lower in seasons 2 and 3. Comparing the results for both types of product, there is a clear downward effect on prices of local tomatoes during the peak production season, suggesting that market prices are likely influenced by the local production level.

One further contributing factor to the price discounting may be the capacity limitations in marketing and distribution by local producers in Hawaii. Since large national producers with more marketing and logistics competence have access to a larger market, production surpluses can be spread over more market areas with less need for discounting. In comparison, small local farms are often constrained by lack of distribution channels and market outlets (Martinez et al., 2010). In the case of Hawaii, because local tomatoes are exclusively supplied to the Hawaiian Islands, this may result in discounting at the retail level in times of production surplus.

Lastly, the Armington analysis shows that consumer choices with respect to locality and organic origins are elastic, and that both local and organic tomatoes are quite substitutable to import nonorganic tomatoes. ”

Meat Demand in an Era of High Prices

The journal Applied Economic Perspectives and Policy just accepted a paper I've written with Glynn Tonsor, which provides new estimates of consumer demand for different meat products using what is probably one of the largest and longest-running surveys choice experiments (a survey method) to date.  

The graph below showing changes in retail meat prices from January 2010 to January 2015 is  what motivated the paper. Beef and pork prices rose dramatically over this period (note: in the past few months they've come back down) whereas chicken prices were and still are fairly stable.   The following is further motivation from the paper:

“Industry observers have expressed surprise about how consumers have responded to recent price changes (Ishmael, 2014). In particular, expenditures for beef and pork have not fallen as much as some people expected given the high prices. Industry analysts have asked “where is the tipping point” when consumers will stop buying beef and pork (Rutherford, 2014), but it may be that demand elasticities are more non-linear than previously realized. Moreover, relative price swings would have seemed to have favored chicken over beef and pork, and yet there does not seem to be a high degree of substitution in the current market environment. Such observations raise the possibility that cross-price elasticities have changed or are lower at higher price levels.”

You can read the paper for the methods.  Here I'll just highlight what we found.

First, people with different incomes choose different things.  High income consumers are more likely to choose steak and chicken breast than are low income consumers, and the opposite is the case for chicken wings, ground beef, and deli ham.  

Second, beef prices are more sensitive to changes in the price of chicken than the reverse.  Here's an illustration of that phenomenon using our estimated model for middle income consumers.

Third, and somewhat surprisingly (though consistent with industry observations over this period), the quantity of beef and pork demanded is less sensitive to price changes when prices are high as compared to when prices are low.  In econ-jargon, demand is more inelastic as prices rise.  You can see that in the graphs above, and the paper fleshes out that finding a bit more by showing the bias in models that ignore this non-linearity in demand. 

Hopefully these new estimates will help us better predict in the near future what happens when beef and pork prices fall, and will help producers better anticipate the impacts of future price hikes.

This analysis used a huge data set (110,295 choices made by 12,255 consumers) collected over a year and half long period.  This is of course from my Food Demand Survey (FooDS).  The present analysis assumed people's preferences staid the same over this period.  Up next on the research agenda is to look at how these demand estimates have been changing (or not) over time using even more data over a longer time period., and investigating whether these survey-based demand changes can forecast changes in retail meat prices.   

Price impacts of avian influenza (bird flu)

Since the last time I posted on the issue, avian influenza has continued to spread, particularly in flocks of egg-laying hens, and the price impacts are becoming more apparent. 

Here's what I wrote back in April:

“Demand for eggs is likely much more inelastic [than turkey] because of fewer substitutes. The elasticity of demand for eggs is probably somewhere around -0.15 to -0.20. The USDA-APHIS data indicates that about 4 million chickens (I believe these are egg-laying chickens) have been killed due to the flu. There are about 300 million laying hens in the U.S., implying this is a supply reduction of about 1.3%. Following the same logic as before, a 1.3% supply shock in the short run would cause a (0.013/0.15)*100=8.7% increase in egg prices in the immediate short run. Why so much higher than for turkey? Because demand for eggs is likely more inelastic than is demand for turkey. If the outbreak in egg laying hens doubles, reducing supply by 2.6%, that would imply a price increase of 17.3% in the short run. ”

Now, here's what Kelsey Gee wrote in the Wall Street Journal just yesterday:

“Avian influenza has resulted in the deaths or extermination of at least 38.9 million birds, more than double the previous major U.S. outbreak in the 1980s. Of that total, more than 32 million are egg-laying hens, accounting for about 10% of the U.S. egg-laying flock.

The wholesale price of “breaker” eggs—the kind sold in liquid form to restaurants like McDonald’s Corp., food-service supplier Sysco Corp. and packaged-food producers—nearly tripled in the past month to a record $2.03 a dozen on Thursday, according to market-research firm Urner Barry. Meanwhile, U.S. prices for wholesale large shell eggs, those sold at the grocery store, have jumped about 85% to $2.20 a dozen in the Midwest. ”

The actual price impacts aren't that far off from what were predicted from my very simply supply/demand model.  In the very short run, supply is predetermined, so the price impacts of a reduction in supply are determined entirely by the shape of the demand curve.  A very simple demand curve is Q = e*P, where Q is the proportionate change in quantity, P is the proportionate change in price, and e is the own-price elasticity of demand.  Changes in price are thus given by: P=Q/e.  

Thus, if the change in quantity is about -10% as indicated in the WSJ article, and the elasticity of demand is about -0.15 as I previously suggested, the expected short-run price change is P = 0.1/0.15 = 0.667, or a 66.7% increase.  

The 85% price increase cited in the WSJ is larger than the projected 66.7% increase.  This could be because consumer demand for eggs has fallen among some consumers worried about bird flu (see my recent survey for evidence on that), so we may be witnessing not only movements along the demand curve but also a shift in the demand curve.  Or, it could simply be that demand for eggs was more inelastic that I previously assumed.  An own-price elasticity of egg demand of -0.117 rather than -0.15 would imply an 85% price increase in response to a 10% reduction in quantity supplied.  

But, no matter the cause of the price increases, it certainly isn't good for consumers who are harmed by having to pay higher prices for a smaller number of eggs. Producers who have lost flocks are certainly worse off.  The only beneficiaries are those egg producers who've (at least so far) avoided the outbreak.  

Are consumers really spending more on food away from home?

A couple days ago, the Wall Street Journal ran a story that started as follows

“Retail-sales figures released by the U.S. Commerce Department garnered considerable attention last month when news reports suggested they showed Americans spent more money dining out than buying groceries for the first time ever.

Some observers jumped from there and attributed the shift to the growing clout of millennials, saying they prefer breaking bread with friends at restaurants, while sad-sack baby boomers who didn’t save enough for retirement are stuck cooking at home.

But as it turns out, reports on the decline of home cooking were half baked. They demonstrate, once again, that it is important to understand how the government compiles statistics to avoid jumping to conclusions the figures don’t support.”

I agree.

As the story points out, the government's data ignores sales from some major grocery establishments like Wal-Mart.

This is an issue we've been tracking in the Food Demand Survey (FooDS) for over two years now.  Our data from a nationally representative sample of consumers show it's not even close.   People spend a lot more money on food at home.  Here's the data from our second annual report.

Our most recent release, just a couple days ago shows at home consumption at about $96/week and away from home at about $53/week.  

Thus, our data clearly supports the conclusion drawn by Jo Craven McGinty in the WSJ:

“The government’s monthly retail-sales report provides valuable information that reveals legitimate trends, providing users understand what the numbers represent.

In this case, no matter how you slice it, spending on dining out hasn’t surpassed spending on groceries”