What's Going on With Wheat Futures?

One of the primary ways farmers have to manage price risk is via the futures market.

Before getting to a potential problem that has emerged, I'll first provide a short primer for those unfamiliar with futures markets 

An Oklahoma or Kansas wheat farmer is likely to begin planting sometime in September or October, but when planting they don't yet know what the wheat price will be at harvest in June or July the next year.  So, to protect themselves against adverse price fluctuations, a farmer might turn to the Kansas City Hard Red Winter Wheat Futures Contract.  The CME Group has a futures contract that settles every year around harvest in July.  Right now, the July 2017 contract is priced at about $4.50/bushel.  

For simplicity sake, let's say a farmer faced the same July 2017 futures price back in September of 2016, and they wanted to protect the price associated with (i.e., hedge) 5,000 bushels of wheat (which is exactly the size of one futures contract).  In September 2016, the farmer would sell one July 2017 contract, receiving  5000*4.50=$22,500.  This action has now contractually obligated the farmer to deliver 5,000 bushels of wheat come July to "offset" their selling position [addendum: while other futures contracts work in this way, this isn't true for winter wheat; rather than delivering wheat, the farm has contracted to deliver a "registered electronic warehouse receipt"].  Normally, however, a farmer doesn't want to go through the hassle of actually having to deliver physical wheat to a delivery point, so they instead buy back (in this example) one futures contract to offset their position when June or July rolls around.  If the price of the July 2017 contract falls from September to July, the farmer makes money from the futures market (e.g., if the price falls to $4.00, the farmer has has to spend 5000*4=$20,000 to offset their original position of $22,500, making $2,500), which helps them offset the loss in expected wheat price they receive when they sell their wheat in the cash market.  Exactly the opposite happens if the price of the July 2017 contract increases - the farmer looses money from the futures market, but receives a higher than expected cash price.  This is why it is said that using the futures market "locks in" the price at the time of planting.  

Although most farmers never actually delivery their wheat to settle their futures contract, this threat of delivery is what ties the futures price to reality.  If, for example, a farmer notices that come July 2017, the July 2017 futures contract is trading at a price well above the cash price being paid for wheat "on the ground" in grain elevators, they have a strong incentive to offset their futures position by actual delivery rather than buying a futures contract.  These arbitrage opportunities are what should force the futures market price to eventually equal the cash market price when July 2017 rolls around.   

All of that is a lead in to this video put out by Art Barnaby at Kansas State University.  It seems that farmers, at least in some situations, are not actually able to deliver wheat to offset their futures positions.  Aside from fundamental concerns about what is being measured by futures market in this case, one farmer in the video says:

“A lot of us were relying on that and felt very betrayed by the fact that what we understood to be a contract was not. ”

[Addendum Barnaby sent me a note of clarification.  The underlying issue here is that farmers have been generally taught and told that they can settle wheat contracts by the delivering physical commodity, when in fact the underlying contract says something different. He indicated: "Farmers are not obligated to deliver 5,000 bushels of wheat; they are obligated to deliver a registered electronic warehouse receipt issued by warehousemen against stocks in warehouses.  This is the reason farmers can’t deliver wheat on a short futures.  You will find this in the contract  . . .The market is trading the value of a CME approved warehouse receipt because that is the only thing that can be delivered."]  

Unanticipated Effects of Soda Tax, example 1037

On the surface the logic of a soda tax seems simple: raise the price of an unhealthy food, people consume less, and public health improves.  But, as I've pointed out again and again on this blog, the story is much less simple than it first appears.  

First, even if we believe people suffer from various behavioral biases, higher prices almost certainly make people worse off.  Second, when we raise the price of one unhealthy thing, people might substitute to consume other unhealthy things.  Third, if the tax is just added at the checkout counter and not on the shelf display, it may not have nearly the effect on purchase behavior as assumed.  Forth, if people know the reason for the tax, some may "protest" and buy more instead.  Fifth, the projected weight loss from such taxes often relies on unreasonable rules of thumb like 3500kcal=1lb. Six, even when taxes have an effect, the causal impact may arise more from an "information effect" rather than a "price effect."  Seventh, such taxes may induce unanticipated effects because of how sellers respond to the policy.  Finally, soda taxes are regressive - having a proportionally larger effect on on lower income households (see also my co-authored paper on effects of "unhealthy" food taxes more generally).

Now, comes this new paper in the American Journal of Agricultural Economics by Emily Wang, Christian Rojas, and Francesca Colantuoni, which incorporates the insight that some households are more likely to respond to promotions and to store.  The abstract:

“We apply a dynamic estimation procedure to investigate the effect of obesity on the demand for soda. The dynamic model accounts for consumers’ storing behavior, and allows us to study soda consumers’ price sensitivity (how responsive consumers are to the overall price) and sale sensitivity (the fraction of consumers that store soda during temporary price reductions). By matching store-level purchase data to county-level data on obesity incidence, we find higher sale sensitivity in populations with higher obesity rates. Conversely, we find that storers are less price sensitive than non-storers, and that their price sensitivity decreases with the obesity rate. Our results suggest that policies aimed at increasing soda prices might be less effective than previously thought, especially in areas where consumers can counteract that price increase by stockpiling during sale periods; according to our results, this dampening effect would be more pronounced precisely in those areas with higher obesity rates.”

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.  

Turkey Prices - Thanksgiving Edition

With Thanksgiving just around the corner, now is as good a time as any to take a look at turkey prices and see how the the price of the centerpiece of the holiday meal has changed over time.

Using monthly data from the Bureau of Labor Statistics (maintained by the LMIC) from January 1980 to October 2016, here is the trend in whole, frozen turkey prices.  In inflation adjusted terms, turkey prices fell by half from 1980 to 2008.  Then, along with other agricultural commodities, turkey prices rose and then fell again.  Still, prices today are about 40% lower than they were in the 1980s in inflation adjusted terms.  The nationwide price of turkey in October 2016 (the last reported by the  BLS) was $1.69/lb.      

An interesting feature of the data in the graph above is the apparent cyclical nature of turkey prices within a year.  This raises the question: are you paying more or less for turkey when Thanksgiving rolls around?  Looking at the monthly data since 1980, the answer might be a bit surprising: November tends to be the month with lowest prices for turkey. Prices of turkey in November tend to be  about 5% lower than the average annual price.  Moreover, October tends to be the month with the highest price for turkey (about 3-4% higher priced than the annual average price).  Thus, the largest price swing happens from October to November with prices typically falling about 8% just prior to Thanksgiving.  

This pattern of price fluctuation might be a bit surprising.  Isn't it the case that demand for turkey is highest in November? If so, shouldn't a demand increase drive up prices?  Yes, but producers also know when demand spikes occur and they can plan production and storage accordingly (this is a fairly highly integrated industry) so that there is ample supply during this time.  Additionally, research on this topic has suggested that retailers might use turkeys as so-called "loss leaders".  Knowing that many consumers will be shopping for turkeys, retailers will offer specials and discounts  on the item everyone is looking for to get them in the door so that they'll buy all the other things it takes to make a Thanksgiving meal.  

Finally, it's instructive to look at proteins more generally.  How pricey is turkey relative to the other big ticket meat items that families might put on their dinner plate?  If turkey got too expensive, you can substitute toward another tasty main course. (Growing up, my family was never a big fan of turkey, so we often opted for steaks or ham).   

Here are the relative price trends since January 2000 (again based on BLS prices).  As of last month, beef steaks are about 4.4 times more expensive (on a $/lb basis) than turkey, and beef roasts are about 3.1 times more expensive than turkey.  Another way to say this is that for the same fixed budget, one could buy four times as much turkey as they could beef steak (no minor issue if a dozen folks are headed to your house).  Pork chops and ham are both about 2.3 times the price of turkey.  That said, beef and pork are more affordable relative to turkey than they were last year at this time.  From October 2015 to October 2016, the prices of the beef and pork products investigated here have fallen 11.8 to 16.6% relative to the price of turkey.  Whole chickens are about the same price as turkeys, though slightly cheaper on per-pound basis.

Now that you know the prices, figure out how many pounds you need to feed the gathering, how much you can spend, and buy whatever it is that brings you and your family the greatest joy.  Happy Thanksgiving!  

Country of Origin Labeling and Cattle Prices

Last week, I traveled quite a bit - from Georgia to Montana and back to Oklahoma.  In all three locations, I heard a claim that I hadn't yet heard before.  Namely that the low cattle prices we are now observing is a result of the repeal of mandatory country of origin labeling (MCOOL) for meat around the first of this year (note: the repeal came about a result of a series of World Trade Organization rulings against the U.S. policy).

I have to admit to being skeptical of the claim.  Agricultural economists have been researching this issue for quite some time (e.g., I have a paper on the topic with John Anderson published more than a decade ago back in 2004).  By and large the conclusion from this body of research is that MCOOL has had detrimental effects on beef producers and consumers (e.g., see this recent report prepared for the USDA chief economist by Tonsor, Schroeder, and Parcell).  It is true that some consumer research (including my own) reveals consumer interest in the topic and willingness-to-pay premiums for U.S. beef over Canadian or Mexican beef in surveys and experiments; however, most consumers were unaware MCOOL was even in place, and research using actual market data hasn't been able to identify any shifts in retail demand as a result of the policy (a summary of this research is in the aforementioned report).

So, let's put my initial skepticism to the side and look at the data.  Here is a graph of fed steer prices (blue line) and number of fed steers marketed (red line) over the past several years (these are USDA data from the LMIC and represent the 5-market weekly weighted average including all grades).   

The solid black vertical line indicates the point where MCOOL stopped being enforced by the USDA (just prior to January 1, 2016).  Looking at cattle prices, one can see how the claim that the repeal of MCOOL caused a drop in cattle prices came about, as the repeal came right after the peak of fed steer prices, after which prices began to fall rather dramatically.  

But, is this just a coincidence?  Correlation is not always causation.  

The red line in the graph shows the number of steers marketed (I plotted the 6 week moving average to smooth out some of the "jumpiness" in the line).  There is a strong inverse correlation between the number of fed steers marketed and the price of fed steers.  When more cattle are brought to market, prices fall and vice versa.  The correlation coefficient is -0.78 over this time period (January 2, 2000 to early November 2016).  

What started happening at almost the exact same time MCOOL was repealed?  Producers started marketing more cattle.  Here's the thing: one can't create a fed steer overnight.  The production decisions that led to the increase in fed steers around January 1, 2016 would have had to have been made around two years before.  Were producers so prescient that they could anticipate the exact time of the repeal of MCOOL two years prior?  Or, rather, was this a "natural" part of the cattle cycle?  

As the above graph shows, producers started having many fewer cattle to sell beginning in '08 on into 2012 for a variety of reasons such as drought and high feed prices.  These lower cattle numbers led to higher prices, which in turn eventually incentivized producers to retain heifers and add more supply to reap the benefits of higher prices.  When did all those extra cattle start hitting the market?  It turns out (largely by chance) that it was the same time MCOOL was repealed.  

Let's go one step further.  Because the supply of fed cattle is relatively fixed in the short run (as production decisions have to be made many months prior), we can use the above data to get a very crude estimate of the demand for fed cattle.  Using just the data shown in the above graph, I find that 81% of the variation in (log) live steer prices is explained by changes in the (log) quantity of steers marketed.  Estimates suggest that a 1% increase in the (six month moving average of the) number of steers marketed is associated with a 0.5% decline in live steer prices.  

Since the 1st of the year there has been a roughly 120% increase in the number of steers marketed (from an average of around 14,600 head/week just prior to the first of the year to an average of around 32,500 head today), and our simple demand model would suggest that this would lead to a 120*0.5=60% decline in cattle prices.  Yet, cattle prices have "only" declined about 25% (from around $133/cwt at the first of the year to around $100/cwt now).  So what?  Well, if MCOOL was the cause of the reduction in cattle prices, we would have expected an even larger fall in cattle prices than our simple demand model predicted, but instead, we're actually seeing a smaller fall than expected.  

Now, let's address one possible criticism of the above discussion.  What if the rise in fed steers marketed in the graph above is because of cattle flowing into the US from Canada and Mexico once MCOOL was repealed?  Here is data on imports of cattle from Canada to the US (again from LMIC).

There was a fall and then a larger uptick in the number of cattle imported from Canada to the US right after MCOOL, but nothing out of the ordinary from the typical fluctuations in the three years prior.  For example, the "spike" in total imports (slaughter cows + fed cattle + feeder cattle) around May of 2016 is at least 5,000 head smaller than the five previous spikes that occurred when MCOOL was in place.   

Even if I take the roughly 5,000 extra imports of fed cattle that came in from Canada after MCOOL from January 1, 2016 to the middle of May, and assumed even than 75% were steers, this would represent only 13% of the number of steers in the 5-market dataset sold to packers.  At most, this would cause a 13*0.5 = 6.5% decline in U.S. fed cattle prices according to my simple demand model.  This is nowhere near the 25% decline actually observed since the 1st of the year.  Moreover, look at what happened to cattle imports during this summer.  They fell.  They fell at a time when U.S. cattle prices were falling.  So, it can't be that extra Canadian imports were the cause of falling U.S. prices during mid summer.

In summary: while it is conceptually possible that the repeal of MCOOL could adversely affect U.S. cattle prices, any actual effect appears to be quite small (if there is any effect at all).  The fact that cattle prices fell immediately after the repeal of MCOOL appears to be a coincidence.  The falling prices seem more to do with "normal" changes in supply resulting from the cattle cycle than anything to do with MCOOL.