Measuring consumer food demand in experiments
It seems plausible that milk sold with a label indicating the farmers did not use the rBST hormone will be viewed favorably by consumers. It suggests that there is something unsafe about milk from farms that did use BST, and that seeing one milk saying they did not use rBST might cause consumers to place less value on milk without that label (to see an example of this label and more discussion about this topic, see this article. If rBST did not compromise the milk in some way, why would producers say something about it on the label? That is probably what consumers are thinking, but to really determine whether this is the case, we need to collect data on consumer behavior.
Purchasing data on grocery store sales of food is easy to do, so you might think we could analyze data on how sales of rBST milk changes when non-rBST milk is and is not also on sale, (Note that saying “non-rBST milk” doesn’t mean the milk is free of the BST hormone, as all milk contains the hormone; instead it refers to milk acquired from cows not treated with rBST). Imagine a scenario where consumers purchase X amount of rBST milk when the price of milk is $3.00 per gallon. Then, for the first time, non-rBST milk is sold in the store at a price of $3.50. Some consumers purchase the non-rBST milk at $3.50 and others buy the rBST milk at $3.00. Then, the non-rBST milk is removed from the shelves. If consumers still purchase X gallons at $3.00 then the temporary presence of non-rBST milk did not alter how consumers view regular milk. But if sales of regular milk at $3.00 per gallon is (1/2)X, then the temporary presence of non-rBST milk caused consumers to be very skeptical of regular, rBST milk, and when only rBST milk was available, they purchased far less of it.
Unfortunately, such data may be difficult to find, as most stores have never removed rBST milk from the shelves, and even if it did, it would be difficult to determine whether the fall in purchases of rBST milk was due to the introduction and subsequent withdraw of non-rBST milk, or if some other factor (like new human health research) had caused milk demand to fall. Also, we are concerned about the total demand for milk, and changes in shopping behavior at one store doesn’t tell you how they behave in other stores.
When good data on actual consumer purchases in the grocery store are not available, agricultural economists tend to turn to experiments instead, where the setting, products, information, and prices can be controlled.
A milk experiment
A team of agricultural economists recently conducted an experiment to determine whether the presence of non-rBST milk stigmatizes regular, rBST milk. The subjects in the experiments were recruited through the use of email lists and various publications, in an attempt to obtain a representative sample of all Americans. Such samples are never perfectly-representative though, as there will always be one type of person who buys milk but prefers not to participating in experiments. By attending of one of fifteen different experimental sessions, the participants could earn $15. What follows is a simplified version of the experiment, where most of the details not pertinent to this discussion are ignored. During the session, subjects were given $5 in cash and allowed to submit (1) a bid in one auction to purchase a quart of milk made from cows treated with rBST (2) a bid in another auction to buy a quart of milk from cows that were not treated with rBST and (3) a bid in a third auction to buy a quart of organic milk (which, of course, does not come from cows treated with rBST).
At the end of the experiment one and only one of the three milk products were randomly selected to be the “binding” auction, which meant the bids for the non-binding auction were collected as data but not used to distribute milk. There was an equal chance that the rBST, non-rBST, and organic milk auction would be selected, so subjects had to take each auction seriously. Moreover, subjects knew only one bid would be binding, so they knew that the $5 could be used to buy only one product, and would not have to be split among three.
The meaning of value
When economists use the word “value” they are referring to a very specific measure: the maximum amount of money a person will pay for an item. If a consumer tells us that they will pay up to $2.00 for a quart of organic milk, this means they will always buy it when the price is less than $2.00 (so the consumers must actually have at least $2.00 to pay for it) and will never buy it when the price is more than $2.00. In his novel The Picture of Dorian Gray one of Oscar Wilde’s characters referred to a man who, “knew the price of everything and the value of nothing.” Economists know exactly what the value is to a person, so long as they can observe their behavior when confronted with different prices. For instance, if a person buys one quart of milk when the price is $1.00 but buys none with the price is greater than $2.00, the economist knows that the person values one quart of milk more than $1.00 but less than $2.00. By using sophisticated auctions like that described below, the economist can identify the person’s value precisely.
An unusual auction
Now back to the experiment. Let us look at the particular auction the researchers used for rBST, non-rBST, and organic milk. Most readers are used to an auction where the highest bidder wins, receives the item, and pays an amount equal to that highest bid. This is referred to as an English auction. When economists measure the value consumers place on a product they do not want to use the English auction, because people tend to bid slightly less than their true value. Instead, economists want a different auction that is incentive-compatible, meaning people have the incentive to bid an amount exactly equal to their true value.
INSERT VIDEO DEMONSTRATING THE DIFFERENCE
Randomize what you cannot control
The appeal of a controlled experiment like this one is that researchers can evaluate how consumer behavior changes in response to only one or a few factors. For instance, the experiments took place in such a small period of time it is unlikely that new health information regarding milk would have altered preferences, allowing researchers to control for the passing of time. Also, by holding the auction in an experimental setting instead of the grocery store, the researchers know that milk purchases would not be swayed by changes in the price of other goods in the grocery store. Most of the things you can think of that alter milk purchasing patterns were controlled by auctioning off milk in a controlled experiment.
There are always some things that will affect consumer behavior that the researcher cannot hold perfectly constant. For instance, the consumer may be influenced by which milk product they are presented with first. Those who bid in an auction first for the rBST milk and then for the non-rBST milk might behave differently than if they were presented with the non-rBST milk first. Whenever a factor in an experiment is expected to influence behavior, the researchers “control” for this by randomizing the factor. In this example, the order in which the auctions took place were randomized. Some bid on rBST milk first and non-rBST milk second, and some bid on non-rBST milk first and rBST milk second (I’m ignoring organic milk here to keep the explanation simple). This way, once the average bid for each milk product is calculated from the sample, the averages are not influenced by the order of the auction in any systematic manner. Half were influenced by seeing rBST first, half were influenced by seeing non-RBST first, leaving the results [largely] free of bias.
Use statistical tools to account for things that can be neither randomized nor controlled
There will always be some factors influencing results that cannot be controlled for in the experiment, nor randomized. The demographics of a sample is an example. It is difficult for the researcher to acquire a sample of subjects whose demographics is a perfect reflection of the U.S. For example, females are more easily recruited into surveys and experiments than men, and gender does influence the value of food. In this case the researcher will use statistical tools like regression analysis, that allow researchers to measure the particular manner in which a demographic is influencing the results. They can then transform the samples such that they behave as if they were a representative sample.
For example, let us suppose that the experiment sample consists of 80% females and 20% males. On average, females value a certain milk product at $2.00 while, on average, males value that same milk product at $1.00. Because females were 80% of the sample the average value of the milk for the sample is (0.8)($2.00) + (0.2)($1.00) = $1.80. However, if the U.S. population is half male and half female, the average value of the milk product would be (0.5)($2.00) + (0.5)($1.00) = $1.50. So even though the average value in the sample was not representative of the U.S., a number of statistical tools are available that make make the sample behave as ifit were representative.
Result #1
After the experiment was complete the agricultural economists set about calculating how average bids varied among the organic, non-rBST, and rBST milk, as shown below. Consumers clearly place a higher value on organic milk, valuing it at around $0.30 more per quart than the other two milk types. The value of milk with and without rBST is nearly identical, suggesting that consumers are largely indifferent as to whether the farmer uses the rBST hormone or not. Perhaps the presence of non-rBST milk does not lower the value of rBST milk?
Figure 1—Consumer willingness-to-pay for organic, non-rBST, and BST milk
Result #2
When the researchers investigated further they discovered some evidence that the presence of non-rBST milk indeed stigmatizes rBST milk, lowering its value. They recognized that when non-rBST milk was presented to the consumer first, and rBST milk second, the value of the rBST milk was much lower. This suggests than when consumers are first made aware that some farms do not use rBST, and are then presented with rBST milk, they penalize the second milk harshly. Moreover, once statistical tools were used to remove the effect of demographics and other variables (variables that could be neither controlled nor randomized), the discount assigned to rBST became even larger. Thus they concluded that selling non-rBST milk acts to lower the value consumers place on regular, rBST milk.
