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When Consumers Don't Want to Know

Since I first started working on the topic of animal welfare, I've had the sense that some (perhaps many?) consumers don't want to know how farm animals are raised.  While that observation probably rings intuitively true for many readers, for an economist it sounds strange.  Whether we're talking about GMO labeling, nutritional labels, country of origin labels on meat, or labels on cage free eggs, economists typically assume more information can't make a person worse off.  Either the consumer uses the information to make a better choice or they ignore it all together.    

There is a stream of literature in economics and psychology that is beginning challenge the idea that "more information is better."  One simple explanation for the phenomenon could be that consumers, if they know for sure they will continue to consume the same amount of a good, could be better off ignoring information because the information could only lower their satisfaction (perhaps because they'll feel guilty) for doing something they've already committed to doing.  In this paper by Linda Thunstrom and co-authors, 58% of consumers making a meal choice chose to ignore free information on caloric content, a finding that Thunstrom calls "strategic self ignorance" arising from guilt avoidance. 

Another possible explanation that I've previously published on is that, when people have limited attention, more information on topic A might distract people from a topic B, even though topic B ultimately has a larger impact on the consumers well-being.  

It may also be the case that people want to believe certain things.  They derive satisfaction from holding onto certain beliefs and will avoid information that challenges them.  These ideas and more are discussed by Russell Golman, David Hagmann and George Loewenstein in a nice review paper on what they call "information avoidance" for the Journal of Economic Literature.

A graduate student in our department, Eryn Bell, has been working with Bailey Norwood to apply some of these concepts to the topic of animal welfare.  They conducted a survey of 1,000 Oklahomans and asked them one of the two simple questions shown below.  Depending on how the question was asked, from 24% to 44% of respondents self declared that they would rather NOT know how hogs are raised.  The primary reasons given for this response were that farmers were trusted (a belief consumers may prefer to hold), that there are more important issues to worry about (limited attention), and guilt aversion. 

In the same survey, Bell and Norwood also included a set of questions based on some ideas I suggested.  The question gave respondents the option to see a picture of how sows are raised or to simply see a blank screen for a certain period of time.  People were divided into three groups that varied how long they had to see the blank screen.  The idea was that we could use the waiting time as a "cost", which would allow us to ask: how long are people willing to wait to NOT receive free information?  As it turns out, people weren't very sensitive to the waiting time.  Nonetheless, regardless of the waiting time, about a third of respondents preferred to see an uninformative blank screen as opposed to a more informative screenshot of sow housing.  These findings suggest at least some people, at least some of the time, would prefer not to know.  

When behavioral biases meet the market

Have you ever gone shopping, only to be overwhelmed by the number of options available to choose from?  You're not alone.  In fact, psychologists have created a name for the phenomenon: the "excessive choice effect."  In one of the more famous studies on the topic, aptly titled "When choice is demotivating", the authors found that when consumers were offered the opportunity to buy an exotic jam, 30% bought when only 6 varieties were presented.  However, only 3% of consumers bought when 24 variety were presented.  On the face of it, this seems to violate basic economic logic: when there are more varieties available, there is a greater likelihood of finding one you like, and thus there should be a higher likelihood of purchase.  

These sorts of findings have led to popular books (like this one titled The Paradox of Choice) and some bold claims that we'd all be happier and our society would have less depression if we (or namely the government) restricted our choice and freedom.  

Well, as it turns out, subsequent studies found that the "excessive choice effect" doesn't always exist, and the phenomena is much more nuanced than first suggested.  

Now, enter of of my Ph.D. students, Trey Malone (who is on his way to an assistant professor position at Michigan State University).  Our co-authored paper on this topic was just released by the Journal of Behavioral and Experimental Economics.  Trey's insight was this: if the "excessive choice effect" (or ECE) exists, surely companies will want to do something about it.  It's bad business to present consumers with so many options that they don't make a purchase.  Yet, in many markets (and in particular in the market for craft beer which was the focus of our study), there is an apparent explosion of variety of choice.  What's going on?  

From the paper:

In a competitive market, the choice architecture is endogenous, and sellers compete to provide environments that consumers find appealing, thereby increasing profits. In such cases, the market, at least partially, provides incentives to ameliorate the ECE by, for example, reducing search costs for consumers (e.g., see Kamenica, 2008; Kuksov and Villas-Boas, 2010; Norwood, 2006). This raises the possibility that ECE may arise in laboratory contexts or oneshot field experiments while at the same time having limited relevance in day-to-day business decisions. Whereas prior research mainly focus on the identification of an ECE, we show that sellers have access to market-specific mechanisms (or informational nudges) that narrow its influence. We demonstrate that if the ECE exists, sellers can mitigate or exasperate its negative effects through targeted interventions.

The interventions (or private nudges) that we consider were beer sellers providing consumers more information about the varieties either through a "special" or the provision of beer advocacy scores.  

Trey worked with a local wine bar in town to run field experiments. Unbeknownst to the patrons, we strategically varied the number of options on the beer menu over time.  The menu either presented 6 or 12 options (note that the menu of 12 included all 6 of the varieties on the smaller menu).  And, we also varied information about the beers as previously indicated, sometimes there was no extra information (the control) and other times we tried to reduce search costs by labeling one of the options a "special" or by providing beer advocacy scores for each option (these are akin to a quality rating by a reliable third party).  

The results are summed up in the following graph:

Thus, we found that the excessive choice effect was alive and well in a real-life purchase setting (people were more likely to NOT buy a beer when there were 12 options as compared to 6), but only when no extra information was provided.  The effect reversed itself when the menu included beer advocate scores. These results show how the excessive choice effect might be turned on and off by companies manipulating search costs.  

One of the main lessens here is that it would be a mistake to take a finding of a supposed "behavioral bias" (like the excessive choice effect) in a laboratory experiment to make grand claims for large government interventions without also considering how consumers and businesses themselves might react to those very same biases in the course of everyday life.  

Do you plan to spend more or less eating out in the next two weeks?

The title of this post is based on a question I ask of food consumers every month in my Food Demand Survey (FooDS).  If I had to guess your response, I'd go with "spend less."  Why?  Because every month, for almost four years, that has been the average response to the question (the exact question is: "Do you expect to spend more or less on food bought during grocery shopping in the next two weeks as compared to the previous two weeks?" and response categories are: "I plan to spend about . . . 10% less, 5% less, the same, 5% more, or 10% more").   

FAFHanticipate.JPG

Here is the problem with the above results.  They are almost certainly false.  If people are continually, month after month, saying they plan to spend less on food away from home, the cumulative effect would ultimately be a negative amount of spending.  

Moreover, another question I ask on the survey relates to how much the respondent says they spend (in dollars) on food away from home (exact question wording: "What has been you (or your household's) usual WEEKLY expense for meals or snacks from restaurants, fast food places, cafeterias, carryout or other such places?"  The response categories are: less than $20, $20-$39, . . . $140-$159, $160 or more).  

In the most recent issue of FooDS, we estimate the average level of spending on food away from home in January 2017 was $53.26/week.  The average answer from the previous month (December 2016) was $50.89/week.  So, in terms of stated expenditure, there was a $53.26-$50.89=$2.37 increase (or a (2.37/50.89)*100=4.66% increase). Yet, (and here is the problem), In December 2016, people said they planned to reduce spending on food away from home by, on average, -0.59%, and in January 2017, they said they plan to reduce spending on food away from home by, on average, -1.47%.

Here is what I get if I calculate "actual" changes in reported levels of spending on food away from home against people's stated plans to increase or decrease spending (the blue bars are the same blue bars as in the above graph, they just look different because the vertical axis has been re-scaled).       

So, what is going on here?  One possible answer is that consumers suffer from a type of self-control problem.  We tell ourselves we want to reduce the amount we're spending on food away from home in the future.  But, when the future arrives, we forget our plans and have fun eating out with our friends and keep spending as usual.  If this is correct, eating out is a sort of "guilty pleasure" - something we enjoy but wish we could force our future selves to cut back on.     

The propensity of an individual to say they plan to reduce spending on food away from home relates to a variety of demographic variables (even after controlling for the month-to-month effects that may be driving changing spending patterns).  Income is a major determinant.  Lower income people are much more likely to say they plan to reduce spending on food away from home than higher income respondents.  Indeed, for the highest income households, there is no consistent upward or downward bias in planned spending patterns for food away from home.  Other (smaller) determinants include gender, age, and participation in food assistance programs with women, older, and SNAP participants being more likely to say they plan to reduce spending on food away from home.

A less nefarious explanation for the above phenomenon might be that our survey is conducted in the middle of the month, and if people are paid at the beginning of the month (or at the end of the previous month), then there might be less remaining in the food budget for "splurges" like spending on food away from home by the time the middle of the month arises and they rationally plan to spend less in the following two weeks.  

I doubt this is true for two reasons.  The first is that results from other surveys back up the "self control" explanation.  For example, this article in the Wall Street Journal a couple years ago pointed to a survey of higher income consumers that asked what kept them from saving more money each month.  The most common answer, given by 68% of respondents, was "dining out".  The second reasons is that we observe no such phenomenon in our survey for stated changes in spending on food AT home.  Here is the average response each month for how consumers expect to change spending on food at home.  As can be seen, the value goes up and down and is neither consistently negative or positive.     

If you have other explanations for why people consistently say they plan to spend less eating out next month, I'd love to hear them.

What's going on in your brain?

Ever wonder why you choose one food over another?  Sure, you might have the reasons you tell yourself for why you picked, say, cage vs. cage free eggs. But, are these the real reasons?

I've been interested in these sorts of questions for a while, and along with several colleagues, have turned to a new tool - functional magnetic resonance imaging (fMRI) - to peak people inside people's brains as they're choosing between different foods.  You might be able to fool yourself (or survey administrators) about why you do something, but you're brain activity doesn't lie (at lest we don't think it does).  

In a new study that was just released by the Journal of Economic Behavior and Organization,  my co-authors and I sought to explore some issues related to food choice.  The main questions we wanted to know were: 1) does one of the core theories for how consumers choose between goods of different qualities (think cage vs cage free eggs) have any support in neural activity?, and 2) after only seeing how your brain responses to seeing images of eggs with different labels, can we actually predict which eggs you will ultimately choose in a subsequent choice task?   

Our study suggests the answers to these two questions are "maybe" and "yes".  

First, we asked people to just look at eggs with different labels while they were laying in the scanner.  The labels were either a high price, a low price, a "closed" production method (caged or confined), or an "open" production method (cage free or free range), as the below image suggests.  As participants were looking at different labels we observed whether blood flow increased or decreased to different parts of the brain when seeing, say, higher prices vs. lower prices.  

We focused on a specific areas of the brain, the ventromedial prefrontal cortex (vmPFC), which previous research had identified as a brain region associated with forming value.  

What did his stage of the research study find?  Not much.  There were no significant differences in brain activation in the vmPFC when looking at high vs. low prices or when looking at open vs. closed production methods.  However, there was a lot of variability across people.  And, we conjectured that this variability across people might predict which eggs people might choose in a subsequent task.  

So, in the second stage of the study, we gave people a non-hypothetical choice like the following, which pitted a more expensive carton of eggs produced in a cage free system against a lower priced carton of eggs from a cage system.  People answered 28 such questions where we varied the prices, the words (e.g., free range instead of cage free), and the order of the options.  One of the choices was randomly selected as binding and people had to buy the option they chose in the binding task.  

Our main question was this: can the brain activation we observed in the first step, where people were just looking at eggs with different labels predict which eggs they would choose in the second step?

The answer is "yes".  In particular, if we look at the difference in the brain activation in the vmPFC when looking at eggs with a "open" label vs. an "closed" label, this is significantly related to the propensity to choose the higher-priced open eggs over the lower-priced closed eggs (it should be noted that we did not any predictive power from the difference in vmPFC when looking at high vs. low priced egg labels).  

Based on a statistical model, we can even translate these differences in brain activation into willingness-to-pay (WTP) premiums:

Here's what we say in the text:

Moving from the mean value of approximately zero for vmPFCmethodi to twice the standard deviation (0.2) in the sample while holding the price effect at its mean value (also approximately zero), increases the willingness-to-pay premium for cage-free eggs from $2.02 to $3.67. Likewise, moving two standard deviations in the other direction (-0.2) results in a discount of about 38 cents per carton. The variation in activations across our participants fluctuates more than 80 percent, a sizable effect that could be missed by simply looking at vmPFCmethod value alone and misinterpreting its zero mean as the lack of an effect.

The Rise of “Nudge” and the Use of Behavioral Economics in Food and Health Policy

The Mercatus Center just published a short piece I wrote on the the application of behavioral economics to food policy.  Here are a few excerpts:

The rising popularity of applying behavioral economics in policymaking—or the creation of policies that “nudge” people into changing their decisions—might seem a bit odd to a food company executive. After all, advertisers and marketers have been using psychological insights for decades to encourage consumers to buy and pay more. Yet a number of bestselling books on the topic of behavioral economics have been published in the last decade, such as Nudge, Predictably Irrational, and Thinking Fast and Slow, and insights from the field are increasingly influencing policy discourse. So while behavioral economics might be seen as simply the merger of economic and psychological insights, it must also be partially understood as an attempt to influence the way government interacts with citizens. While marketers use psychological insights to boost company profits, advocates of the nudge argue that these same insights might be used by government to increase consumers’ well-being.

and 

It is commonly argued that governments should be allowed to enact paternalistic policies and nudge consumers because businesses do it all the time—such policies would supposedly level the playing field. It is of course true that we are constantly bombarded by advertisements and private nudges. But there is a crucial difference between government and private-business nudges. That difference is the role that competition plays in encouraging businesses to respond to consumers. When we are bamboozled or misled by a company in a way we ultimately dislike, we stop buying its product or find a new supplier. This knowledge often (though not always) constrains companies that fear the loss of reputation that might come from undertaking actions that work against their consumers’ desires. These same incentives prompt entrepreneurs to develop better alternatives. Government, with its power to mandate and coerce, lacks the intense competitive pressures provided by the profit motive. None of this is to say that people might not come to accept and appreciate certain forms of government paternalism (who among us now bristles at seat belt laws?), it is only to say that the fruitful application of behavioral economics to food policy is much more complicated than is often supposed.

I also point out what I think is a key asymmetry: behavioral economic results are almost always used to advocate for more regulation and intervention, but at least some behavioral economic results could be interpreted to have the opposite implication.  I also give an assessment on how behavioral economics can be fruitfully used by governments and companies alike.