A Vote-Buy Behavior Gap

Glynn Tonsor at Kansas State University has created a great resource for the readers of Feedstuff magazine.  Glynn writes a periodic column where he takes recent research from the academic literature and boils it down to a layman's perspective.  I was pleased to see he featured some work by Kate Brooks at the University of Nebraska and myself in his most recent column.  Here were the implications Glynn took from our research:

Implications: This study highlights the potential pitfalls of inferring public preferences from private choices. In this particular study private choices suggested stronger preferences than were reflected in public preferences for a ban restricting production practice options. Conversely, in other settings the opposite behavioral differences are observed. One of the clearest examples is the approximate 5% market share held by cage-free eggs (revealing that the majority of egg consumers are not willing to pay cage-free market premiums) and majority of residents expressing support in ballot settings for bans on laying hen cages. There are several reasons researchers may find the same individual to behave differently when making decisions as a food purchasing consumer than when making decisions as a voting resident. Identification of these reasons and the economic implications of these behavioral patterns are an area in need of additional research as there is a growing list of parallel examples that present complex dilemmas for livestock producers.

Research on The (lack of) Effectiveness of Bloomberg's Large Soda Ban

Much has been written about the merits or demerits of Bloomberg's large soda ban (here was my recent take on it in the New York Daily News).​

However, there has been much less actual research conducted to determine whether such restrictions might curb consumption or on how retailers might respond.  Well, some researchers from UC San Diego conducted a small scale study on the issue that was just published in the journal PLoS One.

What they showed is that food companies can get around the ban by offering bundles of smaller-sized drinks and that people respond in kind by buying more soda!  The study reminds me of what happened when San Francisco tried to ban giving away toys in Happy Meals; McDonalds decided to instead sell them for a very low price ($0.10).  

That's the problem with a lot of these regulations - people and companies find a way around them in ways that the regulator couldn't envision and, as this PLos ONE study shows, it might even lead to weight gains.  It's like squeezing a balloon - the air doesn't leave it just moves to a different place.  Banning large soda or Happy Meal toys doesn't diminish demand for these items, it just causes people to seek out alternative means to get them.  ​

Here is the study abstract:​

Objectives

We examined whether a sugary drink limit would still be effective if larger-sized drinks were converted into bundles of smaller-sized drinks.

Methods

In a behavioral simulation, participants were offered varying food and drink menus. One menu offered 16 oz, 24 oz, or 32 oz drinks for sale. A second menu offered 16 oz drinks, a bundle of two 12 oz drinks, or a bundle of two 16 oz drinks. A third menu offered only 16 oz drinks for sale. The method involved repeated elicitation of choices, and the instructions did not mention a limit on drink size.

Results

Participants bought significantly more ounces of soda with bundles than with varying-sized drinks. Total business revenue was also higher when bundles rather than only small-sized drinks were sold.

Conclusions

Our research suggests that businesses have a strong incentive to offer bundles of soda when drink size is limited. Restricting larger-sized drinks may have the unintended consequence of increasing soda consumption rather than decreasing it.

While the study findings are intriguing, it must be said that the study is far from perfect.  For example, the study involves a bunch of college students making a number of hypothetical choices.  I'd much prefer to see an experiment where people actually had to pay (and eat) what they bought.  Moreover, as the study authors readily acknowledge, the study doesn't reveal whether people would actually drink both sodas or just give one to a friend, nor did it differentiate between diet or full calorie soda.  Thus, there appears to be fertile ground for additional research. 

Fat taxes may be even less effective than previously thought

An article that just appeared in the most recent issue of the American Journal of Agricultural Economics by Yuqing Zheng of RTI and Edward McLaughlin and Harry Kaiser of Cornell University presents some interesting thoughts regarding fat and soda taxes.

Most of the studies on fat and soda taxes use elasticities of demand to simulate the effectiveness of a tax.  The elasticity of demand tells us how responsive consumption of a product is to a change in it's price.  So, for example, an elasticity of demand of -0.6 would tell us that for every 1% increase in price, consumption would fall by 0.6%

Zheng and colleagues point out, however, that most people don't "see" the tax when they're shopping.  It only shows up on the bill when you check out.  As such, it is incorrect to directly use the price elasticity of demand  ​to infer how consumption of soda or fatty foods will change after a tax.  

They show that an excise tax (​which is levied on the supplier rather than the consumer) is probably more effective at reducing soda (or fat) consumption than a retail sales tax, but even excise taxes are likely to to be less effective at reducing consumption than an equivalent price increase.  

As a result, researchers need to adjust the demand elasticities before calculating the effects of a soda or fat tax (regardless of whether the tax is excise or retail).  Yet, almost no one does this.  The researchers show, however, that the required adjustment can be fairly dramatic.  In their "baseline" scenario, they show that the elasticity of demand needs to be reduced by a factor of 0.14.  So, if the elasticity of demand was -0.6, then we'd project a 1% increase in sales tax would only reduce consumption by 0.6*0.14 = 0.084%.  Instead, previous research on this topic has applied the original elasticity (e.g., 0.6) rather than the adjusted elasticity (e.g., 0.084).  Clearly, the adjusted elasticity will imply much lower effectiveness of the tax.

The authors conclude:​

Therefore, even a large increase in the sales tax rate on food and beverages will only reduce demand by a moderate degree.

and

our analysis of sales and excise taxes offers some explanation (e.g., imperfect tax knowledge, slow learning) on why the impact of sales tax is so difficult to detect, thus bridging the gap between the simulation studies and the empirical findings

Do Small Reductions in Caloric Intake add up to Big Changes in Weight?

The answer is: probably not.​

​This is important question because there are many studies finding that various interventions (from fat taxes to menu labels) have very (though sometimes statistically significant) small effects on caloric intake.  Proponents of the policies are often undeterred - and say things like "well, a 20 kcal reduction every day can really add up to big weight loss over time."

As I've already discussed, some of this sort of analysis ​is based on the faulty logic that 3500kcal = 1lb.  But, as was mentioned in that post, our body does not react linearly to caloric changes in the fashion implied by this formula.  

Now, there's more on this topic by Trevor Butterworth in a well-written and catchy-titled post ​Sex And Lies! The Iffy Science Of Measuring Calories.  Here is a key excerpt:  

Hall was responsible for filling in the crucial measurements that elucidated one of the most widespread myths highlighted by Allison et al.: the idea that small, consistent changes in energy intake or expenditure will, over time, lead to large changes in weight. The assumption appears to have been based on the 1958 calculation by Max Wishnofsky that one pound of body fat gained or lost is equal to 3,500 kilocalories. This seemed to give people a convenient way to estimate weight loss through diet or exercise, while promising extremely convenient results. If you simply knocked off a 100 kilocalories from your energy intake each day—a ten-minute jog, or a mile walk—you'd end up losing over 50 pounds in five years. Little wonder that early proposals for soda and fat taxes promised to save Americans from themselves: pay a little more, consume a little less, watch a lot of weight disappear in a few years.

Hall first heard the claim listening to a dietician make a calculation for an obese patient. His intuition told him that this calculation was incorrect and would lead to exaggerated weight loss predictions. When he asked for a reference, he was pointed to a nutrition and dietetics textbook. "I subsequently found the mistake everywhere I looked." People weren't stopping to think "about the dynamic interaction between energy intake and expenditure, which is complicated," he says. What they failed to take into account was that "the rate of weight loss changes over time and is primarily determined by the imbalance between energy intake and expenditure—a value that also changes over time." To radically simplify his model, this means that cutting calories in your diet leads to a decreasing calorie expenditure, which in turn slows weight loss until weight eventually plateaus after a few years. "Of course," says Hall, "cheating on your diet will cause your weight to plateau much sooner." In the case of soda taxes, Hall and researchers at the US Department of Agriculture showed how static modeling overstated weight loss by 346 percent after five years.

Do People Want Calorie Labels on Menus?

On Tuesday evening, I was on air with Gil Gross who has a talk show on AM radio in San Francisco.  He wanted to talk about some research we recently published on menu-labeling.  I previously blogged about some of the results, but I wanted to re-mention something that came up during our talk.​

After discussing our finding that menus having only calorie information had no effect (they actually increased total calories ordered on average, though not significantly) and menus with a "traffic light" symbol had a small to moderate effect, the host asked whether people wanted these labels.  ​

Well, we actually asked precisely that question on a survey administered at the end of the meal.  ​Here is the exact phrasing of the question as it appeared on the 1-page survey.

We found 30.5% said they wanted a "menu with no nutritional information", 42% said they wanted a "menu with calorie contents of menu items listed", and only 27.5% said they wanted a "menu with a symbol to represent the calorie content of menu items."  ​

​So, curiously, the most popular option is the one that had zero effect (and if anything increased total calories).  The menu which actually lowered caloric intake was actually least preferred.  

On a last note, people sometimes take these kinds of survey questions to indicate what a business (or government) should do.​  That's not the right interpretation.  Just because consumers say they want labels doesn't mean it's good business (or good public policy) to provide them.  Labels cost money (and might change behavior in ways that cost money) that must be weighed against any benefits they provide.  Moreover, if consumers really want these labels, won't they frequent restaurants who voluntarily provide them?  Thus, there seems to be a clear incentive here for restaurants to provide the labels if they are truly demanded - and indeed many restaurants voluntarily do it already.