The non-price effects of soda taxes and bans

The American Journal of Agricultural Economics just published a paper I co-authored with Sunjin Ahn, who is a post-doc at Mississippi State University entitled “Non‐Pecuniary Effects of Sugar‐Sweetened Beverage Policies.” (for the non-economists out there, “non-pecuniary” just means non-price).

Here was our motivation for the study:

“There is some market evidence that passage of SSB [sugar sweetened beverage] taxes might generate outcomes beyond that predicted by price elasticities (or the pecuniary effects). Non‐pecuniary effects could amplify the effects of a tax, increasing the intended effects of the policy. In particular, the tax (and the debate and publicity surrounding it) could send information to consumers about the relative healthfulness of beverage options and send cues as to which choices are “socially acceptable”
...
Signaling and information effects associated with SSB taxes are only one potential non‐pecuniary effect, and it is possible that some non‐pecuniary factors, such as reactance, could dampen the effects of a tax, and in the extreme could result in outcomes opposite that intended by the policy. ... Reactance is thought to arise from perceptions of threats to individual freedom, among other factors (Brehm 1966). Thus, although it seems clear that non‐pecuniary effects might exist, the size and the direction of the effect is ambiguous. ”

We tackled this issue by conducting a series of experiments through surveys with consumers. We asked consumers to participate in a series of simulated grocery shopping exercises. Consumers first made choices between beverage options at a given set of prices, and then they were randomly allocated to different treatments where either:

• A) prices of SSB increased but respondents were not told why,

• B) prices of SSB increased and respondents were told it was a result of a soda tax,

• C) prices of SSB increased and respondents were told it was a result of a shortage of sugar beets and sugar cane,

• D) the size of SSB was reduced but respondents were not told why,

• E) the size of SSB was reduced and respondents were told the reduction was due to a government ban on large sized sugared sodas, or

• F) the size of of SSB was reduced and respondents were told the reduction was due to a plastic shortage.

By comparing how choices of SSBs change when people were told prices or size changes were a result of a policy vs. other non-policy factors, we can get a sense of the size and direction of the non-pecuniary effects.

When conducted our first study in 2016, we found significant results related to the SSB taxes. In particular, our results suggested people who were told price changes were a result of a tax were more likely to choose SSB than people who were not given a reason for the price change. We certainly weren’t the first to find such an effect. Here is a bit about previous research on this topic:

“Just and Hanks (2015) argued that consumers might respond with resistance when a new policy obstructs their ability to obtain their preferred option. They argued that the phenomenon arises because consumers are emotionally attached to consumption goods, resulting in reactance. Policies perceived as paternalistic might cause consumers to “double down” on purchases of forbidden or restricted goods (Lusk, Marette, and Norwood 2013). Just and Hanks (2015) constructed a model in which controversial policies such as a sin tax could lead to an increase in the marginal utility for a good, potentially leading to increased consumption even if prices rise. In addition, Hanks et al. (2013) found that demand for unhealthy foods under a tax frame increased while the demand for subsidized healthy foods fell. Similarly, Muller et al. (2017) found that almost 40% of low‐income individuals increased their share of expenditures on unhealthy food after an unhealthy food tax.”

When we sent the paper off for review, we received a number of valuable comments, which caused us to make a number of changes to our experiment, and repeat the study with some extensions in 2019. What did we find with these newer data? On average: nothing, nada, zilch. There was no significant difference in the average market share of SSBs across the various information treatments. However, we did find significant variability in the treatment effects, meaning some people choose more SSBs when they knew it was a tax/ban and others chose less; however, these variations were only partly explained by demographic effects. In summary, our results didn’t provide a clear answer on the question we sought out to address: non-pecuniary effects, to the extent they exist, seem to work in different ways for different people, making the net effect small and hard to identify, at least in our experimental setting.

A note on the publication process is worthwhile. Normally, it is very hard to publish null results. This is problematic for the advancement of science because it results in publication biases like the file draw problem. To the credit of Tim Richards, the journal editor, and the three anonymous reviewers at the American Journal of Agricultural Economics, we received a positive reaction and ultimately, after a more changes, acceptance for publication even though we failed to replicate our previous result and found null effects. This is really an example of peer-review working at it’s best.

Does a Good Diet Guarantee Good Health?

To be sure, dietary factors contribute to bad health at least some of the time for some people.  But, how large a role does diet play?  Stated differently: even if you eat well all the time, are you guaranteed to be free of cancer, heart disease, and diabetes?  Far from it according to two recent studies.  

The first was published Friday in Science by Tomasetti, Li, and Vogelstein, who investigated cancer causes.  When discussing the things that can cause cancer, causes normally fall into one of two broad categories: nature (environmental factors) or nurture (inherited genetic factors).  These authors, however, point to a third factor: as we grow, our cells naturally replicate themselves, and in the process, unavoidable DNA replication errors occur which ultimately lead to cancer.  The authors calculate that these replication errors or  

“mutations are responsible for two-thirds of the mutations in human cancers.”

Secondly, I ran across this interesting paper published a couple weeks ago in the Journal of the American Medical Association.  The authors attempted to ferret out how many deaths from heart disease, stroke, and type 2 diabetes (what the authors call "cardiometabolic deaths") that result each year annually come about from over- or under-consumption of certain types of foods.  As this critic pointed out, it is important to note that the authors estimates are associations/correlations NOT causation.  As such, I'd suggest caution in placing too much interpretation on the impacts from different types of food.  Nonetheless, there were a couple of other less-well-publicized results which I found interesting.

First, the authors found:

“In 2012, suboptimal intake of dietary factors was associated with an estimated 318 656 cardiometabolic deaths, representing 45.4% of cardiometabolic deaths.”

Stated differently, 54.6% of deaths from heart disease, stroke, and type 2 diabetes seems to be caused by something other than diet.   

The other result that I found interesting from this study is that there has been a big decline in so-called cardiometabolic deaths.  The authors write:

“Between 2002 and 2012, population-adjusted US cardiometabolic deaths per year decreased by 26.5%.”

Some of this decline, they argue, is due to reduced sugar consumption and increased nut/seed consumption from 2002 to 2012.

Why does all this matter?  Because these statistics help us understand the impacts of dietary and lifestyle changes.  To illustrate, let's take the above cancer statistic: 66.7% of cancers are caused by unavoidable replication errors. That leaves 33.3% of cancers, some of which are diet and lifestyle related and some of which are caused by inherited genetic factors.  For sake of simplicity, lets say you have zero risk from inherited genetic factors. Also note that the National Cancer Institute suggests that the chances of getting a new cancer in a given year are 454.8 per 100,000 people (or a 0.45% chance).  

Putting it all together, your chance of getting cancer from random errors in DNA replication is 0.667*0.45%=0.30%, and your chance of getting cancer from diet and lifestyle factors (assuming no inherited risks) is 0.333*0.45%=0.15%.  So, even if you could completely eliminate the cancer risk from diet and lifestyle factors, you'd go from a 0.45% chance of getting a new cancer to a 0.30% chance, a reduction of 0.15 percentage points.

The intractability of the soda tax debate

This recent article claims that the new soda taxes in Philadelphia are causing a larger than expected drop in soda sales.  

Did that piece of news change your mind on whether the soda tax is a good or bad idea?  My guess is: probably not.  As humans, we're adept at finding ways of confirming our prior beliefs and positions.  That is, we suffer from various forms of confirmation bias.  

Let's take the above story at face value: after the tax was implemented, we find a large reduction in soda consumption.  What are the expected reactions by the competing camps? (note: by definition, a large reduction in soda consumption implies that the receipts from the tax are smaller than expected as people are avoiding the tax by buying less soda).

The pro-tax folks would say:

• "Ah-ah!  This simple solution has a big public health benefit.  It got people to stop consuming all those useless, empty calories, and now we'll finally make headway on obesity and diabetes.”

• “This big drop in consumption was accomplished without costing consumers much.  In fact their expenditures on soda fell!  Now they have more money to spend on healthier items.”  

The anti-tax folks would say:

• “We told you this tax policy would cost jobs.  Nobody is buying soda anymore, and people will have to be laid off at the beverage manufacturing plants and the beverage distributors.”
• “You promised that the tax would fund public education but there aren’t enough new tax receipts to fund any new programs or to give teachers meaningful raises.”
• “People may have stopped buying soda, but look now they’re buying more [insert the untaxed, unhealthy food of your choice here].  

Now, instead imagine the opposite case was observed.  Suppose that after the tax was implemented, we find no (or a small) reduction in soda consumption.  What are the possible reactions by the competing camps? (note: by definition, a small reduction in soda consumption would imply that the receipts from the tax are higher than expected – the government is raking in money as people are still buying soda and paying the tax).

The pro-tax folks would say:

• “Look at all the new money we’ve raised to finally get to work on [insert your favorite public program or cause here].”
• “We're finally making "Big Soda" pay for all the costs they've been imposing on society.”
• "The soda tax is just one small part of an overall plan to reduce obesity and improve public health." 

The anti-tax folks would say:

• “This policy created a bureaucratic agency to oversee the tax, increased the size of government, and look, it didn’t have any impact on obesity or public health as promised.”
• “We told you this was a regressive tax.  The majority of the new tax dollars being generated are being paid by lower income households.”
   

This sort of conundrum shows that it is hard to have an intellectually honest debate about the evidence.  It also suggests that policy advocacy (or policy opposition) is often more about competing values or philosophies than it is about empirical evidence (after all, both sides claim to want evidence-based decision making). In general, I think it is troubling if someone can't answer the question: "What evidence would it take to convince you that you were wrong?"

As more locations - from Seattle to Santa Fe - are considering the adoption of soda taxes, it would be useful if folks stated, before adoption takes place, what outcomes would or would not support their initial opposition or advocacy to the tax.  Because right now, any post-tax outcome can be interpreted as evidence in favor of either position. Or, just be honest, and say that opposition or advocacy for the tax is not an evidence-based position, but rather one based on some underlying philosophy or set of values.

As for me, I'll admit that much of my opposition to soda taxes is indeed value-based based.  I tend to favor freedom of choice and limited government, and I haven't been convinced by the market-failure arguments that would justify the tax.  Now, let me put that to the side and say that most of my writing on the subject has argued that, empirically, soda taxes are unlikely to have much effect on obesity/diabetes rates.  As a result, I see the policy as an ineffective means to achieve the desired end (by the way if we want to fund more public education, there are likely more efficient was of doing that than taxing soda).  Moreover, if it is true that the tax doesn't much change consumption, it implies consumer demand is relatively inelastic, which also implies that the tax burden primarily falls on the consumer rather than the producer (note: economic theory indicates that it doesn't matter whether the tax is technically imposed on the producer or the consumer - it is the underlying elasticities of supply and demand that determine who actually bears the burden of the tax). So, if the claim in the above article is true and the soda tax has a "large" effect on soda consumption, that would undermine many of my empirical arguments against the soda tax.  

But, I'm not sure that evidence showing that a soda tax had a large reduction in soda consumption would turn me into a tax advocate.  After all, if you showed me that a tax on broccoli caused a large reduction in broccoli consumption, I wouldn't suddenly become a broccoli-tax advocate.  Rather, I think the kind of evidence I'd find more persuasive, if one wanted to substantively more me away from an anti-soda tax position, is evidence that soda consumption causes an externality (and "no" the presence of Medicare/Medicaid is not evidence of an efficiency-reducing externality) or that, in this particular case, there were substantively perverse information asymmetries (although the appropriate policy here is probably information provision not a tax), or behavioral biases that citizens themselves want "corrected" via government action (just because a soda tax passes with more than 50% of the vote doesn't really "count" as evidence here because many of the people who vote in favor of the tax don't consume much taxed soda).  

Banning Soda Purchases Using Food Stamps - Good idea or bad?

According to Politico:

“The House Agriculture Committee this morning is delving into one of the most controversial topics surrounding the Supplemental Nutrition Assistance Program: whether to limit what the more than 40 million SNAP recipients can buy with their benefits. Banning SNAP recipients from being able to buy, say, sugary drinks has gotten some traction in certain public health and far-right circles, but it looks like the committee’s hearing will be decidedly open-minded on the debate. ”

I've written about this policy proposal several times in the past.  It's an example of good intentions getting ahead of good evidence.  Do SNAP (aka "food stamp") participants generally drink more soda than non-SNAP participants?  Yes.  Is excess soda consumption likely to lead to health problems?  Yes.  But, will banning soda purchases using SNAP funds reduce soda consumption.  Probably not much.  

In fact, I just received word that the journal Food Policy will publish a paper I wrote with my former Ph.D. student, Amanda Weaver, on this very topic.  First is the logical (or theoretical) argument:

“In public health discussions, however, the conceptual arguments related to the Southworth hypothesis have received scant attention (see Alston et al., 2009, for an exception). A soda consuming SNAP recipient who spends more money on food and drink than they receive in SNAP benefits can achieve the same consumption bundle regardless of whether SNAP dollars are prohibited from being used on soda by rearranging which items are bought with SNAP dollars and which are bought with other income. Thus, an extension of the Southworth hypothesis to this case would predict little or no effect of a soda restriction as long as the difference in total food spending and SNAP benefits does not exceed spending on sugar-sweetened beverages. ”

If that wasn't transparent, consider the example I gave in this paper I wrote for the International Journal of Obesity:

“To illustrate, consider a SNAP recipient who receives $130 in benefits each month and spends another $200 of their own income on food for total spending of $320. Suppose the individual takes one big shopping trip for the month and piles the cart with food, including a case of Coke costing $10. Suppose the cost of all the items in cart comes to $320. SNAP benefits cannot cover the entire amount, but the individual can place a plastic divider on the grocery conveyer belt, put $130 on one side (to be paid for with the SNAP benefits), and put $200 on the other side (to be paid for with cash). Now, suppose there is a ban on buying soda with SNAP. What happens? The individual can simply move the $10 case of Coke from the SNAP side of the barrier to the cash side and replace it with other items worth $10. The end result is the same regardless of whether the SNAP restriction is in place or not: spend $320 and Coke is purchased. ”

So, in theory, people can "get around" these sorts of SNAP restrictions very easily making the restriction ineffectual.  

Now, back to my Food Policy paper.  Our experiment results show the following: 

“As conjectured by H3, for the 65% of participants (78/120) who did not consume soda in T3, soda expenditures were unaffected soda restriction. H4 posited that consumers who had expenditures of more than $2 (including a soda purchase) in T3 would likewise be unaffected by the soda restriction as they moved to T4. However, this hypothesis was rejected (p<0.001). Soda expenditures fell from an average of $1.000 to $0.588, contrary to the theoretical prediction. We find that 58.8% (20/34) of the respondents to which the hypothesis applied behaved as the theory predicted (they did not change soda expenditures); however, the remaining 41.1% (14/34) reduced soda expenditures when moving from T3 to T4. ”

So, maybe restrictions on soda purchases by SNAP recipients will affect their soda consumption after all.  Here are our thoughts on that:

“Previous research has identified heterogeneity in cognitive abilities and in consistency with economic theories (Choi et al., 2014; Frederick, 2005), and future research might seek to explore the extent to which cogntive ability plays a role in the ability of extramarginal consumers to recognze that they can achieve the same consumption bundle despite the soda restriction. In addition, our experiment was a one-shot game. In a field environment, respondents can talk to friends, gain experience, and alter behavior over time as they learn that the same consumption bundle can be achieved despite the restriction. This learing conjecture could be tested in an experimental setting by conducting repeated trials with feedback. It could also be tested using field data (after a policy was passed) by investigating the change in soda purchases for inframarginal buyers over time. Another hypothesis that could explain the anomolous result is that the soda restriction could have non- pecuinary effects, providing information about realtive healthfulness of items or signaling what people “should” be doing. For example, Kaplan, Taylor, and Villas-Boas (2016) found that, following a widely publisized vote to tax sodas, Berkeley California residents reduced soda consumption before the tax was even put into place, illustrating significant information effects surrounding soda consumption policies. Future research could further explore this signaling effect by including a treatment that restricts purchases of food items not generally percieved as unhealthy or by including survey questions about percieved healhfulnes of an item before and after a restriction.”

Another thing to keep in mind is that such restrictions may limit people's willingness to participate in SNAP in the first place.  Even in our experimental context, we find that soda restrictions do indeed affect participation as measured by use of the "coupon" or "stamp" (both whether it is used at all and the amount of the coupon used).  

All in all, I think the above discussion shows that despite the intuitive appeal of a simple policy restricting SNAP purchases, the actual consequences are likely to be much more complicated. 

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.”