How Fat Taxes Affect the Rich and the Poor

I'm pleased that the Economic Journal has decided to publish the paper Distributional Impacts of Fat Taxes and Thin Subsidies I wrote with  Laurent Muller, Anne Lacroix, and Bernard Ruffieux of the University of Grenoble and the French National Institute for Agricultural Research.  

Here is an excerpt

“How do the price policies differentially affect women at different points in the income distribution? Beliefs about the relative effects of fat taxes and thin subsidies on the poor relative to the non-poor are often premised on two assumptions. First is the assumption that the poor consume less healthful diets than the non-poor, perhaps due to the higher costs of more healthy diets (e.g., Drewnowski and Specter, 2004). The second assumption is that price policies are more likely to benefit low income consumers because low income consumers have more room for improvement, and because of their financial situation, they are likely to be more responsive to price changes. In short, a common view is that price policies can help the poor “catch up” to the non-poor in terms of the healthfulness of their diets.

Our experimental results confirm the first assumption: poor women tended to purchase less healthy food than the non-poor women. The implication is that, holding initial consumption patterns constant, policies which tax unhealthy food and subsidise healthy food will be regressive, favouring the non-poor more than the poor. But, people can change consumption patterns in response to price policies. If the poor are more responsive to price policies than are the non-poor, then inequalities will be dampened. This hypothesis, however, was rejected. Behavioural adjustments to the price policies amplified rather than dampened the divergent fiscal impacts of the price policies.”

In short:

“The tax/subsidy policies serve to widen the gap between the poor and non-poor, increasing the inequality in health and fiscal outcomes. Fat taxes cause the poor to pay disproportionally more for food than the non-poor and thin subsidies primarily flow to the non-poor. These effects occur because the non-poor already consume healthier diets but also because the non-poor are more price responsive than the poor”

Our approach to addressing this issue is quite different than that of previous studies.  Here's what's unique about our appoarch

“The advantage of the experimental set-up is that people’s choice behaviours are directly observed (rather than inferred as in a simulation study). In addition, the setting does not require the use of econometric models to infer behavioural responses. There is no need to assume a functional form or structure for responses; each individual can respond in their own unique way according to their own preferences. The experiment attempts to measure the overall fiscal effect (based on a day’s food choices) rather than simply focusing on one or two foods or a few food product categories. The experiment environment also allows us to study larger price variations (+/- 30%) than would likely have been feasible outside the lab, and as such, makes the price changes particularly salient.”

Here is one of the key figures from the paper.  The figure shows the distribution of price indices (i.e., the relative change in prices paid) after the introduction of a combined unhealthy-food-tax and healthy-food-subsidy policy for low income women as compared to a reference group (i.e, "normal" income women).

The Laspeyres index calculates the change in prices paid relative to the initial pattern of consumption; the Paasche index is similar except that it weights prices paid using the new pattern of consumption.  A greater difference between the two indices reveals greater substitution and responsiveness to the policy.

The figure above shows that 25-30% of  the low income consumers paid more for food after the price policy (they had an index greater than 100), and given the similarity of the two red lines, were less responsive (perhaps because of being more habit prone) than the richer consumers.  Moreover, at the individual level, the Paasche index was higher than the Laspeyres index for 35.9% of low income individuals.  These individuals did not shift their diet in the intended direction.

We ended the paper as follows:

“Whatever health benefits these policies might create, this paper suggests they need to be weighed against the adverse monetary effects they have on some of the poorest people in society.”

Food, farm, and kitchen innovations

 A few links I've come across recently on food, farm, and kitchen innovations:

• Probiotics for seeds?  "Researchers are testing more than 2,000 different microbial seed coatings on half a million test plots in the U.S."
• No more grocery store checkout lines?  "The concept . .  will allow grocery store customers to skip the check-out lines and instead scan items with their phones as soon as they stuff them into their cart."
• Hand-held food scanners to indicate nutritional content
  • "Hold it about half an inch from homogeneous food — food with the same texture as a glass of OJ, as opposed to mixed vegetables — and the sensor compares the near-infrared signature with patterns stored in the cloud. It will relay nutrient info to your phone via BLE (Bluetooth low energy) and create a food log in the DietSensor app. Snap a pic with your phone to complete the process. Calories, carbs, protein, fat, and alcohol levels are covered.  At the very least, it handles the record-keeping hassle."
• Run your whole kitchen through an app on your phone?  
• Wine dispensers
  • " Simply take a vial of wine and turn it upside down into the top of the machine. An embedded chip in the vial tells the machine what type of wine it is. Then, the machine chills the wine (red or white) to the optimal temperature, aerates it, and dispenses it into a glass below."

Immigration and agriculture

Diana Prichard, who runs the Righteous Bacon blog, alerted me to a project she's working on to create a documentary highlighting the important relationship between immigration and agriculture. 

“Immigration Feeds America

77% of farmworkers in the U.S. are immigrants. Loss of even half of foreign born dairy workers alone would result in an estimated 33% increase in milk prices—and immigrants are not only working in dairy. They grow our nation’s fruit and vegetables; raise our poultry, pork, beef and lamb; shepherd flocks of sheep that produce our wool; and produce the trees, shrubs and flowers that grace our front lawns.

But you won’t hear about these contributions on the campaign trail, and most media portrays them as helpless and voiceless. Farmworker, a debut documentary and companion publication by award-winning journalist Diana Prichard is working to change that—but we need your help. ”

Learn more and donate here.

Farmers markets and food safety

Last spring, I noted that Marc Bellemare from he University of Minnesota gave a provocative seminar in our department on the relationship between farmers markets and foodborne illness.  This weekend, the Marc discuss the research in a piece for the New York Times. 

Here is the main finding:

“As we will report in an updated version of an unpublished working paper released last summer, we found correlations that, in statistical parlance, are too robust to ignore. First, we found a positive correlation between the number of farmers markets per capita in a given state and in a given year and the number of reported outbreaks, regardless of type, of food-borne illness per capita in that state that year. Then, we found a similar positive correlation between farmers markets per capita and reported individual cases of food-borne illness per capita.”

And,

“And even if our results did identify a causal relationship between farmers markets and food-borne illness, it would not be possible to identify the precise mechanisms through which this happens, and it would be a critical mistake to conclude that the foods sold at farmers markets are themselves to blame. That is because most cases of illness are caused by consumers who undercook or fail to wash their food. Indeed, our results may suggest that many people erroneously believe that food bought at farmers markets needn’t be washed because it is “natural.””

Food Demand Survey (FooDS) - January 2016

The January 2016 edition of the Food Demand Survey (FooDS) is now out.

Here are a few highlights from the regular tracking portion of the survey:

• Willingness-to-pays (WTP) for all meat products, except pork chops, were down a bit this month compared to last, but were generally higher than was the case a year ago.  The changes in WTP were generally small and within the margin of error (which varies across meat products but is typically about +/- 7%).  
  • On a related note, my paper with Glynn Tonsor, where we used these WTP choice data to estimate demand inter-relationships is now finally out in the journal Applied Economic Perspectives and Policy (I previously discussed that paper here)
• There was a large drop in plans to eat away from home in January compared to December.
• There was also a large drop in awareness of E Coli and Salmonella in the news, and a small drop in concern for these issues as well (a likely Chipotle effect).  The same pattern of results was also true for GMOs and antibiotics.  
• Two different questions suggested an uptick in concern for farm animal welfare at the beginning of 2016.

Three new ad hoc questions were added to the survey this month.

The three questions inquired about consumers’ perceptions of taste, health, and safety of the eight different food products for which we track WTP.  The first question asked: “How tasty or untasty do you consider the following products, where -5 is very untasty and +5 is very tasty?” Participants were asked the same questions twice more, only the words “tasty or untasty” were replaced with “healthy or unhealthy” and “safe or unsafe”.

Chicken breast was, on average, perceived as most healthy and as the most tasty. While beans and rice were perceived as the safest option, it was also the least tasty of the eight choices. Participants perceived deli ham was, on average, one of the least healthy, least tasty, and least safe products. Pork chop and chicken wing fell in the middle for each of the three categories. On average, all six meat products were perceived as less safe than the two non-meat products.

The average perception of taste can be plotted against average perceived health or
average perceived safety.

There is a slight positive correlation between perceived taste and health (correlation
coefficient of 0.15).  Similar plots reveal a slight negative correlation between perceived taste and safety (correlation coefficient of -0.14) and a strong positive correlation between perceived health and safety (correlation coefficient of 0.83).   All of this of course is at the aggregate level; plots like this could be created for each and every one of the 1,000 respondents.

What the above graph shows is that although beef products rate relatively well in terms of taste, they fall well below chicken breast in terms of perceived health.  I can use my demand model estimates (the model that gives rise to the WTP values) to do some thought experiments.  What if ground beef was perceived as healthy or as tasty as chicken breast?  How much would WTP for ground beef increase?  

First, we have to ask how much people value improvements in taste, health, and safety.  My model estimates suggest, unsurprisingly, that the higher the perceived taste, health, and safety, the higher the WTP for a product. But, by how much?  I find that a 1 unit increase in perceived taste (on the -5 to +5 scale) has about twice the impact on WTP as a 1 unit increase in safety (again on the -5 to +5 scale) and about the 1.4 times the impact on WTP as a 1 unit increase in perceived health (again on a -5 to +5 scale).  So, changes in perceived health have a bigger impact than changes in perceived health, which in turn has a bigger impact than changes in perceived safety.

All that would seem to suggest that  meat industry organizations would want to focus on improvements in perceived taste.  And that's true.  Increasing the perceived taste of pork chops by 1 unit, for example, would increase WTP by $0.36, whereas increasing perceived health by one unit only increases WTP by $0.25 (note: the mean WTP for chops was about $3.94 this month).

But, it is also important to note that there are larger differences in perceived healthiness across the meat products than there is in perceived taste or safety.  This leads me back to the question I asked earlier: What if ground beef was perceived as healthy or as tasty as chicken breast? How much would WTP for ground beef increase?  Here are my projections based on the model estimates and average perceptions.  

If ground beef had the same average taste perceptions as chicken breast, WTP for ground beef would increase $0.09.  If ground beef had the same average health perceptions as chicken breast, WTP for ground beef would increase $0.45.  If ground beef had the same average safety perceptions as chicken breast, WTP would increase $0.11.  For reference, average WTP for ground beef was $4.36 this month.  

The last thing I'll note is that it's not all about perceived taste, health, and safety.  Average WTP for steak, for example, is about $7.43 whereas average WTP for chicken breast is only $5.34.  How is it that people are willing to pay more for steak than chicken breast when they tell us that they think chicken breast is tastier, healthier, and safer?  The answer is that people care about other stuff than just these three things.  There's just something that makes a steak a steak and a chicken breast a chicken breast that is hard to put in words.  Call it "steakyness"  (not to be confused with the popular dance move).  Of the roughly $2 premium people are willing to pay for steak over chicken breast, about 20% can be explained by taste, health, and safety perceptions, and the other 80% is a desire for "steakyness."