Berkeley Soda Tax

There have been a number of news stories about this new paper in the American Journal of Public Health that studied the impact of Berkeley's new sugar-sweetened beverage tax (aka "soda tax").  The authors surveyed residents of Berkeley before and after the implementation of the tax and asked about beverage consumption.  They also surveyed people in Oakland and San Francisco (who were presumably not affected by the tax) before and after the tax.  By comparing these two groups before and after, the authors can calculate something like a difference-in-difference estimate of the impact of the tax.

What did they find?

“Consumption of SSBs decreased 21% in Berkeley and increased 4% in comparison cities (P = .046). Water consumption increased more in Berkeley (+63%) than in comparison cities (+19%; P < .01).”

The results have been largely heralded as indicating that the taxes "work".  Here is a bit from the organization Healthy Food America:

“this study provides another key piece of evidence that sugary drink taxes work, not just to raise revenue for important community priorities, but also to reduce consumption and shift sales from an unhealthy product to healthier drinks, such as bottled water,” said Jim Krieger, MD, MPH, executive director of Healthy Food America. “As four other communities consider their own taxes this fall, the Berkeley findings join those from Mexico and elsewhere to show that sugary drink taxes have great benefits – especially in low income communities.””

We shouldn't be too surprised that a tax reduces consumption - more confirmation that the demand curve slopes downward.  Yay Econ 101!  The real question about soda taxes hasn't been "whether" but "how much" consumption falls when prices rise.  

First, I'll touch on some conceptual issue related to the interpretation of the study then offer a few thoughts on the study methods.  

As indicated, I've seen numerous studies showing that this paper "proves" that soda taxes "work."  I'm not sure what "work" means.  There have been scores of studies projecting impacts of soda taxes, and virtually all suggest the taxes will lower soda consumption by some amount (though curiously the evidence is much less clear if you look at studies that have looked at actual sales data before and after taxes).  But the goal isn't to reduce soda consumption for the sake of reducing soda consumption.  The goal, presumably, is to make people's lives better - to reduce obesity or other dietary related diseases.  On this front, the evidence is much less clear that soda taxes will have a substantive effect on body weight.  Moreover, as other studies have shown, we need to be cognizant of what people eat and drink instead when they substitute away from higher-priced soda, and many of these options could have adverse health impacts as well.

The largest conceptual issue in all this is whether a tax can actually make people better off.  Yes, a tax can reduce consumption.  But, does that mean people are happier?  Even if people switch to a lower-priced alternative after a tax, it doesn't follow that they're necessarily better off.  After all, consumers could have chosen the lower-priced alternative before the tax if that's what they really preferred.  Thus, the tax causes people to choose a lesser-preferred option.  This is a standard economic result: consumer welfare falls when prices rise.  Here's what I wrote in a piece for the Canadian Journal of Diabetes. 

“More fundamentally, one must ask what conceptual basis is being used to assert that SSB taxes will increase consumers’ welfare? Presumably, some consumers already consider health impacts when they choose what to eat and drink. More generally, taxing food or SSBs is analogous to reducing consumers’ real income, which almost certainly harms the consumers (9). Perhaps consumers suffer from lack of information or other cognitive biases, but even so, Lusk and Schroeter (10) show that only in very limited cases would a tax increase consumers’ long-term welfare. Sugden (11) further points out the philosophical (not to mention political) problems encountered when attempting to base public policy on the presumption of consumers’ behavioural biases. In particular, asserting that someone else consumes “too much” SSBs presumes that the nutrition expert or politician knows better which factors most impact an individual’s ultimate well being than the individual herself or himself. Such paternalism may be justifiable in the case of children or the mentally impaired, but it is less compelling when considering the general population. It is likely the case that excess consumption of SSBs will lead to health problems; however, people care about tasty, satisfying foods and beverages in addition to health. Life is full of difficult tradeoffs, and it is conceptually problematic for a third party to deem another person’s choices wrong or incorrect, given that different people have different preferences, incomes and constraints (assuming that people are making decisions with accurate information about the risks they face). If the argument is that people do not understand the risks of SSBs, then the appropriate policy response is information provision, not a tax.”

I went on to tackle the argument that rising public health care costs justify the tax, but I won't belabor the point: showing a tax "work" involves much more than showing that it reduces consumption.  

Now on to the Berkeley study's methods.  Overall, this is a nicely designed study that uses a difference-in-difference approach to try to tease out a causal effect.  My biggest beef with the study is that it relies on consumers' stated consumption behaviors.   The Berkeley tax has been a high profile event, and no doubt many Berkeley residents were aware of the debate and policy change.  It is possible that what we're picking up is some form of social desirability bias: Berkeley residents know they and their neighbors passed a tax on soda, and now here's this researcher asking about soda consumption.  The social pressure is clear: I don't want to be the kind of person who consumes the product everyone else wants to tax.  I don't want to look like some kind of social outcast, so I'm going to hedge and give a lower level of consumption than I actually consume.  

Why didn't the authors do this study using scanner data based on actual grocery sales?  These data are easily attainable from companies like Nielsen and IRI and can't be much more expensive than the surveys the authors conducted.  Even still, there would be other questions about the longevity of the effect, the substitution toward other food and beverages after the tax, the degree of substitution across city boundaries, and so on.

All that said, I'm more than willing to accept the finding that the Berkeley city soda tax caused soda consumption to fall.  The much more difficult question is: are Berkeley residents better off?  

Politics of Food Reform

James McWilliams has an interesting article in the Pacific Standard on how the food movement's ideals have fallen by the wayside in recent political discussions. As he notes, eight years ago when Obama was first running for office, the food movement was soaring.  McWilliams argues that the food movement got derailed by fights about overly-simplistic dichotomies and food labels, which ultimately hindered their efforts and left consumers confused and activists demotivated.  

He writes: 

“The ultimate answer to this question hinges on the misguided categories through which agricultural reformers have long used to affect change. The various dichotomies we have conventionally used to frame the general debates over food — organic/conventional, genetically modified organisms (GMO)/non-GMO, family farm/industrial farm, local/non-local, grassfed/feedlot, and so on — has had three outcomes that, in the last decade, have started to render food reform unpalatable to most political actors.”

The problem with these dichotomies are that they, firstly:

“have left consumers vaguely confused. This confusion has subjected them to considerable labeling manipulation. Consider the organic industry’s recent attack on the voluntary non-GMO label.”

Secondly:

“the conflicts generated by these terms are exacerbated by the fact that the labels rarely conform to the associations imposed upon them. This divergence further leaves consumers in a fog of confusion and, in so doing, alienating political interest for an altogether different reason.”

The final problematic outcome of past efforts, according to McWilliams, is:

“our clumsily conceptualized food categories involves agribusiness. To the extent that progressives have articulated a vision of agricultural reform, they have done so in a way that allows agribusiness giants to worship at the altar of progressive standards. ”

While I do not fully buy into McWilliams vision for a future of farm and food policy (and I think he misdiagnoses the economic reasons why we grow so much "corn and soy — to feed a handful of animal species — mostly chickens and cows", his critique of the efforts of the food movement are insightful and spot on.  Of course, there is another reason the grander visions of the food movement that involve "a new set of organizing principles" has failed to materialized.  That vision isn't palatable to most farmers and consumers and would require a fair amount of coercion to achieve.  

Regardless of the broader issues at play, McWilliams' article is highly recommended.

Which other government programs are us fat?

A few days ago, I took on the claim that farm subsidies are making us fat (the answer is most likely "no").  However, there are other government programs that potentially affect food prices - what about those programs?  Have they contributed to the rise in obesity?

A new paper in by Julian Alston, Joanna MacEwan, and Abigail Okrent in Applied Economic Perspectives and Policy asks whether funding for agricultural research and development (R&D) can explain the rise in obesity.  The chain of logic goes like this: there is extensive evidence that funding for agricultural research increases productivity; higher productivity means getting more food using fewer resources; more food means lower food prices; more food at lower prices means more food intake; more food intake leads to obesity.  Ergo, government funding for agricultural research leads to obesity.  

So what did the authors find?  They found that agricultural R&D spending probably did have a modest effect on obesity rates, but that R&D also resulted in enormous benefits to consumers and producers.  The authors write:

“Our analysis of historical counterfactuals suggests that it would have been very expensive to have foregone past R&D-induced productivity growth, even if in doing so we were able to reduce obesity and related healthcare expenditures.”

And, if we had undone the R&D efforts that led to the food price changes since the 1980s:

“This would be a costly reversion; it would cost consumers $65.01 billion, of which only $4.72 billion would be offset by savings in public healthcare costs, to reduce average U.S. adult body weight by 4.85 lbs. This translates to a cost of $55.6 per pound after the savings in public healthcare costs are taken into account.”

In summary:

“The implication is that agricultural R&D policy is unlikely to be an effective policy instrument for reducing obesity, both because the effects are small and because it takes a very long time, measured in decades, for changes in research spending to have their main effects on commodity prices. Moreover, as our results and others have shown, the opportunity costs of reducing agricultural research spending in the hope of eventually reducing the social costs of obesity would be very high because agricultural research yields a very large social payoff.”

Having now discussed the effects of farm subsidies and agricultural research, what about programs like the government-sanctioned check-off programs?  That was the topic of a session at the most recent AAEA meetings in Boston.  Parke Wilde from Tufts and Harry Kaiser from Cornell debated the role of check-off programs and their role in affecting public health and nutrition.  I was unfortunately unable to attend the session, but Parke offered a preview of it on his blog.  I hope to see some research on this topic in the near future.  

Are Farm Subsidies Making Us Fat?

In the past couple weeks, there have been a number of popular press articles suggesting that farm subsidies are a big part of the reason Americans eat unhealthy and are overweight. Here's the title from the New York Times: "How the Government Supports Your Junk Food Habit", and Fox News: "Government heavily subsidizes junk food, report suggests", and NPR: "Does Subsidizing Crops We're Told To Eat Less Of Fatten Us Up?". All the hubbub seems to stem from this article by some CDC researchers in JAMA Internal Medicine, which shows people who are more overweight tend to get more of their calories from foods that happen to be subsidized.

But, as we should all know by now, correlation is not causation.  Here's Tracie McMillian in a piece for National Geographic:

“But what the study does not show is the degree to which subsidies—and, in particular, the ones that are currently in place—actually persuade people to eat more of those foods. The researchers, by the way, admit this: “We cannot say [the link between subsidies and consumption] is causal from this study,” says K.M. Vankat Narayan, a lead author.

So while there’s an accepted correlation between low prices and increased purchases, nobody really knows how much farm subsidies matter when it comes to which foods people buy—and eat.”

She's right on the first part and wrong on the second.  There are actual lots of people who know how much farm subsidies contribute to food consumption, and they're called agricultural economists (in fact, McMillian goes on to then cite two prominent food and agricultural economists on the issue: Parke Wilde and David Just).  My view is in line with Wilde's and Just's:

“Indeed, in contemporary America, “the potential impact of the agricultural subsidies on consumption right now is inconsequential,” argues David Just, an agricultural and behavioral economist at Cornell University. Subsidies for farmers are unlikely to have much impact on consumer prices, adds Wilde, because farmers’ share of what we pay at the store is so little. ”

Let me pause right here and say that the question of the causal relationship between farm policy and unhealthy food consumption is an empirical, positive question, not a normative one.  There are a variety of reasons one may think we should or should not have farm subsidies (I generally find myself in the latter camp for reasons I won't go into here), but for the moment let's set the "should" question aside and ask what the evidence actually says on the link between farm subsides and unhealthy eating.  

Here's what I wrote on the issue in a recent Mercatus paper (which came out well before all the JAMA paper and the resulting news stories):

“Despite popular claims to the contrary, research suggests that farm subsidies have likely had little to no effect on obesity rates. First, although such policies may have had some effect on farm commodity prices, these inputs account for only a small share of the overall retail cost of food. For example, in 2013, only 7 percent of the retail price of bread was a result of the farm-gate price of wheat and other agricultural commodities. Even the enormous price swing that took wheat from around $3 per bushel in 2006 to almost $12 per bushel in February 2008 (a 300 percent increase) would be expected to increase the price of bread by only about 14 percent. Second, agricultural policies are mixed, and some policies (such as those for sugar, ethanol promotion, and the Conservation Reserve Program, or CRP) push the prices of agricultural commodities up rather than down. Third, despite the widely varying agricultural policies across countries and over time (see figures 14–16), those policies do not correlate well with differences in food prices and obesity rates across countries or with changes in obesity rates over time.”

In the model I used for the forthcoming paper I wrote on the distributional impacts of crop insurance subsidies, I find that the complete removal of crop insurance subsidies to farmers would only increase the price of cereal and bakery products by 0.09% and increase the price of meat by 0.5%, and would also increase the price of fruits ad vegetables by 0.7%.  So, while these policies may be inefficient, regressive, and promote regulatory over-reach, their effects on food prices are tiny, and depending on which policy we're talking about, could push prices and consumption  up or down.  

For those truly interested, here's a small list of academic papers by economists on the relationship between farm policy and obesity/health (for links to the actual papers, just do a quick googlescholar search).

Alston, Julian M., Daniel A. Sumner, and Stephen A. Vosti, “Farm Subsidies and Obesity in the United States: National Evidence and International Comparisons,” Food Policy 33, no. 6 (2008): 470–79. 

Balagtas, J.V., Krissoff, B., Lei, L. and Rickard, B.J., 2014. How Has US Farm Policy Influenced Fruit and Vegetable Production?. Applied Economic Perspectives and Policy, 36(2), pp.265-286.

Beghin, John C., and Helen H. Jensen. "Farm policies and added sugars in US diets." Food Policy 33, no. 6 (2008): 480-488.

Miller,J. Coreyand Keith H. Coble, “Cheap Food Policy: Fact or Rhetoric?” Food Policy 32, no. 1 (2007): 98–111. 

Okrent, Abigail M.  and Julian M. Alston, “The Effects of Farm Commodity and Retail Food Policies on Obesity and Economic Welfare in the United States,” American Journal of Agricultural Economics 94, no. 3 (2012): 611–46.

Rickard, B.J., Okrent, A.M. and Alston, J.M., 2013. How have agricultural policies influenced caloric consumption in the United States?. Health Economics, 22(3), pp.316-339.

Zilberman, D., Hochman, G., Rajagopal, D., Sexton, S. and Timilsina, G., The impact of biofuels on commodity food prices: Assessment of findings. American Journal of Agricultural Economics, 95, no. 2 (2013) : 275-281.

Farm Subsidies - Magnitudes and Comparisons

Continuing the discussion of the paper I wrote entitled "The Evolving Role of the USDA in
the Food and Agricultural Economy", today I'll discuss some USDA farm support programs (in another post, I'll discuss the academic research on effects of these and other USDA programs). 

In 2012 (the last date of the Census of Ag), the average government payment per farm receiving payments was $9,925. However, a large percentage of farms receive no government payments . In particular, farms that sell less than $50,000 worth of products tend not to receive payments, while the opposite is true for farms with sales greater than $50,000. For the 3.9 percent of farms with sales of $1 million or more, 71.2 percent receive payments averaging $40,559. Whereas the smallest farms receive the smallest average payments in total dollars, they receive the largest payments when expressed relative to value of production. Farms with sales of less than $1,000 that receive payments tend to get 9.36 cents for every dollar of output produced, but farms with sales of more than $1 million that receive payments tend to get only about 2 cents for every dollar of output produced.

Although government payments represent a small fraction of the value of output (i.e., gross revenue), they are certain to represent a much higher fraction of farmers’ net income. In fact, USDA Census of Agriculture data show that in 2012, the average net cash income for each category of farm with sales of less than $24,999 was negative. Those farms operate at a loss; because of this, whatever government payment they receive is infinitely greater than what they
make from farming. The average payment as a percentage of net income (for those receiving payments) is 31 percent, 18 percent, 13 percent, and 7 percent for farms with total sales in the categories $100,000 to $249,999, $250,000 to $499,999, $500,000 to $999,999, and $1 million or more, respectively.

It is interesting to compare all this with SNAP payments.  As indicated, of the farms receiving payments in 2012, the average payment was $9,925. By contrast, USDA data indicate that the average payment per individual receiving SNAP in 2012 was $133 per month, which amounts to $1,596 annually. SNAP payments increase at a decreasing rate with the size of the household. For a four-person household receiving SNAP benefits, the average payment was $440 per month, or $5,280 per year, in 2012. Food assistance programs represent a larger share of the USDA budget than do farm support programs because SNAP recipients far outnumber the recipients of farm program payments, not because each SNAP recipient receives a higher payout than does each recipient of farm supports.

It is also useful to compare US farm support payments with those in other countries.  For this, we can turn to data from a World Bank project led by the Kym Anderson and colleagues. 

The nominal rate of assistance (NRA) is defined as the percentage increase or decrease in gross returns to farmers caused by government policies. A positive number means a country’s
policies are pushing up agricultural prices and returns, and a negative number implies the opposite. The gross rate of assistance (GRA) is the NRA expressed in absolute dollar terms (in the year 2000) instead of in percentage terms. The GRA is the NRA multiplied by the value of agricultural production in a country divided by the number of farmers.

Figure 14 shows the average NRA, and figure 15 shows the average GRA of 53 different countries from 2000 to 2010. The figures contain a selection of developed and developing countries to provide insight into the diversity of agricultural policies around the world. The United States had an average NRA of 11.2 percent and a GRA of $3,576 per farmer over this period. That means that the gross returns of US farmers are 11.2 percent (or $3,576 per farmer) higher than would have been the case were it not for various government policies. Some countries, such as Norway, Iceland, Switzerland, and the Republic of Korea, have NRAs higher than 100 percent. Thus, US agricultural policies push farmer prices and returns higher than would be the case in the absence of such policies, but by an amount far less than is the case in some other countries and far more than in others.

Whereas figure 15 shows a snapshot of the GRA at a point in time, figure 16 shows changes in the GRA per farmer over time in eight selected locations (all in 2000 dollars). The GRA per farmer in the United States increased sharply from the 1970s to the 1980s and has subsequently stayed around $3,000 per farmer per year. The GRA per farmer in Japan has risen over the entire period considered from only $536 per farmer per year in the 1960s to $8,653 per farmer per year from 2000 to 2009. New Zealand dramatically lowered the GRA per farmer from the 1980s to the 1990s. Brazil and China have policies that are relatively neutral with regard to farmer gross returns. Until recently, countries in the European Union had highly distorting policies equivalent to taxes in excess of 100 percent.

In most locations (except eastern Europe and central Asia), agricultural policies have distorted the overall economy less since the 1980s. From 2000 to 2010, the United States had a welfare reduction index (WRI) of 17; the only locations that had less distorting policies were Australia and New Zealand, which had an average index of only 3.8 over this period (figure 17).

The welfare reduction index (WRI)  accounts not only for transfers but also for trade policies that affect the food and agricultural economy. According to Anderson, Rausser, and Swinnen, the WRI is calculated as “the percentage uniform trade tax which, if applied equally to all agricultural tradables, would generate the same reduction in national economic welfare as the actual intrasectoral structure of distortions to domestic prices of these tradable goods.”

The previous graphs aggregate the effects of agricultural and trade policies across all commodities. Figure 18 shows the average NRA for 11 different commodities in the United States from 2000 to 2010. During that period, sugar, cotton, and milk producers benefited most, with NRAs of 75 percent, 56 percent, and 39 percent, respectively. Barley and wheat had relatively low NRAs. Other commodities like beef and pork (not shown in the graph) had NRAs near zero.

To put these figures in perspective, it is useful to compare them with other distortions in the economy. In a remarkable statement, Anderson, Rausser, and Swinnen write,

“In 2004, existing agricultural and trade policies accounted for an estimated 70 percent of the global welfare cost of all merchandise trade distortions, even though the agricultural sector contributes only 6 percent of global trade and 3 percent of global GDP.”

In short, despite the small contribution of agriculture to global GDP, agricultural policies are responsible for the lion’s share of welfare losses that result from trade distorting policies.

In the paper I also talked about the fact that USDA impacts on the economy likely extend beyond those caused by explicit farm-commodity policies. To get a sense of such impacts, I utilized the RegData database.  You can read the paper for more details on that data set, or look at some of the work by Levi Russel who blogs at FarmerHayek.com.