Cost Effectiveness of Soda Taxes

In a piece for Cato, Christopher Snowden discusses the effectiveness (or lack thereof) of soda taxes that seem to be gaining traction worldwide.  Snowden's views closely mirror my own.  I like the way he framed the relative effectiveness of soda taxes in this passage:

“Whilst the benefit remains forever on the horizon, the cost can be easily calculated; it is simply the amount of money squeezed from consumers by the tax. In New Zealand, for example, advocates claim that a 20 per cent tax on soda would save 67 lives per year and raise $40 million (NZ).[12] Leaving aside the reliability of the New Zealand forecast, this works out as a cost of $600,000 (NZ) for every life that is extended and does not represent good value for money.

Political action on public health grounds is often justified by the costs of unhealthy lifestyles to the healthcare system, and therefore to the taxpayer. The economic costs of obesity are often misrepresented and fail to account for savings to taxpayers, but even if they were more reliable it is far from obvious that additional taxes would relieve the economic burden.[13] For example, the UK’s Children’s Food Campaign recently claimed that a 20 per cent tax on sugary drinks would reduce healthcare costs in London by £39 million over twenty years, but their own figures suggest that the tax itself will relieve Londoners of £2.6 billion over the same period.[14] The cost of the tax will therefore exceed the savings by several orders of magnitude.”

By the way, if you want to see which (out of more than 100) action will produce the biggest bank for your buck, check out the work of the Copenhagen Consensus, which routinely conducts cost-benefit analysis on a whole set of issues.  See their list for the most cost-effective actions.

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.”

Impacts of Agricultural Research and Extension

About a month ago, I posted on some new research suggesting decline rates of productivity growth in agriculture.  Last week at a conference in Amsterdam, I ran into Wally Huffman from Iowa State University, and knowing he's done work in this area, I asked him if he had any thoughts on the issue.  As it turns out, along with Yu Jin he has a new paper forthcoming in the journal Agricultural Economics on agricultural productivity and the impacts of state and federal spending on agricultural research and extension.  

Jin and Huffman also find evidence of a slowdown in productivity growth, writing: 

“We find a strong impact of trended factors on state agricultural productivity of 1.1 percent per year. The most likely reason is continued strong growth in private agricultural R&D investments. The size and strength of this trend makes it unlikely for average annual TFP growth for the U.S. as a whole to become negative in the near future. However, for two-thirds of the states, the forecast of the mean ln(TFP) over 2004-2010 is less than trend. The primary reason is under-investment in public agricultural research and extension in the past. For public agricultural research where the lags are long, it will be impossible for these states to exceed the trend rate of growth for TFP in the near future.”

They also find large returns to spending on agricultural research, and even larger returns to spending on extension.  They find the following:

“For public agricultural research with a productivity focus the estimated real [internal rate of return] is 67%, and for narrowly defined agricultural and natural resource extension is over 100%. Stated another way, these public investment project could pay a very high interest rate (66% for agricultural research and 100% for extension) and still have a positive net present value. Hence, these [internal rate of return] estimates are quite large relative to alternative public investments in programs of education and health. In addition, there is no evidence of a low returns to public agricultural extension in the U.S., or that public funds should be shifted from public agricultural extension to agricultural research. In fact, if any shifting were to be recommended, it would be to shift some funds from public agricultural research to extension. ”

The paper includes a couple really interesting graphs on research spending and extension employment over time.  First, they show that for four major agricultural states, real spending on agricultural research peaked in the mid 1990s. 

And, while extension staff has declined in some states, it hasn't in others.  

Why we eat better today

Megan McArdle has an excellent post at Bloomberg review that she titled The Economics Behind Grandma's Tuna Casseroles.

McArdle sets out to explain why we eat differently (and in many ways better) than our grandparents.  Here's my favorite passage:

“You have a refrigerator full of good-looking fresh ingredients, and a cabinet overflowing with spices, not because you’re a better person with a more refined palate; you have those things because you live in 2015, when they are cheaply and ubiquitously available. Your average housewife in 1950 did not have the food budget to have 40 spices in her cabinets, or fresh green beans in the crisper drawer all winter.”

She also notes that food preference were probably similar in the 1950s as compared to today, it's just that our grandparents couldn't afford to eat the way we now do, and technological changes have made what were previously "fancy" foods available to the masses.  Take, Jello for instance:

“The foods of today’s lower middle class are the foods of yesterday’s tycoons. Before the 1890s, gelatin was a food that only rich people could regularly have. It had to be laboriously made from irish moss, or calf’s foot jelly (a disgusting process), or primitive gelatin products that were hard to use. The invention of modern powdered gelatin made these things not merely easy, but also cheap. . . . Over time, the ubiquity of these foods made them déclassé. Just as rich people stopped installing wall-to-wall carpeting when it became a standard option in tract homes, they stopped eating so many jello molds and mayonnaise salads when they became the mainstay of every church potluck and school cafeteria. That’s why eating those items now has a strong class connotation.”

There is a lot more at the link and the whole thing is worth reading.

Is the growth in agricultural productivity slowing?

Last week I gave a talk at the University of Nebraska, and Julian Alston from UC Davis was also there.  He presented some recent research with Matt Anderson and Phil Pardey about productivity growth in agriculture.  While I have seen some discussions about the possibility of a slowdown in productivity growth in developing countries, Alston's research suggest it is a phenomenon alive and well here at home.  This is important stuff.  Falling productivity growth has important implications for sustainability, food security, and research and development. They write: 

“We detect sizable and significant slowdowns in the rate of productivity growth. Across the 48 contiguous states for which we have very detailed data for 1949– 2007, U.S. multifactor productivity (MFP) growth averaged just 1.18 percent per year during 1990–2007 compared with 2.02 percent per year for the period 1949–1990. MFP in 44 of the 48 states has been growing at a statistically slower rate since 1990. Using a longer-run national series, since 1990 productivity growth has slowed compared with its longer-run growth rate, which averaged 1.52 percent per year for the entire period, 1910–2007. More subtly, the historically rapid rates of MFP growth during the 1960s, 1970s and 1980s can be seen as an aberration relative to the long-run trend. A cubic time-trend model fits the data very well, with an inflection around 1962. We speculate that a wave of technological progress through the middle of the twentieth century—reflecting the progressive adoption of various mechanical innovations, improved crop varieties, synthetic fertilizers and other chemicals, each in a decades long process—contributed to a sustained surge of faster-than-normal productivity growth throughout the third quarter of the century. A particular feature of this process was to move people off farms, a one-time transformation of agriculture that was largely completed by 1980.”

Here's a graph from their paper showing the change in proportional growth rate in yields (i.e., the log of yields) over time for 6 crops with the inflection point indicated for when growth rates began decelerating.