Sunday, November 01, 2015

The Cult of Statistical bacon is not really as bad or worse than cigarettes!

 In their very well known article "The Cult of Statistical Significance", Ziliak and McCloskey write:

"William Sealy Gosset (1876-1962)  aka “Student,” working as Head Experimental Brewer at Guinness’s Brewery, took an economic approach to the logic of uncertainty. Fisher erased the consciously economic  element, Gosset's "real error."  We want to bring it back….Statistical significance should be a tiny part of an inquiry concerned with the size and importance of relationships."

For those unfamiliar with the history of statistics, Gosset was the one that came up with the well known t-test so many of us run across in any basic statistics class. A lot of issues are addressed in this paper, but to me one related theme is the importance of 'practical' or what I might call 'actionable' statistics. And context matters. Are the results relevant for practical consideration? Is the context realistic?  Are there proper controls? What about identification? For instance, not long ago I wrote about a study that attempted to correlate distance from a farm field and exposure to pesticides and autism that has been criticized for a number of these things, even though the results were found to be statistically significant.  As well as this one attempting to claim that proteins from Bt (read "gmo") corn were found in the blood of pregnant women. And...not to forget, the famous Serelini study that claimed to connect roundup herbicide to cancer in rats, that was so bad that it was retracted. Context, and economics (how people behave in the context of real world decision making scenarios) really matter. Take for instance, California's potential consideration to put roundup on a list of known carcinogens that might actually cause environmental harms in a number of ways magnitudes worse than roundup itself ever could.

So what does this all have to do with bacon? Well recently you might have heard a headline like this: “Processed meats rank alongside smoking as cancer causes – WHO.” 

This is a prime example of the importance of putting science and statistical significance, effect sizes, context (like baseline risks in the case of WHO quote above) and practical significance into perspective. Millions of people have heard this headline, taken the science at face value, and either acted on it or given it way more credence and lip service than it deserves. At a minimum every time for the rest of their life they have a piece of bacon they might think, wow, this could be almost as bad or worse than smoking.

Economist Jayson Lusk has a really nice post related to this with several quotes from a number of places, and I'm going to borrow a few here. From an article he links to in the Atlantic:

"the practice of lumping risk factors into categories without accompanying description—or,  preferably, visualization—of their respective risks practically invites people to view them as like-for-like. And that inevitably led to misleading headlines like this one in the Guardian: “Processed meats rank alongside smoking as cancer causes – WHO.”

“One thing rarely communicated in these sorts of reports is the baseline level of risk.  Let's use Johnson's example and suppose that eating three pieces of bacon everyday causes cancer risk to increases 18%.  From what baseline?  To illustrate, let's say the baseline risk of dying from colon cancer (which processed meat is supposed to cause) is 2% so that 2 out of every 100 die from colon cancer over their lifetime (this reference suggests that's roughly the baseline lifetime risk for everyone including those who eat bacon).  An 18% increase means your risk is now 2.36% for a 0.36 percentage point increase in risk.  I suspect a lot of people that would accept a less-than-half-a-percentage point increase in risk for the pleasure of eating bacon….studies that say that eating X causes a Y% increase in cancer are unhelpful unless I know something about my underlying, baseline probably of cancer is without eating X.”

The real cult of statistical significance (and in effect all of the so called science that follows from it) is a cult like believing and following by multitudes that hear about this study or that, overly dramatized by media headlines, (even if it is a solid study, potentially taken out of context and misinterpreted to fit a given agenda or emotive response), and then synthesized into corporate marketing campaigns and unfortunately public policies. Think gmo labeling, gluten free, antibiotic free,  climate change policy, ad naseam.

Thursday, October 29, 2015

Applied Microeconomics: The Normative Representative Consumer and Welfare Analysis

In a previous post, I pondered some questions related to using market demand functions to make welfare statements, following broadly Microeconomic Theory by Andreu Mas-Colell, Michael D. Whinston, and Jerry R. Green (MWG).

Making welfare statements about aggregate demand revolves around a few key concepts including a positive representative consumer, a wealth distribution rule, and a social welfare function. At a high level, these concepts seem to represent the technical assumptions and characteristics that need to hold in order to make most of the basic analysis of an intermediate microeconomics course mathematically sound or tractable for applied work. Here is a shot at some high level explanations:

positive representative consumer- at a high level, a hypothetical consumer who's UMP facing society's budget constraint generates a market or economy's aggregate demand function

wealth distribution rule - for every level of aggregate wealth, assigns individual wealth.
This rule or function is what allows us to write aggregate demand as a function of prices and wealth in order to move forward with the rest of our discussion about welfare analysis.

Examples given in MWG include wealth distribution rules that are a function of shareholdings of stocks and commodities which make wealth a function of the market's price vector

social welfare function (SWF) - this assigns utility to the vector of utilities for all 'I' consumers in an economy or market. W(u1,.....,uI) or can be written in terms of indirect utilities W(v1,....vI). 

Maximizing Social Welfare and Defining the Normative Representative Consumer

The wealth distribution rule is assumed to maximize society's social welfare function subject to a given level of aggregate wealth. The optimal solution indicates a particular indirect utility function v(p,w)

Normative Representative Consumer- a positive representative consumer is a normative representative consumer relative to social welfare function W(.) if for every (p,w) the distribution of wealth maximizes W(.). v(p,w) in the optimum is the indirect utility function for the normal representative consumer. 

For v(p,w) to exist, we are assuming a SWF, and assuming it is maximized by an optimal distribution of wealth according to some specified wealth distribution rule.

An example from MWG: When v(p,w) is of the Gormon form, and the SWF is utilitarian, then an aggregate demand function can always be viewed as being generated by a normative representative consumer.  

Tuesday, October 27, 2015

Applied Microeconomics: The Strong Axiom of Revealed Preference,Aggregation, and Rational Preferences

Professionally most of my focus has been empirical and to a great extent, has been agnostic when it comes to micro theory. Take data mining and machine learning, social network analysistext mining or issues related to big data for instance. Or many of the other issues I have taken up at EconometricSense. A lot of what I have worked on has been more about data, algorithms, and experimental design than the nuts and bolts of microeconomic theory.

However, there are some theoretical issues in microeconomics that I either have forgotten, or never really understood that well.

Particularly these issues have to do with the strong axiom of revealed preference, the market aggregated demand function, and welfare analysis as discussed in one of my graduate texts (Microeconomic Theory by Andreu Mas-Colell, Michael D. Whinston, and Jerry R. Green).  From that text  (MWG) I basically get the following:
  • The strong axiom (SA) of revealed preference is equivalent to the symmetry and negative semi-definiteness of the slutsky substitution matrix
  • Violations of the SA mean cycling of choices or violations of transitivity
  • If observed demand follows the SA, then preferences that rationalize demand can always be recovered
  • It is impossible to find preferences that rationalize a demand function when the slutsky matrix is not symmetric
That means, for an individuals' observed demand function, if the slutsky matrix is not symmetric, you can't make welfare statements based on the area beneath the demand curve.

What happens when we aggregate individual demand to get a market demand function? It seems to me that the data of interest in most applied work is going to be related to an aggregate market demand curve. Based on Green et al:
  • the chances of the SA "being satisfied by a real economy are essentially zero"
  • If we allow individuals in an economy to have different preference relations/utility functions, when we aggregate to get a market demand function, the negative semi-definiteness of the slutsky matrix (equivalent to the weak axiom of revealed preference) might hold, but "symmetry will almost certainly not." 
  • While positive effects of an equilibrium might hold, without symmetry the SA does not and we therefore cannot make statements about consumer welfare based on the area beneath an observed empirical market demand function
This last conclusion leaves me with a lot of questions to ponder:
  1. What does that imply with regard to empirical work? It seems to not matter for positive effects (for instance a conclusion that a wage set above equilibrium causes a surplus of labor). 
  2. But, how much does it matter that I can't use an empirical demand function to calculate changes in consumer surplus for a change in prices? Maybe it only matters if I am interested in calculating some amount? 
  3. For any individual, if the SA might holds (which is possible), we certainly know a price increase would reduce consumer surplus, put them on a lower indifference curve and make them worse off. Regardless of the conclusions above, wouldn't that hold for all consumers represented by the aggregate market demand curve? Can't we make a normative statement  (in  terms of a qualitative directional sense even if we can't calculate total surplus) about all consumers even if the SA fails in the aggregate but holds for each individual?
Now,  the MWG text mentioned above does go on in later chapters to discuss the notions of a positive and normative representative consumer as well as a social welfare function and wealth distribution mechanisms and implications for welfare analysis. But I'd really like to know about #3. Can we make directional statements about changes in welfare as long as we know that any attempt at quantification or calculation of surplus would be invalid due to violations of the SA?

Is this a case where one should just take the example of Milton Freidman's pool players who behave as if they know physics? Maybe all of the assumptions (like the SA) fail to hold for a market demand function, but we still feel confident making directional or qualitative welfare statements about price changes because everything else about the model predicts so well?

Any thoughts from readers?

I found it interesting, that the issues in the bulleted statements related to the MWG text were never addressed that I can tell in any of my undergraduate principles or intermediate micro texts, nor even in Nicholson's more advanced graduate text. It just seems like these texts jump from individual demand to market demand as a horizontal summation of individual's demand curves and go straight to welfare analysis and discussions about consumer surplus without discussing these issues related to the SA.

Note: I definitely spent some time with the issue of consumer surplus calculations based on compensated vs uncompensated demand curves. I don't think that is the issue here at all.

****updated modified on October 29, 2015

Wednesday, September 30, 2015

Big Data, Ag Finance, and Risk Management

I recently was reading an article on AgWeb, How the feds interest rate decision affects farmers; and the following remarks stood out to me:

“You need to plan for higher rates. Yellen said in her remarks that the expectation is that the federal funds rate will rise to 1.5% by late 2016, 2.5% in late 2017, and 3.5% in 2018, so increases are coming. You can manage those hits by improving your efficiency and productivity in your fields and in your financials, which will allow you so to provide detailed cost projections and yield estimates to your banker. “Those farmers who are dialing those numbers in will be able to negotiate a better interest rate, simply by virtue of all that information,” Barron says.”

So to me this brings up some interesting questions. How interested are lenders in knowing about farmers data management and how they are leveraging their data generated across their enterprise? Does your farm need an IoT strategy? Or will these things work their way out in the financials lenders already look at regardless?

Regardless of what lenders are after, it would make sense to me that producers would want to make the most of their data to manage productivity and efficiency in both good and bad times. Firms like FarmLink come to mind.

From a research perspective, I would have some additional questions:
  1.  Is there a causal relationship between producers that leverage IoT and Big Data analytics applications and farm output/performance/productivity
  2. How do we quantify the outcome-is it some measure of efficiency or some financial ratio?
  3. If we find improvements in this measure-is it simply a matter of selection? Are great producers likely to be productive anyway, with or without the technology?
  4. Among the best producers, is there still a marginal impact (i.e. treatment effect) for those that adopt a technology/analytics based strategy?
  5. Can we segment producers based on the kinds of data collected by IoT devices on equipment, aps, financial records, GPS etc.?  (maybe this is not that much different than the TrueHarvest benchmarking done at FarmLink) and are there differentials in outcomes, farming practices, product use patterns etc. by segment

See also:
Big Ag Meets Big Data (Part 1 & Part 2)
Big Data- Causality and Local Expertise are Key in Agronomic Applications
Big Ag and Big Data-Marc Bellemare
Other Big Data and Agricultural related Application Posts at 
Causal Inference and Experimental Design Roundup

Friday, September 25, 2015

EconTalk: Matt Ridley, Martin Weitzman, Climate Change and Fat Tails

In a recent EconTalk podcast with Russ Roberts, Matt Ridley comments on a previous discussion with Martin Weitzman regarding the tail risk associated with climate change:

"the fat tail on the distribution, the relatively significant even if small possibility of a really big warming has got a heck of a lot thinner in recent years. This is partly because there was a howling mistake in the 2007 IPCC Report, the AR4 Report (Fourth Assessment Report: Climate Change, 2007), where a graph was actually distorted. And a brilliant scientist named Nick Lewis pointed this out later. It's one of the great, shocking scandals of this, that a graph--and I'm literally talking about the shape of the tail of the graph--was distorted to make a fatter tail than is necessary. When you correct that, the number gets smaller. When you feed in all these 14 papers that I've been talking about, all the latest observational data, 42 scientists involved in publishing this stuff, most of the mainstream scientists--I'm not talking about skeptics here--when you feed all that in and you get the average probability density functions for climate sensitivity, they turn out to have much thinner tails than was portrayed in the 2007. And that Martin Weitzman is basing his argument on. So the 10% chance of 6 degrees of warming in 100 years becomes much less than 1% if you look at these charts now."

Very interesting, because I thought Weitzman's discussion of tail risk was compelling. Unlike Nassem Taleb's characterization of tail risk and GMOs. I think a key to policy analysis must  revolve around getting the distribution correct, particularly the tails of the distribution, then getting the discount rate correct as well. Will there ever truly be a consensus in relation to climate change policy?

EconTalk: Matt Ridly on Climate Change Consensus

In a fairly recent EconTalk podcast with Russ Roberts, Matt Ridley discusses the consensus about climate change:

"if it's true that 97% of scientists are all of a particular view about climate, then let's go and ask what that view is. And if you go and look at the origin of that figure, it was that a certain poll--of 79 scientists, by the way, an extraordinarily small sample--said that, 97% of them agreed that human beings had influenced climate and that carbon dioxide was greenhouse's not referring to a consensus about dangerous climate change. It's referring to a consensus about humans' ability to affect the climate."

This is similar to what I wrote before back in 2008  after actually reading the IPCC 4th Assessment report. And more recently I have commented on how difficult it may be to solve the knowledge problem and actually attempt to price carbon (for which there is no consensus), and given this consensus view, from a policy perspective, the science just might not support doing anything drastic to try to stop climate change (i.e. carbon taxes, CAFE standards, other regulations).

So I continue to think that you don't  necessarily have to be a climate change skeptic or 'denier' to be a denier on climate policy (or at least push back a little)

Friday, September 11, 2015

Does California's EPA really have an 'intent' to put Glyphosate on its list of 'known' carcinogens?

There have been some recent headlines lately about California's EPA expressing an 'intent' to put glyphosate on its list of 'known' carcinogens.

Here is one example:

Yes, a subgroup of the WHO did suggest not long ago that glyphosate was a 'probable' carcinogen, but I wonder if hairdressers, or third or swing shift workers are going to get a warning printed on their payroll slip telling them that along with roundup herbicide, their profession is known to the state of California to cause cancer?

Here's more:

"In recent years use of glyphosate has exploded from 10 million pounds in 1993 to 280 million pounds in 2012. More than 90 percent of soybeans grown in the United States are genetically modified to withstand Roundup, which ends up in the beans themselves. More glyphosate is found in genetically modified soybeans than non-GMO varieties....The widespread use of this toxic herbicide in GMO food production is one reason more than 90 percent of Americans want foods containing genetically engineered ingredients to be labeled. Americans should have the same right as consumers in 64 other countries around the world when it comes to knowing what’s in their food."

'Widespread use of this toxic herbicide?' That is a very interesting statement. Sure, toxic might make sense in comparison to a pure source of crystal clear mountain spring water. But we are not going to sustainably feed the world on rainbows, fresh cut flowers, and crystal clear water. 

Of all of the chemicals used in modern agriculture, roundup is one that should be most applauded by those with environmental and health concerns, not stigmatized. When you consider its relative toxicity compared to a number of chemistries it has replaced, and its prominent and complementary role in GMO crops and the associated drastic reductions in greenhouse gas emissions, increased practice of no-till, and reduced runoff and groundwater pollution (i.e. nitrates in groundwater and algal blooms among other things) you might consider the roundup + roundup ready technology as one of the 'greenest' technologies ever put on the market.

Of course, maybe there is some inherent rent seeking going on behind the scenes, special interests interested in labeling and others might see the success of a sustainable technology like this as huge barrier to their political agenda, or business strategy (think Chipotle). The more this can be stigmatized in the media and through political means (like labeling or California's prop 65 list) the better they set strategically in advancing their agenda. Of course, it also (at least short term) doesn't hurt the other manufacturers of more toxic chemicals and might help get back some market share! I'm sure those happy about the California news would never consider it, but I think a world without roundup (or glyphosate in general) would be a world with more toxic chemical intensive agriculture.

Oh yeah, and Americans deserve the same right as citizens in 64 other countries and the world for that matter of having a food and regulatory system based on sound science and rigorous economic policy analysis.

See also:

Modern Sustainable Agriculture

Public Choice Theory for Agvocates

Monday, August 24, 2015

How Safe Is Your Ground Beef? Well, you tell me did you cook it properly?

I have recently came across an article in consumer reports:

This really gets interesting at the end when consumer reports actually recommends only grass fed and/or organic beef. (Never mind the negative environmental/sustainability issues that can also be associated with that) And their results on bacterial contamination are based on irrelevant comparisons between 'raw' ground beef. They did not test differences between properly handled and prepared ground beef, because the differences would be zero! It also makes me wonder, by making these kinds of recommendations are they possibly endangering some consumers by shaping perceptions in such a way that could promote 'risk homeostasis' - making consumers feel safer and likely take fewer precautions if they buy organic/grass fed premium brands? It seems to me the only responsible thing they should recommend is proper cooking and handling since that has the largest significant impact on safety regardless of how it's raised or marketed. I haven't actually unpacked the analysis or methodology on the 'raw' beef comparisons (as irrelevant as they may be) but am interested to see what kind of reactions come about from those that have!

Friday, July 03, 2015

The Use of Knowledge in (a Big Data) Society

I recently ran across a very interesting article in Forbes titled "Big Data vs. Hayek" that made some observations about how companies were using big data in ways that might at first seem anti-hayekian. For example:

“They found the centralized algorithms were outperforming decentralized local manager knowledge consistently, and profits went up….It’s not just apartment owners either. So-called revenue management software is also widely used by airlines and hotels….It’s also notable that Uber uses an algorithm to set prices rather than letting drivers set them”

“What’s interesting about such centralized, algorithmic approach to price setting is how un-Hayekian it is. In particular, I’m thinking of Hayek’s essay “The Use of Knowledge in Society” where he makes the case for the use of decentralized markets to utilized widely dispersed information to make choices.”

I think of course, yes corporations do tend to act and behave in ways that are anti-hayekian. (see this EconTalk podcast Coase, externalities, the firm, and the state of economics):

"If capitalism and markets and prices, the Hayekian system of communicating information via price signals, if it works so well, why do firms exist? Because firms are almost by definition top down rather than bottom up. They use command and control rather than purchases within the firm, although there are exceptions to that. Some firms do use price signals for their decision-making inside the firm. But many firms do not. Their decisions are made not by prices but by fiat, by decisions on the top. "

Firms exist in general because they seem to find that the 'costs' of using the price system to allocate resources internally can tend to outweigh the 'benefits.' There is a lot more to Coase's theory of the firm, but given this basic premise it is not surprising that in many cases firms will choose to use a more centralized approach than a decentralized one, and in certain cases Big Data, the internet of things (IoT), and modern computing power and analytics can toy with those tradeoffs at the margin. So in some cases we might find big data incenting more centralization and less in others. The Forbes article actually makes this point in the conclusion:

"Instead, these marketplaces provide ratings and other informational systems that help buyers and sellers overcome information asymmetries, and are helping markets function better and even more dispersed than before..."

It could be the case that when it comes to internally facing resource allocation decisions, certain practices within firms seem to have more of a decentralizing flavor, while big data is forcing the invisible hand on the customer facing decisions by allowing firms more than ever to leverage very granular bits of data related to each customer's particular knowledge of circumstances, time, and place. The internet of things is one example. As I have mentioned before, in the agriculture sector, local knowledge can be key in big data applications (See Big Data: Causality and Local Expertise are Key in Agronomic Applications).

Dan Frieberg points out some very important things to think about when it comes to using agronomic data in a Corn and Soybean Digest article "Data Decisions: Meaningful data analysis involves agronomic common sense, local expertise." 

The following quote from the article is telling:

"big data analytics is not the crystal ball that removes local context. Rather, the power of big data analytics is handing the crystal ball to advisors that have local context"

Also, when it comes to product line offerings in terms of seed choices and hybrid seed technology, big data and analytics is forcing companies to offer more options tied to local knowledge (see What does the farmer say...about seed choices? (Channeling Hayek))

"The choice of what crops we should grow, how they should be produced in terms of management practices and technology, and ultimately the variety of foods we choose to consume is an example of what economists refer to as the knowledge problem. While it might be possible to patent a given trait or hybrid, no one company can get too firm a grasp on this knowledge problem, regardless of their market share in the seed industry today. (not to mention, no government agency would have sufficient knowledge either). Given the vast array of considerations in seed choice and management practices, there is always going to be an incentive for some supplier to cater to the unique needs of individual producers, as advances in genomics and technology drive production not farm by farm or acre by acre but inch by inch."

I agree 100% with the conclusion of the Forbes article:

"we should not get ahead of ourselves in declaring the death of decentralized knowledge and decision-making."

Farm Link and the Rise of Data Science in Agriculture
 Big Ag Meets Big Data (Part 1 & Part 2)

Thursday, June 25, 2015

Jurassic World: Mutant dinosaurs more likely related to technologies used in organic & conventional farming?

Jayson Lusk has an interesting take on Jurassic World:

"In many ways the new animal they created reminds me much more of what might happen from mutagenesis (a technique widely practice in plant breeding for many decades and is NOT regulated as biotechnology, in which seeds are exposed to radiation or chemicals to cause mutations).  The reason I say that is  mutagenesis could cause several possible (and unexpected) genetic changes, which is exactly what happened with the dinosaur.  By contrast,  transgenic (or intragenic) biotechnology typically involves moving one gene from one species (or within a species) to another, in cases where it is well understood what the particular gene does."

I have not seen the movie, but from what he describes in his full post, I am on the same page. He mentions there is some language in the movie that implies that these dinosaurs may have been developed using techniques related to plant or animal biotechnology, or extensions of practices we might be using today in modern agriculture. I would guess then it is based on some sort of embryo transfer and gene insertions related to frogs and some bit of dinosaur DNA based on the post.

But don't misinterpret the title of this post. I am not saying that embryo transfer/cloning/recombinant DNA techniques (or whatever are actually used in the movie I have not seen) are used in organic farming! But if we want to distinguish between technologies used in both organic and biotech crops, and ask among these, which are most likely to produce unexpected 'mutant' results or consequences, the evidence clearly points to organic, or conventional non-GMO methods.

In fact, in conventional and organic crop improvement programs, as Jayson mentions, chemicals and radiation are used specifically to create 'mutant' crops. But the hope is for 'superhero' type mutants not 'super villians.' The only problem is, research shows that these methods are very imprecise and impact thousands of genes in unknown and unpredictable ways compared to transgenic/gmo based approaches!

We also know that based on things like microarray analysis and other research, that even traditional plant breeding introduces greater and unpredictable genomic disruptions than transgenic techniques.

It has always been very interesting to me that despite these differences, there are no calls for labeling conventional or organic crops that use these techniques, but such a strong emphasis on the much more controlled and precise genetic changes brought about by GMOs! (interesting but not surprising for a number of reasons we could get into like rent seeking etc.) And, don't start talking about 'fat' tails or the precautionary principle etc. because fat tail  and precautionary principle arguments would equally apply to organic and conventional technologies if not be even more relevant.

If it comes down to what is more 'natural' we know that research has also shown that the kinds of genetic modifications used in modern agriculture based on specific gene insertions into plants has occurred naturally over time with positive benefits! Just like today's roundup resistant crops were produced using agrobacterium to insert the resistant genes into soybeans, and then the best hybrids containing the gene were selected by plant breeders and sold to farmers, our ancient ancestors selected sweet potatoes containing improved traits conferred by gene transfers from Agrobacterium and they didn't even need a lab to do it!

 See also:


For more references on plant breeding and crop improvement technologies and genomic disruptions see: Biotechnology and Genetic Disruptions

Fat Tails, the Precautionary Principle, and GMOs

Additional References:

The genome of cultivated sweet potato contains Agrobacterium
T-DNAs with expressed genes: An example of a naturally transgenic food crop
PNAS|May 5, 2015|vol. 112|no. 1

Batista R and others (2008). Microarray analyses reveal that plant mutagenesis may induce more transcriptomic changes than transgene insertion. Proceedings of the National Academy of Sciences of the United States of America 105(9): 3640–3645

Baudo MM, Lyons R, Powers S, Pastori GM, Edwards KJ, Holdsworth MJ, Shewry PR. (2006). Transgenesis has less impact on the transcriptome of wheat grain than conventional breeding. Plant Biotechnol J. 2006 Jul;4(4):369-80

Wednesday, June 17, 2015

AgriGenomics - Genomic and Biochemical Mechanisms Associated with Drought Tolerance

"As Dr. Nam-Chon Paek of Seoul National University in Korea stated, 'We all expect that drought will be the major challenge for crop production in the near future. Understanding drought-responsive signaling and the molecular and biochemical mechanisms of drought tolerance in model plants such as Arabidopsis and rice provide new insight into how to develop drought-tolerant crop plants through conventional breeding or biotechnological approaches."


Tuesday, April 21, 2015

What's the big deal about farm subsidies? Four big questions about big ag, subsidies, food, and GMOs

There are a lot of misperceptions about farm subsidies that tend to surface in the media and in political discussions coming from commentators on both the right and the left. Below are four questions with answers that address issues related to farm subsidies that I have found to be most often misunderstood.

1) Do farm subsidies encourage farmers to plant biotech or GMO seeds?

There are no specific subsidies that target biotech crops. It is true in general that many corn and soybean growers receive subsidies related to their crops, and they are largely biotech, but a grower receives the same subsidy for a conventional vs. organic vs. biotech planted acre of field corn. Where the climate permits, most growers rotate corn, wheat, and soybeans, and while wheat crops qualify for many of the same subsidies associated with corn and soy, there are no biotech/GMO wheat crops planted in the US today. What would happen if we eliminated all farm subsidies? Because of the relative production benefits and risk reduction associated with planting biotech crops, elimination of subsidies might make these crops more attractive and increase their planting. Because we are largely subsidizing risk, removal of subsidies would lead the market to more efficiently price risk, and biotech traits would play a large role.

2) If subsidies drive the production of commodities and most of these are GMO,  aren’t we indirectly subsidizing GMOs?

The overall impact of completely eliminating U.S. commodity protection and subsidies at the commodity level in terms of total acres produced and commodity prices would be minimal, as reported by researchers at UC Davis. As their projections show, from a production standpoint, the impact is very small for the major biotech crops including corn and soybeans. If anything, the supply of wheat is impacted the greatest among row crop commodities, and it is not a biotech crop. Note that during the 2012 Midwest drought the impact on production was much greater than the impact of farm subsidies.  Even with the drastic drop in crop prices that have followed as the drought eased during the last two years (prices for corn have fallen almost 50% from the peak in 2012 to current futures prices) we have continued to have record acres planted.  And during the immediate post drought period, we did not see these record commodity prices translate into high retail prices or reduced consumption of processed foods. Extreme prices did not drastically alter the behavior on either the production or consumption side of the equation. The ‘positive’ impacts on fruit and vegetable production is modest at best and given the price elasticity discussion in the sections that follow, likely would not impact consumer choices at the retail level.

So why do we plant so much corn and soybeans? As stated in Alston et al (2010):

“Farm commodities have indeed become much more abundant and cheaper over the past 50 years in the world as a whole as well as in the United States, but not because of subsidies.This abundance mainly reflects the effects of technological innovations and increases in farm productivity, which has alleviated hunger and poverty throughout the world while at the same time reducing pressure on the world’s natural resources.”

3) Do farm subsidies make unhealthy foods cheaper and contribute to obesity?

Because subsidies have such a small impact on the overall supply of commodities, and wholesale prices (as illustrated above), the consequences of removing subsidies on prices at the retail level would be too small to have any meaningful impact on consumer choices. As stated in Alston, et al (2010):

“U.S. farm subsidies have had generally modest and mixed effects on prices and quantities of farm commodities, with negligible effects on the prices paid by consumers for food and thus negligible influence on dietary patterns and obesity. This result is consistent with some previous work by economists on the issue”

The implied price elasticity for retail food calculated in Alston (2007) is .08%. So a 1% increase in the retail price of food reduces consumption by .08% If we had another drought, causing corn prices to increase 50%, and even if that translated into a retail price increase of corn based food products by 50%, we would see a reduction in consumption of about 4%. More specifically, Alston (2010) found:

“Eliminating U.S. grain subsidies alone would lead to a small decrease in annual per capita caloric consumption—simulated to be 977 calories per adult per year, which would imply a 0.16% per year reduction in average body weight assuming 3,500 calories per pound. In contrast, removing all farm subsidies, including those provided indirectly by trade barriers, would lead to an increase in annual per capita consumption in the range of 200 to 1,900 calories—equivalent to an increase in body weight of 0.03% to 0.30%.”

4) Do farm subsidies largely prop up wealthy farmers vs. helping small farmers thrive in a volatile, competitive global and corporate dominated marketplace?

It's true that many subsidies are tied to commodity production. Those that grow more commodities (i.e. larger farms) will get more money from the government. As a result larger producers take in a larger share of all subsidies (especially those related to commodities). However, subsidies account for a much smaller percentage of income for large producers, and make up a much larger percentage of total income for medium or small producers.

As the chart above (from the USDA) shows, in 2008 farms earning less than $250,000 /yr recieved a much greater percentage of their income in the form of government payments, while subsidies only accounted for 4% of income for producers with the largest incomes. The chart below indicates that this relationship seems to hold across years for the last decade.

In general, a lot of perceptions about farm subsidies are incorrect. They do not favor large farms or biotechnology, and they do not encourage the consumption of unhealthy foods or impact obesity.

Further Reading and References:

Reduced costs and risk, chemical application, and production and environmental benefits:

Journal of Agribusiness 19,1(Spring 2001):51S67 © 2001 Agricultural Economics Association of Georgia
Biotechnology in Agriculture: Implications for Farm-Level Risk Management
Shiva S. Makki, Agapi Somwaru, and Joy Harwood

Genetically Engineered Crops: Has Adoption Reduced Pesticide Use? Agricultural Outlook ERS/USDA Aug 2000

GM crops: global socio-economic and environmental impacts 1996- 2007. Brookes & Barfoot PG Economics reportOctober 2010:Vol. 330. no. 6001, pp. 189 - 190DOI: 10.1126/science.1196864

Greenhouse gas mitigation by agricultural intensification Jennifer A. Burneya,Steven J. Davisc, and David B. Lobella.PNAS  June 29, 2010   vol. 107  no. 26  12052-12057

Impact of Subsidies on Commodity Production, Food Prices, and Obesity

Farm Subsidies and Obesity in the United States
Julian M. Alston, Daniel A. Sumner, and Stephen A. Vosti
Agricultural Resource Economics Update
V. 11 no. Nov/Dec 007
U.C. Davis

Choices. 3rd Quarter 2010 | 25(3)
Julian M. Alston, Bradley J. Rickard, and Abigail M. Okrent
JEL Classifications: I18, Q18

USDA Sources on Subsidies by Farm Type

USDA Report- Government Payments and the Farm Sector: Who Benefits and How Much?

USDA Report-Farm Income and Costs: Farms Receiving Government Payments