Using Social Network Analysis to Understand the Influence of Social Harassment Costs and Preferences Toward Biotechnology

In a previous discussion I described how social harassment costs (Borland and Pulsinelli, 1989) might explain why some consumers could hold seemingly contradictory views about science (i.e. accepting certain scientific views related to global warming but rejecting other scientific views related to genetically modified foods). 

In my graduate school research I hypothesized that consumers adopt a worldview v (regarding climate change, food preferences, religious beliefs, public policy, etc.) that gives them the greatest level of utility seemingly invariant to evidence supporting some alternative worldview v'.

U(v) > U(v')  (1)

One way to to explain this would be to model utility as a function of social harassment  'c'. 

U(v, c) > U(v', c)  (2)

for c > k

U(v, c) < U(v', c)  (3)

for c < k

In this formulation social harassment provides disutility, and would enter the utility function as a negative term. If social harassment is great enough to exceed some threshold 'k', consumers with preferences like those above may choose to ignore scientific evidence that lowers utility by conflicting with their vision or the vision of their peers.  The level of 'k' may vary depending on the consumers sensitivity to social pressure.

Some of the implications of this model were that consumers might increase utility and reduce social harassment by avoiding information that conflicts with their world views, they might also seek information that supports utility maximizing views regardless of weight of evidence. 

This also seemed to align with a number of ideas supported by findings from behavioral  and public choice economics (Caplan, 2007; Kahneman, 2011). For example the idea that beliefs that are irrational from the standpoint of truth-seeking are rational from the standpoint of utility maximization (Caplan, 2007).

In graduate school I attempted to investigate this empirically by developing a survey instrument to measure preferences toward genetically modified foods as well as attitudes toward abortion, climate change, embryonic stem cell research, animal welfare as well as political ideology, education levels, and science knowledge. I found that respondents with a positive view of embryonic stem cell research and those that were more concerned about the impacts of climate change were less likely to accept the safety of genetically modified foods. This is in spite of evidence of the safety of biotechnology or its potential for mitigating the impacts of climate change. However, the sample size was very small and as noted elsewhere a better instrument and structural equation modeling approach might offer a much richer and more rigorous understanding of the latent factors shaping consumer perceptions.

Additionally, the behavioral theoretical utility model above is very general. While this model's predictions could be loosely supported by the empirical work, many untested assumptions remain. For instance, the level of social harassment 'c' and the threshold 'k'. These are abstract latent factors hard to estimate and validate empirically. 

However, if we think of social harassment being a function of our exposure to media, social media, and peers, we can begin to frame up an analytical strategy for better understanding these phenomena in the context of social network analysis (SNA). For example, assume two actors, 'A' and 'B' who have preferences similar to (2) and (3) above. And assume a simple network of connections with peers as depicted below:

Each node (depicted as black, white or grey dots above) represents a peer's sentiment toward genetically modified foods. For subject A, strongly influenced by peers with negative sentiments, we might hypothesize that the social harassment costs associated with believing in the safety of biotech crops could be high even in the face of strong scientific evidence (which they may not be aware of, discount highly, or avoid in order to maximize utility). For subject B, social harassment costs in relation to these beliefs might be much lower and likely be imposed rarely by a few peripheral connections. This is just a toy example, but this framework helps motivate a number of questions:

• How exactly should these networks be defined and constructed to properly frame the question/hypothesis I have? Who/what entities should each node represent (people, media outlets, websites, celebrities, scientists, etc.)?
• Connections between nodes are referred to as edges and represent pathways through which information and social harassment costs might flow - should different edges be given different weights as a function of the entity represented by each node? Are there interactions between the type of node and the type of information flowing from it? 
• Is there any correlation between network metrics (i.e. degree centrality, eigenvector centrality) and influence on preferences/perceptions? 
• What can we learn from previous research in SNA in the area of viral marketing? Are there key nodes that can be influenced? 
• What role does network architecture play in information diffusion, influence, and ultimately the level of social harassment costs of a given node (ultimately this is what I would want to quantify to empirically support the theoretical model above)?
• Are there causal inferential approaches with the necessary identification properties allowing us to interpret these effects causally? (see perhaps Tchetgen et al., 2020)

Applications could extend beyond perceptions of genetically modified foods to include climate change, food preferences, religious beliefs, or vaccines. Johnson et al.(2020) has made a lot of progress using a similar framework to study the spread of disinformation across social networks as it relates to attitudes toward vaccination:

"Here we provide a map of the contention surrounding vaccines that has emerged from the global pool of around three billion Facebook users. Its core reveals a multi-sided landscape of unprecedented intricacy that involves nearly 100 million individuals partitioned into highly dynamic, interconnected clusters across cities, countries, continents and languages. Although smaller in overall size, anti-vaccination clusters manage to become highly entangled with undecided clusters in the main online network, whereas pro-vaccination clusters are more peripheral. Our theoretical framework reproduces the recent explosive growth in anti-vaccination views, and predicts that these views will dominate in a decade. Insights provided by this framework can inform new policies and approaches to interrupt this shift to negative views. Our results challenge the conventional thinking about undecided individuals in issues of contention surrounding health, shed light on other issues of contention such as climate change and highlight the key role of network cluster dynamics in multi-species ecologies."

A recent discussion of this paper can be found via the Data Skeptic podcast: https://podcasts.apple.com/sg/podcast/the-spread-of-misinformation-online/id890348705?i=1000491199543 

References:

Borland,Melvin V. and Robert W. Pulsinelli. Household Commodity Production and Social Harassment Costs.Southern Economic Journal. Vol. 56, No. 2 (Oct., 1989), pp. 291-301

The Myth of the Rational Voter: Why Democracies Choose Bad Policies. Bryan Caplan. Princeton University Press. 2007

Johnson, N.F., Velásquez, N., Restrepo, N.J. et al. The online competition between pro- and anti-vaccination views. Nature 582, 230–233 (2020). https://doi.org/10.1038/s41586-020-2281-1

Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

Eric J. Tchetgen Tchetgen, Isabel R. Fulcher & Ilya Shpitser (2020) Auto-G-Computation of Causal Effects on a Network, Journal of the American Statistical Association, DOI: 10.1080/01621459.2020.1811098

SNA and Related Posts at EconometricSense:

Perceptions of GMO Foods: A Hypothetical Application of SEM

An Introduction to Social Network Analysis with R and NetDraw

GMM, Endogeneity, SNA, Viral Marketing, and Causal Inference

SNA & Learning Communities

Using SNA in Predictive Modeling

The Robustness of SNA Metrics

All SNA Posts at EconometricSense

Related Posts and Background at EconomicSense

Consumer Perceptions of Biotechnology: The Role of Information and Social Harassment Costs

Fat Tails, the Precautionary Principle, and GMOs

Defining Consensus Regarding the Safety of Genetically Modified Foods 

Comments of Rule for Rules on Gene Editing Technology

Rational Irrationality and Satter's Hierarchy of Food Needs

The 'Free From' Nash Equilibrium

The Challenging Tradeoff of Weighing Biased Consumer Preferences Against Marketing Food with Integrity

Polarization of Controversial Science and Limitations of Science Literacy

Voter Irrationality and Systematic Bias: Applications in Food and Biotechnology

Left vs Right Science vs Risk vs Propensity to Regulate

Consumer Perceptions of Biotechnology: The Role of Information and Social Harassment Costs

Agricultural biotechnology offers tremendous benefits to farmers and to society as it provides tools for mitigation of a number of environmental externalities related to water quality and food safety (USDA, 2000; Munkvold, 1999). However, perceptions of the safety of recombinant DNA technology (a.k.a. genetically engineered foods) on the part of consumers can shape the policy environment in ways that may inhibit expanded use of biotech traits in agriculture.

As a graduate student I found it particularly interesting that some consumers had strongly held science based views related to climate change, but might at the same time have views related to the safety of genetically modified foods that were at the time inconsistent with the larger scientific community. What could explain this?

In my work I hypothesized that consumers adopt a worldview v  (regarding climate change, food preferences, religious beliefs, public policy, etc.) that gives them the greatest level of utility.

U(v) > U(v')  (1)

One way to to explain this would be to model utility as a function of  social harassment  'c'. 

U(v,c) > U(v',c)  (2)

for c > k

U(v,c) < U(v',c)  (3)

for c < k

In this formulation social harassment provides disutility, and would enter the utility function as a negative term (I later found out you could alternatively model this similarly introducing a 'bliss' point in a utility model such that consumers might obtain utility from holding a certain viewpoint up to some level of saturation beyond which disutility sets in).

If social harassment is great enough to exceed some threshold 'k', consumers with preferences like those above may choose to ignore scientific evidence that lowers utility by conflicting with their vision or the vision of their peers.  The level of 'k' may vary depending on the consumers sensitivity to social pressure.

Those that are sensitive to social pressure and whose preferences are impacted strongly by the veracity of a particular vision may be resistant to conflicting evidence. 

If they were to accept the alternative (perhaps scientifically supported) viewpoint v*, and peers find these views distasteful, social harassment would lower utility. This could give the appearance of holding conflicting views related to scientific issues. An example would be accepting scientific consensus in some areas like evolution (where social harassment may be lower) but rejecting it in other areas like the safety or benefits of genetically engineered (GE) foods (where social harassment  may be higher in many circles). 

What do I mean by 'social harassment' and how might this relate to preferences toward genetically engineered foods? We might view them as a form of peer pressure, political correctness, or social norming. Consumers may choose a certain worldview (or express it through consumption patterns signaling their social viewpoints) based on their desire to be accepted by others. As a result they may discard any conflicting information or evidence and maximize utility by holding onto their world view 'v.'

U(v,c) > U(v',c) (2)

for c > k

I attempted to explore this theory empirically leveraging a data set containing demographics and survey responses related to political and religious views, food consumption preferences (organic/natural etc.), attitudes toward animal welfare, views on other scientific advances like stem cell research, scientific literacy, and attitudes toward genetically engineered foods. 

I found that respondents with a positive view of embryonic stem cell research and those that were more concerned about the impacts of climate change were less likely to accept the safety of genetically modified foods. This is in spite of evidence of the safety of biotechnology or its potential for mitigating the impacts of climate change. My theory of social harassment would be consistent with those empirical findings. (much more advanced work has been done in the last 15 years - see links and references below)

While I was aware at the time of previous work empirically estimating consumer attitudes toward genetically engineered foods (see references below) I was not aware of other related work in behavioral and public choice economics.

In retrospect, this not so different from the concept of 'rational irrationality' discussed in Bryan Caplan's 'The Myth of the Rational Voter':

"...people have preferences over beliefs. Letting emotions or ideology corrupt our thinking is an easy way to satisfy such preferences...Worldviews are more a mental security blanket than a serious effort to understand the world."

This means that:

"Beliefs that are irrational from the standpoint of truth-seeking are rational from the standpoint of utility maximization."

And in application:

"Support for counterproductive policies and mistaken beliefs about how the world works normally come as a package. Rational irrationality emphasizes this link."

From Kahneman's Thinking Fast and Slow:

"emotional attitude drives beliefs about benefits and risks and dominates conclusions over arguments."

Borland and Pulsinelli's Social Harassment Costs and Abatement

My idea of social harassment was inspired by Borland and Pulsinelli's work, although their formulation was in the context of household production (inspired by Gary Becker, 1965) with social harassment built into a budget constraint and utility maximization framework. Their discussion of social harassment costs as 'guilt trips' for driving gas guzzlers in the face of shortages and price controls was the motivating example for my thinking. 

A key idea from their theory is the concept of purchasing social abatement. Society will permit individuals to purchase goods or services that it finds distasteful if they also purchase abatement for that good.

While their paper predates contemporary notions of carbon offsets, the idea of hollywood stars or politicians buying carbon offsets to avoid social harassment from peers because of their jet setting lifestyles could be one application of social abatement. It follows from their logic that there is a market for goods that can be purchased for the purpose of social abatement. 

Perhaps some goods are 'bundled' with social abatement. For instance, a consumer that believes that beef consumption contributes excessively to climate change might be willing to buy beef if it has socially abating attributes like being grass fed, organic, or hormone free. Never mind that the carbon footprint of U.S. beef represents less that .5% of global greenhouse emissions and 3% of total U.S. GHG emissions, or the fact that these products may not actually lower beef's carbon footprint (and could possibly increase it - see also Rotz et al 2018). Another example, parents might be OK with a sugary cereal or drink if it is at least made with non-GMO ingredients (where the social points gained from being 'non-GMO' outweighs or abates social points lost from being a bad parent giving their kids sugary foods)

Social harassment can be explicit, in terms of negative comments from friends or colleagues, or they can simply be internal perceptions. But either way the purchase of socially abating goods or goods with socially abating characteristics could be explained this way. And food marketers are capitalizing on that in various ways in the form of free-from food labeling among other things.

Both my formulation and Borland and Pulsinelli's concept of social harassment costs would fit these trends in food preferences. My perspective differs in that social harassment impacts the views we adopt and the role of information in changing or shaping those views. These views either translate directly to consumption choices or indirectly as a means of signaling our views on food systems etc. In this formulation, consumer views are invariant to new information if it conflicts with their adopted view, because if others found out they had strayed in thought or conviction, they would incur social harassment disutility. So we might adopt a worldview that is unsupported by the wealth of scientific evidence. Purchases that signal socially desirable preferences help guarantee the higher level of utility and lower levels of social harassment. For those with the most strongly held views, they may evangelize others to adopt them (imposing additional social harassment on others). This signals that not only do I conform to the socially acceptable worldview, but I'm practicing my religion at the highest level.

Additional Implications

Social harassment may also be interacting with social media by making us aware of socially acceptable and unacceptable behaviors. This plays a role in influencing our worldviews as well as providing a platform for signaling our world views. This might explain the proliferation of increased attention paid to food in the last decade. 

While consumers might increase utility and reduce social harassment by avoiding information that conflicts with their world views, they might also seek information that supports utility maximizing views regardless of weight of evidence. 

In their paper "Monetizing disinformation in the attention economy: The case of genetically modified organisms (GMOs)" Ryan, Schaul, Butner and Swarthout provide an in depth background on the attention economy, disinformation, the role of the media and marketing as well as socioeconomic impacts. They articulate how how rent seekers and special interests are able to use disinformation in a way to create and economize on misleading but coherent stories with externalities impacting business, public policy, technology adoption, and health. These costs, when quantified can be substantial and should not be ignored:

"Less visible costs are diminished confidence in science, and the loss of important innovations and foregone innovation capacities"

Merchants of misinformation and disinformation can exploit consumers (and voters) with preferences sensitive to social harassment. 

Conclusion

The idea that facts alone often fail to change consumers minds is not novel. And the concept I leveraged related to social harassment and social harassment costs might not be so different from ideas related to social norming or social proof. However, I think it is a useful exercise to think through the implications of different formulations of these concepts because they can help us better understand the role of science and evidence in consumer perceptions and decision making. Better understanding may improve science communication. This could have implications for climate change, food sustainability, as well as vaccines and other impacts on public health.

Related Reading:

Perceptions of GMO Foods: A Hypothetical Application of SEM

Fat Tails, The Precautionary Principle, and GMOs

Defining Consensus Regarding the Safety of Genetically Modified Foods

Rational Irrationality and Satter's Hierarchy of Food Needs

The 'Free From' Nash Equilibrium

The Challenging Tradeoff of Weighing Biased Consumer Preferences Against Marketing Food with Integrity

Polarization of Controversial Science and Limitations of Science Literacy

Voter Irrationality and Systematic Bias: Applications in Food and Biotechnology

Left vs Right Science vs Risk vs Propensity to Regulate

Additional References:

Abdulkadri, Abdullahi O, Simmone Pinnock, and Paula Tennant. " Public Perception of Genetic Engineering and the Choice to Purchase Genetically Modified Food." Paper presented at the American Agricultural EconomicsAssociation Annual Meeting. 2004

Adulaja, Adesoji, et al. "Nutritional Benefits and Consumer Willingness to Buy Genetically Modified Foods." Journal of Food Distribution Research . Volume 34, Number 1. 2003 p. 24-29.

Baker, Gregory A. "Consumer Response to Genetically Modified Foods: Market Segment Analysis and Implications for Producers and Policy Makers." Journal of Agricultural and Resource Economics" Vol 26, No. 2. 2001. p.387-403.

Becker, G.S. (1965). ‘A theory of the allocation of time’, ECONOMIC JOURNAL, vol. 75(299), pp. 493–517

*Borland,Melvin V. and Robert W. Pulsinelli. Household Commodity Production and Social Harassment Costs.Southern Economic Journal. Vol. 56, No. 2 (Oct., 1989), pp. 291-301

Camille D. Ryan, Andrew J. Schaul, Ryan Butner, John T. Swarthout, Monetizing disinformation in the attention economy: The case of genetically modified organisms (GMOs), European Management Journal, Volume 38, Issue 1, 2020, Pages 7-18, ISSN 0263-2373

The Myth of the Rational Voter: Why Democracies Choose Bad Policies. Bryan Caplan. Princeton University Press. 2007

Chiappori, P.‐A. and Lewbel, A. (2015), Gary Becker's A Theory of the Allocation of Time. Econ J, 125: 410-442. doi:10.1111/ecoj.12157

Russell Golman, David Hagmann, George Loewenstein. Information Avoidance. Journal of Economic Literature, 2017; 55 (1): 96 DOI: 10.1257/jel.20151245

Hine, Susan and Maria Loureiro. "Understanding Consumers' Perceptions Toward Biotechnology and Labeling."Paper presented at the American Agricultural Economics Association Annual Meeting . 2002.

Jones, Gerald M., Anya McGuirk and Warren Preston. "Introducing Foods Using Biotechnology: The Case of Bovine Somatotropin." Southern Journal of Agricultural Economics. Vol 24, No. 1 1992. p 209-223

Lacey Wilson, Jayson L. Lusk,Consumer willingness to pay for redundant food labels,Food Policy, 2020,101938, ISSN 0306-9192,

Jayson L. Lusk, Brandon R. McFadden, Norbert Wilson, Do consumers care how a genetically engineered food was created or who created it?,Food Policy,Volume 78,2018,Pages 81-90,ISSN 0306-9192

Nicholas Kalaitzandonakes, Jayson Lusk, Alexandre Magnier, The price of non-genetically modified (non-GM) food,Food Policy,Volume 78,2018,Pages 38-50,ISSN 0306-9192

B. R. McFadden, J. L. Lusk. What consumers dont know about genetically modified food, and how that affects beliefs. The FASEB Journal, 2016; DOI: 10.1096/fj.201600598

National Academies of Sciences, Engineering, and Medicine. 2016. Genetically Engineered Crops: Experiences and Prospects. Washington, DC: The National Academies Press. https://doi.org/10.17226/23395.

C. Alan Rotz et al. Environmental footprints of beef cattle production in the United States, Agricultural Systems (2018). DOI: 10.1016/j.agsy.2018.11.005

The New Food Fights: U.S. Public Divides Over Food Science. Differing views on benefits and risks of organic foods, GMOs as Americans report higher priority for healthy eating DECEMBER 1, 2016 https://www.pewresearch.org/science/2016/12/01/the-new-food-fights/

Steak-umm Tweet Storm Tackles Coronavirus and Science Literacy

Have you ever heard of the company Steak-umm or their thin sliced frozen steak products (think Philly cheesesteak) found in a number of grocery stores across the country? If you have a twitter account you may have come across a seemingly random tweet or retweet by folks a bit perplexed by why this company was sharing tips about misinformation related to the coronavirus epidemic sweeping the country.

I've been historically a bit of a critic of a number of companies and brands for their often deceptive approaches to food marketing. In Thinking Fast and Slow About Consumer Perceptions of Technology and Sustainability in Agriculture and The 'free from' Nash Equilibrium Food Labeling Strategy I discuss how food marketing efforts leverage consumer behavioral biases to promote their products at the expense of science literacy and possibly in direct contradiction to consumer preferences related to healthy and sustainable food systems.

There are big costs to these marketing tactics (which borderline misinformation and disinformation campaigns). In their research "Monetizing disinformation in the attention economy: The case of genetically modified organisms (GMOs)" Ryan, Schaul, Butner and Swarthout provide an in depth background on the attention economy, disinformation, the role of the media and marketing as well as socioeconomic impacts. They articulate how how rent seekers and special interests are able to use disinformation in a way to create and economize on misleading but coherent stories with externalities impacting business, public policy, technology adoption, and health. These costs, when quantified can be substantial and should not be ignored:

"Less visible costs are diminished confidence in science, and the loss of important innovations and foregone innovation capacities"

See additional links that follow for more background and context around behavioral economics and food marketing tactics. But in a world where deceptive advertising has often often been the norm and even praised (Chipotle comes to mind see here and here), out of nowhere comes this viral storm of tweets from Steak-umm pushing back against misinformation related to coronavirus:

friendly reminder in times of uncertainty and misinformation: anecdotes are not data. (good) data is carefully measured and collected information based on a range of subject-dependent factors, including, but not limited to, controlled variables, meta-analysis, and randomization

— Steak-umm (@steak_umm) April 7, 2020

In explaining 'why' they think their messaging was so effective they state:

people think it's bizarre, ironic, and funny when a frozen meat company points out the importance of critical thinking, but chances are the same message would never "go viral" if it was from a person. our society values entertainment over truth and that's a huge problem

— Steak-umm (@steak_umm) April 8, 2020

They clearly get that evidence doesn't necessarily move the needle when it comes to science communication and persuasion. As discussed in a number of the posts below consumers tend to believe the things that maximize utility, not necessarily their science or policy literacy. How emotional attitude (system 1) drives beliefs about benefits and risks and overrides careful thinking about the strength of actual evidence.

The heroes of the day, @steak_umm have clearly figured this out and demonstrate that in addition to the coherence of the story, entertainment value goes a long way getting folks to pay attention.

Related Links

Thinking Fast and Slow About Consumer Perceptions of Technology and Sustainability 

Rational Irrationality and Satter's Hierarchy of Food Needs 

The 'free from' Nash Equilibrium Food Labeling Strategy

Polarized Beliefs on Controversial Science Topics

Voter Preferences, The Median Voter Theorem, and Systematic Policy Bias

The Food Desert Mirage

If you build a new supermarket in a food desert, will low income households go there to buy healthier food? Are Dollar Stores cornering the market in poor neighborhoods reducing options for healthy food choices?

There is a misconception, a mirage if you will, related to the relationship between proximity of super markets that sell healthy foods and actual consumption and health effects. As discussed in this New Food Economy article 'Is it time to retire the term food desert':

"The idea that supermarkets enter into food deserts and all of a sudden provide access to healthy food is a little bit of a misconception"

Public Health literature provides evidence that households in lower income neighborhoods tend to eat less healthy food. These neighborhoods are often characterized as being food deserts due to the lack of access to healthy groceries for a given geography. Policy and discussion involving food deserts is often colored by an implicit or assumed causal relationship between food deserts (lack of supply of healthy food options) and nutrition and health outcomes. Failure to better understand this causal relationship can lead to potentially bad policy decisions. According to this City Journal article 'Unjust Deserts'  some communities have essentially banned or greatly restricted Dollar General from operating their stores which provide a variety of low priced products. However, some research questions a relationship between food choices and the presence or absence of a Dollar General store.

In a Health Economics Review article (Drichoutis, 2015), using a combination of difference-in-difference and propensity score matched analysis authors looked at the relationship between BMI in children and the proximity of Dollar General Stores and failed to find a relationship.

The authors conclude:

"Combatting the ill effects of a bad diet involves educating people to change their eating habits. That’s a more complicated project than banning dollar stores. Subsidizing the purchase of fresh fruits and vegetables through the federal food-stamp program and working harder to encourage kids to eat better—as Michelle Obama tried to do with her Let’s Move! campaign—are among the economists’ suggestions for improving the nation’s diet. That’s not the kind of thing that generates sensational headlines. But it makes a lot more sense than banning dollar stores."

A paper from the National Bureau of Economic Research this past year took a very exhaustive look at the relationship between food deserts, poverty, and nutrition. "THE GEOGRAPHY OF POVERTY AND NUTRITION: FOOD DESERTS AND FOOD CHOICES ACROSS THE UNITED STATES." Working Paper 24094 (http://www.nber.org/papers/w24094).

This paper helps provide a very rigorous empirical understanding of these relationships that can be leveraged for more effective policy and interventions to improve nutrition and health.

They used a very rich dataset consisting of:

1) Nielsen Homescan data - 60,000-household panel survey of grocery store purchases

2) Nielsen’s Retail Measurement Services (RMS) data - 35,000-store panel of UPC-level sales data (this covers 40% of all U.S. grocery store purchases)

3) Nielsen panelist survey data on nutrition knowledge

4) Entry and location data for 1,914 new supermarkets by zip code

Among the many findings uncovered in this data source was the following:

"over the full 2004-2015 sample, households with income above $70,000 purchase approximately one additional gram of fiber and 3.5 fewer grams of sugar per 1000 calories relative to households with income below $25,000."

Their data reflects what has been found in the public health literature in relation to low income households and nutritional health. In addition, household food purchase data was transformed using a modified version of the USDA's Healthy Eating Index (HEI) based on dietary recommendations. These various sources were brought together to give a very rich picture of household choice sets, retail environment, consumption patterns, and nutritional quality.

Using a regression based event study analysis and a structural demand model they examine the impact of supermarket entry on the nutritional quality of changes in food purchases. They also are able to separate the main drivers explaining the differences in the measured nutritional quality index (HEI) of food purchases between low and high income groups.

They model household and income group preferences using both constant elasticity of subsitution (CES) and Cobb-Douglass utility specifications. They apply this model to the rich data sources mentioned above using a Generalized Method of Moments (GMM) framework and use the model estimates to simulate policies that allow households of different incomes to be exposed to similar prices and product availability. (i.e. to make apples to apples comparisons and determine what's driving healthy vs. unhealthy food choices among low income households in food deserts vs. wealthier households).

Key Findings:

1) When new supermarkets open in what was formally a food desert, they find most of the changes in consumption are related to shifting purchases from more distant super markets to the new local super market. The change in the healthy eating index or substitutions away from unhealthy purchases from convenience and drug stores to more healthy food was minimal. This is because even in food deserts among low income households, willingness to travel was quite substantial and mitigated the lack of access to local healthy food.

" households in food deserts spend only slightly less in supermarkets. Households with income below $25,000 spend about 87 percent of their grocery dollars at supermarkets, while households with incomes above $70,000 spend 91 percent. For households in our “food deserts,” the supermarket expenditure share is only a fraction of a percentage point lower"

"one supermarket entry increases Health Index by no more than 0.036 standard deviations for low-income household"

They conclude that access to supply of healthy food or lack thereof explains only about 5% of the difference in the healthy eating index between low and high income households. Access does not appear to be driving the nutrition-income relationship.

2) Most of the differences in healthy vs unhealthy food choices by income group are driven by demand factors...i.e. preferences. When faced with the same choices and same prices, lower income households simply made purchases with a lower HEI.

"The lowest-income group is willing to pay $0.62 per day to consume the healthy bundle instead of the unhealthy bundle, while the highest-income group is willing to pay $1.18 per day."

They find that wealthier households value fruit three times the rate of lower income households and twice the rate for vegetables compared to lower income households.

Policy Implications

The authors reference studies by Montonen et al (2003) and Yang et al (2014):

"consuming one additional gram of fiber per 1000 calories is conditionally associated with a 9.4 percent decrease in type-2 diabetes" and consuming "3.5 fewer grams of sugar per 1000 calories is conditionally associated with a ten percent decrease in death rates from cardiovascular disease."

Improvements of the HEI definitely could be a driver for better health. However focusing on access may not be the greatest way to lever change. Certainly the correlations between income, food deserts, and healthy eating hold in this study and can be great flags to predict or identify which populations may need intervention. However, as this study points out the intervention should be based on theoretical and causal relationships that go beyond the supply of healthy foods and focus on aspects related to food preferences and demand. The authors conclude:

"For a policymaker who wants to help low-income families to eat more healthfully, the analyses in this paper suggest an opportunity for future research to explore the demand-side benefits of improving health education—if possible through elective interventions—rather than changing local supply."

References:

Drichoutis, A.C., Nayga, R.M., Rouse, H.L. et al. Food environment and childhood obesity: the effect of dollar stores. Health Econ Rev 5, 37 (2015). https://doi.org/10.1186/s13561-015-0074-2

NBER. "THE GEOGRAPHY OF POVERTY AND NUTRITION: FOOD DESERTS AND FOOD CHOICES ACROSS THE UNITED STATES." Working Paper 24094 (http://www.nber.org/papers/w24094)

Are Fruits and Vegetables Becoming Less Nutritious?

Here are some highlights from research on this topic:

--> Mineral nutrient composition of vegetables, fruits and grains is not declining.

--> Allegations of decline due to agricultural soil mineral depletion are unfounded.

--> Some high-yield varieties show a dilution effect of lower mineral concentrations.

--> Changes are within natural variation ranges and are not nutritionally significant.

--> Eating the recommended daily servings provides adequate nutrition.


Reference:

Robin J. Marles, Mineral nutrient composition of vegetables, fruits and grains: The context of reports of apparent historical declines, Journal of Food Composition and Analysis, Volume 56, 2017,
Pages 93-103, ISSN 0889-1575, https://doi.org/10.1016/j.jfca.2016.11.012.
(http://www.sciencedirect.com/science/article/pii/S0889157516302113)

HT: James Wong https://twitter.com/Botanygeek

Addressing Gender Inequality in Developing Countries Through Crop Improvement

A lot of production related benefits of biotechnology have been discussed in the literature, for instance decreased greenhouse gas emissions (Brookes and Barfoot, 2017), reduction in exposure to toxic chemicals (Kouser & Qaim, 2011), and food safety(Munkvold et. al, 1999). However additional research indicates that there may also be social benefits related to gender equality as discussed in
Social and Economic Effects of Genetically Engineered Crops (National Academies of Science, 2016).

Below are some highlights from this research:

• Women comprise a significant proportion of agricultural related labor in developing countries (~43%)
• Women in developing countries face significant challenges related to access to education, information, credit, inputs, assets, extension services, and land 

The adoption of biotechnology in developing countries has had some mitigating effects:

• In India biotechnology adoption (Bt cotton) resulted in increased work hours and income for women (Subramanian and Qaim, 2010)
• Reduced exposure and freeing women from spraying toxic chemicals and related labor (Bennett et al., 2003; Zambrano et al., 2013; Zambrano et al., 2012; Smale et al., 2012)
• Increased importance of women in decision making within households (Yorobe and Smale, 2012; Zambrano et al., 2013; Rickson et al., 2006

References:

National Academies of Sciences, Engineering, and Medicine; Division on Earth and Life Studies; Board on Agriculture and Natural Resources; Committee on Genetically Engineered Crops: Past Experience and Future Prospects. Genetically Engineered Crops: Experiences and Prospects. Washington (DC): National Academies Press (US); 2016 May 17. 6, Social and Economic Effects of Genetically Engineered Crops. Available from: https://www.ncbi.nlm.nih.gov/books/NBK424536/

Graham Brookes & Peter Barfoot (2017) Environmental impacts of genetically modified (GM) crop use 1996–2015: Impacts on pesticide use and carbon emissions, GM Crops & Food, 8:2, 117-147, DOI: 10.1080/21645698.2017.1309490

Bennett R, Buthelezi TJ, Ismael Y, Morse S. Bt cotton, pesticides, labour and health: A case study of smallholder farmers in the Makhathini Flats, Republic of South Africa. Outlook on Agriculture. 2003;32:123–128.

Kouser, S., Qaim, M., Impact of Bt cotton on pesticide poisoning in smallholder agriculture: A panel data analysis,Ecol. Econ. (2011), doi:10.1016/j.ecolecon.2011.06.008

Comparison of Fumonisin Concentrations in Kernels of Transgenic Bt Maize Hybrids and Nontransgenic Hybrids. Munkvold, G.P. et al . Plant Disease 83, 130-138 1999.

Rickson ST, Rickson RE, Burch D. Women and sustainable agriculture. In: Bock BB, Shortall S, editors. Rural Gender Relations: Issues and Case Studies. Wallingford, UK: CABI Publishing; 2006. pp. 119–135.

Smale M, Zambrano P, Paz-Ybarnegaray R, Fernández-Montaño W. A case of resistance: Herbicide-tolerant soybeans in Bolivia. AgBioForum. 2012;15:191–205.

Subramanian A, Qaim M. The impact of Bt cotton on poor households in rural India. Journal of Development Studies. 2010;46:295–311

Yorobe JM Jr, Smale M. Impacts of Bt maize on smallholder income in the Phillipines. AgBioForum. 2012;15:152–162

Zambrano P, Smale M, Maldonado JH, Mendoza SL. Unweaving the threads: The experiences of female farmers with biotech cotton in Colombia. AgBioForum. 2012;15:125–137.

Zambrano P, Lobnibe I, Cabanilla DB, Maldonado JH, Falck-Zepeda J. Hiding in the plain sight: Women and GM crop adoption. Paper presented at the 17th ICABR Conference: Innovation and Policy for the Bioeconomy, June 18–21. Ravello, Italy: 2013.

GWP* Better Captures the Impact of Methane's Warming Potential

Understanding the differences in the way CO2 vs methane behaves is fundamental to understanding their respective roles impacting climate change, and personal and policy decisions related to mitigating future warming. A practical example, properly accounting for these differences, the global impact of U.S. beef consumption (or other ruminant food sources) over time in terms of carbon footprint (related to enteric emissions) could be even less than previously understood. Understanding this can help direct attention to those areas where we can make the biggest difference in terms impacting climate change.

 From:

 Allen, M.R., Shine, K.P., Fuglestvedt, J.S. et al. A solution to the misrepresentations of CO2-equivalent emissions of short-lived climate pollutants under ambitious mitigation. npj Clim Atmos Sci 1, 16 (2018) doi:10.1038/s41612-018-0026-8


"While shorter-term goals for emission rates of individual gases and broader metrics encompassing emissions’ co-impacts2,6,31 remain potentially useful in defining how cumulative contributions will be achieved, summarising commitments using a metric that accurately reflects their contributions to future warming would provide greater transparency in the implications of global climate agreements as well as enabling fairer and more effective design of domestic policies and measures."

https://www.nature.com/articles/s41612-018-0026-8#Sec1

See also:

A Green New Deal for Agriculture?

Religiousity, Beef, and the Environment

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

Hybrid Corn vs. Hybrid Cars

Welfare Analysis: Just Do It!

Some Beef Related Posts From the Incidental Economist

I'm a big fan of the Incidental Economist blog where I have learned a lot about healthcare economics. Recently healthcare economist Austin Frakt has shared some video monologues discussing meat, fake meat, health and the environment.

In the first video he discusses some recent research related to meat consumption and health, mainly there is no evidence that red meat presents a major health concern. And the challenge of observational data and research related to this:



However, in this  next video, I think the facts being referenced are making some assumptions that need clarification. Mainly, there seems to be an assumption that beef produced and consumed in the U.S. is exchangeable with beef produced in developing countries or that land devoted to beef production is exchangeable for land that could be used for food production purposes. Reducing consumption of beef in the U.S. likely won't have the impacts on consumption in other countries in the simplified way this story is often told.  U.S. beef accounts for .5% or less of global greenhouse gas emissions accounting for fossil fuel and grain consumption, as well as land use alternatives. And most of the land used for beef production isn't suitable for any other type of food production. Ruminants are able to convert inedible plant and fiber on marginal lands to highly palatable nutrient dense food sources. Adding a little grain (accounting for ~ 7% of the U.S. corn crop) can shorten the time grazing and increase production actually decreasing lifecycle greenhouse gas emissions.



I
n this final video, Dr. Frakt discusses how alternative/fake meat products are in fact NOT a healthier alternative to real beef:

Welfare Analysis: Just Do It!

Some time ago I wrote a couple posts discussing some of the issues in microeconomics that perplexed me the most in graduate school.

In  Applied Microeconomics: The Strong Axiom of Revealed Preference,Aggregation, and Rational Preferences I discussed some of the properties of consumer preferences that were required to rationalize a demand function. This came down to properties of what is known as the Slutsky substitution matrix which was require to be symmetric and negative semi-definite. These properties satisfy the strong axiom (SA) of revealed preference. As stated in the widely adopted graduate micro text by Andreu Mas-Colell, Michael D. Whinston, and Jerry R. Green (MWG) chances of the SA "being satisfied by a real economy are essentially zero."

In a follow up post Applied Microeconomics: The Normative Representative Consumer and Welfare Analysis I discussed the idea of a 'normative representative consumer.'  In order to have a normative representative consumer, we have to assume a social welfare function, and assume it is maximized by an optimal distribution of wealth according to some specified wealth distribution rule.

Making more 'impossible' assumptions didn't seem to help. And in fact, as I eventually found out according to Arrow's Impossibility Theorem, they really were practically impossible. So....when it comes to policy analysis (like for instance policies related to climate change) how do economists include social welfare in a cost benefit analysis?

There was a really great discussion about this in a Macro Musings podcast with James Broughel hosted by David Beckworth.

James Broughel: "And the welfare measure that they use is a social welfare function that they derive from the Ramsey neoclassical growth model, which is a famous economic growth model. So they take a welfare function from that model, they say this is society's preferences or this is the social planner's preferences or something along those lines. And then their goal is to maximize that....Well, the most obvious problem with this approach is that it relies on this social welfare function, which is supposed to describe the aggregated preferences of everyone in society. And aggregating the time preferences of everyone in society is really just a special case of aggregating the preferences in general, which runs into this issue of Arrow's Impossibility Theorem."

Arrow's theorem* requires that in order for any social welfare function to represent society's preferences (which are an aggregation of individual preferences) it must obey six axioms:

1) It must rank all social states
2) It must obey transitivity (see my previous post about symmetry of the Slutsky substitution matrix)
3) The ranking must be positively related to individual preferences
4) New social states should not affect the ranking of original social states - also referred to as independence of irrelevant alternatives
5) The ranking should not be based on customs overriding individual preferences
6) Rankings are not made by a dictator

Arrow's theorem states that there is no social welfare function that can aggregate preferences or a social decision rule that can satisfy all six axioms. Like I mentioned in my previous posts, it seems like based on 'the math' and the theory, welfare analysis for applied policy work isn't feasible. Maybe we should just limit ourselves to positive analysis (focusing on efficiency). So how do economists approach normative welfare related policy questions?

James Broughel: "they just say, well, that's society's preferences. And this has become a convention in economics, it's done all over the place."

David Beckworth: "Because it's tractable, right? It's easy to do. The math is easy."

James Broughel: "Yeah, you can do the math. But, there really isn't any basis for it. I think that they would, the advocates of this approach would acknowledge that. They would say, our approach is normative, but hey, lots of economists agree on it."

So the tongue in cheek answer is how do you do welfare analysis despite all of the challenges I have discussed? You make some impossible assumptions and 'just do it' because the math is easy....sort of. But reflecting on this over the years I have come to accept there are a number of problems that require these kinds of simplifying assumptions to motivate more critical thinking about the alternatives we face in a policy and decision making environment, as imperfect as that may be.

Most of the pocast was actually about two major schools of thought regarding the appropriate discount rate for doing cost benefit analysis for policies with long term impacts (again like climate change).  Even if we are able to achieve scientific consensus on the impacts of climate change, the actual policy solutions have to be evaluated in terms of the costs today vs. the benefits of mitigating future climate events. That requires a discount rate, which as David and James discuss, there is no solid consensus on what is appropriate. That merits a future post!

*Microeconomic theory:basic principles and extensions. 8th Edition
Walter Nicholson (2002)

Thinking Fast and Slow About Consumer Perceptions of Technology and Sustainability in Agriculture

Farming is the world’s most important career — that’s why it needs a new image

From AgFunder News: https://agfundernews.com/farming-is-the-worlds-most-important-career-thats-why-it-needs-an-image-makeover.html

"Right now the field is in the midst of profound change as advanced technologies including green chemistries, robotics, artificial intelligence, IoT, autonomous vehicles, machine learning, regenerative agriculture and biomimetics transform how farms look and function. It might seem like the stuff of science fiction, but autonomous vehicles, indoor farming and drone pollination are becoming more common throughout the sector.Looking at, and more importantly, talking about farming as a part of the tech revolution has the potential to ignite the curiosity and imagination of the next generation.millennials want meaningful careers that help make the world a better place. Often that interest is funnelled towards jobs in CleanTech, non-profits, the environment or the arts. But farming is an overlooked industry with incredible potential to help improve the world."

I tend to agree.

From Drovers: https://www.drovers.com/article/consumers-speak-sustainable-farmers-wanted

"Consumers used to want farmers to be local, healthy or safe, but a new word is topping the chart this year, according to a new global study by Cargill. In a word, consumers want farmers to be sustainable."

However the theme above related to the need to promote the technological savy of farmers was echoed in this survey:

"Although 75% of the respondents thought technologically advanced farming was a good thing, very few respondents see farmers that way today. “Technologically savvy” was one of the terms least associated with farmers."

This explains why technological advancements in agriculture that actually improve sustainability (Bt, Glyphosate resistance, finely textured beef, etc.) are often rejected when in fact it delivers much of what they are asking for.

I've written before about some of the challenges related to consumer attitudes and perceptions about agriculture.  See the links below. But along the lines of all of these themes I find a common thread in Daniel Kahneman's Thinking Fast and Slow:

"emotional attitude drives beliefs about benefits and risks and dominates conclusions over arguments."

Bad arguments and misleading intuition are driven by a number of biases mentioned in the book.

One of these biases is the 'affect heuristic' which "simplifies our lives by creating a world that is much tidier than reality. Good technologies have few costs in our imaginary world we inhabit, bad technologies have no benefits, and all decisions are easy. In the real world, of course we often face painful tradeoffs between costs and benefits."

I think this applies very well to food and agricultural technologies vs other kinds of technology.

Good Technology: Impossible Burger/Tesla
Bad Technology: Biotechnology
Easy Decisions: Meatless Monday/Ban Glyphosate

Real World Tradeoffs: U.S. beef contributes less than .5% of global greenhouse gas emissions, so going meatless on Mondays (or campaigning to replace beef with alternatives) likely won't have the impact many consumers believe. We also know that glyphosate is a low toxic herbicide that in combination with biotech traits has helped enable environmentally important farming practices including reduced tillage, reduced energy use, and has helped substitute away from more toxic chemistries(link see also Hybrid Corn vs. Hybrid Cars). Banning glyphosate (or creating a risk and litigation environment effectively banning its continued use) might seem like an easy 'costless' solution but there are definitely tradeoffs.

Additionally:

"System 1 is able produce quick answers to difficult questions by substitution, creating coherence where there is none....The question that is answered is not the one that was intended, but the answer is produced quickly and may be sufficiently plausible to pass the lax and lenient review of system 2"

There definitely seems to be a coherent story among consumers (and voters/politicians) about how good technologies and farming practices (local, natural, organic, non-GMO, vegan etc.) must be sustainable and virtuous while modern (high tech) 'industrialized' technologies and practices must be destructive, risky and harmful. Further, coherence and tidyness implies those advocating a different story with any strong or weak connection to companies producing and marketing these technologies must be biased and non-credible sources regardless of their expertise or what is found in the scientific literature.

It is very difficult to battle the 'coherence' and 'tidyness' of the stories and perceptions that is formed in the minds of consumers and critics of agriculture. This is definitely an area where some food marketers and the 'free from' approach to labeling seems to be most damaging (and profitable?). To say the least, after spending more than a decade studying consumer and voter preferences in relation to food and technology in the agriculture space, I think we are only beginning to scratch the surface. Maybe we have reached a critical mass or turning point in consumer interest in these topics, but can science communication and advocacy turn the tide?

Rational Irrationality and Satter's Hierarchy of Food Needs 
The 'free from' Nash Equilibrium Food Labeling Strategy
Polarized Beliefs on Controversial Science Topics
An Economic Analysis of Preferences for Genetically Engineered Foods
Voter Preferences, The Median Voter Theorem, and Systematic Policy Bias

Economics, Evidence, and High Causal Density

How do we form our beliefs about the solutions to societies most complex problems? Do we trust data? Theory? Both? What does it mean to base policy on science and evidence?

According to Manski:

"Social scientists and policymakers alike seem driven to draw sharp conclusions, even when these can be generated only by imposing much stronger assumptions than can be defended. We need to develop a greater tolerance for ambiguity. We must face up to the fact that we cannot answer all of the questions that we ask."

I think Russ Roberts puts it well in his EconTalk Episode with Noah Smith:

"Can you think of a study that was so decisively performed in terms of the crossing of t's and dotting of i's that the identification and all the econometric challenges were met with such impressiveness that people on the other side of the debate had to throw up their hands and say, 'Well, I guess I was wrong. I've got to change my view.' Because I can't think of one. I can't think of one. And if that's true, then I would suggest that economics has some serious problems in claiming it's a science."

When it comes to evidence there are lots of challenges. For the most part, in economics and the social sciences it's often impossible to implement randomized controlled trials to identify treatment effects related to policy changes. For the most part we have to leverage observational data using quasi-experimental designs. The challenge for both approaches as Jim Manzi discusses in his book ''Uncontrolled: The Surprising Payoff of Trial-and-Error for Business, Politics, and Society'  is the issue of 'high causal density.'

In an environment of high causal density "the number of causes of variation in outcomes is enormous, and each has significant potential effects compared with those of the potential cause of interest. We don't know enough to list each of them and hold them constant, but if we randomly assign patients to the test and control groups, then these hidden conditionals won't confound our estimate of treatment causality."

Unfortunately in the social sciences, causal pathways are extremely complex. There are always hidden conditionals we may not be able to measure or don't have sufficient knowledge to even consider. Given that hidden conditionals are always present, a well entrenched proponent of a given policy can always find a reason to explain why it has failed to prove itself out in the face of evidence.

But Jim does more than offer criticisms of theory and methods. He introduces the concept of 'Liberty as Means.'  Embracing the concepts of evolutionary economics, he promotes a flexible system of government that sounds a lot like federalism. As he discusses, the mistake we often see from both the right and the left is enforcement of social norms at the national level vs. fostering numerous experiments at the local level.

While economic theory and applied econometrics are useful and powerful tools for policy analysis,  these tools will not necessarily help provide clear cut  always defensible evidence to improve public policy. These methods will never discover a 'Polio vaccine' for policy. It is in fact their shortcomings that provide the strongest argument for our constitutional republic and federalism that our founders envisioned.

Reference: Uncontrolled: The Surprising Payoff of Trial-and-Error for Business, Politics, and Society, by Jim Manzi https://www.amazon.com/Uncontrolled-Surprising-Trial---Error-Business/dp/046502324X/ 

See also: EconTalk: Manzi on Knowledge, Policy, and Uncontrolled

Tariffs and the Corn-Soybean Industrial Complex

Recent trade policy talks and tariffs imposed by the Trump administration have had an impact on soybean prices (see: Trump's And China's Tariffs Could Do Permanent Damage To Soybean Farmers). As a result, one time payments have been proposed to help farmers but going into the next marketing year nothing is on the table.

An interesting observation is that some folks typically critical of the Trump administration have found this to be a silver lining. Their story goes something like this: Not all that is Trump is bad because hopefully he's breaking down the corn-soybean industrial complex. The trade war is overpowering the effects of the subsidies that usually keep the machine churning out the kinds of crops that are harming the planet and making us sick at the expense of more sustainable and healthy fruits and vegetables.

This isn't really new, its just another version of the same criticisms we often hear from the politically correct food activist crowd (i.e. the pro organic, pro-heirloom/nostalgic market,anti meat, anti-grain, anti-commodity anti-biotech agriculture folks)

Subsidies (primarily crop insurance) can impact marginal changes in the mix and total acres of corn and soybeans each year, but they are not a primary driver in the decision to grow those crops vs. vegetables etc. The difference has more to do with biology than policy.

Economist Jayson Lusk discusses the impacts of reducing or removing these subsidies: 

"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"

When we try to connect this to food consumption and the impacts on obesity, the evidence is very weak.

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%.”


The difference in prices between grains and vegetables won't change much with changes in subsidies and the impact on obesity is less than trivial. One reason commodities and grains are favored over other crops is they are more affordable, cost less to produce, and store much better. As Tamar Haspel notes in a previous Washington Post article:

"Factor in that corn delivers 15 million calories per acre to broccoli’s 2-ish million, and the cost to grow broccoli (25 cents per 100 calories) is 50 times larger than corn (half a cent per hundred calories). And that’s just the difference on the farm. After harvest, that broccoli needs to be refrigerated and transported to where it’s going before it spoils. Broccoli has nutrients that corn doesn’t, of course, so it’s a good thing that we eat some. But an all-vegetable, or mostly vegetable, diet is prohibitively expensive for most people"

At the end of the day, labeling the complex network of producers, scientists, retailers, merchandizers, processors, and traders involved in feeding a hungry global population as the 'corn-soybean industrial complex' may have dramatic appeal. But the biology and economics involved tell another story.

References:

Choices. 3rd Quarter 2010 | 25(3)
FARM POLICY AND OBESITY IN THE UNITED STATES
Julian M. Alston, Bradley J. Rickard, and Abigail M. Okrent
JEL Classifications: I18, Q18

Rational Irrationality and Satter's Hierarchy of Food Needs

In HIERARCHY, DISAGREEMENT, AND FOOD POLITICS food economist Jayson Lusk discusses Maslow's Hierarchy of Needs and a modification or application by Ellyn Satter. Satter conceptualizes a hierarchy of food needs. Basically the idea is that as society reaches more advanced levels of economic development and incomes rise, our preferences related to food change.

"Satter called the top of this pyramid "instrumental food" and she said such foods were consumed to "achieve a desired physical, cognitive, or spiritual outcome."  If we're talking about food satisfying a particular view of what I think of myself (I eat what I am) or food satisfying a "spiritual outcome", why would we expect you and I to agree on what is "best"?  In this sense, we might expect food consumption to be more politicized"

Another way of thinking about this is that high end food fads marketed by the likes of Chipotle and Whole Foods are 'normal goods' i.e. as incomes rise their consumption should increase. There is a reason why you only find certain food chains and grocery stores in areas where incomes are higher.

Satter notes: "These instrumental reasons may or may not be rational or supported by scientific inquiry."

This is not so different from the concept of 'rational irrationality' discussed in Brian Caplan's 'The Myth of the Rational Voter':

"...people have preferences over beliefs. Letting emotions or ideology corrupt our thinking is an easy way to satisfy such preferences...Worldviews are more a mental security blanket than a serious effort to understand the world."

This means that:

"Beliefs that are irrational from the standpoint of truth-seeking are rational from the standpoint of utility maximization."

And in application:

"Support for counterproductive policies and mistaken beliefs about how the world works normally come as a package. Rational irrationality emphasizes this link."

One of the main themes in the book is that this leads to systematic biases in voting behavior and policy. Particularly, these kinds of preferences create a gap between economic principles and policies supported by most economists vs. the general public. The authors note that this division probably is not unique to economics and they are correct. As Jayson Lusk notes, a few years ago research from the Pew Foundation identified a number of scientific issues for which there is a gap between views held by scientists and the public. 

So how does this play out? A colleague brought up a very important point. Rational irrationality implies that there are costs associated with irrational beliefs, and people are willing to hold on to certain world views given the costs are low. Since the costs associated with voting are much lower, and voters don't necessarily bear the full costs of their actions we would expect to see 'rational irrational' behavior more often in voting than we see with regard to food purchasing behavior. However, when we think about Satter's hierarchy the idea is that with increased incomes preferences for food become more abstract (related to politics, ideology, social status etc.). Consumers are willing to pay for that. However, for higher income consumers the share of food in the household budget is relatively small (Engel's Law). Hence the costs of 'irrationality' are minimal compared to what those costs would be for lower income consumers or at the bottom of Satter's hierarchy. This means that wealthier demographics and wealthier societies can afford to be 'rationally irrational' to some degree when it comes to actual food purchases as well as voting.

When you think about the opportunity this presents to food marketers in addition to special interest agendas like the non-GMO Project and US Right to Know combined with low cost voting and it’s a perfect storm.  As this influences food manufacturers and the regulatory environment, we begin to see an impact on food choices on the shelves. This impacts the way food is labeled, marketed, and perceived and the ingredients used or not used. This has impacts going all the way back the supply chain to the farm gate. These influences may come at the expense of more affordable options that may otherwise be produced with more efficient and sustainable technologies. This can exasperate issues related to food waste and food insecurity. Examples include Vermont's GMO labeling law, push back against new food technologies like the arctic apple, and the attempt in Brazil to ban glyphosate and related court cases here in the U.S.

Don't Throw Good Science Out With the Dirty COI Bathwater

There has been a lot of conversation lately regarding conflicts of interest in research. This recent tweet by Andrew Kniss resonated a lot with me:

Things I've learned recently about how to handle Conflicts of Interest:
1) if COI is not disclosed, dismiss the work as biased.
2) if the COI is disclosed, dismiss the work as biased.
3) if no COI exists, dismiss the work as biased because the author isn't being transparent.

— Andrew Kniss (@WyoWeeds) September 14, 2018

No doubt conflicts of interest are important to be aware of and understand. We definitely want to maintain the highest integrity with regard to science communication and research. However, it is important that COI 'labels' don't become the new 'free-from' label i.e. we don't want a conflict of interest to necessarily become conflated with bad science any more than we would want a GMO label to be conflated with unhealthy or unsustainable. We don't want COI to become the red herring for smear campaigns, political correctness, or a disincentive to doing good science.

About a year ago during one of his excellent talking biotech podcasts (specifically regarding the movie Food Evolution) Kevin Folta made an excellent point about COI and bias in research:

"I've trained for 30 years to be able to understand statistics and experimental design and interpretation...I'll decide based on the quality of the data and the experimental design....that's what we do."

COI involve a delicate balance. I think the recent controversy around COI highlights the importance for producers and communicators of science to get this right. There's also a challenge for consumers of science to know how to recognize good science without throwing it out with the COI bathwater.

CRISPR and Gene Editing Blueprint Analogy

There was a nice guest post on AgWeb recently titled:

Gene Editing: Building Better Blueprints, One Gene at a Time. 

I really like the blueprint analogy as a means to help people understand how gene editing is similar and different from other technologies. Many consumers that are skeptical of advances in food technology are comfortable with older technologies or don't realize the differences.

As Bob Reiter stated in the article:

"Now consider this: what if there was a defect in the blueprint for the house? If we followed those instructions anyway, the defect would be built into the house – which could later lead to structural problems, ranging from minor to catastrophic, depending on which part the defect involved."

Messing up the blueprint is what a lot of consumers are hesitant about when it comes to traditional recombinant DNA technologies (a.k.a. 'GMOs'). They are worried about unknown downstream structural problems and the impact that could have on human health. To put this in other terms, genomic disruptions. In response they advocate for more regulations, testing, and labeling of 'GMO' foods and many are calling for a similar framework for gene edited foods. And food manufacturers take advantage of the marketing opportunities created by these concerns. Ever heard of the non-GMO Project?

But the blueprint analogy is actually helpful here. As Bob explains, in college he was careful about designing the blueprint. If we think of gene editing like making careful targeted changes to the blueprint, USDA organic approved technologies (methods using radiation or chemical mutagens) are more like his intoxicated fraternity brothers sneaking in making random changes to his plans without him knowing. Perhaps they introduce really cool innovations! On the other hand, the roof might leak, the plumbing could drain backwards, or worse. To put it differently, the number of genomic disruptions are far greater and unknown.

You would think, if customers and regulators were concerned about Bob's targeted changes (maybe they would insist that someone from the county does an inspection before proceeding with the construction) they would really be worried about the changes brought about by his inebriated counterparts. However, if we analogize back to mutagenic conventional and organic food, they don't seem concerned at all. They have accepted a build it and see what happens later attitude. No testing. No labeling. (other than maybe that Butterfly food marketers like to stamp on everything from rock salt to water). Of course, from a scientific risk based perspective, there probably is not a reason for testing or labeling these foods....if consumers already understand and accept this that should be a step further down a path toward newer 'safer' technologies that promise so much more.

You can only take an analogy so far but I like Bob's.

See also: Organic Activists Realize Hypocrisy On Gene Editing and Biotech

References:

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

The convergence of data science, genomics, and technology

This is a couple years old but just as relevant and inspiring:

"I believe the future of agriculture will be shaped by continued improvements in efficiency. By more effectively applying the advancements that have come from the green and biotech revolutions, we can continue to see yield increases across the world. We can use data science to drive agronomic practice improvements that enhance existing technologies, like advanced seed genetics. Data science technologies can build upon the yield potential already present in each seed by providing farmers with actionable insights they can use to drive efficiency improvements on their operations, getting the most out of every single plant." - Erik Andrejko, Director of Science, Head of Data Science at The Climate Corporation (2015)

From: https://climate.com/blog/applying-data-science-to-enhance-farming-practices

See also: Monoculture vs. the Convergence of Big Data and Genomics

The 'free-from' Nash equilibrium

Recently I was reading an article, "The big Washington food fight" in Politico discussing challenges of bringing diverse interests and perspectives on food issues under one roof through the Grocery Manufacturers Association. 

There are a couple things influencing my thinking about this. One is the idea that voters and consumers may have systemic biases in their knowledge and preferences in general and specifically about food and technology. The other thing is related to recent research showing a divergence between public perceptions and science driven by political leaning....a divergence that widens *with* more education and science knowledge (see http://www.pnas.org/content/114/36/9587 ).

So in this context, what does it mean to say 'the customer is always right' and how do you give the customer what they want, but do it with integrity? There seem to be two dominant approaches or paradigms followed by food companies for dealing with this. 

One approach is going all in with 'negative' advertising or 'free from' labeling regardless of scientific justification. This paradigm feigns or fakes transparency in the sense it acknowledges consumer preferences related to knowing 'what is in their food' but adds lots of confusion about substantial differences related to food safety and sustainability. The other paradigm takes a 'less is more' approach in terms of honest disclosure about these technologies.

A more generous interpretation of the first behavior is that these food retailers and manufacturers are cognizant of consumer preferences, and assume great deal of consumer ignorance. Take for instance consumers attempting to avoid gluten (reasons why merit a separate discussion). Retailers may assume consumers are extremely ignorant of the fact that gluten originates from wheat based ingredients. A number of food products (like apples, raisins, ground beef, potatoes, carrots etc.) generally would not possibly contain gluten unless they were highly processed or prepared using some wheat based ingredient. As an extreme example for illustrative purposes, we might imagine an uninformed consumer choosing between a bag of carrots and a loaf of bread. A manufacturer would feel they are helping the consumer simplify the decision by adding a 'gluten free' label to the bag of carrots. Additionally, if competitor brands don't have the label, they may risk losing a sale to the 'gluten free' labeled product if a large enough number of uninformed consumers are trying to avoid gluten. We end up with a Nash equilibrium strategy to employ 'free from'labels that really make no sense from a nutritional or scientific standpoint. Gluten is just one example, the logic easily carries over to a number of food products and ingredients (i.e. free-from labels related to added hormones in pork and poultry, GMO free tomatoes etc.)

Helping consumers avoid what they *think* or *perceive* to be harmful to themselves or the environment using this strategy may help increase or defend sales, but it does very little to truly educate consumers about food choices. It likely perpetuates ignorance and myths about food, nutrition, health, and sustainability. Worse, in some cases it may directly or indirectly lead to consumers actually choosing marginally less healthy or less sustainable products or technologies either directly or indirectly because of decreased viability of marketing alternatively sustainable foods (i.e. the loss of rBST from the milk supply).

Whichever paradigm becomes the most dominant (both in the marketplace and the ballot box) may ultimately influence the types of products we see on the shelves and reduce the potential for healthier and more environmentally sustainable solutions to challenging worldwide problems. Efforts to escape this less than optimal Nash equilibrium position could include restrictions limiting free from labels to only non-obvious food products but I am not sure this is a viable solution.

Sometimes people devise cooperative ways to escape from a Nash equilibrium without resorting to taxes or regulation. Nobel prize winning economist Elinor Ostrom's work speaks to this:

"Predictions that individuals will not devise, precommit to, and monitor their own rules to change the structure of interdependent situations so as to obtain joint benefits are not consistent with evidence that some individuals have overcome these problems, although others have not." - Governing the Commons: The Evolution of Institutions for Collective Action. By Elinor Ostrom

But how would this work? The recent backlash by the scientific community regarding StonyField Organic's portrayal of young girls in a Facebook video and the Peel Back the Label movement are two examples of social harassment costs or other monitoring behaviors within the industry that may give some hope. Will this continue or become a large enough force for change?