Thursday, December 30, 2021

Facts, Figures, or Fiction: Unwarranted Criticisms of the Biden Administration's Failure to Target Methane Emissions from Livestock

Background

Methane has gotten a lot of attention recently in relation to fighting climate change:

"The oil, gas and coal industries are the largest source of human-caused methane emissions. An Environmental Defense Fund study found that cutting methane emissions now could slow the near-term rate of global warming by as much as 30%."

While these facts may be true, it takes theory to explain facts, and unfortunately bad theory leads to bad decisions even if we get the facts right. A recent article in Politico provides an example in it's criticism of the Biden administration's failure to target methane emissions from livestock to combat climate change:

"This creative accounting and the administration’s policies belittle the livestock industry’s role in the methane emergency. While Biden and other U.S. officials are preaching the importance of slashing methane emissions to prevent catastrophic warming and imposing tough new methane regulations on fossil fuel companies, they are allowing super-polluting meat and dairy corporations to continue to emit massive amounts of the same greenhouse gas with impunity."

Are all methane sources equal?

Accounting for methane is key, but there is a lot of nuance to understand about methane in order to account for it appropriately so that we take the right course of action when it comes to policy and food choices.

Let's start with a bigger picture looking at total GHG emissions by source:

Source: https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks 

When we drill into agriculture and focus on beef in the U.S. we find that it accounts for about 4% of total emissions. But on a global scale, which matters most to climate change, overall, total GHG emissions related to U.S. beef consumption accounts for less than 1/2 of 1% (i.e. .5%) of global GHG emissions (EPA GHG Emissions Inventory, Rotz et al, 2018). When we talk about methane emissions associated with eating U.S. sourced beef in the U.S., we are talking about a very thin slice of total global warming potential. 

When we zoom in on this slice of potential and focus on methane this is what we see according to the current administration's Methane Emissions Reduction Action Plan:

Source: https://www.whitehouse.gov/wp-content/uploads/2021/11/US-Methane-Emissions-Reduction-Action-Plan-1.pdf  

Enteric emissions account for all ruminant livestock emissions in the U.S. which would include both beef and dairy but that gives us a pretty good picture. Again, we have facts that are all true, but *how* should we interpret this? A naive interpretation would be to simply compare the pieces of the pie assuming that we can make apples to apples comparisons between each piece and choose a course of action based on the 'facts.'  But this would be misleading without understanding the underlying biology and data generating mechanisms giving rise to this data.

The crude infographic that I put together below sheds some light on this (See this video for a better illustration or Dr. Frank Mitloehner's more detailed explanation of the biogenic carbon cycle here; see also Allen, M.R., Shine, K.P., Fuglestvedt, J.S. et al., 2018). At the highest level, methane emissions produced by beef cattle are constantly recycled. The ultimate source of methane starts in plants and is consumed by livestock and later removed from the atmosphere in the form of CO2 by plants again to repeat. This can be visualized by a tank with water going in and eventually draining out. In this context methane is a 'flow' gas.

Methane sourced from natural gas and petroleum behaves differently. When we extract, refine, and burn fossil fuels the methane associated with this is released into the atmosphere, but absent any sort of mitigation it ultimately converts to CO2 where it remains to have a long lasting warming effect. This can be visualized by a tank with water going in but never draining out. 


In relation to the first tank representing enteric emissions from livestock, there are additional nuances. When we look at U.S. cattle inventories over the last 30 years what we see is that the rate of flow from the faucet has mostly been decreasing. We have not only been recycling the same methane in the atmosphere over and over the last few decades, but less of it. Thanks to advances in economic development, technological change, innovations in management, marketing, and pricing value in the beef industry (for just a few examples see herehere, here, here, and here), we've seen gains in beef production and quality. Additionally, in 2007 compared to 1977 we were able to produce the same amount of beef using roughly 30% fewer cattle and 30% less land. Feed and and water usage were down between 15-20% with a 16% lower carbon footprint (Capper, 2007). All of these factors have culminated in a healthier, more nutritious, higher quality product with a lower carbon footprint. We can't say the same about methane associated with fossil fuels and transportation which continues to flow at greater rates and doesn't get recycled. 


Source: https://www.nass.usda.gov/Newsroom/2021/01-29-2021.php 

So when you get in your car to go to your favorite restaurant, the associated methane and CO2 emissions that result represents new and long lasting emissions. For the most part the steak or burger on your plate doesn't directly add any new warming potential to the atmosphere that didn't already exist, nor has any steak or burger you may have eaten in the last 30 years based on this data! 

Are all sources of beef equal?

Why focus on U.S. beef production and consumption in this discussion? Because in the Politico article and in many conversations like this, the context is often subtly switched between consumers of U.S. beef and consumption of beef sourced in other parts of the world as if they are substitutes. This change in context ignores important differences between technological capabilities and production practices but also differences in incomes, tastes, and preferences. A lot of the criticism of U.S. beef may actually be true in relation to beef produced and consumed in other parts of the world. We are not burning down rain forests in the U.S. in order to produce and consume beef, and the indirect connection between U.S. beef production and consumption and deforestation in other parts of the world is very weak due to the way global beef markets function. However, there are opportunities to make beef greener in other parts of the world that should not be ignored and should be researched further (see Mrode et al., 2019; Silva et al., 2018; Gates, 2017).

Should we just ignore the very potent warming potential represented by methane emissions associated with U.S. beef consumption just because it represents a thin slice of the global pie that is relevant to climate change? No, but we should put it in the proper perspective, and think of the overall global portfolio of choices we make in our diets and daily lives and not get anchored on facts divorced from the proper context so we can actually make impactful decisions. 

Consumer fads and a climate friendly behavior change strategy

As discussed above, even if all U.S. consumers gave up beef tomorrow cold turkey, there is an upper limit on the impact we can have globally. Modest changes either reducing beef consumption or switching to alternative proteins would be even less impactful. However, we should still recognize that lots of small changes could add up to have a meaningful effect in the aggregate. Given the behavioral and nutritional challenges that make any meaningful reduction in beef consumption mostly impractical at a population level (and ignoring the elephant in the room that is transportation) it is an empirical question as to what other seemingly arbitrary lifestyle changes we could suggest to decrease our impact on climate - maybe that once a week trip to the grocer to buy in bulk instead of having the fleet of Amazon, UPS, and FedEx trucks down your street multiple times a week is one example. Other consumerist trends we've seen that could also be adding to our carbon footprint could involve the fads and infatuation with local, natural, and organic food consumption, and the notorious 'free-from' food marketing campaigns that tend to demonize climate saving technologies (see here, here, here, here, here, and here for related info). 

Putting the lens of behavioral science on this, we need to think about the problem we are trying to solve or outcome we are trying to achieve (climate change mitigation) and consider the behavioral map that relates all of the target actions we could take to achieve this outcome. What role does science literacy and misinformation and disinformation play in the trends and food fads noted above that could lead to hesitancy to adopt climate saving technologies? Which solutions are technically correct but also the most impactful at scale from a behavior change perspective? Is a reduction in modern U.S. beef production or consumption the target behavior we should be trying to change compared to other options? Maybe for some people but I'm not convinced it is a global solution. 

Getting the most nutritional bang for our climate buck

How do we know we are getting the most nutritional bang for our climate buck when thinking through this? In a 2010 Food and Nutrition Research article, authors introduce the Nutrient Density to Climate Impact (NDCI) index. Metrics like this could add some perspective. According to their work:

"the NDCI index was 0 for carbonated water, soft drink, and beer and below 0.1 for red wine and oat drink. The NDCI index was similar for orange juice (0.28) and soy drink  (0.25). Due to a very high-nutrient density, the NDCI index for milk was substantially higher (0.54) than for the other beverages. Future discussion on how changes in food consumption patterns might help avert climate change need to take both GHG emission and nutrient density of foods and beverages into account."

Authors Drewnowski, Adam et al. apply this more nuanced approach to 34 different food categories including meat and dairy:

"Efforts to decrease global GHGEs while maintaining nutritionally adequate, affordable, and acceptable diets need to be guided by considerations of the ND and environmental impact of different foods and food groups. In a series of recent studies, the principal sustainability measure was carbon cost expressed in terms of GHGEs (8, 14, 15). Testing the relation between nutrient profile of foods and their carbon footprint can help identify those food groups that provide both calories and optimal nutrition at a low carbon cost."


Just as combining trips and carpooling might be effective ways to reduce your carbon footprint getting the most out of every mile driven and gallon of gas used, to be truly impactful regarding climate change, we should be trying to get the most out of every bite we take and ounce we drink. 

Weighing efficiency and values

The previous discussion starts to sound a lot like a position related to optimization and efficiency which ultimately requires making value judgements that science and economics can't make.

As discussed in Heyne, Boettke, and Prychitco's text The Economic Way of Thinking:

"efficiency is essentially an evaluative term. It always has to do with the ratio fo the value of output to the value of input...in effect it depends on what people want done and how they value what they want done. It follows that the efficiency of any process can change with changes in valuations."

What I am getting at is that maybe people prefer to have sustenance from beef vs rice or other alternatives and we have to give weight to that in a policy framework. Physical and technical facts alone can never fully determine efficiency. That's what makes economics so powerful. Its the study of people's choices and how they are made compatible. It is way more than just the study of the technical allocation of resources because it forces us to consider each individual's preferences based on the knowledge of their specific circumstances of time and place.

Science and economics can't make value judgements for us, but we should strive get the facts right, and the stories we tell with the facts need to be true to the science behind them. 

Additional and Related References:

HJ. L. Capper, The environmental impact of beef production in the United States: 1977 compared with 2007, Journal of Animal Science, Volume 89, Issue 12, December 2011, Pages 4249–4261, https://doi.org/10.2527/jas.2010-3784

Rafael De Oliveira Silva, Luis Gustavo Barioni, Giampaolo Queiroz Pellegrino, Dominic Moran, The role of agricultural intensification in Brazil's Nationally Determined Contribution on emissions mitigation, Agricultural Systems, Volume 161, 2018, Pages 102-112, ISSN 0308-521X, https://doi.org/10.1016/j.agsy.2018.01.003.

Mrode, R., Ojango, J., Okeyo, A. M., & Mwacharo, J. M. (2019). Genomic Selection and Use of Molecular Tools in Breeding Programs for Indigenous and Crossbred Cattle in Developing Countries: Current Status and Future Prospects. Frontiers in genetics, 9, 694. https://doi.org/10.3389/fgene.2018.00694

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 

https://phys.org/news/2019-03-beef-resource-greenhouse-gas-emissions.html

What cowboys can teach us about feeding the world. Could a cattle ranch in Australia improve food security in Africa? Bill Gates. Gates Notes. July 18, 2017. https://www.gatesnotes.com/Development/What-Cowboys-Can-Teach-Us-About-Feeding-the-World?WT.mc_id=07_18_2017_10_AustralianCattle_BG-LI_&WT.tsrc=BGLI

Scarborough, P., & Rayner, M. (2010). Nutrient Density to Climate Impact index is an inappropriate system for ranking beverages in order of climate impact per nutritional value. Food & nutrition research, 54, 10.3402/fnr.v54i0.5681. https://doi.org/10.3402/fnr.v54i0.5681

Drewnowski, Adam et al. “Energy and nutrient density of foods in relation to their carbon footprint.” The American journal of clinical nutrition 101 1 (2015): 184-91 .

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

Thursday, October 21, 2021

The Supply Chain Knowledge Problem

Our current supply chain struggles can largely be understood through the lens of the fundamental problem of economics, the knowledge problem. The knowledge problem was originally characterized by Hayek:

"The economic problem of society is not merely a problem of how to allocate given resources....it is a problem of utilization of knowledge which is not given to anyone in its totality."

This can be understood by recognizing that 'know how' and 'know what' are spread across many minds to paraphrase some of the work by economist Kenneth E. Boulding and as discussed in Peter Boettke's Living Economics. The knowledge problem is also exemplified in the words of Leonard E. Read's pencil in his essay I, Pencil, "Not a single person on the face of this earth knows how to make me."

This excellent YouTube video update of Read's essay provides a modern illustration:


"if I didn't already exist you might think that such a flowering of free cooperation, competition, and creation was either impossible or magical and yet here I am!"


How does this apply to our supply chain issues? Well because 'know how' and 'know what' are spread across so many minds, not a single person on the face of the earth knows how to make anything. As a result, no one has the knowledge to fix our supply chains. Our supply chains are the result of human action but not human design. Of course this is a feature and not a bug. As a result most consumers and policy makers usually remain comfortably blind to the knowledge problem and the role of the price mechanism that solves it.


Our economy is not analogous to an engine that will automatically restart after shutting down like the engine of a car at a traffic light. Instead of thinking of our economy and the supply chains that sustain it as a mechanical system that can be engineered by technicians, a better analogy is an evolving ecosystem. Each product we consume and its components have evolved to fit into very specific niches. We could think of our supply chains as habitats that have been threatened by COVID and our response to it.


Just as restoring an ecosystem after an environmental disaster requires an understanding of ecology, we must understand the ecology of our markets and supply chains in order to restore our economy and avoid an even worse ecological disaster. We must recognize that the knowledge problem post COVID is more challenging than pre covid made evident by recent price spikes and shortages that some people could be confusing for monetary inflation. We have to understand that our supply chains evolved over a number of years, even decades, and ‘regrowth’ will take time and things may not grow back to look like they did before.This could mean higher prices now and well into the near future for a number of goods, with some items reaching new higher equilibrium levels as tastes, preferences, and production practices may have changed post COVID. 


COVID and our response to it unfortunately destroyed the ‘know what’ and ‘know how’ that was spread across millions of minds and across decades of building our supply chains. There is no simple blunt monetary or fiscal policy that can substitute for the ‘know how’ and ‘know what’ it’s going to take to rebuild them. It’s going to take time. Prices have to search and signal for the ‘know how’ and ‘know what’ to rediscover and rebuild what was lost.


Our supply chains co-evolved over time with a number of prohibitions and frictions. We learned during the pandemic the potential of relaxing some prohibitions such as those in healthcare, which allowed supply to creatively meet demand using telemedicine. What other opportunities exist to help rebuild our supply chains?


Policy makers must think carefully about how to respond going forward and must be willing to allow new species to emerge as different sustainable patterns of specialization and trade evolve post COIVD. Because, they don't possess the ‘know how’ and ‘know what’ to fix it. If anything, COVID has reminded us all of the words of Frederick Hayek:"The curious task of economics is to demonstrate to men how little they really know about what they imagine they can design."



Notes and References:

Friedrich Hayek (September 1945). "The Use of Knowledge in Society" (PDF). The American Economic Review. 35 (4): 519–530

Living EconomicsYesterday, Today, and Tomorrow. Peter J. Boettke. 2012.


Sunday, August 08, 2021

Battling Vaccine Hesitancy: Asking and Not Telling?

We often hear that science and evidence rarely will change minds when it comes to biotechnology or climate change,  (or vaccine hesitancy). But some think maybe there is a strategy to get out in front of misinformation. In a previous post I discussed an article 'Finding a Vaccine for Misinformation.' The authors discuss 'inoculating' consumers through gamification so that they are less susceptible to misinformation. 

"Introne believes that he can use this approach to target the weakest links in false narratives and bring people closer to changing their minds. He says that if he can deliver information that doesn’t conflict with a person’s belief state but still brings them around to a more accurate point of view, “then I’ve got a pretty powerful thing.”

Thinking more about this I was reminded of an article in the Journal of the Federation for American Societies for Experimental Biology (FASEB) where Jayson Lusk and Brandon McFadden observed the following:

1) consumers, as a group, are unknowledgeable about GMOs, genetics, and plant breeding and, perhaps more interestingly

2) simply asking these objective knowledge questions served to lower subjective, self-assessed knowledge of GMOs (i.e., people realize they didn't know as much as they thought they did) and increase the belief that it is safe to eat GM food. 

So essentially, just asking skeptics the right questions appeared to mitigate the Dunning Kruger effect and decreased resistance to evidence based views on the safety of genetically engineered foods. Asking, rather than telling in this scenario seems consistent with the strategy of innculating consumers against misinformation and disinformation. 

References: 

News Feature: Finding a vaccine for misinformation.Gayathri Vaidyanathan. Proceedings of the National Academy of Sciences Aug 2020, 117 (32) 18902-18905; DOI: 10.1073/pnas.2013249117 https://www.pnas.org/content/117/32/18902

McFadden, B.R. and Lusk, J.L. (2016), What consumers don't know about genetically modified food, and how that affects beliefs. Faseb, 30: 3091-3096. https://doi.org/10.1096/fj.201600598

Thursday, August 05, 2021

Rational Irrationality and Behavioral Economic Frameworks for Combating Vaccine Hesitancy

Background and Introduction


Some previous work on vaccine hesitancy related to childhood vaccinations inspired by Caplan's notion of rational irrationality indicates parents willing to bear costs as high as $8,000 in order to avoid vaccinating their children. What is the associated willingness to pay (WTP) in order to avoid COVID vaccination? What kinds of intervention strategies are supported by various behavioral economic frameworks for combating vaccine hesitancy in the case of COVID19?


Social Harassment Costs and Imperviousness to Evidence


In a previous post, I discussed the role of social harassment as it relates to one’s worldview and the disutility associated with changing one’s mind or updating one’s prior about that worldview as a result.


 

 

(Figure 1)

 

Depending on one's peer group, and the level of social harassment, consumers might express preferences that otherwise might seem irrational from a scientific standpoint. For example, based on peer group, a consumer might embrace scientific evidence related to climate change, but due to strong levels of social harassment, reject the views of the broader medical and scientific community related to the safety of genetically engineered foods. 


Near Neoclassical Demand Curve and Rational Irrationality


Bryan Caplan's notion of rational irrationality might also explain these kinds of preferences:


"...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."


This can be modeled in the form of a kinked ‘near’ Neoclassical demand curve as depicted below. Caplan hypothesized that in many cases, the cost of holding irrational beliefs can be low or near zero and people make tradeoffs with regard to the level of rationality they consume.




(Figure 2)



Below Pa, people are willing to make tradeoffs between price and the ‘amount’ of irrationality they consume. It might then follow that if members of society are opposed to genetically engineered foods, they may be willing to pay up to Pa to avoid foods with GMO ingredients.


Implications for Combating Vaccine Hesitancy


So if the cost of holding antivax views (we can think of costs in terms of perceived risk of serious illness, loss of work, risk of quarantine, and other opportunity costs associated with not getting vaccinated) is below some level Pa, then one may be willing to make tradeoffs with regard to the level of irrationality they want to consume (we can think of the level of consumption as level of vaccine hesitancy or probability of getting vaccinated). This is represented by the portion Pa - Qa of Caplan’s near neoclassical demand curve representing rational irrationality.


Murphy (2016) extends Caplan’s model of rational irrationality to include applications where demand for irrationality occurs at prices greater than zero. In his paper he applies this theory to things like willingness to pay for ‘fair trade goods’ and vaccine hesitancy. 

 

For example, he calculates the willingness to pay (WTP) to avoid childhood vaccinations from the parent’s perspective as follows:

 

WTP = WTP to avoid 1 yr sickness × premium for child × increase in probability of 1yr of sickness

 

He looks at vaccines for pertussis, invasive pneumococcal disease, and varicella and based on certain assumptions calculates the WTP. 

 

Using the median assumption that parents value the statistical life of their children 50% more than they value their own lives, the cost implicit in not vaccinating for these three diseases is US$8,420. As pointed out earlier, as many as ten percent of families exhibit this willingness-to-pay—and they do so repeatedly should they have more than one child. Under the influence of retracted evidence, thousands of parents retreat to the naturalistic fallacy, rejecting modern medicine they deem to be artificial.”

 

How might we apply this to combating vaccine hesitancy related to COVID? For instance, if these parents were offered more than their WTP to avoid vaccination then they may be willing to get their children vaccinated for the three conditions mentioned above. But what is the WTP to avoid COVID vaccination? $8000 is really high on an individual basis, and given the resistance and hesitancy we have seen to this point I would not expect a very low price point among the most staunch resistors. This may explain why some have concluded that offering lottery tickets to induce vaccinations may not have been as impactful as hoped:


“Our results suggest that state-based lotteries are of limited value in increasing vaccine uptake. Therefore, the resources devoted to vaccine lotteries may be more successfully invested in programs that target underlying reasons for vaccine hesitancy and low vaccine uptake”

 

The hope of the lottery was based on the idea that people tend to either overestimate or completely ignore low probability events. From a behavioral economic perspective we were hoping that those that were ignoring the risk of COVID might overestimate their chances of winning the lottery and be induced to get vaccinated. Apparently the expected values of the lottery did not exceed WTP in the case of COVID vaccination. There has been some recent interest in offering direct payments to people to get vaccinated. For instance the idea of paying up to $100 or even $1000 has been floated in the last year. 


Some have pushed back on this. Recently the Biden administration has apparently endorsed $100 payments.

  

Depending on an individual's relative WTP, paying folks to be vaccinated may or may not be promising. If social harassment costs (based on my framework) are an important factor, then this could also impact the optimal WTP to target with such an outreach.

 

We also have to recognize the role of externalities. While there are negative externalities associated with not getting vaccinated, the positive externalities are great. For instance, if we were doing a WTP calculation to encourage vaccination, we should add some premium to that payment to account for positive externalities associated with getting vaccinated to justify the costs and increase the effectiveness of the incentive. It is an important question if the WTP for the vaccine hesitant on average is so large that this becomes prohibitively expensive.

 

Alternatively, targeting WTP does not have to be shouldered by government. Private employers can also offer similar incentives to get vaccinated either in the form of direct payments or penalties.


But it is hard to say if these sorts of WTP calculations would be useful for targeting 'the right' payment to incentivize vaccination if that is even something we should be doing, or if it is cost effective especially given the heterogeneity of preferences and attitudes toward risk in the population. We would need to know more. But the concept itself is probably most useful as a way to think about and quantify the level of resistance and think of what kinds of communication strategies and nudges would work best to increase vaccinations. What things could we do to reduce WTP or increase the opportunity costs of refusing the vaccine. More below.

 

Other Approaches

 

In 'Finding a vaccine for misinformation'  (Vaidyanathan, 2020) authors address the challenges of misinformation as it relates to vaccine hesitancy and leverage some of the same behavioral economic frameworks.

 

They go on to explain that our worldview (pre-existing internal stories based on our our mental tapestry of culture, knowledge, beliefs, and life experiences) determines which gist is stored and resonates (and impacts our resistance to updating our priors with new evidence).

 

Part of their strategy for dealing with this is 'inoculating' consumers through gamification so that they are less susceptible to misinformation. 

 

"Introne believes that he can use this approach to target the weakest links in false narratives and bring people closer to changing their minds. He says that if he can deliver information that doesn’t conflict with a person’s belief state but still brings them around to a more accurate point of view, “then I’ve got a pretty powerful thing.”

 

In the rational irrationality and social harassment frameworks above, by circumventing or inoculating against misinformation and getting out in front of it you can combat hesitancy or dampen the the extent to which adopting worldview  v* lowers utility. Similarly, if we can deliver information in a way to get people to adopt v* without lowering utility, that would be a very impactful communication strategy. 

 

BE works has applied behavioral economics to understanding and responding to vaccine hesitancy. They identified four cognitive factors driving hesitancy including one factor related to valuing personal beliefs over evidence (which sounds a lot like the rational irrationality framework we have been discussing here). (See “COVID-19 Vaccine Hesitancy: A Behavioral Lens on a Critical Problem” ) They followed up with a report and recommendations on combating hesitancy based on these findings (BEACON: A Strategic Framework for Overcoming Vaccine Hesitancy). These reports and more are available from the BE Works website (https://beworks.com/covid-19/ )

 

One of the strategies highlighted in this work consistent with the rational irrationality and social harassment frameworks laid out above includes leveraging social capital:

 

"Communications aimed at sharing relevant vaccination-positive stories of people within the recipients’ peer groups, or other groups to whom an individual feels a strong social connection, could foster a positive view of vaccination and help them see it as a routine and valued step within their identified community...."

 

Communications from key people in a social network (i.e. figure 1 above) may accomplish this. So an outreach targeted at these people or enlisting their efforts could be an impactful way to get members to accept vaccinations without increasing related social harassment costs and lowering utility. These people might also be a way to deliver information that doesn’t conflict with a person’s belief state as discussed above (having the same impact on social harassment and utility).

 

Conclusion

 

While we may not be able to guess everyone's WTP to get vaccinated, we should diversify our approach to targeting it or equivalently raising the opportunity costs of not getting vaccinated such that P > Pa in the context of near neoclassical demand curve above. The most effective approach may be private sector initiatives such as vaccine requirements or bonus payments for getting vaccinated. There are also ways we might leverage behavioral economics and behavioral design frameworks to magnify our impact. Most of our learnings from combating misinformation and disinformation indicate that this takes more than communicating accurate information, it requires communicating with intent and influence. But in the case of vaccinations, even small wins can result in great improvements as Murphy points out in his article.

 

 “Economic education may struggle to sway the median voter; it may only move those with roughly correct priors regarding economic questions towards a more consistent, factual worldview. On the other hand, for each and every person convinced to vaccinate their children, the world is made better off. Some may dismiss these prescriptions, but they may have far more practical effect. Convince 300 individuals that free trade is good, the chance this changes trade policy is vanishingly small. Convince 300 individuals to vaccinate their children, and society tangibly improves. When it comes to persuasion on private markets, unlike politics, every- one is the marginal decision-maker for the irrationality present in their own lives.”

 

Similar to the swiss cheese model of non-pharmacological interventions in absence of a vaccine, a layered approach based on several behavioral economics frameworks seems most pragmatic for dealing with vaccine hesitancy.

 

See also:


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


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


Consumer Perceptions, Misinformation, and Vaccine Hesitancy







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

 

Murphy RH. The willingness-to-pay for Caplanian irrationality. Rationality and Society. 2016;28(1):52-82. doi:10.1177/1043463115605478


 News Feature: Finding a vaccine for misinformation.Gayathri Vaidyanathan. Proceedings of the National Academy of Sciences Aug 2020, 117 (32) 18902-18905; DOI: 10.1073/pnas.2013249117 https://www.pnas.org/content/117/32/18902

Saturday, July 10, 2021

Can Capitalism Be A Force For Good When it Comes to Food?

Great discussion at the AgTech So What podcast about capitalism and food innovation. Probably an innovation that gets the most headlines these days, and discussed in the headlines is related to plant based proteins and companies like Impossible Foods. But to answer the question more broadly, can capitalism be a force for good in the food and agricultural sector, we can look at previous ag tech innovations to get some kind of answer. 

For example, positive benefits associated with the development of biotech crops include non-trivial decreases in greenhouse gas emissions equivalent to the removal of nearly 12 million cars from America's roads on an annual basis (this is roughly 50% of the number of new cars purchased annually). Additionally, we see benefits in terms of improved health and safety related to decreased levels of mycotoxins, reduced pesticide exposure, reduced groundwater pollution, and improved biodiversity to name some of the health and environmental benefits as well as social benefits related to gender equity.

In the livestock sector we've also seen incredible improvements in the health and environmental benefits related to beef. Thanks to advances in economic development, technological change, innovations in management, marketing, and pricing (for just a few examples see here, here, here, here, and here), we've seen gains in beef production and quality. For instance, consider Brad Johnson's work at Texas Tech related to increasing marbling and healthy fats without increasing unhealthy backfat while also reducing time on feed. Or like the research in beef genetics and air quality and emissions at U.C. Davis.

In 2007 compared to 1977 we were able to produce the same amount of beef using roughly 30% fewer cattle and 30% less land. Feed and and water usage were down between 15-20% with a 16% lower carbon footprint (Capper, 2007). All in all, based on full lifecycle analysis, U.S. beef consumption accounts for less than .5% of global greenhouse gas emissions. Additionally when compared to beef produced and consumed in other parts of the world, the carbon footprint of beef produced and consumed in the U.S. is 10 times or more lower (Herrero et al., 2013).

While not realized yet, with technological advancements like blockchain and IoT, the potential to exploit innovative ideas like animal welfare units discussed by economist Jayson Lusk could be another unexploited opportunity given the right strategy.

And these technologies don't require scaling up 100 fold or doubling every year for the next 16 years the way some analysts project for cell cultured meat. Nor do they require drastic dietary or lifestyle changes. These positive benefits are driven by capital investment and consumer and producer driven choices in the marketplace without the requirement of coercive mitigating policies or significant behavior change. That's not to say more can't be done or that the last mile won't be difficult, but it is a testament to the role markets and technological innovation have played in the last few decades that is often overlooked or even shunned in many contemporary conversations.

References:

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

https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions 

Lusk, J.L. The market for animal welfare. Agric Hum Values 28, 561–575 (2011). https://doi.org/10.1007/s10460-011-9318-x

Environmental impacts of genetically modified (GM) crop use 1996–2015: Impacts on pesticide use and carbon emissions
Graham Brookes & Peter Barfoot
GM Crops & Food Vol. 8 , Iss. 2,2017
Link: http://www.tandfonline.com/doi/full/10.1080/21645698.2017.1309490

The environmental impact of recombinant bovine somatotropin (rbST) use in dairy production Judith L. Capper,* Euridice Castañeda-Gutiérrez,*† Roger A. Cady,‡ and Dale E. Bauman* Proc Natl Acad Sci U S A. 2008 July 15; 105(28): 9668–967

Texas Tech University. "Increasing marbling in beef without increasing overall fatness." ScienceDaily. ScienceDaily, 5 May 2016. <www.sciencedaily.com/releases/2016/05/160505223115.htm>.

J. L. Capper, The environmental impact of beef production in the United States: 1977 compared with 2007, Journal of Animal Science, Volume 89, Issue 12, December 2011, Pages 4249–4261, https://doi.org/10.2527/jas.2010-3784

Herrero M, Havlík P, Valin H, Notenbaert A, Rufino MC, Thornton PK, Blümmel M, Weiss F, Grace D, Obersteiner M. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc Natl Acad Sci U S A. 2013 Dec 24;110(52):20888-93. doi: 10.1073/pnas.1308149110. PMID: 24344273; PMCID: PMC3876224.

Saturday, April 24, 2021

The Economics of Innovation in Biopharma


This podcast touches on the lack of innovation in pharma and criticism about outsourcing innovation. Do these criticisms ignore recent technological advances in biotech (and the convergence of AI and genomics) that have reduced the minimum efficient scale in drug discovery creating new opportunities for startups, small firms, and scientist entrepreneurs? When we think of therapeutics as dispensing knowledge packed into a capsule or syringe, knowledge that has properties of both a private and public good (i.e. non-rival and partially excludable) scientist entrepreneurs are better incentivized and able to capture greater value from their discoveries in a venture capital funded startup environment than a larger institution like pharmaceutical companies or universities (even with Bayh-Dole Act). Drug discovery is risky, but by combining option value and discovery of new information with staged investment VC firms can discover positive NPV projects that would otherwise be rejected under conventional financing models. The combination of technological change, the economics of knowledge, and venture capital seems to reduce the comparative advantage of innovating 'in-house.' Maybe it is the case that large pharmaceutical firms have more of a comparative advantage navigating the valley of death that lies between a discovery and a cure by focusing on the regulatory approvals and marketing efforts necessary to deliver those products than they have in drug discovery?

Saturday, April 03, 2021

Consumer Perceptions, Misinformation, and Vaccine Hesitancy

In graduate school I focused on how consumer consumption patterns signal social viewpoints, and the role of information and misinformation in the process. Particularly interesting was the observation that some consumers had strongly held science based views related to some issues while simultaneously holding other views that were inconsistent with views of the larger scientific community. What could explain this? I hypothesized a utility maximizing model that involved world views and social harassment costs consistent with the idea that viewpoints that may be irrational based on an objective related to scientific truths and evidence can be rational from the standpoint of personal utility maximization. This isn't so different from the idea of coherence, from Kahneman's Thinking Fast and Slow, where they argue that the coherence of the story matters more than the quality of the evidence. 

In 'Finding a vaccine for misinformation' authors address the challenges of misinformation as it relates to vaccine hesitancy and leverage some of the same behavioral economic frameworks. They explain:

"A coherent story works because our minds don't just encode facts and events into memory...we also store bottom line meaning or 'gist' and it is the stored gist, not the facts, that typically guides our beliefs and behaviors"

They go on to explain that our worldview (pre-existing internal stories based on our our mental tapestry of culture, knowledge, beliefs, and life experiences) determines which gist which is stored and resonates.

Part of their strategy for dealing with this is 'inoculating' consumers through gamification so that they are less susceptible to misinformation. I'm not sure gamification is the answer, but at the least what can be learned from this research definitely could lead to progress on this front:

"Introne believes that he can use this approach to target the weakest links in false narratives and bring people closer to changing their minds. He says that if he can deliver information that doesn’t conflict with a person’s belief state but still brings them around to a more accurate point of view, “then I’ve got a pretty powerful thing.”

This reflects a lot of what we have learned over the years. Simply presenting facts and evidence, telling people they are wrong on the internet so to speak, isn't going to change minds or behavior. Our communication has to be much more strategic with laser like intent. 

References:

News Feature: Finding a vaccine for misinformation.Gayathri Vaidyanathan. Proceedings of the National Academy of Sciences Aug 2020, 117 (32) 18902-18905; DOI: 10.1073/pnas.2013249117 https://www.pnas.org/content/117/32/18902

Related References:

Information Avoidance and Image Concerns. Exley, Christine L and Kessler, Judd B. National Bureau of Economic Research. Working Paper No. 8376 January 2021. doi. 10.3386/w28376. http://www.nber.org/papers/w28376

Related Reading:





Saturday, February 06, 2021

The Convergence of AI, Life Sciences, and Healthcare

Several years ago I was writing about the convergence of AI and genomics in agriculture:

"The disruptions of new technology, big data and genomics (applications like FieldScripts, ACRES, MyJohnDeere or the new concept Kinze planters that switch hybrids on the go etc.) will require the market to continue to offer a range of choices in seeds and genetics to tailor to each producer's circumstances of time and place." (1)

We have also seen a similar convergence in healthcare:

"A series of breakthroughs in medical science and information technology are triggering a convergence between the healthcare industry and the life sciences industry, a convergence that will quickly lead to more intimate—and interactive—relationships among people, their doctors, and biopharmaceutical companies."  (2)

This excellent segment on WBUR just a few years later picks up on the same themes:

Nobel Laureate and MIT Institute professor Phil Sharp has an even broader vision of this convergence: It’s not just computer science and biology that are converging, but engineering, physics, material science and agriculture too, he says.

“Life science is part of all of those processes and bringing physicists and engineering and information technology together to integrate life science with the translation to solving those problems is what convergence is about,” Sharp says. “It'll be decades of exciting science and exciting technology.” (3)

There are a number of parallels I want to discuss below including outcomes and value based pricing, precision medicine and precision agriculture, venture capital and digital solutions, and how these trends are leading to products and solutions that can address some of society's biggest problems like healthcare quality and cost, social determinants of health, and climate change.

Outcomes and Value Based Pricing

Due to this convergence, better data and technology are creating new opportunities. Health insurance companies, healthcare providers, and seed companies are entering into value based contracts where payments are based on outcomes and quality. 

In healthcare:

"By leveraging appropriate software tools, big data is informing the movement toward value-based healthcare and is opening the door to remarkable advancements, even while reducing costs. " (4)

"Value-based healthcare is a healthcare delivery model in which providers, including hospitals and physicians, are paid based on patient health outcomes. Under value-based care agreements, providers are rewarded for helping patients improve their health, reduce the effects and incidence of chronic disease, and live healthier lives in an evidence-based way." (5)

(See below or  https://healthinformatics.uic.edu/blog/shift-from-volume-based-care-to-value-based-care/ for an excellent infographic explaining this promising shift in healthcare)

In food and agriculture we are seeing risk sharing and outcomes based pricing contracts as well:

"...executives are touting their new pricing model, outcome-based pricing, as the potential pricing paradigm of the future. The model involves Bayer setting an expected yield outcome for a product or seed, based on a farm's data and history stored on the company's digital ag platform, FieldView, as well as the company's own research on their products. If a farmer's final yield falls below that expected value, the company will rebate a certain portion of the original price of the product. If the yield instead surpasses the initial set value, the farmer shares a pre-agreed portion of that additional income with the company." (6)

Precision Medicine and Precision Agriculture

Instead of one size fits all best practices for seed, pest management, tillage, and nutrient management recommendations driven by research from university and industry trials, growers can get individually customized prescriptions, not just at the farm or field level, but within field and moving closer and closer to the row foot level for some decisions. The combination of advanced genomics with big data generated from precision agricultural applications (remote sensing, IoT, automated steering, GPS/GIS) makes one size fits all obsolete. 

As I quoted previously: 

"That's also why the market has driven companies to treat hybrid selection like a 'big data' problem and they are developing multivariate recommender systems as tools to assist in this (like ACRES and FieldScripts). The market's response to each individual producer's unique circumstances of time and place also ensures continued diversity of crop genetics planted. There are numerous margins that growers look at when optimizing their seed choices and it will require a number of firms and seed choices to meet these needs as the industry's focus moves from the farm and field level to the data gathered by the row foot with each pass over the field." (1)

Similarly, in healthcare, the golden age of medicine driven by the 'omics' revolution and big data will allow us to move away from one size fits all generalizations of research and medicine allowing us to "tailor medical treatment to the specific characteristics of each patient involving the ability to classify individuals into subpopulations that are uniquely susceptible to a specific treatment, sparing expense and side effects and is derived from doubts on the results of subgroup analyses and on non responders in clinical trials" (7)

"Health systems will have to go rapidly from a one-size-fits-all model of treatment to a more customized model, which still uses mass-manufactured but where treatments are selected for patients based on specific biomarkers," Joshi said. "But we can now see the next advance in personalized medicine potentially going even further, something much more personalized, like a tailor-made suit...."Big data and advances in our understanding of genomics are providing us with the footholds into establishing and understanding, for the first time ever, the causal genetic factors that help us manage that golden triangle of treatment: the right target, the right chemistry, and the right patient." (2)

Venture Capital and Digital Platforms and Solutions

Monsanto's (now Bayer Crop Science) acquisition of The Climate Corporation occurred about the same time I was penning my first post on this convergence, and was the first major move in industry that solidified these potential synergies in my mind at least. This convergence has drawn the interest and has been fueled by a number of startups and venture capital firms. Farmer's Business Network (FBN) seems to be positioning itself as a disruptor, like the Amazon of agribusiness providing a platform that includes everything from purchasing inputs, crop analytics, finance and marketing, and more direct access to genetics. In the livestock space, companies like AAD (Advanced Animal Diagnostics) and Connecterra are building tools and services analogous to a Fitbit for cows. Body Surface Translations (BST) is a company whose image processing technology has targeted both problems in animal and human health.  Tim Hammerich (the Future of Agriculture) and Sarah Nolet (AgTech So What?AgThentic, Tenacious Ventures) have weekly discussions with innovators pioneering new solutions in this space covering a range of topics including automated irrigations systems, blockchain, regenerative agriculture, carbon sequestration and a range of companies from startups to larger players including Wal-Mart and Coca-Cola. Where Food Comes From is leveraging QR codes and mobile technology paired with their source verification processes to connect consumers to information about the people and processes behind the food they consume.  IN10T is a digitally powered data driven company helping bridge the gaps between innovations and real world application of these technologies. Venture capital firm Foresite Capital even leverages data science to drive their investment strategy in therapeutics, diagnostics, and devices. This includes digital health apps like mindstrong which is leveraging AI for better diagnosis, monitoring, and treatment of behavioral health conditions and everlywell focused on actionable healthcare diagnostics and health engagement. Evidation is a company that leverages data from digital devices and sensors capturing, quantifying, and analyzing behavior, or mapping the 'behaviorome' in the context of human health (8). This is just a tiny survey of companies and products that I have encountered in just the last few years.

Addressing Society's Bigger Problems

This convergence is allowing us to address problems in healthcare like quality, cost, access and health equity. When it comes to the food we eat, AI, technology, and genomics is providing us the tools to combat issues like climate change, water quality, nutrition, safety, equity, and access. 

It's obvious when you look at the big picture, this convergence is leading to progress that is both complimentary and synergistic across a range of industries related to food and healthcare. Better food and a healthier environment and planet  led to better health outcomes. Healthcare payers and providers are realizing the importance of these issues in healthcare. Each is separately addressing key social determinants of health in ways that were not possible before:

"During the past several decades, it has become increasingly apparent that a person’s “health” is influenced by many more factors than health care alone. These other determinants are defined by the conditions and environment in which people are born, grow, live, work, and age, reaching beyond just what the delivery of acute care services can influence. These “social determinants of health” result in billions of dollars of additional costs annually. By working to mitigate the negative impacts of these factors, significant benefits can be achieved that improve both access and outcomes for individuals and lower overall costs." (9)

As I stated several years ago:

"as big data drives more diversity into every seed planted in every acre across every field, we may possibly begin to mitigate some of the risks and concerns traditionally associated with monoculture. So it is true, when you look across row after row and see only corn, you might technically call it 'monoculture' but it's not your grandparent's monoculture." 

As a result of the convergence of AI and life sciences, it's not your grandparent's healthcare either. 

References and Related Readings:

(1) Monoculture vs. the Convergence of Big Data and Genomics. Matt Bogard. October 13, 2017. https://www.linkedin.com/pulse/monoculture-vs-convergence-big-data-genomics-matt-bogard/ (previously published as: Big Data + Genomics != Your Grandparent's Monoculture. Economic Sense. December 22, 2014. http://ageconomist.blogspot.com/2014/12/big-data-genomics-your-grandparents.html

(2) Big Data Gets Personal as Healthcare and Life Sciences Converge. By Bob Evans, Senior Vice President, Oracle.  https://www.oracle.com/industries/oracle-voice/big-data-gets-personal.html

(3) Next Chapter For Biotech? Many Say 'Convergence' With Data Science. WBUR. NPR. Bioboom June 8, 2018. https://wbur.fm/2MaaMkA

(4) Healthcare Big Data and the Promise of Value-Based Car. NEJM Catalyst. Brief Article. Jan 1, 2018

(5) What Is Value-Based Healthcare?. NEJM Catalyst. Brief Article. Jan 1, 2017

(6) Q&A With Bayer on Outcome-Based Pricing. By Emily Unglesbee. DTN Progressive Farmer. 10/2/2019 

(7) Capurso L. Evidence-based medicine vs medicina personalizzata [Evidence-based medicine vs personalized medicine.]. Recenti Prog Med. 2018 Jan;109(1):10-14. Italian. doi: 10.1701/2848.28748. PMID: 29451516. 

(8) Why Foresite Capital is Betting Big on the Convergence of AI and Biotech. August 23, 2018. https://soundcloud.com/levine-media-group/why-foresite-capital-is-betting-big-on-the-convergence-of-ai-and-biotech   Check out their current portfolio of investments: https://www.foresitecapital.com/portfolio/ 

(9) Beyond the Boundaries of Health Care: Addressing Social Issues https://www.ahip.org/beyond-the-boundaries-of-health-care-addressing-social-issues/ 

Related: 

What does the farmer say...about seed choices? (Channeling Hayek) http://ageconomist.blogspot.com/2013/12/what-does-farmer-say-about-seed-choices.html 

Big Data: Causality and Local Expertise Are Key in Agronomic Applications. http://econometricsense.blogspot.com/2014/05/big-data-think-global-act-local-when-it.html

Modern Sustainable Agriculture Annotated Bibliography. http://ageconomist.blogspot.com/2011/02/modern-sustainable-agriculture.html

Infograph on shift from volume-based care to value-based care

University of Illinois at Chicago