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