While science rightly uses empirical evidence (”facts”) as the ultimate arbiter of truth, those who experiment and analyse field data usually only credit or discredit ideas / frameworks that some theorist has previously invented.
Tagline. Science: We finally figured out that you could separate fact from superstition by a completely radical method: observation. You can try things, measure them, and see how they work!
Hence the name “theory-killers” for experimental physicists.
Where do these theories come from, though? My own experience and my observations of others lead me to believe that an economic theorist’s deep creative centre is informed, flavoured, shaped, and sullied by her own personal experiences, biases, stereotypes, and assumptions about what’s normal. If you talk to people who have deeply integrated into their psyche concepts like “opportunity cost”, “rationality”, “search”, “strategy”, “information”, “evolution”, “optimisation”, and so on, and you disagree with this statement, please tell me.
(For example: a professor of game theory told me that he cannot fathom the motivations of a suicide bomber. He can’t fathom them, so he can’t model them, so we have no theory to predict and curtail their bombing behaviour.
Example 2: Do you think Daniel Ellsberg started running psychological experiments at random until he stumbled upon his famous "Ellsberg Paradox"? No, he had the idea in his head that these two kinds of “uniform distribution” should be different—perhaps getting the idea from Keynes or Frank Knight—and then tested the idea.)
Since there’s a "lone genius" limit on novel* economic theories, a finite upper bound follows on how much fact-checking can improve a theory’s soul. Although one can certainly benefit from pulling on threads, reading monographs, looking at data tables and so on, ultimately I believe deep insights come from the same brain process that generates the fallacy of lack-of-imagination (argumentum ad ignorantiam). Just as people form judgments by the “Does this fit with what can I imagine” test, so too—says I—do economic theories rise from the same murky pit. Personal experiences where we’ve taken in reams of high-dimensional streaming data (like at work) feed this imaginative capacity, such that we can run and assess counterfactual dramas in our heads (sort of like a Monte Carlo). "What if the vendor had said this to my boss? Nah, she wouldn’t have reacted that way. Not like her." There are some biologists who say that our brains have an especial capability to think through such human dramas. (And in writing that sentence I used the same often fallacious imaginative faculty.) The imaginative faculty is abused by cheap stereotypes—
- the welfare queen driving a Cadillac,
- a corporate fat-cat,
- the grasshopper and the ant,
- an obnoxious forex trader mouthing “get a job” to NHS protesters from his glass palace,
- the middle-class working stiff who glides to a job he hates and home to a meaningless life,
- images from movies,
- stories or stereotypes that are easy to visualise and easy to remember,
- the personal symbols / mental shortcuts Douglas Hofstadter talks about in this video.
Ideas can be checked against experiences and personal symbols much more easily than against a tome of facts. Since theoretical creativity proceeds in inspirational flashes and needs to run verificational checks at the speed of imagination, only the checks that can be done very quickly influence the creative process.
* Of course most theories derive from the joining of ideas from the existing literature. But those aren’t “novel” ideas.
It’s my conviction, therefore, that theoretical economists would come up with better theories if they spent more time in “the real world” and less time thinking about isomorphisms.
The problem is more acute in economics than in physics, because economic theories are much harder to kill (so many alternative explanations / dismissals one can retreat to) — which shifts some of the burden of correctness to the theorists. If you know that
- a compelling idea (like “Those who spend other people’s money will be wasteful”) will be hard to falsify;
- it will spread memetically through influential minds;
- it’s important to get this right, or else the former USSR and Latin American countries (𝓞 1 billion people) will be screwed over by your idea
then you would be quite reasonable in polishing & perfecting a theory—working to cleanse yourself of biases and myopia, asking yourself if what you’re writing is really quite true, what are the underlying assumptions, and so on.
The problem is also more important for economic theorists to address because those who theorise about the human mind have, erm, direct access to the thing they’re theorising about.
The difficulty of killing an economic theory has been discussed much elsewhere:
and if you read the things I read, you’ve probably had similar thoughts as:
- "Really? It took this long for ‘neoindustrial’ ideas like ‘The economics of serfdom differ from the economics of a modern web programmer’ to become acceptable?" And neo-industrial uses a totally neoclassical approach but just in a meta context—rational response to the incentives that come with a social framework, or perhaps game theory rationally optimising evolution rather than individuals.
- "Really? People think you can just use a probability distribution to model a person’s or a firm’s thought-process?"
- "Really? We just shrug off counterevidence to the theories by saying they’re only models?”
- "Really? Real numbers and Lagrangians are underlying all of this?”
- "Really? It’s so controversial that utility is derived from relative and not absolute wealth?”
and many others. Point being, if you are educated on this stuff, then I’m sure you can see how the Slutzsky decomposition is a compelling advance in “research technology”, but can’t carry over as-is to the ultimate subject of interest, which is human behaviour and feelings.
Am I just carping? A bit, but I also can propose something like a solution. If those who give out grants for economic research could be convinced that
- business experience
- time spent in poor countries
- experience in a variety of economic roles outside of academia
were important indicators of future relevancy and correctness of research—along with knowledge of a body of literature, knowledge of mathematical/statistical/experimental methods, consulting/political experience, and/or a Ph.D.—then up-and-coming economists would have the incentive to spend time in “the real world” and find out, in a personal way, what the people they theorise about go through.