OK, apparently I have more frustration from yesterday bottled up than I thought.
In the last post I discussed that it's important to keep in mind that textbooks and intellectual histories are two very different things.
Here I want to stress that models of the world and understandings of the world are also two very different things and you're going to get tripped up if you forget that.
I may have a model where I have a nice social welfare function generated from perhaps unreasonably smooth utility functions, maybe just incorporating risk - maybe not even incorporating risk! - where I assume that all the agents are excellent at calculus.
I don't think through this model because it necessarily matches my vision of the real world in all it's particulars. Instead, I think through this model because it offers me a way to work through the most important ideas while pushing the less important ideas (for this application at least - they may be very important elsewhere) into the background. We all do this all the time. The benefit of doing it with math is at least I'm being upfront about what I'm assuming!
So it would be a waste of your time to try to tell me, for example, that not everyone knows calculus (or even has all the data to apply calculus to). I know that. If you get worked up about this, you are confusing:
1. Making an assumption in the model, and
2. Making an assumption about the real world
If you think I'm doing #2 then you are misunderstanding the whole exercise and how economic science is done.
Even if you understand I am doing #1, we might still have a fruitful debate over whether I should do #1. Maybe the departure from reality is sufficiently great that only nonsense comes out of the model - no insights worth working with. We can argue about that. I might say that although people don't actually do calculus when making decisions, we can probably agree they're trying to figure out the best option for them, and they are probably saying something in their head like "I'm going to keep doing this until the cost to me of doing it again is higher than the benefit of doing it again". That's not a very big assumption on my part, after all. And that's a pretty fair account of all that I'm importing into the model by using calculus.
So I'd maintain it's still a nice little model to help me think about the world and keep all the forces I'm juggling in some semblance of order so that my puny little brain that evolved on the savannah can get some take-away insight from the exercise.
A final note - this is not Friedman's methodology. I am not saying that any assumptions are OK as long as they produce an outcome that matches reality. What I am saying is that imperfect representations of reality (calculus optimization vs. humans seeking out the best option), by making the problem easier to work with, can generate more insights than the imperfection costs.
The problem is that many people who use models of any type do not always remember your point. You seem to greatly underestimate how many economists behave like #2. They make a model to estimate the increase in tax returns if the rate is changed (for example) and then report that as truth. Yes, good economists understand that models are not the real world. But bad economists do not.
ReplyDeleteI worry about formal, mathematical models because it is easy to make this mistake. When thinking all the time in math, it is hard (for me at least) to remember that the accuracy of a model to the real world is always an open question. Economists can make the same error with verbal models, but I believe it is less likely. Math brings a hubris with it. My last blog post was on this. Maybe most other economists are just that much smarter than me.
You're right, bad economists misinterpret models. But, bad economists are bad economists with or without models. Before they used formal theories to make their case, they made convoluted arguments. 100 years ago, maybe we would have been arguing for models, thinking that they would at least help to keep our thinking straight.
DeleteTo echo Coase- bad economists cannot get away with bad verbal economics as easily. They can say silly things using math and people (especially non-economists) might listen. Think of how many people believe every word in Freakonomics (not saying this is good or bad economics) without understanding any of the data/math/econ behind Levitt's result. They just trust math = science = truth. Verbal economics has to go through a much harder B.S. filter it seems.
DeleteThere's hardly any math in Freakonomics. Perhaps in the academic papers it draws on, but most people aren't going to read that. They were convinced by Dubner's verbiage!
DeleteI've been in the science field for decades. There are lots of bad scientists out there, but even good ones frequently fool themselves about what or how much the data tells them. A lot of times the importance of the shortcomings of the model are decided after the fact when the data supports (or doesn't) the expected outcome. In science there's a lot of group think involved too.
DeleteI like the calculus example. I don't doubt there are models where you could convince me that an agent knowing calculus is interchangeable with an agent having a preference towards optimization/minimization of some variable.
Wonks Anonymous - ya that was my first thought. Freakonomics is fairly empirical but I think of that as a good example of literary economics.
Deleteeconpointofview - I would have no issue at all with using estimates from these models to provide an assessment of the change in behavior associated with a change in tax policy (I don't get exactly what you mean by "the increase in tax returns"). There's nothing wrong with using these models to get insights about these things is there?
In my experience, literary economics is as likely to mislead as mathematical economics.
A planet moving through space follows a path described by fancy differential equations.
ReplyDeleteDo we worry that the planet does not understand the equations??
The planet's position can be described very accurately. The accuracy degrades over time.
Do we worry that the error after a few million years is not so good ??
The relations we use to describe the real world have differing utility. Each description
should be studied so that we can understand what it describes well and where it fails.
We should not be surprised when a description fails to describe a part of the world
that is outside its area of competence.
This work has not been completed for fields where the underlying reality is noisy!
I am not sure if I should cry or laugh about your reply. What exactly is like physics in economics that your analogy fits?
Delete"The relations we use to describe the real world have differing utility. Each description should be studied so that we can understand what it describes well and where it fails." Yeah, sure. We calculate all differing utilities. :)
I am just asking me now ... is this a troll post?
-- Nietzschikus --
=I might say that although people don't actually do calculus when making decisions, we can probably agree they're trying to figure out the best option for them, and they are probably saying something in their head like "I'm going to keep doing this until the cost to me of doing it again is higher than the benefit of doing it again".=
ReplyDeleteHere you beautifully demonstrate that mainstream econ isn't based on a proper opportunity cost approach. In a proper opportunity cost approach cost exists only at the moment of choice. One thus can't choose to follow some course of action until costs outweigh benefits because otherwise one would be able to predict his own choices.
To clarify, the statement I quoted is either a trivial truism (a person may choose to continue doing X until he chooses to stop doing it) or it is false if it implies that a person may choose when he will choose to stop. In the first interpretation, calculus is useless because the point where the person will choose to stop isn't determined. In the second, it precludes free will.
ReplyDelete