Learning about theory does not teach people how to theorize

A random question from a Stanford University PhD micro exam looks something like this:

The "Robinson Crusoe economy" is the simplest possible general equilibrium model, and students who can solve for Crusoe's leisure and coconut consumption choices have presumably learned something about general equilibrium theory.

But they haven't learned how to theorize. 

Theorizing - creating theories to understand and explain the world - starts off by identifying an interesting question. Creating exam questions is theorizing, because the question setter has to identify a puzzle. Answering exam questions is one step removed from the act of theorizing. The question has already been identified. My sense - and I could be wrong - is that a non-trivial number of post-comp PhD students feel something like this:

 

They can follow the most complicated plans, and build any model they are asked to build. But they struggle to come with an idea of their own; to decide what they want to build. Nothing in their training has encouraged them to fill their minds with ideas, nor taught them to distinguish the awesome from the not-so-awesome.

Identifying a problem is only the first step towards creating a theory of one's own. Theorizing is about abstraction. In the exam question above, picking coconuts serves as a metaphor for an entire economy's productive activity, and the complexities of technology are reduced to the production function: c=f(l)=l^1/2. This is, as I have argued before, the power and beauty of theory: it sacrifices literal truthiness in order to capture radical (as in "at the root of") truths.

When students are taught about theory, they are presented with simple, pre-abstracted, models. It's like being asked to re-arrange the furniture in de-cluttered, minimalist home - a useful exercise that introduces the student to basic principles of design and organization. Yet when students go out to build their own theories, they are faced with explaining a world of complexity.  Before they can make any progress, they have to throw a whole load of stuff out. But economic theory courses spend little time explicitly discussing methodology: what makes for a good explanation, and thus should be in the model - e.g. incentives, prices -  and what can safely be bracketed out. So people end up lost.

 

It could also be that students struggle to theorize because they lack training in logical reasoning. Economic theory is deductive. All that math is just a way of (a) formalizing a set of assumptions and (b) deducing the implications of those assumptions. Logical reasoning is about taking a step back and asking what do these assumptions actually mean? Are they consistent with the real world? Are they capturing key aspects of the problem I'm trying to model? It makes no sense, for example, to assume constant returns to scale when modelling monopoly, because monopolies do not exist in a world with constant returns to scale.

Years ago I was chatting to a PhD student about his thesis. He said "I've got my model all worked out, I just don't know what to put in between the equations". ["How about economics?"] Training in logical reasoning - understanding that economic theorizing is a process of deduction, that the mathematical calculations are simply a way of working out the implications of the model's initial assumptions, and so each step in those calculations has an economic meaning - might help people work out what to put in between the equations. I don't know.

In theory courses - whether in economics or in other disciplines - theory becomes an object of study. Professors teach about theory - because this is how they were taught, because this is how textbooks are organized, and because it's relatively easy to teach students how to step up and solve a series of standard models.

But to teach students how to do theory? It's like riding a bicyle - ultimately, the only way to learn is just to push off and start peddling. Send people off to model the world and see what they come up with.

Comments

[Squeeky Wheel]

That example is pretty disturbing. That looks like a high school calc problem. Looking again I see that near zero knowledge of economics is required. That's scary.

Teaching undergrads to do abstraction is tough (I do this in context of programming) - they tend to want straight answers and don't like fuzzy grading. But with phd students that shouldn't be an issue. Give them some data and ask for a model.

[Jacques René Giguère]

Squeaky Wheel: yep. That's what you get when your enrollment target are math majors...

[NoniMausa]

And of course the coconut problem has a number of assumptions about the picker and the coconut trees which are not made explicit. But these elements are essential to solving the problem. For instance: how few coconuts can the man live on?how many trees are there, and what annual production of 'nuts? How long do the trees live on average, and what number of fallen 'nuts germinate? and so on. These elements, if not considered, might lead our castaway to maximizing his efforts the way the Easter Islanders did.

Noni

[Ralph Musgrave]

Nothing beats a genuine desire to get at the truth. You've either got that or you haven't. And if you haven't, no amount of training will help.

[Tom Brown]

Frances, this is an interesting post. I love the room photos... a good way to make that point.

Let me say up front that I'm not an economist or a scientist, nor have I had training in econ (and only a limited amount in science). You're probably aware that econ bloggers such as Noah Smith, John Cochrane, David Glasner and others have written some posts recently asking what's wrong with econ and giving an overview of some of the recent trends as well. Noah is particularly good at touching on some of the "theory of science" issues w/ regards to econ IMO.

I realize that you're concentrating here on creating (rather than testing) theories (BTW, theories or hypotheses? I always thought that a theory was a hypothesis that had not been falsified, despite repeated and concerted efforts to do so by the scientific community: i.e. a theory is as good as it gets in science, and to achieve that lofty status a lowly hypothesis must spend some time in the trenches... and survive!). But one thing I don't see much of on econ blogs are sequences like this: hypothesis stated, with a development leading to specific models, in turn leading to testable predictions (testable against future empirical data). I have the impression that it's rare (on blogs anyway!) to explicitly make economic hypotheses vulnerable to falsification. I would think that economists would be taking great pains to clearly and prominently spell out exactly what (in terms of real world data) would constitute falsification of their hypotheses. Would I find what I'm looking for if I bothered to read econ journals rather than blogs? Surely even a pure econ theorist must spend some time thinking about precisely what observed data would constitute falsification, even if they never concern themselves with doing the actual empirical testing. If they don't do this, aren't they making themselves vulnerable to the claim that they're doing nothing more than creating unfalsifiable hypotheses?

[Squeeky Wheel]

Jacques: part of my horror was that the math majors are being tested on high school level math. Perhaps that question is not representative and is intended as a check of pre-reqs, just placed in econ context. (I do something similar at the start of my semester - a test which primarily signals what I consider to be background knowledge)

[Herbert]

Interestingly, the stanford exam contains an obvious error: The variable "l" is first used to represent leisure (it increases utility) and second to represent effort (it increases coconut output).

In a coherent exam, the professor should combine utility log l + a log c with the production function f(l) = sqrt (L-l).

[Frances Woolley]

Nonimusa: "And of course the coconut problem has a number of assumptions about the picker and the coconut trees which are not made explicit. For instance: how few coconuts can the man live on?"

Actually, that is built into the structure of the utility function: utility goes negative infinity as coconut consumption goes to zero. If one wanted to put a higher minimum level of coconut consumption into the model, the way to do it would be to change the utility function to u=log(l)+alog(c-c') where c'=minimum required coconut production. But it wouldn't really change much.

It's true that this is not a dynamic resource extraction problem, where Robinson has to figure out how many coconuts to harvest over time, but that's o.k. Notice that this is just the first part of a multi-part question. The point of the question is to examine the consequences of alternative firm ownership structures. One could do that in a multi-period setting, but a lot of insights can be gained from just the one period.

In some ways your comment illustrates the "knowing what to throw out" problem - these considerations just may not be relevant to the problem at hand.

Squeeky Wheel - notice that it's just part (a) of a multi-part problem. Click on the link and read the entire exam before writing it off. A good exam will contain both easier and more difficult questions. But, yes, mathematicians have an advantage in theory courses - but not necessarily in doing theory.

[Jamie]

This is an interesting post. I like the pictures. I’m not an economist or an academic of any type. I spent many years as a management consultant. There are similarities between academia and consulting. Both follow a process which is roughly:

Ask question – think about question – answer question.

When I gave up consulting I started to read economics blogs expecting to see a similar style of thinking albeit focused on the macro-economy rather than the individual businesses and government departments with which I was familiar. However, I found something completely different so I thought about what was causing the difference.

My perception is that the difference arises mostly from who is asking the question.

Consulting works as follows:

Client asks the question
Consultant discusses the question with the client to understand what complications associated with the question are preventing the client from answering the question himself
Consultant thinks about the question and the complications
Consultant answers the question using language which can be understood by the client.

Academia appears to work as follows:

Academic asks the question
Academic thinks about the question
Academic answers the question using language which can be understood by the academic (and, optionally, a few other academics).

Hence, in consulting the asking and answering of the question are split responsibilities between the client and the consultant. Also, the client determines whether the answer is credible and useful. The consultant makes money only if the client is satisfied.

In academia, the academic both asks the question and answers it, and also determines whether the answer is credible and useful. Further, with tenure arrangements in place, the academic makes money even if he neither asks a useful question nor provides a useful answer.

Am I the only person who notices this difference? Well, I note that there is considerable unrest amongst economics students in many countries as they claim that academic economists don’t answer the real-world questions asked by the students, and don’t provide credible or useful answers to the academics’ own questions.

http://www.theguardian.com/education/2014/may/04/economics-students-overhaul-subject-teaching

In short, a division of labour between asking and answering questions challenges both parties and encourages innovation. When one party has a monopoly of both roles, you and up with a sterile environment. It’s easier to avoid asking difficult questions as it would then be inconveniently difficult to answer them particularly when the questions might challenge prior beliefs.

How do you think that you could help PhD students find interesting and useful questions to answer with their new-found techniques? What are the main obstacles to achieving this? [See what I did there]!

[Avon Barksdale]

Frances,

Math in economics is about language – it's how to know if your thens really follow from your ifs. That language is important, and while theory is much more than the math, the math is necessary. A necessary but not sufficient condition to contribute to a discipline is the ability to solve all the standard problems. This is true in physics, it's true in mathematics, and it's true in economics.

I do find a delicious irony in your post. A while back you blogged the post, In praise of cookbook econometrics. In this post you write:

“They can follow the most complicated plans, and build any model they are asked to build. But they struggle to come with an idea of their own; to decide what they want to build. Nothing in their training has encouraged them to fill their minds with ideas, nor taught them to distinguish the awesome from the not-so-awesome.”

Well, I guess you have your answer to the end state of cookbook training. Curiosity is the most important part of creativity. Any student who finds it acceptable to use a cookbook to get an answer without the immediate desire to figure out how it actually works (which would mean going to the library that evening and working through the theory), that student will never contribute in any meaningful way to the discipline.

[Frances Woolley]

Jamie: "In short, a division of labour between asking and answering questions challenges both parties and encourages innovation. When one party has a monopoly of both roles, you and up with a sterile environment."

You raise a very interesting question, though I'm not sure I entirely agree with your answer. Clients - who, in my case, are usually government folks - ask quite different questions from the ones academics ask, because they have fundamentally different aims for the research enterprise. To take a really simple example - a Canadian government client is probably going to be interested in analysis using Canadian data, e.g., what are the effects of reduced corporate tax rates on Canadian firms' growth/hiring/investment. An academic who wishes to establish an international reputation would be well advised to use American data, because the American experience tends to be seen as more universal/worthy of publication in top journals.

I've also found that "clients" often ask quite boring questions - e.g. "tell me what is known about XYZ". Something they could quite easily find out themselves - if academic research wasn't so heavily gated!

Avon "Well, I guess you have your answer to the end state of cookbook training."

Not at all. The point of my "in praise of cookbook econometrics" was that there is little knowledge gained from cranking through endless series of proofs or knowing the precise formulas for calculating various estimators. In both of these posts I'm arguing that it's more important to step back and understand what one is doing and why than to get bogged down with endless details.

This could easily come out as anti-math. I don't want it to be. Math is a powerful tool for deductive reasoning. But knowing math is not the same as knowing how to do theory.

[Avon Barksdale]

Frances,

Cranking through endless proofs is not teaching mathematics or economics or anything for that matter. Economics taught properly generates a deep interest in mathematics and geometric constructions in particular. Physicists often cross over into the world of pure math and I would say that any physicist worth his/her salt has a deep appreciation for what connections we learn from pure math. Econ students should have the same experience. Proofs are not endless incantations, they are part of a rich vein of discovery that not only leads to new ideas, but to student driven questions and an understanding as to how so many mathematical structures that economists use have the same root. What happens if we relax an assumption or extend the structure? Why does this proof require some weird condition, and wait a minute, doesn't this proof rest on the same structure as the stuff in my totally different econ course from last year? You mean it's the same thing in drag - I can turn the problem around like that? - wow! That's curiosity, that's how you generate new ideas, and that is how students learn to build theories. Understanding the journey that the proofs take you on is necessary, but not sufficient. This process works in physics, it works in mathematics, and it works in good academic economics (not the endless self serving drivel for the rent seekers).

Otherwise, I think we are left with what Wolfgang Pauli put best:
________
| |
| |
| |
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This is to show the world that I can paint like Titian … Only technical details are missing.

[Tom Brown]

Avon, you write:

"Physicists often cross over into the world of pure math and I would say that any physicist worth his/her salt has a deep appreciation for what connections we learn from pure math. Econ students should have the same experience."

In the 3rd to last paragraph of this comment, I briefly give an example of somebody whom I think is making a commendable effort to use the scientific method in econ: from hypotheses to models to real-world testable predictions. See if you agree.

[Nigel]

And the exam setters can't even write English: "... and the only goods ... IS ...leisure and coconuts." God help us.

[Jamie]

Frances, Thanks for the reply.

Frances: “An academic who wishes to establish an international reputation would be well advised to use American data, because the American experience tends to be seen as more universal/worthy of publication in top journals”

Yes, I have seen this sentiment from many economists so I know what you are saying is true. I am glad I am not an academic economist. To an outsider, ‘top (American) journals’ and ‘thought police’ appear to be closely related terms.

Frances: “I've also found that ‘clients’ often ask quite boring questions”

Yes, that is true. However, that is the main point of clients. Most useful questions are pretty boring. Also, if clients always asked questions at the same level as experts then there would be no point in experts. Clients would just answer their own questions. Clients also use boring questions to test experts before trusting them with more complex questions.

Although I am not an economist and have never knowingly dealt with economics students after they arrive in the workplace, I have dealt with ex-students of other disciplines. They often arrive in the workplace armed with intellectually stimulating techniques for answering questions which don’t exist in the real world. They are then assigned to help answer a real question, from a real client, which doesn’t involve their stimulating techniques. The mature ones buckle down and learn how to think. The others follow various paths to the exit door while causing havoc for both their client and their colleagues.

I can see that there are some areas of academia where it is possible to ask a question for which there is no existing demand for an answer. For example, no-one asked the Google guys to develop their search engine. However, that is an example of new technology. Economics is not really in that line of business.

As a non-economist reading blogs I am very conscious that the questions I ask myself about economics (and economists) are not the same questions which interest economists. However, the reason I read blogs is to get answers to MY questions. I am just a dumb client.

Here are four examples.

First, one of the problems facing non-economists who read about economics is that economists are very poor at defining a common vocabulary and explaining to non-economists precisely what they mean by various terms. I can see that defining common terminology is ‘quite boring’ but, without this terminology, economists just routinely talk past each other and their non-expert audience.

Here is part of a recent debate on ‘inflation’ between two PhD economists who have different definitions of ‘inflation’. To a non-economist both participants in this debate come across as idiots.

http://noahpinionblog.blogspot.co.uk/2014/07/austrianism-wrong-inconceivable.html

Here is Scott Sumner asking for a definition of ‘aggregate demand’ even though he has used the term many times in the past. I think this is a good question but Sumner is interested in answering the question only because HE thinks it is interesting, not because someone like me thinks it is interesting.

http://www.themoneyillusion.com/?p=27080

My question is why do economists think they need mathematics to promote precise thinking while, at the same time, avoiding a common vocabulary which would also promote precise thinking?

Second, economists divide themselves into tribes which then have verbal wars with each other. My question is where do these tribes come from? For example, do economists have established political views and then use economics to develop propaganda for their political views? Alternatively, do they develop their political views as a result of their studies? If it’s the latter then what causes economists to develop different views? For example, right-wing economists always seem to see recessions as being caused by supply problems while left-wing economists see the cause as demand problems. Why is this? And why does no-one define a set of rules for determining the causes of individual recessions (like a medical doctor diagnosing symptoms in her patient)?

Third, economists argue that ‘central planning’ doesn’t work. However, I know that I can refuel my car at any time of the day or night anywhere in the country. That is an example of successful central planning by Shell or Exxon or another of the oil majors. So how can Shell and Exxon develop successful central plans for oil products when Soviet governments fail with their plans? I think I know the answer to this question but I’m interested to know what economists think is the answer.

Fourth, one of the problems in economics is the use of highly summarised (and probably inaccurate) statistics. How could economists develop better data collection techniques? With the advent of electronic commerce why can’t some economist invent an application to help real people set budgets and monitor their spending, including monitoring their own personal rates of inflation?

I am not expecting answers to my questions here. What I am saying is that the rest of society can define a wide range of questions for which they would like answers from economists. However, economists seem to prefer to develop techniques which might be able to answer other questions if only the PhD students learning these techniques could think of suitable questions to ask. There is something very wrong in all of this.

[Denis Drew]

To borrow a phrase from my family doctor back in the Bronx, back in the 70s: "All these histories (here we can substitute the word "theories") are b***s***. I got punched in my chest; that's why I have a lump." Economists of the left and right remind me of blind guys on the right and left of an elephant trying to picture what it. You start with a full picture of the real world -- and if theory helps out, good; starting with theory is childish (to use a clean word).

Minimum wage: the 65% of McDonald's customers going through the drive through drive through in their $4 a gallon gulping four-wheelers are not scared off by diabetes or clogged arteries -- if prices go up 25%: hey; it's addictive (along with the happy glow that the people inside are all making $30,000 a year). Arbitrage: if Wal-Mart wages go up 50%, Wal-Mart prices go up 3.5%. Do you think James Riddle Hoffa (world's most unethical good guy) would have stood still for a spread like that? Forget your equations about the last marginal whatever. :-)

[Frances Woolley]

Nigel "And the exam setters can't even write English"

It's quite likely that English is the exam setter's second or third language. And we all make mistakes.

Jamie - " the rest of society can define a wide range of questions for which they would like answers from economists. However, economists seem to prefer to develop techniques which might be able to answer other questions if only the PhD students learning these techniques could think of suitable questions to ask."

Think of economic research as a huge library with no catalogue, and most of the books written in a language that you don't understand. In terms of the questions you ask - which are actually good and interesting ones - a lot of them are either unanswerable, or have already been answered. E.g. "How could economists develop better data collection techniques?" We're working on it. There's lots of research into the use of administrative data or scanner data. In the Canadian context, Statistics Canada has advisory boards that guide the design of their various surveys. I think Steve Gordon is involved with some - I've been involved with others. The answers are out there. But could you find them, or break through the paywalls surrounding them, or understand the answers even if you did find them? Perhaps you could, but thousands couldn't.

[Avon Barksdale]

Jamie,

If you are interested in economics enough, start reading real economics instead of following technical blogs. Start with Hal Varian's Intermediate Microeconomics and go from there. Move your confusion to a higher level.

[Tom Brown]

Avon, I see you compare with physics above. Here's a guy that really tries to use the scientific method in macro, IMO (follow the links in the latter half of my comment here):

http://mainlymacro.blogspot.com/2014/07/what-annoys-me-about-market-monetarists.html?showComment=1405907128255#c1541075929191573517

[Tom Brown]

Got one in spam (it's short!)

[Jamie]

Frances: “The answers are out there. But could you find them, or break through the paywalls surrounding them, or understand the answers even if you did find them? Perhaps you could, but thousands couldn't”.

I am sure that the answers to some questions are out there while others are not. Some are in progress. Some are too difficult. Some are relevant to the world and others are not. That’s not really the point.

I have no interest in breaking through paywalls that have been set up to keep me out or to understand answers written in technical language which can be understood only by other technicians. That’s not my role in society. The role of academic economists is to educate the rest of us even if the rest of us are less than ideal students. It’s not to put barriers in the way of learning and then to blame the rest of us for our failure to understand.

As I see it, the essential point of economics is that we are all better off through division of labour. That applies to all goods and services, including economics education which is just a professional service (like consulting).

If I go to McDonalds I don’t care about the trials and tribulations of providing Big Macs. I just want to eat an edible and affordable Big Mac. If a McDonalds’ employee told me that he had a great hamburger but that it was hidden behind a paywall, I would not decide that I should solve the paywall problem. If he told me that I couldn’t eat a Big Mac as I didn’t know how to cook a Big Mac to perfection, I would not decide that I should learn that skill either. Rather, I would go somewhere else and never return to McDonalds.

Finally, just to go back to the start, please note that my comments have been based on your perceived problem of the inability to PhD students to find suitable questions to answer with their mathematical techniques. As far as I can see that is still a problem but neither you nor anyone else here has yet provided an answer. I think it’s a supply and demand mismatch but, if that’s wrong, then you still need an alternative hypothesis.

I won’t take up more of your time. Thanks for replying to my posts. I do appreciate when economists take time to converse with the rest of us. That IS customer service!

[Jamie]

Avon: “If you are interested in economics enough, start reading real economics instead of following technical blogs. Start with Hal Varian's Intermediate Microeconomics and go from there. Move your confusion to a higher level”.

That’s not helpful. Nevertheless, here is a response. Please reply only if you are going to be civil and treat my views with respect even if you think I am wrong.

I have spent thirty years in business and government roles. As a result, I have an understanding of a number of aspects of the economy as a participant. That doesn’t make me an economist and I’m sure that there are many things that I could learn. However, the opposite is also true. An academic economist who has spent an equivalent time in academia also has an understanding of a number of aspects of the economy but only as an observer rather than as a participant.

It seems to me that both participants and observers could learn by listening to each other. However, academics seem to think of their view as the only view worthy of consideration even when there is little observable evidence that the academic view is adding much value to society, and even when students complain about the poor quality of their education due to its narrow nature.

I have looked at several economics textbooks. I usually get no further than supply and demand curves. I don’t know of anyone who thinks about running a business using the concepts of supply and demand curves. My perception is that only an observer would offer up such a concept. The reality is much more messy and it’s the messiness which causes most of the problems. It is not clear to me why I should study further into this material when even the first page is highly dubious.

There are many ways of learning and different people have different strengths and weaknesses. If you learn some things about economics from a book and I learn other things from practical experience then I think we would benefit from sharing. You, on the other hand, seem to think that I should read a book to become more like you while you have nothing to learn from me. We’ll have to disagree.

[Jamie]

Avon: This process works in physics, it works in mathematics, and it works in good academic economics (not the endless self serving drivel for the rent seekers).

This isn’t helpful either but here is another response. Academic economists always compare economics to physics and it’s not clear why. I would say that economics is more like medicine i.e. how to fix real diseases in the economy, or like nature/evolution where the object is to study a constantly changing complex system.

This distinction, on its own, means that I am dubious about the use of mathematical models as the dominant thinking tool in economics. These models require economists to ignore the diversity in the economy in order to simplify the mathematical models sufficiently to make them soluble. For example, the use of “representative agents” seems to push any discussion of inequality to the margins.

Individual businesses are much simpler than the macro-economy. They do use mathematical models in their planning processes. However, even at this simpler level, everyone involved acknowledges the limitations of these models for the same type of reasons I mentioned above. A mathematical model can tell you what will happen if your assumptions are valid and there are no important missing assumptions. Real life is always more complex. Businesses adopt their own plans based on their own mathematical models but they also put in place agile business designs and contingency arrangements for when, inevitably, the plans don’t play out as expected. Again, it is the cases where things go wrong that are the most interesting and most difficult to deal with, and these are the cases which the mathematical planning tools can’t deal with.

[Avon Barksdale]

Jamie,

It seems that you don't like the mathematical abstraction used in economics. You say, “It is not clear to me why I should study further into this material when even the first page is highly dubious.” Think about it this way. When a cheetah on the plains of Africa takes down a gazelle, it does so not by running straight at its prey, but by trying to match its path to the gazelle. That is, the cheetah tries as best as it can to catch the gazelle by running parallel to it at the last instant, even if the gazelle is running on a zig-zag or curved path. Now, I can model the cheetah's prey catching behaviour, using calculus, as a 2-dimensional trajectory tangency matching problem. I suspect that the cheetah does not know calculus, but nonetheless, the cheetah by and large behaves as though he does. This happens in economics. Of course people don't solve complicated dynamic programs to solve their consumption-savings problems, but they behave as if they do. The only question is, how close does your model work at explaining behaviour? In some cases, it might be excellent, in others, it might only get the signs right. The point is, all mathematical modelling, whether it is in physics or economics, is about writing down an approximation to reality. Some models are better than others, some are useful, but they are all wrong – no one knows the ultimate Truth and we will never find it. Humans will only ever achieve an approximate understanding of the Universe, regardless of how good that approximation eventually becomes.

So when a budding PhD student in economics or physics is looking for a problem, he/she is looking to create a mathematical model that is not trivial (explains only the obvious) or so complicated that everything is a special case (and intractable), but a model with an almost magical amount of complexity that self consistently explains, in a suitably approximate sense, a wide range of non-trivial observations, which (hopefully) other people will find interesting. That is actually really hard to do and it's in that sense that economics compares to physics better than to medicine. The discipline of economics is not about engineering society or healing it from its ills – adding toe of frog or eye of newt of policy when needed – it's about understanding human behaviour, not too unlike understanding how the cheetah catches the gazelle on the savannah.

[Bob Smith]

Jamie:

"I don’t know of anyone who thinks about running a business using the concepts of supply and demand curves."

I suspect you're right that few businessmen (or woman) running a business expressly use the concepts of supply and demand curves. I suspect ALL of them intuitively use the logic represented by the simple supply and demand curves in shaping their business practices. Think of businesswoman learning that the demand for her company's product was less than expected and its warehouses are filled with extra products. What are the usual responses? Lower the price and reduce production (i.e., shifting along the supply curve)? Run a new ad campaign to increase demand (i.e., shifting the demand curve)? Both of those are responses predicted by the most simplistic supply and demand diagram.

Now, you might say that those are self-evident responses, so that the insights offered by the simple supply and demand curve are trite. Fair (although you'd be surprised at how many people don't find these points self-evident - the notion that increasing the cost of labour might reduce the demand for it, for example, is apparently lost on the current government of Ontario), but that's why the simple supply and demand curve gets taught on the first day of introductory economics courses.

"A mathematical model can tell you what will happen if your assumptions are valid and there are no important missing assumptions. Real life is always more complex"

The first point is that nothing in economics requires mathmatical modeling. The simplified supply and demand curve model can be, but needn't be, a mathmatical model. One can express the underlying logic behind it in words (demand for a good generaly rises as its price falls, the supply of a good generally increases as its price rises). That being said, it's often easier to express (and understand) more complicated models mathmatically than to express them in words. And, of course, those mathmatically models can be more readily tweaked or modified to consider the implications of the sorts of issues that you're concerned about - for example, I think it's fair to say that vast quantities of economic research is devoted to modelling the implications of poverty, inequality, diversity etc. that concern you (and it's unfortunate that too many prominent people who are utterly ignorant of what economists do - I think of the David Suzuki types [Mods: Sorry if this provokes a flurry of hate posts] - claim otherwise). In that sense, I think the objection to mathmatical modelling is misguided. Math is just a different, but convenient, language that can be used to express ideas.

Second, no physical or social science can (or should) purport to model "real life". Modelling "real life" requires omniscience which, outside of the legal and medical professions, no one purports to have. If that's the standard, then there's little point in trying to model anything. But of course, the fact that we're not omnisicent doesn't mean we can't come up with theories or models of reality that, generally, correspond to reality, or at least to the particular aspects of reality that we're interested in, that can be tested against reality and which provide useful insight as to how people behave or how the economy works.

The simple mathmatical models of supply and demand curves don't purport to describe reality, they're simplified abstractations of reality, but they're simplified abstractions that make falsifiable (and, generally, not falsified to a material degree) predictions about reality which give us insight as to why things happend the way they do and how we can shape economic behaviour in the future.

[Nick Rowe]

Part of the problem is that most businesses are monopolistically competitive, rather than the perfectly competitive supply+demand model. If you raise price you will lose some customers, and if you cut price you will gain some customers. How many? And what are your extra costs per extra customer? I think the model of monopolistic competition (skip to chapter umpteen) will make a lot more sense to most business people.

The other part of the problem is that a model that is useful for someone on the ground won't always be useful for someone flying over the same ground, and vice versa.

And to bring this back to Frances' point, we first need to ask, before building a model, "What do I want this model for?"

[FR Woolley]

Bob: no physical or social science can (or should) purport to model "real life".

Nick: we first need to ask, before building a model, "What do I want this model for?"

The person who wants a model to capture every single element of the real world is a hoarder, unable to distinguish what is worth keeping and what is not. Models have to simply; they have to abstract. The question is: how to simplify, how to abstract. That's when to ask Nick's question - what's worth keeping depends upon what will be useful, which depends upon what the model is for.

[Tom Brown]

Jamie & Avon,

What if "understanding human behaviour" turns out to be irrelevant for making a viable theoretical model of the economy?

An analogy: suppose the 19th century physicists who developed and explained the rational for the ideal gas law had started off deciding they needed to "understand molecular behaviour" before they could do anything? Well, thankfully they didn't: They knew almost nothing about molecules: only that there were an enormous number of them (in a human scale container of gas) and that they could be energized in different modes (e.g. move in the x, y, z directions, rotate, and internally vibrate). And in fact the only "micro physics" which survives to the macro level in their gaw law is a sum total of the modes possible for energy to be stored in. They did not attempt to build a "representative agent" model of the molecule. There are NO micro-foundations other than this sum.

Since that time physicists have been able to employ similar concepts to directly study the physics of other emergent systems on a macro scale with very little reference to any micro physical foundations. For example, properties of the Earth's water cycle can be accurately predicted using the technique of entropy maximization, with almost no reference to the physics of water.

The trouble with applying these techniques to general complex systems, however, is that not all complex systems have constraints or conservation laws, which has been a requirement for use of the maximum entropy technique. But recently, a means of generalizing these techniques to such systems has been worked out. Economics is potentially an example of such a system, and over the last year these techniques have been applied to it, resulting in some intriguing results. We'll see if the core hypothesis, as applied to economics (micro and macro), hold up as more evidence is collected, but so far it doesn't look bad to me.

So perhaps we can ditch models of expectations, agents, utility maximization, indifference curves, rational expectations and nearly all micro-foundations altogether, and still have a viable useful theoretical model that compares well to the empirical evidence. And this model fills some gaps that current models do not cover, so rather than just a curiosity, it could end up making a unique and valuable contribution to the field.

But Jamie, interestingly enough, this new theory can still be used to produce supply and demand curves! That's one of the most fundamental things it can be used for actually.

[Avon Barksdale]

Tom Brown,

What if "understanding human behaviour" turns out to be irrelevant for making a viable theoretical model of the economy?

Nope. Economics is the study of human behaviour.

"An analogy: suppose the 19th century physicists who developed and explained the rational for the ideal gas law had started off deciding they needed to "understand molecular behaviour"

Go to Wikipedia and look up Renormalization Group. It might clear up your misunderstanding. You are talking about physics at different distance scales and how the degrees of freedom reorganize as we move to lower energy.

"...representative agent model",

these are specific models in economics, they are not all encompassing. Sometimes it's a useful assumption, sometimes not. Consumer choice theory is NOT based on a representative agent - everyone has his/her own preferences.

"So perhaps we can ditch models of expectations, agents, utility maximization, indifference curves, rational expectations and nearly all micro-foundations altogether,..."

Nope. These would be heterodox economic theories, and these are pretty much useless. Not sure what "gaps" you are referring to. (And please don't tell me "bubbles" and the efficient market hypothesis - there is nothing in the 2008 crash that invalidates the efficient market hypothesis.)

[Jamie]

All,

Thanks for your replies. I have based my reply on a quote from Tom but the reply is aimed at everyone.

Tom Brown: “What if "understanding human behaviour" turns out to be irrelevant for making a viable theoretical model of the economy?”

Tom, You have achieved the impossible with this sentence. You have found something where I agree completely with Avon! Economics is about understanding human behaviour. So is management consulting. So is most everything else of any value like music or art.

Most management consulting problems arise because people are different. They think about the world differently from each other; they mistake their specific view for THE TRUTH; they decide that any other view must be WRONG; as a result, they start verbal or physical wars with each other.

Much of human behaviour can be understood by thinking about religion. People adopt religions because they believe in concepts like love and peace and tolerance. In fact they believe in these concepts so much that they are sometimes prepared to kill anyone who dares to have a very slightly different view of love and peace and tolerance.

This type of thing happens all the time in business and government. Think of a business. The Human Resources manager thinks of the business in terms of its people. The Finance manager thinks of the business in terms of its financial transactions. The factory manager thinks of the factory as a complex place filled with specific machines and specific people. The head office planning manager thinks of the factory as little more than a formula to be plugged into his mathematical model. Also, the planning manager thinks of time solely in terms of planning periods whereas the factory manager thinks of time on a minute by minute basis so, in particular, they have very different views of cause and effect. The CEO often thinks of the business in a very data oriented way (also broad but often shallow) whereas a worker in the factory thinks of the business in a very physical way (also narrow but deep).

A successful business uses these different perspectives to build something which is greater than the individual perspectives. Failing businesses have wars between perspectives. Each camp in the war agrees only that all of the other camps are full of crazy people who are intent on destroying the business. Customers are ignored. The quality of products and services is left to atrophy. Everything becomes subservient to THE WAR. It’s the war that then destroys the business.

For further examples of this see virtually any debate on politics or economics. Public debates BETWEEN economists are often of this type. The debate we are having here is because economists and non-economists have different perspectives on economics. We all mistake our view for THE TRUTH and also we also misconstrue other people’s views.

I think that a key difference between economists and non-economists is on whether economics is just an academic research subject or whether it has specific intent to add value to real world decision making. Avon compares people to cheetahs who operate on instinct. He sees economists as the only people who have the power of thought and sees my criticism as indicative of my disapproval of mathematics. That’s not what I am saying.

If Avon’s cheetahs were as smart as Avon and could converse with him in a sort-of shared language then what I am saying is two things. First, Avon could ask the cheetahs if they had any specific questions they wanted answered about catching prey. Second, Avon could ask the cheetahs how they perceive the world in order to get better insight into the best parameters for his models. Instead, economists just talk with other economists and ignore the rest of us. That results in conversations such as this one where Frances is asking why PhD economists can’t think of questions for their own models to answer.

Earlier in this debate, I asked a question about central planning and why it works when Shell and Exxon do it but didn’t work when Soviet governments did it. I don’t know anything about Soviet governments but I have some limited experience of central planning in Shell. My perception of the difference is that Shell and Exxon base their planning firmly on a forecast of demand. Planned supply is configured to meet forecast demand ALWAYS. That is the dynamic. Even for new products, businesses use marketing to create demand and then configure supply to meet the demand they expect to create. Soviet governments on the other hand seemed to believe that if they supplied something then demand would emerge. ‘If we build it they will come’. Much of academic economics appears to me to be an equivalent of Soviet style planning which is unresponsive to the requirements of the market i.e. students and non-economists who want to learn about economics.

[Jamie]

Avon: “The discipline of economics is not about engineering society or healing it from its ills”

This is part of the problem. If I saw economics as a purely academic study then we wouldn’t be having this conversation because I wouldn’t be sufficiently interested. It’s the fact that economists argue that we should re-engineer society based on the models of economists that causes the problems. That’s why the rest of us want involvement.

As I said earlier, it is almost impossible for an outsider to disentangle economic science from an economist’s own political prejudices. It often feels like the existence of mathematical models is being used as propaganda in favour of what the economist thinks is the optimum society. This is particularly true when the economist answers only his own questions based on his own models and using the very parameters which the economist thinks are most important in determining a good social design e.g. a representative agent.

We see herding behaviour in animals which seems to me to be equivalent to the behaviours we see in human panics such as stock market crashes and fires. If I were modelling that type of behaviour I wouldn’t start with a “representative cheetah”. Rather I would think about the herd and the interactions between cheetahs. The problem here is that it’s the assumptions in the model that determine the outcomes of the model. It’s not the use of mathematics that is the problem. It’s the assumptions. We need to discuss the assumptions. Then you can build the model as you are the expert in that area.

This is all inherently political. If there is significant herding behaviour in the economy then there is more need for political intervention to maintain stability. When economists base their thinking on a representative agent, with the unspoken assumption that society is just a summation of representative behaviours (“there is no such thing as society” as someone once said) then herding can be ignored. That’s why people like me think of representative agents as right wing propaganda.

[Jamie]

Tom Browne:

I have seen the blog you link to on Information Transfer Economics. A few points.

One of the core techniques for understanding ANY system (machine, human body, business) is the use of ‘flow’ models and there are many, many different types of these models. If you want to understand how any organisation works then a good way is to understand the flows of materials, money and other types of information in that organisation. For example, flows in the planning cycle or in the operation of the business. Information flows horizontally between steps in a manufacturing process, or between a business and its customers. Information also flows vertically between workers and management, or between one layer of management and another, or between the business and its regulators.

I could make many observations on information and economics. For example, we are inundated with information on the prices of things which have markets e.g. houses, shares. As a result, we obsess about these things. On the other hand, we have no information on the price/value of, say, the road network. As a result, we don’t obsess about the road network. In fact, we mostly ignore it. Why spend money on the road network when it won’t result in an information flow that tells us that the spending has increased the value of the roads?

Another example. Information is lost as you move up an organisation. It’s also lost between the micro-economy and the macro-economy. The key information problem in macro-economics is that so much information is lost that there is insufficient information left on which to base logical arguments. That’s what leads to the need for economists to make so many assumptions, but the assumptions then cloud the conclusions.

The Information Transfer Model blogger (Jason if I remember) is making a fundamental mistake in my view. My perception is that Jason believes that his technique can provide a better understanding than mainstream economic techniques by using a different type of mathematics. It can’t. The real problems are in the information (and, specifically, the lack of information) not the mathematics.

Macro-economists have access to only highly summarised, delayed, inaccurate data which measures the world only once every planning period. There are only very few examples of major depressions, hyperinflation etc on which to base analysis, and the same effect may have had different causes in different cases. Any cause and effect combination which is less than a planning period apart will be invisible to macro-economists. Macro-economists can’t drill down into their data to look for more detail on causes and effects. That’s why I asked Frances about improvement in the area of data collection. That’s why the assumptions made by economists on causes and effects determine the answers they get.

Imagine a business which suffers the equivalent of a recession. This week’s sales are down by 10%. What action should managers take? There is insufficient information to make any sensible decision so the only sensible course of action is to seek more information. In a business, managers can usually drill down into their data to the level of individual transactions. They can also speak directly to colleagues, customers, suppliers etc. In other words, they can solve the problem by seeking more information. Macro-economists can’t do that so they are left in the same position as a business manager who had to decide a course of action based just on the existence of the drop in sales rather than its causes. In that case, the business manager would have to make assumptions and the assumptions would mostly be wrong. Even if an assumption proved correct to solve one instance of a problem it might be totally wrong for another instance of the ‘same’ problem.

I am much more sympathetic to Jason about the general use of ‘flow’ (or ‘transfer’) in economics. I think it is almost entirely absent in many debates. Nick Rowe often accuses people like me of wanting ‘concrete steps’ for everything. I think that is directly related to the fact that people like me think in flows (like engineers) while people like Nick don’t. That’s back at a perspective problem again, though, and that can’t be solved by a different type of mathematical model.

The perspective of Cullen Roche and his gang is that a deep understanding of the operational aspects of the banking system is vital to an effective understanding of economics. From my perspective, they are saying that an understanding of operational flows is key. At heart that is because, we need to understand how these flows interact. Which flows are the causes and which are the effects? This matters at a macro-level because one of the key debates is whether the central bank can push money into the economy to stimulate the economy or whether money must be pulled out of the banking system by demand.

I like Cullen’s take on things. In my language, he deals with operational information flows and the signals implied by these flows. I’d guess that most of Cullen’s readers are people who intuitively think about flows even if they don’t use that term.

[Jamie]

As you can probably tell, one of my hobby-horses is that language and perspective are parts of many human problems. I wrote another post the other day on this, mostly about cars, which I think is also relevant to this debate.

http://pragcap.com/about-that-inflation-defintion/comment-page-1#comment-180781

[Tom Brown]

Avon, I'm certainly not an expert on the theory I referred to. I did my best to transmit my as yet flawed understanding of it. But one thing that particular theoretical model does support is a version of the efficient market hypothesis (if I recall correctly), so I don't think that's where your differences lie. Also, if you think the theory is useless, I invite you to produce a theoretical model of the general price level that works across different economies and decades as well as the one I referenced does. I'm definitely not saying it can't be done, but the author has put it forward and asked for others to produce other models to compare it with, and so far nobody has taken him up on his challenge... though he did compare against the Fed's P* model (7 to 8 parameters) and another NY Fed model (42 parameters) and TIPS spreads. His is a 3 parameter model, and he does have multiple predictions on his website, including for US inflation out to 2020 and Canada, the ECB, and others.

Perhaps you can explain to me where the author goes wrong. Here's his "hard core" of hypothesis:

http://informationtransfereconomics.blogspot.com/2014/06/hard-core-information-transfer-economics.html

And the models themselves:

http://informationtransfereconomics.blogspot.com/2014/06/the-information-transfer-model.html

So don't put too much stock in my quote about human behavior: that's my personal (and probably flawed) impression from examining the theory and the resultant models. But I'd LOVE to see someone accept the author's challenge and produce a competing model and set of predictions to go up against it.

The author does not suggest that mainstream economics is useless... he's suggesting that he has another means of making a model. In fact one of the most important things to the author is that he can find correspondences between his theory and existing mainstream theories. In terms of what contribution this new model can make, here's the author on that subject:

http://www.themoneyillusion.com/?p=27080#comment-357369

So he's not trying to replace mainstream econ... he's looking for a supplement to it to give some further insight that perhaps mainstream econ is weak on. Plus his theory is falsifiable, and he's not interested in patching it up with epicycles (adding parameters). So if it fails it fails. The author is very up front about that. But take a look at the performance of it yourself, and see if you think it can be declared a failure yet. I'm genuinely interested in seeing what people think of his performance with regard to the empirical data. The model has strengths and weaknesses: e.g. it's probably not the best choice for deciding between NGDPLT and IT (all such CB strategies look the same to it), and ordinary business cycles are almost "in the noise" for it. It's concerned instead with a limited set of dynamics for long term trends.

So don't take my flawed word for it, challenge or ask the author.

[Tom Brown]

Jamie & Avon, you'll note I wrote above:

"What if "understanding human behaviour" turns out to be irrelevant for making a viable theoretical model of the economy?"

Emphasis on "for making *a* viable": I never stated that this was irrelevant to make *any* model: this was more a comment on my understanding of the author's model, which does not approach the problem from a "micro-foundations" perspective (yet it's still completely theoretical: not ad-hoc). So to Jason (the author) I think this is irrelevant for his model... I think it's safe to say that the jury is still out on his particular attempt.

You two seem very certain of your answers BTW. I don't trust much which is stated with that kind of certainty... especially in econ (or religion, or politics, ... which are perhaps all too often pretty much the same things?)! :D

I saw this quote yesterday from Richard Feynman on Noah Smith's site, and I thought to myself "It's a pity this doesn't apply to economists!":

"It's a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty--a kind of leaning over backwards. For example, if you're doing an experiment, you should report everything that you think might make it invalid--not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you've eliminated by some other experiment, and how they worked--to make sure the other fellow can tell they have been eliminated.

Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can--if you know anything at all wrong, or possibly wrong--to explain it."

Replace "scientific" with "economic" in the above and see if that sounds silly to you. From what I've read on most econ blogs, it sure sounded laughable to me (especially when thinking about the typical comments section!). But maybe I'd change my mind if I read academic econ journals??? I don't know. (Worthwhile Canadian Initiative is an exception of course! :D)

[Tom Brown]

... BTW, Jason's is the first econ blog I've ever read which openly discusses the specific empirical evidence which would falsify his models. When's the last time you saw Krugman, Williamson or Cochrane write "If we see X, Y or Z in the empirical data then that constitutes very strong evidence that my hypotheses are likely wrong, and if that happens I'll consider them to be false, write a post mortem on them and move on." ... where X, Y and Z are very concrete and specific, and without 10 asterisks attached. Personally, I've never seen any economist write something remotely resembling that (but perhaps that's what goes on in the econ journals?). But that's pretty much word for word what Jason has stated on his blog. I find it refreshing. But if you do have counter examples, I really would love to see them. I certainly don't read every blog or every blog entry.

[Avon Barksdale]

Tom,

Yes, I am aware of Feynman's quote – it's from his speech on Cargo Cult Science. I am also well versed in his actual contributions to physics. I used a lot of his ideas in my PhD thesis, and many subsequent papers.

I agree, lots of econ is cargo cult. In fact, a lot of what gets posted on WCI is cargo cult, often by the professors themselves, no less. I would submit that anyone who uses economics to try to engineer society is practising cargo cult science in one form or another. Add a touch of taxes here for increased social utility reasons, tinker and fine tune monetary policy with discretion, forecast the stock market or real estate prices - that's all cargo cult. But a lot of econ is not cargo cult - it asks the right questions, which lead to better questions. Read John Cochrane's book, “Asset Pricing” to get a sense of what economic science looks like and how to do it right. Incidentally, Cochrane's undergrad degree is in physics, and his physics background jumps off the page when you read his book.

From my experience, cargo cult science pollutes economics because people have vested interests in getting answers other people want. No one lobbies the government to re-interpret the top quark data to push its mass up or down, but we get these battles in the public sphere because the welfare state has so much power to divert wealth to the slickest salesmen. These are the rent seekers and the do-gooders, and they have little interest in honesty or truth.

The way you avoid cargo cult science is to understand how to know when you're wrong - what laws did you guess that just tell a really bad story. Understand what the data tells us, even if it's noisy, and constantly question assumptions. Appreciate that you might only get approximate answers and that it's better to understand the limit of your knowledge than to invent dragons at the edge of the world. Also, like in any science, the more extraordinary the claim, the more extraordinary the required evidence. At its heart, economics is about people and thus it invokes an ethical component, which separates physics from economics. Start from the real laws of human beings: 1) humans are self-interested 2) humans try the best they can to satisfy their self-interest. If you start from those two laws, you quickly see that you want to organize society as much as possible around voluntary cooperation. Be wary of cargo cult science from those who focus on coercion and government for solutions (who also seem to forget that government is made of self-interested human beings, too).

If you are interested, this is what Feynman thought about economics:

“There was a special dinner at some point, and the head of the theology place, a very nice, very Jewish man gave a speech. It was a good speech, and he was a very good speaker, so while it sounds crazy now, when I’m telling about it, at that time his main idea sounded completely obvious and true. He talked about the big differences in the welfare of various countries, which cause jealousy, which leads to conflict, and now that we have atomic weapons, any war and we’re doomed, so therefore the right way out is to strive for peace by making sure there are no great differences from place to place....Everybody was listening to this, and we were all full of sacrificial feeling, and all thinking we ought to do this. But I came back to my senses on the way home...
The idea of distributing everything evenly is based on a theory that there’s only X amount of stuff in the world, that somehow we took it away from the poorer countries in the first place, and therefore we should give it back to them. But this theory doesn’t take into account the real reason for the differences between countries - that is, the development of new techniques for growing food, the development of machinery to grow food and do other things, and the fact that all this machinery requires the concentration of capital. It isn’t the stuff, but the power to make the stuff, that is important. But I realize now that these people were not in science; they didn’t understand it. They didn’t understand technology; they didn’t understand their time.” (Surely You’re Joking, 282-283)

[Tom Brown]

Jamie, you write:

"Tom, You have achieved the impossible with this sentence. You have found something where I agree completely with Avon!"

I'm a uniter, not a divider. :D

"So is most everything else of any value like music or art."

Personally I haven't bought any music in 15 years, and not one piece of art (but I do like the illustrations of dead presidents on the cash in my tightly clenched fist).

"Much of human behaviour can be understood by thinking about religion."

If that's true, then I'll never understand it.

"The Information Transfer Model blogger (Jason if I remember) is making a fundamental mistake in my view. My perception is that Jason believes that his technique can provide a better understanding than mainstream economic techniques by using a different type of mathematics."

Hmmm, I don't think that's true. I think he's proposing a very different view which he hopes can supplement mainstream macro. Going back to the gas law analogy: Perhaps reductionism in principle can always get you where you want to go (with enough computing resources), but it might also be terribly inefficient if applied to the wrong problem. The gas law might be an emergent macro law in many alternative universes having different molecular physics. And I think the way to judge whether he's making a "fundamental mistake" or not, is to see how his models perform. But his models are perhaps not so useful for "drilling down" like you mention!

"Macro-economists have access to only highly summarised, delayed, inaccurate data which measures the world only once every planning period."

Jason would probably agree with that. "Macro data is uninformative" is what he says (repeating Noah Smith).

"Nick Rowe often accuses people like me of wanting ‘concrete steps’ for everything."

Jason has declared himself to be a "person of the concrete steppes" on several occasions.

"The perspective of Cullen Roche and his gang is that a deep understanding of the operational aspects of the banking system is vital to an effective understanding of economics."

Funny you should mention that, because Cullen links to a blog I put up under his "Education" pull down. In all honestly, I'm no bank or accounting expert! I put that up to help explain to myself the concepts I was learning there, so I guess it makes an OK tutorial for others trying to learn a few basic things.

Final takeaway: I see Jason as presenting interesting new hypotheses which purport to explain a *limited* set of dynamics. He's not a revolutionary trying to overthrow existing econ. His progression: core hypotheses => auxiliary hypotheses => mathematical models => predictions => statements of what evidence constitutes falsification. Even if he's totally wrong, I love the fact that he's approaching it in this way! (Why can't we expect the same on all econ blogs?)

[Tom Brown]

Avaon, thanks for the Feynman quote: I read that book a long time ago (but I don't recall that quote), and it's one of my favorites (it influenced me to go into a technical field actually).

You write:

"At its heart, economics is about people and thus it invokes an ethical component, which separates physics from economics. Start from the real laws of human beings: 1) humans are self-interested 2) humans try the best they can to satisfy their self-interest. If you start from those two laws, you quickly see that you want to organize society as much as possible around voluntary cooperation."

I'm not convinced that's the best starting point for *all* economic theories. Here are two alternative simple starting points, which, as far as I can tell, are free from ethical considerations.

Also, I found this bit of speculation (relevant to your comments I think) to be thought provoking:

"Is the idea of utility in economics a byproduct of our own human sense of agency rather than any solid reasoning?

Were we led astray because we as humans were too close to the problem? Noah Smith mentions something that touches on this in one of his microfoundations posts -- he said we don't know if gravity has microfoundations, but we do know that economics does (it's people).

Did we just assume that humans (agents, firms, households) are the microfoundations? Maybe the microfoundations should be based on information ...

And since we're at the "micro" level and we know we have thoughts, did we go ahead an allow them into economics because, hey, they must matter? That's really not a good reason."

Jason has a PhD in physics too. You two could have a discussion well over my head.

[Tom Brown]

Avon, I might add that I enjoyed this old post by Noah Smith (which I just read yesterday), "The reason macroeconomics doesn't work very well" which includes a link to a review he did of a John Cochrane post called "A satisfactory philosophy of ignorance (John Cochrane edition)".

So I can certainly understand skepticism of something so far outside the mainstream as Jason's hypotheses are. Still, Noah also speaks of "exploring blue-sky ideas that might lead to real leaps in our understanding." So it's good not to ignore the out-there stuff strictly out of habit. The good thing about Jason's theory is it get's right to the models of NGDP and P with very few parameters (one to three parameters in general) to tune, and thus avails itself to immediate comparisons with the empirical data. Still, I think those are words of wisdom by Noah, and if even the mainstream can't collect enough quality data to decide between variants of DSGE, then how are they going to make even more fundamental decisions?

My main takeaway (if Noah is right!)... a LOT more humility is in order it seems to me! Be extremely skeptical of anybody that sounds convinced of anything in econ: the data probably just isn't there to justify their strong opinions. I'm not talking about policy opinions (though I'm sure it applies there even more), I just mean regarding the fundamental science of deciding what models are "more correct" than others. And regarding policy, perhaps he has a point there too: The 1st priority should be "do no harm." Radical policy changes based on theories supported by inadequate evidence (i.e. all theories, since the macroeconomic data is largely uninformative) are unlikely to be helpful... either from the right or the left.

What's your opinion? Do you think Noah and John are correct about the sorry state of macro data, and its inability to let us sort out even the most basic models of what's really going on?

[Avon Barksdale]

Tom,

I have a lot of respect for John Cochrane, for Noah, less so. And while I am a quant (after working for years as research physicist), not an economist, I follow John's professional work from time to time, mostly for fun. As I said before, his textbook, Asset Pricing, is a simply an outstanding piece of scholarship.

Of course we need a lot more humility (Cochrane has made this point more than once). That is why I am against fine tuned or discretionary monetary policy, and why I am against most government programs. I am sceptical of most grand plans presented with “economic” support. If the first policy is “do no harm”, which I agree with, then we should be very reluctant to use central power for just about anything. This debate about NGDP targeting, which DSGE model to use etc., fades quickly – use a simple, predictable rule for monetary policy and then leave it alone. Reduce the central bank to a computer and punt central bank economists back to academia. Potential gains from finessing are lost from the risk of mistakes. There is little sense in using the central bank to try to absolve the fiscal sins of the treasury, or to act as some kind of fly wheel on the economy. That turns into cargo cult science pretty quickly. Having done original research, I can tell you how hard it is to really know something, how much effort it takes not to fool yourself and how much care you need to take to be as right as far as possible. In my experience economists who work in any advisory capacity, whether suggesting a new policy to government or “forecasting” the future, rarely or ever take that care - it is in their self interest not to do so.

I lean towards freedom and markets because government can only accomplish its ends through coercion and violence regardless of how large the majority. Unfortunately, there are circumstances in which we need government, where we need to use the coercive power of the state on otherwise law abiding citizens, but they are few compared to the entirety of our economy.

In life, so far, I have learned this much: states have monopolies of violence, and use them; markets, which rely on voluntary mutual beneficial cooperation, do not. Before I sign on to using the coercive power of the state to achieve actual consequences, I need to see irrefutable evidence that violence or the threat of violence is absolutely necessary. I have a bias towards markets and I have a bias against monopolies of violence whose power so easily tempts the connected, the rent seekers, and the politically strong, to enrich themselves and their friends by tyrannizing the poor and weak. I simply do not understand the reflex to defend the welfare state. It rests on the complete absence of any Hayekian humility whatsoever, and I find it sad that a lot of what gets posted by the professors themselves here at WCI reflects a lack of that humility.

[Tom Brown]

Avon, your opinions come through loud and clear! :D I don't know what it's like to do original research as you have (I'm a lowly un-PhDed engineer).... but suffice it to say, I'm a lot less certain about most of those subjects than you are! (I'm sure you have you reasons, but whenever I hear someone talking about coercion and violence of the state... I immediately associate it with this guy, so that's a bias of my own I guess). I'm thinking that through most of our evolution, we've experienced "violence and coercion of the state" to some extent (where the "state" might be the pack of proto-hominids we co-habitate with to facilitate our survival and reproduction chances). The concept of maximum liberty is just a blink of an eye old in the grand scheme of things. But you're not a no gov guy, just small gov. I like the pragmatism of that. I distrust purists, of all stripes.

You write:

"Reduce the central bank to a computer and punt central bank economists back to academia."

But people build the computer and write the software. And then re-write the software later. I get the idea that this can help reduce capricious modifications... but it's really just a filter to slow things down a bit. Plus, that's all we are: computing state machines. I get your sentiment though... but I keep thinking of those blue screens of death. I'm pretty sure that human kind will be annihilated due to a software bug.

But on that subject, I think if we're automating the central bank, there's no excuse not to do the same for drawing state and congressional district boundaries: put it in the hands of an algorithm, and make it difficult for us to change on a whim. (BTW, that's the idea of term limits, right? "Please don't let me vote for this guy again!!" Lol!... like an alcoholic locking his vodka up in a safe or something). I'm from California, and personally I think it sucks that we get the same number of senators as Wyoming. So yes, I'd rather be from the great state of "Mojave" apparently. :D

[Tom Brown]

... on the subject of "violence and coercion of the state" ... I guess that never really resonates with me, since "the state" has treated me and my family and everyone I know pretty well actually (despite all it's shortcomings).

[Avon Barksdale]

Tom,

"I guess that never really resonates with me, since "the state" has treated me and my family and everyone I know pretty well"

Yes, but there many, many people who aren't treated so nicely. We just have to look at the drug laws in the West and the US in particular, which has destroyed the lives of so many people. In the US, it has sent legions of young black men to prison with no societal benefit whatsoever. And just look at the tax code, how complicated it is, and how it's tilted to provide pork to the median voter, which almost always comes at the expense of the poor and politically disenfranchised (minimum wage, (ware)housing projects, licensure, mortgage interest deductibility, too big to fail policies, etc.) I tremble when I hear: "I'm from the government, and I'm here to help."

Freedom is relatively new, you are correct, And so is explosive economic growth. The two seem to be connected - free or largely free societies have grown rapidly over the last 200 years. The welfare state, as the West has implemented, only came into existence in living memory - post WWII. It is unclear to me whether economic growth of the kind we have seen over the last 200 years can continue in the face of the welfare state.

[Jamie]

Tom and Avon,

We have moved this discussion far away from Frances opening post, so I’ll make one final contribution and then sign off.

Tom: “You two seem very certain of your answers BTW. I don't trust much which is stated with that kind of certainty... especially in econ (or religion, or politics, ... which are perhaps all too often pretty much the same things?)!”

I think we are all on the same side here. I’m not a physicist but I agree with Richard Feynman on certainty. Most of my points are based on what I see as healthy scepticism. My points on perspective are based on the fact that no one perspective represents THE TRUTH – and that includes my perspective. I don’t claim to know how to get the economy out of a recession. I don’t claim to have an optimal model of the economy. I just want better arguments from economists, particularly when their ‘scientific’ views seem to be correlated to their modelling assumptions which are, in turn, correlated with their own political priors. It’s not me who has the certainty. It’s the economists.

Think about a very simply business – a one-man business which makes sandwiches and sells them in a single location. How does this business operate on a day-to-day basis:

1. Demand forecast (how many sandwiches do I think I can sell?)
2. Supply plan (what do I need to do to supply this number of sandwiches?)
3. Actual supply (buy the ingredients and make the sandwiches)
4. Actual demand (sell the sandwiches).

Even at this trivial level, this entire process is conducted in an uncertain environment. The core question driving the dynamics of this business operation is ‘how many sandwiches do I think I can sell’ at step 1? However, the ‘correct’ answer to this doesn’t emerge until step 4. The business is required to commit cost and effort at steps 2 and 3 without knowing actual demand.

An observer of this business will see only step 4 as that is the only information made public. They will see that a number of sandwiches were demanded and supplied at a price. They conclude with certainty that demand = supply. Hence, the absence of information distorts the observer’s view on what is really happening.

The participant sees a process driven by risk and uncertainty while the observer sees only the certainty of the outcome.

Economists are the observers who see the certainty even when they view the economy only from a very narrow and very specific angle, and even when much of their view is based on their own biased assumptions.

Much of economic discourse involves one set of economists who are certain of their views shouting at another set of economists who are equally certain of their totally conflicting views. One set of certainties against another in the (mostly) absence of information. The entire economy is reduced to a discussion of fiscal policy versus monetary policy as those are the only control levers which economists understand. I’m as sceptical as Richard Feynman.