Peter Turchin — What Economics Models Really Say

A Review of Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik (Norton, 2015)

Evonomics
What Economics Models Really Say

Peter Turchin | professor of ecology and evolutionary biology at the University of Connecticut

Lars P. Syll — What is a statistical model?

Best explanation or best guess?

As Bertrand Russell put it at the end of his long life devoted to philosophy, “Roughly speaking, what we know is science and what we don’t know is philosophy.” In the scientific context, but perhaps not in the applied area, I fear statistical modeling today belongs to the realm of philosophy. — Rudolf Kalman

This is important. Since the scientific revolution the progress of knowledge has been moving information from best guess using reasoning (philosophy) to best explanation based on testing hypotheses of a theory against data obtained from observations (science).

Science is true explanation where truth is based on criteria and comparison with criteria. 

Philosophy asks why, that is, for reasons. Science asks how, that is, for mechanisms. 

Philosophical accounts are based chiefly on reasoning from assumptions and it is therefore speculative. 

Scientific explanations are based on how things stand and move in terms of observable relationships, ideally able to be expressed formally. Therefore, science is, well, scientific.

See Richard Feynman, Cargo Cult Science. Engineering and Science, Volume 37:7, June 1974. (pdf) (This is a seminal article in philosophy of science, and as a bonus for reading it, it's funny, too.)

A lot of economic, social science and political science fits Feynman's description of cargo cult science. 

A lot of putative scientific knowledge is actually philosophy, that is, speculation, because it rests on speculation based on assumptions rather than explanation based on rigorous observation. However, some it is even flawed formally because the reasoning process is invalid.

Doing good philosophy is difficult because it is easy to fool oneself by falling into logical traps, as Ludwig Wittgenstein spent the later par to his live exploring. 

Philosophy is a battle against the bewitchment of our intelligence by means of our language. — Philosophical Investigations, § 109

Thus, philosophy in Wittgenstein's sense is a prerequisite to critical thinking.

Doing real science is harder because it requires careful attention not only to logical but also to data collection and processing data into information, keeping the signal to noise ratio within tight boundaries. As Feynman points out, a lot of putative science is mostly just noise.

The first principle is that you must not fool yourself--and you are the easiest person to fool. So you have to be very careful about that. After you've not fooled yourself, it's easy not to fool other scientists. You just have to be honest in a conventional way after that.
I would like to add something that's not essential to the science, but something I kind of believe, which is that you should not fool the layman when you're talking as a scientist. I am not trying to tell you what to do about cheating on your wife, or fooling your girlfriend, or something like that, when you're not trying to be a scientist, but just trying to be an ordinary human being. We'll leave those problems up to you and your rabbi. I'm talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you are maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen. Feynman, "Cargo Cult Science," cited above.

Lars P. Syll’s Blog
What is a statistical model?
Lars P. Syll | Professor, Malmo University

Lars P. Syll — Models vs. reality

Lars P. Syll’s Blog
Models vs. reality
Lars P. Syll | Professor, Malmo University

Chris Dillow — "Consistent with"

In discussing Paul Romer's wonderful concept of mathiness*, Peter Dorman criticizes economists' habit of declaring a theory successful merely because it is "consistent with" the evidence. His point deserves emphasis. 

If a man has no money, this is "consistent with" the theory that he has given it away. But if in fact he has been robbed, that theory is grievously wrong. Mere consistency with the facts is not sufficient.….

The difference between causes and reasons. Reasons are not necessarily causes. "The dog ate my homework."

There may be different plausible explanations for — reasons consistent with — the same data. 

Science is about establishing causal explanation in terms of "mechanism" or "transmission."

Otherwise, it is handwaving.

So, how can we guard against the "consistent with" error? One thing we need is history: this helps tell us how things actually happened. And - horrific as it might seem to some economists - we also need sociology: we need to know how people actually behave and not merely that their behaviour is "consistent with" some theory. Economics, then, cannot be a stand-alone discipline but part of the social sciences and humanities - a point which is lost in the discipline's mathiness.

Stumbling and Mumbling
"Consistent with"
Chris Dillow | Investors Chronicle

See also

Lars P. Syll’s Blog
Consistency and validity is not enough!
Lars P. Syll | Professor, Malmo University

Brian Romanchuk — Why Chartblogging Is Superior To Mainstream Macro

Orthodox-heterodox economic squabbling has once again erupted on the internet. As always, the mainstream argument is that their methodologies are superior because they are based on mathematical models. My main area of interest is the quantitative end of economics, so I do not pay too much attention to some of the purely literary approaches to economics. But even so, I believe that mathematical and statistical methods are being applied incorrectly by mainstream economists, and so whatever modelling advantage they have is largely illusionary. I illustrate this with a few examples, including an explanation why I believe the mainstream debate about the "natural rate" of interest is largely meaningless.…

Nice brief summary, not wonkish.

Bond Economics
Why Chartblogging Is Superior To Mainstream Macro
Brian Romanchuk

Mark Buchanan — Explaining How Economists Explain

…Itzhak Gilboa and a group of economists … recently tried to understand why their profession operates so differently from most sciences. Academic economists, they say, use the term "explanation" in a way that other scientists never would. Instead of developing realistic and testable theories like those in biology or physics, they often aim only to develop "theoretical cases" -- imaginary mathematical worlds with their own rules of cause and effect.

Formalism versus realism, rationalism versus empiricism. Mainstream economists venture into the ivory tower of the mind much further than most philosophers have been willing to tread for fear of becoming lost in their own musings. Talk about being out of touch. It's full-on bonkers as far as explanation is concerned and is purely syntactical without semantic import, that is, mathematical. I guess they know how to develop cool model of possible worlds though. Just not this one.

Bloomberg View
Explaining How Economists Explain

Mark Buchanan
ht Mark Thoma at Economist's View

Lars P. Syll — ‘Rigorous’ evidence can be worse than useless

Department of doh!

"…the literature provides a compelling case that policymakers interested in minimizing the error of their parameter estimates would do well to prioritize careful thinking about local evidence over rigorously-estimated causal effects from the wrong context." —Lant Pritchett & Justin Sandefur

Solving the wrong problem.

Lars P. Syll’s Blog
‘Rigorous’ evidence can be worse than useless
Lars P. Syll | Professor, Malmo University

Peter Dorman — Net Savings and Trade: Krugman is Simply Wrong

I was going to let Paul Krugman’s aside about the trade deficit being “determined” by net national savingspass, but Dean Baker has unintentionally prodded me into action.

It’s actually worse than what Dean says. The sum of a country’s domestic budgets, private and public, is not “equal” to its current account (mostly trade) position; it is the current account position. The two are the same thing. It’s as if my team played your team and you won while we lost. Your victory didn't “determine” our defeat or vice versa: they are one and the same. It’s such a simple idea, but top flight economists like Krugman (who knows trade and open economy macro about as well as anyone on the planet) mess it up just as readily as my introductory students. I've wondered why this is, but it is. (You can read some speculation about why economists don’t distinguish between identity and equality here; see p. 169.)

EconoSpeak

Net Savings and Trade: Krugman is Simply Wrong
Peter Dorman

Daniel Little — Meso causes and microfoundations

In earlier posts I've paid attention to the need for microfoundations and the legitimacy of meso-level causation. And I noted that there seems to be a prima facie tension between the two views in the philosophy of social science. I believe the two are compatible if we understand the microfoundations thesis as a claim about social ontology and not about explanation, and if we interpret it in a weak rather than a strong way. Others have also found this tension to be of interest. The September issue ofThe Philosophy of the Social Sciences" provides a very interesting set of articles on this set of issues.

Particularly interesting is a contribution by Tuukka Kaidesoja, "Overcoming the Biases of Microfoundations: Social Mechanisms and Collective Agents" (link). Here are the four claims advanced in the article:

Understanding Society
Meso causes and microfoundations
Daniel Little | Chancellor, University of Michigan at Dearborn