Nothing compares (personal)

28 May, 2017 at 20:44 | Posted in Economics | Leave a comment


Today is Mother’s Day in Sweden. This one is in loving memory of my mother Lisbeth, and of Kristina, beloved wife and mother of David and Tora.

Those whom the gods love die young.

But in dreams,
I can hear your name.
And in dreams,
We will meet again.

When the seas and mountains fall
And we come to end of days,
In the dark I hear a call
Calling me there
I will go there
And back again.

White Flag

28 May, 2017 at 20:05 | Posted in Varia | Leave a comment

 

Economic modeling — a realist perspective

28 May, 2017 at 13:37 | Posted in Theory of Science & Methodology | Leave a comment

411WDSW5BRL._SX331_BO1,204,203,200_To his credit Keynes was not, in contrast to Samuelson, a formalist who was committed to mathematical economics. Keynes wanted models, but for him, building them required ‘ a vigilant observation of the actual working of our system.’ Indeed, ‘to convert a model into a quantitative formula is to destroy its usefulness as an instrument of thought.’ That conclusion can be strongly endorsed!

Modern economics has become increasingly irrelevant to the understanding of the real world. The main reason for this irrelevance is the failure of economists to match their deductive-axiomatic methods with their subject.

In mainstream neoclassical economics internal validity is almost everything and external validity next to nothing. Why anyone should be interested in that kind of theories and models is beyond yours truly’s imagination. As long as mainstream economists do not come up with export licenses for their theories and models to the real world in which we live, they really should not be surprised if people say that this is not science, but autism.

Studying mathematics and logics is interesting and fun. It sharpens the mind. In pure mathematics and logics we do not have to worry about external validity. But economics is not pure mathematics or logics. It’s about society. The real world. Forgetting that, economics is really in danger of becoming — as John Maynard Keynes put it in a letter to Ragnar Frisch in 1935 — “nothing better than a contraption proceeding from premises which are not stated with precision to conclusions which have no clear application.”

The fundamental econometric dilemma

27 May, 2017 at 10:20 | Posted in Statistics & Econometrics | Leave a comment

fraud-kit

Many thanks for sending me your article. I enjoyed it very much. I am sure these matters need discussing in that sort of way. There is one point, to which in practice I attach a great importance, you do not allude to. In many of these statistical researches, in order to get enough observations they have to be scattered over a lengthy period of time; and for a lengthy period of time it very seldom remains true that the environment is sufficiently stable. That is the dilemma of many of these enquiries, which they do not seem to me to face. Either they are dependent on too few observations, or they cannot rely on the stability of the environment. It is only rarely that this dilemma can be avoided.

Letter from J. M. Keynes to T. Koopmans, May 29, 1941

 

Econometric patterns should never be seen as anything else than possible clues to follow. Behind observable data there are real structures and mechanisms operating, things that are  — if we really want to understand, explain and (possibly) predict things in the real world — more important to get hold of than to simply correlate and regress observable variables.

Math cannot establish the truth value of a fact. Never has. Never will.

Paul Romer

Dido

26 May, 2017 at 21:22 | Posted in Varia | Leave a comment

 

Just face it — austerity policies do not work!

26 May, 2017 at 10:29 | Posted in Economics | 1 Comment

 7ti40If failing to understand some basic Keynes­ian relations is a part of the explanation of what happened, there was also another, and more subtle, story behind the confounded economics of austerity. There was an odd confusion in policy thinking between the real need for institutional reform in Europe and the imagined need for austerity – two quite different things …

An analogy can help to make the point clearer: it is as if a person had asked for an antibiotic for his fever, and been given a mixed tablet with antibiotic and rat poison. You cannot have the antibiotic without also having the rat poison. We were in effect being told that if you want economic reform then you must also have, along with it, economic austerity, although there is absolutely no reason whatsoever why the two must be put together as a chemical compound.

Amartya Sen

austerity22We are not going to get out of the present economic doldrums as long as we continue to be obsessed with the insane idea that austerity is the universal medicine. When an economy is already hanging on the ropes, you can’t just cut government spendings. Cutting government expenditures reduces the aggregate demand. Lower aggregate demand means lower tax revenues. Lower tax revenues means increased deficits — and calls for even more austerity. And so on, and so on.

Kid in suit

26 May, 2017 at 10:06 | Posted in Varia | 1 Comment

 

I used to laugh at my kids when they behaved like this when in kindergarten.
But I guess most people expect something else from a president …

I can’t but grieve for a nation that has given us presidents like George Washington, Thomas Jefferson, Abraham Lincoln, and Franklin D. Roosevelt, and now is run by a witless clown. An absolute disgrace.

Expansionary austerity? You gotta be kidding!

25 May, 2017 at 18:19 | Posted in Economics | Leave a comment


[h/t Gabriel Uriarte]

Modern economics — pseudo-science based on FWUTV

25 May, 2017 at 14:39 | Posted in Statistics & Econometrics | Leave a comment

The use of FWUTV — facts with unknown truth values — is, as Paul Romeer noticed in last year’s perhaps most interesting insider critique of mainstream economics, all to often used in macroeconomic modelling. But there are other parts of ‘modern’ economics than New Classical RBC economics that also have succumbed to this questionable practice:

CnGyMOeWAAEQVaHStatistical significance is not the same as real-world significance — all it offers is an indication of whether you’re seeing an effect where there is none. Even this narrow technical meaning, though, depends on where you set the threshold at which you are willing to discard the ‘null hypothesis’ — that is, in the above case, the possibility that there is no effect. I would argue that there’s no good reason to always set it at 5 percent. Rather, it should depend on what is being studied, and on the risks involved in acting — or failing to act — on the conclusions …

This example illustrates three lessons. First, researchers shouldn’t blindly follow convention in picking an appropriate p-value cutoff. Second, in order to choose the right p-value threshold, they need to know how the threshold affects the probability of a Type II error. Finally, they should consider, as best they can, the costs associated with the two kinds of errors.

Statistics is a powerful tool. But, like any powerful tool, it can’t be used the same way in all situations.

Narayana Kocherlakota

Good lessons indeed — underlining how important it is not to equate science with statistical calculation. All science entail human judgement, and using statistical models doesn’t relieve us of that necessity. Working with misspecified models, the scientific value of significance testing is actually zero – even though you’re making valid statistical inferences! Statistical models and concomitant significance tests are no substitutes for doing science.

In its standard form, a significance test is not the kind of ‘severe test’ that we are looking for in our search for being able to confirm or disconfirm empirical scientific hypotheses. This is problematic for many reasons, one being that there is a strong tendency to accept the null hypothesis since they can’t be rejected at the standard 5% significance level. In their standard form, significance tests bias against new hypotheses by making it hard to disconfirm the null hypothesis.

And as shown over and over again when it is applied, people have a tendency to read “not disconfirmed” as ‘probably confirmed.’ Standard scientific methodology tells us that when there is only say a 10 % probability that pure sampling error could account for the observed difference between the data and the null hypothesis, it would be more ‘reasonable’ to conclude that we have a case of disconfirmation. Especially if we perform many independent tests of our hypothesis and they all give about the same 10 % result as our reported one, I guess most researchers would count the hypothesis as even more disconfirmed.

We should never forget that the underlying parameters we use when performing significance tests are model constructions. Our p-values mean next to nothing if the model is wrong. And most importantly — statistical significance tests DO NOT validate models!

411-y9smopl-_sx346_bo1204203200_In journal articles a typical regression equation will have an intercept and several explanatory variables. The regression output will usually include an F-test, with p – 1 degrees of freedom in the numerator and n – p in the denominator. The null hypothesis will not be stated. The missing null hypothesis is that all the coefficients vanish, except the intercept.

If F is significant, that is often thought to validate the model. Mistake. The F-test takes the model as given. Significance only means this: if the model is right and the coefficients are 0, it is very unlikely to get such a big F-statistic. Logically, there are three possibilities on the table:
i) An unlikely event occurred.
ii) Or the model is right and some of the coefficients differ from 0.
iii) Or the model is wrong.

Yes, indeed. Forgetting — or at least pretending to forget — that third possibility, turns much of ‘modern’ economics and econometrics into post-real blah blah blah pseudo-science.

Financial crises — no big deal

23 May, 2017 at 17:51 | Posted in Economics | 1 Comment

dumstrutMany say or think that there were problems in the financial system that gave rise to the Great Depression. We’ve looked at that in a systematic way using modern theory. And we found that businesses had all kinds of money to invest, and they didn’t. They increased distributions to owners. Why? The answer is that businesses did not perceive they had profitable investment opportunities.

I don’t think financial crises are a big deal.

Edward Prescott

And this blah blah blah guy got a “Nobel prize” …

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