Metamorphosis

15 June, 2018 at 21:55 | Posted in Varia | Leave a comment

 

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High school graduation (personal)

14 June, 2018 at 10:55 | Posted in Varia | 3 Comments

Our youngest, Linnea, graduated from high school today.
Congratulations​ from proud father.

linnea

And here with brothers and sisters:

high five

The microfoundations crusade

14 June, 2018 at 08:36 | Posted in Economics | 3 Comments

I think the two most important microfoundation led innovations in macro have been intertemporal consumption and rational expectations. I have already talked about the former in an earlier post … [s]o let me focus on rational expectations …  [T]he adoption of rational expectations was not the result of some previous empirical failure. Instead it represented, as Lucas said, a consistency axiom …

UnknownI think macroeconomics today is much better than it was 40 years ago as a result of the microfoundations approach. I also argued in my previous post that a microfoundations purist position – that this is the only valid way to do macro – is a mistake. The interesting questions are in between. Can the microfoundations approach embrace all kinds of heterogeneity, or will such models lose their attractiveness in their complexity? Does sticking with simple, representative agent macro impart some kind of bias? Does a microfoundations approach discourage investigation of the more ‘difficult’ but more important issues? Might both these questions suggest a link between too simple a micro based view and a failure to understand what was going on before the financial crash? Are alternatives to microfoundations modelling methodologically coherent? Is empirical evidence ever going to be strong and clear enough to trump internal consistency? These are difficult and often quite subtle questions that any simplistic for and against microfoundations debate will just obscure.

Simon Wren-Lewis

On this argumentation I would like to add the following comments:

(1) The fact that Lucas introduced rational expectations as a consistency axiom is not really an argument to why we should accept it as an acceptable assumption in a theory or model purporting to explain real macroeconomic processes (see e. g. Robert Lucas, rational expectations, and the understanding of business cycles).

(2) “Now virtually any empirical claim in macro is contestable” Wren-Lewis writes. Yes, but so is virtually also any claim in micro (see e. g. When the model is the message – modern neoclassical economics).

(3) To the two questions “Can the microfoundations approach embrace all kinds of heterogeneity, or will such models lose their attractiveness in their complexity?” and “Does sticking with simple, representative agent macro impart some kind of bias?” I would unequivocally answer yes (I have given the reasons why e. g. in David Levine is totally wrong on the rational expectations hypothesis  so I will not repeat the argumentation here).

(4) “Are alternatives to microfoundations modelling methodologically coherent?” Well, I don’t know. But one thing I do  know, is that the kind of miocrofoundationalist macroeconomics that New Classical economists in the vein of Lucas and Sargent and the so-called New Keynesian economists in the vein of Mankiw et consortes are pursuing , are not methodologically coherent (as I have argued e. g. in What is (wrong with) economic theory?) And that ought to be rather embarrassing for those ilks of macroeconomists to whom axiomatics and deductivity are the hallmark of science tout court.

Globalization — a win-lose situation

13 June, 2018 at 14:35 | Posted in Economics | Leave a comment

ZEIT ONLINE: Einigen Menschen würde es ohne Globalisierung also besser gehen?

Holger Görg: Ja. Das ist das große Problem der Globalisierung.

ZEIT ONLINE: Was kann man dagegen tun?

globalGörg: Da sind die Staaten gefordert. Es muss ein soziales Sicherungsnetz geben, das die Menschen auffängt und ihnen ein Einkommen garantiert, wenn sie ihren Job verlieren. So wie in Deutschland und den meisten entwickelten Ländern. Aber das ist nicht genug. Es muss Möglichkeiten zur Weiterbildung und Umschulung geben, um den Menschen eine Perspektive zu bieten. Viele Studien zeigen, dass das Problem der Arbeitslosigkeit nicht nur der Einkommensverlust ist, sondern das Gefühl von Perspektivlosigkeit.

ZEIT ONLINE: Die USA und die EU führen neue Handelszölle ein. Wird das etwas daran ändern, wer von der Globalisierung profitiert?

Görg: Grundsätzlich nicht. Es sind ja nur Zölle für einige wenige Waren. Und wenn man sich die USA betrachtet: Führen Zölle wirklich dazu, dass die Stahlarbeiter wieder zu Globalisierungsgewinnern werden? Das glaube ich nicht. Höhere Preise für Stahl führen dazu, dass weniger Stahl nachgefragt wird. Wegen der hohen Löhne zeigt sich ein Problem: Die Industrien reicher Länder sind nicht mehr wettbewerbsfähig. Gegen die Nachteile der Globalisierung hilft nur Umverteilung, auch international. Eine Möglichkeit wäre, die Gewinne von Unternehmen in allen Ländern ähnlich zu besteuern und mit den Einnahmen die Verlierer der Globalisierung zu unterstützen.

Die Zeit

Two words say​ it all!

13 June, 2018 at 10:16 | Posted in Politics & Society | Leave a comment


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

Contrast explanations in economics

12 June, 2018 at 14:30 | Posted in Economics | Leave a comment

For all scholars seriously interested in questions on what makes up a good scientific explanation, Alan Garfinkel’s Forms of Explanation (Yale University Press 1990) is a must-read. A lot of recent work done within different realist schools in theory of science — e.g. Roy Bhaskar, Andrew Collier, Richard W Miller and Tony Lawson — issue not so little from questions and problems posed by Garfinkel. Especially his advocacy of contrast explanations and critique of methodological individualism and other forms of reductionism are still unsurpassed.

Given this, it is almost scandalous that this modern classic is not reprinted. I was lucky to get a copy from an antiquarian, but of course, this is a book that should have been reprinted long ago!

For those who want to further explore the meaning and potential of contrast explanations, Jamie Morgan’s and Heikki Patomäki’s article in Cambridge Journal of Economics last year is highly recommended reading.

Bayesian religion

12 June, 2018 at 14:19 | Posted in Statistics & Econometrics | Leave a comment

There is a nice YouTube video with Tony O’Hagan interviewing Dennis Lindley. Of course, Dennis is a legend and his impact on the field of statistics is huge.


At one point, Tony points out that some people liken Bayesian inference to a religion. Dennis claims this is false. Bayesian inference, he correctly points out, starts with some basic axioms and then the rest follows by deduction. This is logic, not religion.

I agree that the mathematics of Bayesian inference is based on sound logic. But, with all due respect, I think Dennis misunderstood the question. When people say that “Bayesian inference is like a religion,” they are not referring to the logic of Bayesian inference. They are referring to how adherents of Bayesian inference behave.

(As an aside, detractors of Bayesian inference do not deny the correctness of the logic. They just don’t think the axioms are relevant for data analysis. For example, no one doubts the axioms of Peano arithmetic. But that doesn’t imply that arithmetic is the foundation of statistical inference. But I digress.)

The vast majority of Bayesians are pragmatic, reasonable people. But there is a sub-group of die-hard Bayesians who do treat Bayesian inference like a religion. By this I mean:

They are very cliquish.
They have a strong emotional attachment to Bayesian inference.
They are overly sensitive to criticism.
They are unwilling to entertain the idea that Bayesian inference might have flaws.
When someone criticizes Bayes, they think that critic just “doesn’t get it.”
They mock people with differing opinions …

No evidence you can provide would ever make the die-hards doubt their ideas. To them, Sir David Cox, Brad Efron and other giants in our field who have doubts about Bayesian inference, are not taken seriously because they “just don’t get it.”

So is Bayesian inference a religion? For most Bayesians: no. But for the thin-skinned, inflexible die-hards who have attached themselves so strongly to their approach to inference that they make fun of, or get mad at, critics: yes, it is a religion.

Larry Wasserman

Laughable alternative facts

11 June, 2018 at 23:44 | Posted in Varia | 3 Comments

 

Bowie’s Berlin Heroes

11 June, 2018 at 18:15 | Posted in Varia | Leave a comment

 

On randomness and probability in economics

11 June, 2018 at 11:50 | Posted in Statistics & Econometrics | 10 Comments

Modern mainstream economics relies to a large degree on the notion of probability. To at all be amenable to applied economic analysis, economic observations have to be conceived as random events that are analyzable within a probabilistic framework. But is it really necessary to model the economic system as a system where randomness can only be analyzed and understood when based on an a priori notion of probability?

slide_1When attempting to convince us of the necessity of founding empirical economic analysis on probability models,  neoclassical economics actually forces us to (implicitly) interpret events as random variables generated by an underlying probability density function.

This is at odds with reality. Randomness obviously is a fact of the real world. Probability, on the other hand, attaches (if at all) to the world via intellectually constructed models, and a fortiori is only a fact of a probability generating (nomological) machine or a well constructed experimental arrangement or ‘chance set-up.’

Just as there is no such thing as a ‘free lunch,’ there is no such thing as a ‘free probability.’

To be able at all to talk about probabilities, you have to specify a model. If there is no chance set-up or model that generates the probabilistic outcomes or events – in statistics one refers to any process where you observe or measure as an experiment (rolling a die) and the results obtained as the outcomes or events (number of points rolled with the die, being e. g. 3 or 5) of the experiment – there strictly seen is no event at all.

Probability is a relational element. It always must come with a specification of the model from which it is calculated. And then to be of any empirical scientific value it has to be shown to coincide with (or at least converge to) real data generating processes or structures – something seldom or never done.

And this is the basic problem with economic data. If you have a fair roulette-wheel, you can arguably specify probabilities and probability density distributions. But how do you conceive of the analogous nomological machines for prices, gross domestic product, income distribution etc? Only by a leap of faith. And that does not suffice. You have to come up with some really good arguments if you want to persuade people into believing in the existence of socio-economic structures that generate data with characteristics conceivable as stochastic events portrayed by probabilistic density distributions.

We simply have to admit that the socio-economic states of nature that we talk of in most social sciences – and certainly in economics – are not amenable to analyze as probabilities, simply because in the real world open systems there are no probabilities to be had!

The processes that generate socio-economic data in the real world cannot just be assumed to always be adequately captured by a probability measure. And, so, it cannot be maintained that it even should be mandatory to treat observations and data – whether cross-section, time series or panel data – as events generated by some probability model. The important activities of most economic agents do not usually include throwing dice or spinning roulette-wheels. Data generating processes – at least outside of nomological machines like dice and roulette-wheels – are not self-evidently best modelled with probability measures.

If we agree on this, we also have to admit that much of modern neoclassical economics lacks sound foundations.

When economists and econometricians – often uncritically and without arguments — simply assume that one can apply probability distributions from statistical theory on their own area of research, they are really skating on thin ice.

This importantly also means that if you cannot show that data satisfies all the conditions of the probabilistic nomological machine, then the statistical inferences made in mainstream economics lack sound foundations!

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