## Does drinking cause you to become a man?

26 Jan, 2022 at 19:16 | Posted in Statistics & Econometrics | 1 CommentBreaking news! Using advanced multiple nonlinear regression models similar to those in recent news stories on alcohol and dairy and more than 3.6M observations from 1997 through 2012, I have found that drinking more causes people to turn into men!

Across people drinking 0-7 drinks per day, each drink per day causes the drinker’s probability of being a man to increase by 10.02 percentage points (z=302.2, p<0.0001). Need I say, profound implications for public health policy follow. The Lancet here I come!

Econometric identification sure is difficult …

Great tweet!

## Laplace’s rule of succession and Bayesian priors

26 Jan, 2022 at 15:37 | Posted in Statistics & Econometrics | 1 CommentAfter their first night in paradise, and having seen the sun rise in the morning, Adam and Eve was wondering if they were to experience another sunrise or not. Given the rather restricted sample of sunrises experienced, what could they expect? According to *Laplace’s rule of succession*, the probability of an event E happening after it has occurred n times is p(E|n) = (n+1)/(n+2).

The probabilities can be calculated using Bayes’ rule, but to get the calculations going, Adam and Eve must have an *a priori* probability (a base rate) to start with. The Bayesian rule of thumb is to simply assume that all outcomes are equally likely. Applying this rule Adam’s and Eve’s probabilities become 1/2, 2/3, 3/4 …

Now this might seem rather straight forward, but as already e. g. Keynes (1921) noted in his *Treatise on Probability,* there might be a problem here. The problem has to do with the prior probability and where it is assumed to come from. Is the appeal of the principle of insufficient reason — the principle of indifference — really warranted?

Assume there is a certain quantity of liquid containing wine and water mixed so that the ratio of wine to water (r) is between 1/3 and 3/1. What is then the probability that r ≤ 2? The principle of insufficient reason means that we have to treat all r-values as equiprobable, assigning a uniform probability distribution between 1/3 and 3/1, which gives the probability of r ≤ 2 = [(2-1/3)/(3-1/3)] = 5/8.

But to say r ≤ 2 is equivalent to saying that 1/r ≥ ½. Applying the principle now, however, gives the probability of 1/r ≥ 1/2 = [(3-1/2)/(3-1/3)]=15/16. So we seem to get two different answers that both follow from the same application of the principle of insufficient reason. Given this unsolved paradox, we have reason to stick with Keynes and be skeptical of Bayesianism.

## Beta distribution (student stuff)

25 Jan, 2022 at 09:15 | Posted in Statistics & Econometrics | Leave a comment.

## He ain’t heavy, he’s my brother

24 Jan, 2022 at 15:29 | Posted in Varia | 1 Comment.

In loving memory of my brother Peter.

Twenty years have passed.

People say time heals all wounds.

I wish that was true.

But some wounds never heal — you just learn to live with the scars.

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.

## Models and the need to validate assumptions

24 Jan, 2022 at 09:09 | Posted in Economics | 1 CommentPiketty argues that the higher income share of wealth-owners is due to an increase in the capital-output ratio resulting from a high rate of capital accumulation. The evidence suggests just the contrary. The capital-output ratio, as conventionally measured has either fallen or been constant in recent decades. The apparent increase in the capital-output ratio identified by Piketty is a valuation effect reflecting a disproportionate increase in the market value of certain real assets. A more plausible explanation for the increased income share of wealth-owners is an unduly low rate of investment in real capital.

Say we have a diehard neoclassical model (assuming the production function is homogeneous of degree one and unlimited substitutability) such as the standard Cobb-Douglas production function (with A a given productivity parameter, and k the ratio of capital stock to labor, K/L) *y = Ak** ^{α}* , with a constant investment λ out of output y and a constant depreciation rate δ of the “capital per worker” k, where the rate of accumulation of k,

*Δ*

*k =*

*λ*

*y*

*–*

*δ*

*k,*equals

*Δ*

*k =*

*λ*

*Ak*

^{α}*–*

*δ*

*k*. In steady state (*) we have

*λ*

*Ak**

^{α }*=*

*δ*

*k*,*giving

*λ/δ = k*/y**and

*k* = (*

*λ*

*A/*

*δ)*Putting this value of k* into the production function, gives us the steady state output per worker level

^{1/(1-α)}.*y* = Ak**

^{α}*= A*

^{1/(1-α)}*(*

*λ*

*/*

*δ))*

^{α}

^{/(1-α)}*.*Assuming we have an exogenous Harrod-neutral technological progress that increases y with a growth rate g (assuming a zero labour growth rate and with y and k

*a fortiori*now being refined as y/A and k/A respectively, giving the production function as

*y = k*) we get

^{α}*dk/dt = λy – (g + δ)k,*which in the Cobb-Douglas case gives

*dk/dt = λk*with steady state value

^{α}– (g + δ)k,*k* = (λ/(g + δ))*and capital-output ratio

^{1/(1-}^{α}^{) }*k*/y* = k*/k**If using Piketty’s preferred model with output and capital given net of depreciation, we have to change the final expression into

^{α}= λ/(g + δ).*k*/y* = k*/k**Now what Piketty predicts is that g will fall and that this will increase the capital-output ratio. Let’s say we have δ = 0.03, λ = 0.1 and g = 0.03 initially. This gives a capital-output ratio of around 3. If g falls to 0.01 it rises to around 7.7. We reach analogous results if we use a basic CES production function with an elasticity of substitution σ > 1. With σ = 1.5, the capital share rises from 0.2 to 0.36 if the wealth-income ratio goes from 2.5 to 5, which according to Piketty is what actually has happened in rich countries during the last forty years.

^{α}= λ/(g + λδ).Being able to show that you can get these results using one or another of the available standard neoclassical growth models is of course — from a realist point of view — of limited value. As usual — the really interesting thing is how in accord with reality are the assumptions you make and the numerical values you put into the model specification.

Professor Piketty chose a theoretical framework that simultaneously allowed him to produce catchy numerical predictions, in tune with his empirical findings, while soaring like an eagle above the ‘messy’ debates of political economists shunned by their own profession’s mainstream and condemned diligently to inquire, in pristine isolation, into capitalism’s radical indeterminacy. The fact that, to do this, he had to adopt axioms that are both grossly unrealistic and logically incoherent must have seemed to him a small price to pay.

## DAG thinking (student stuff)

21 Jan, 2022 at 10:30 | Posted in Statistics & Econometrics | 2 Comments.

## Mainstream economics in denial

20 Jan, 2022 at 11:08 | Posted in Economics | 1 CommentWe’d gathered at Downing College, Cambridge, to discuss the economic crisis, although the quotidian misery of that topic seemed a world away from the honeyed quads and endowment plush of this place.

Equally incongruous were the speakers. The Cambridge economist Victoria Bateman looked as if saturated fat wouldn’t melt in her mouth, yet demolished her colleagues. They’d been stupidly cocky before the crash – remember the 2003 boast from Nobel prizewinner Robert Lucas that the “central problem of depression-prevention has been solved”? – and had learned no lessons since. Yet they remained the seers of choice for prime ministers and presidents. She ended: “If you want to hang anyone for the crisis, hang me – and my fellow economists.”

What followed was angry agreement. On the night before the latest growth figures, no one in this 100-strong hall used the word “recovery” unless it was to be sarcastic. Instead, audience members – middle-aged, smartly dressed and doubtless sizably mortgaged – took it in turn to attack bankers, politicians and, yes, economists. They’d created the mess everyone else was paying for, yet they’d suffered no retribution …

Yet look around at most of the major economics degree courses and neoclassical economics – that theory that treats humans as walking calculators, all-knowing and always out for themselves, and markets as inevitably returning to stability – remains in charge. Why? In a word: denial. The high priests of economics refuse to recognise the world has changed.

In his new book,

Never Let a Serious Crisis Go to Waste, the US economist Philip Mirowski recounts how a colleague at his university was asked by students in spring 2009 to talk about the crisis. The world was apparently collapsing around them, and what better forum to discuss this in than a macroeconomics class. The response? “The students were curtly informed that it wasn’t on the syllabus, and there was nothing about it in the assigned textbook, and the instructor therefore did not wish to diverge from the set lesson plan. And he didn’t.”

## Hederskulturens offer

19 Jan, 2022 at 19:01 | Posted in Politics & Society | 1 Comment###### Till *Fadime Sahindal*, född 2 april 1975 i Turkiet, mördad 21 januari 2002 i Sverige

I Sverige har vi länge okritiskt omhuldat en ospecificerad och odefinierad mångkulturalism. Om vi med mångkulturalism menar att det med kulturell tillhörighet och identitet också kommer specifika moraliska, etiska och politiska rättigheter och skyldigheter, talar vi om *normativ *multikulturalism. Att acceptera normativ mångkulturalism, innebär att också tolerera oacceptabel intolerans, eftersom den normativa mångkulturalismen innebär att specifika kulturella gruppers rättigheter kan komma att ges högre dignitet än samhällsmedborgarens allmänmänskliga rättigheter – och därigenom indirekt blir till försvar för dessa gruppers intolerans.

Den normativa mångkulturalismen innebär att individer på ett oacceptabelt sätt reduceras till att vara passiva medlemmar av kultur- eller identitetsbärande grupper.

Men — de som i vårt samhälle visar att de inte respekterar andra människors rättigheter, kan inte räkna med att vi ska vara toleranta mot dem.

Mot dem som i vårt samhälle vill tvinga andra att leva efter deras egna religiösa, kulturella eller ideologiska trosföreställningar och tabun, ska samhället vara intolerant. Mot dem som vill tvinga samhället att anpassa lagar och regler till den egna religionens, kulturens eller gruppens tolkningar, ska samhället vara intolerant.

DE DÖDADe döda skall icke tiga men tala.

Förskingrad plåga skall finna sin röst,

och när cellernas råttor och mördarnas kolvar

förvandlats till aska och urgammalt stoft

skall kometens parabel och stjärnornas vågspel

ännu vittna om dessa som föll mot sin mur:

tvagna i eld men inte förbrunna till glöd,

förtrampade slagna men utan ett sår på sin kropp,

och ögon som stirrat i fasa skall öppnas i frid,

och de döda skall icke tiga men tala.Om de döda skall inte tigas men talas.

Fast stympade strypta i maktens cell,

glasartade beledda i cyniska väntrum

där döden har klistrat sin freds propaganda,

skall de vila länge i samvetets montrar.

balsamerade av sanning och tvagna i eld,

och de som redan har stupat skall icke brytas,

och den som tiggde nåd i ett ögonblicks glömska

skall resa sig och vittna om det som inte brytes,

för de döda skall inte tiga men tala.Nej, de döda skall icke tiga men tala.

De som kände triumf på sin nacke skall höja sitt huvud,

och de som kvävdes av rök skall se klart,

de som pinades galna skall flöda som källor,

de som föll för sin motsats skall själva fälla,

de som dräptes med bly skall dräpa med eld,

de som vräktes av vågor skall själva bli storm.

Och de döda skall icke tiga men tala.

Erik Lindegren

## Maximum likelihood estimation (student stuff)

19 Jan, 2022 at 17:08 | Posted in Statistics & Econometrics | Leave a comment.

## Statistical philosophies and idealizations

18 Jan, 2022 at 18:16 | Posted in Theory of Science & Methodology | 2 CommentsAs has been long and widely emphasized in various terms … frequentism and Bayesianism are incomplete both as learning theories and as philosophies of statistics, in the pragmatic sense that each alone are insufficient for all sound applications. Notably, causal justifications are the foundation for classical frequentism, which demands that all model constraints be deduced from real mechanical constraints on the physical data-generating process. Nonetheless, it seems modeling analyses in health, medical, and social sciences rarely have such physical justification …

The deficiency of strict coherent (operational subjective) Bayesianism is its assumption that all aspects of this uncertainty have been captured by the prior and likelihood, thus excluding the possibility of model misspecification. DeFinetti himself was aware of this limitation:

“…everything is based on distinctions which are themselves uncertain and vague, and which we conventionally translate into terms of certainty only because of the logical formulation…In the mathematical formulation of any problem it is necessary to base oneself on some appropriate idealizations and simplification. This is, however, a disadvantage; it is a distorting factor which one should always try to keep in check, and to approach circumspectly. It is unfortunate that the reverse often happens. One loses sight of the original nature of the problem, falls in love with the idealization, and then blames reality for not conforming to it.” [DeFinetti 1975, p. 279]

By asking for physically causal justifications of the data distributions employed in statistical analyses (whether those analyses are labeled frequentist or Bayesian), we may minimize the excessive certainty imposed by simply assuming a probability model and proceeding as if that idealization were a known fact.

## Juloratoriet (personal)

16 Jan, 2022 at 12:42 | Posted in Varia | Leave a commentKjell-Åke Andersson turned Göran Tunström’s s epic masterpiece* The Christmas Oratory* into a stunningly beautiful and emotionally upsetting movie.

Stefan Nilsson wrote the breathtaking music.

And it still breaks my heart every time I watch it …

## Bayesian superficiality

15 Jan, 2022 at 19:06 | Posted in Theory of Science & Methodology | Leave a commentThe bias toward the superficial and the response to extraneous influences on research are both examples of real harm done in contemporary social science by a roughly Bayesian paradigm of statistical inference as the epitome of empirical argument. For instance the dominant attitude toward the sources of black-white differential in United States unemployment rates (routinely the rates are in a two to one ratio) is “phenomenological.” The employment differences are traced to correlates in education, locale, occupational structure, and family background. The attitude toward further, underlying causes of those correlations is agnostic … Yet on reflection, common sense dictates that racist attitudes and institutional racism

mustplay an important causal role. People do have beliefs that blacks are inferior in intelligence and morality, and they are surely influenced by these beliefs in hiring decisions … Thus, an overemphasis on Bayesian success in statistical inference discourages the elaboration of a type of account of racial disadavantages that almost certainly provides a large part of their explanation.

## Scientific realism and inference to the best explanation

15 Jan, 2022 at 16:28 | Posted in Theory of Science & Methodology | 2 CommentsIn inference to the best explanation we start with a body of (purported) data/facts/evidence and search for explanations that can account for these data/facts/evidence. Having the best explanation means that you, given the context-dependent background assumptions, have a satisfactory explanation that can explain the fact/evidence better than any other competing explanation — and so it is reasonable to consider/believe the hypothesis to be true. Even if we (inevitably) do not have deductive certainty, our reasoning gives us a license to consider our belief in the hypothesis as reasonable.

Accepting a hypothesis means that you believe it does explain the available evidence better than any other competing hypothesis. Knowing that we — after having earnestly considered and analysed the other available potential explanations — have been able to eliminate the competing potential explanations, warrants and enhances the confidence we have that our preferred explanation is the best explanation, i. e., the explanation that provides us (given it is true) with the greatest understanding.

This, of course, does not in any way mean that we cannot be wrong. Of course we can. Inferences to the best explanation are fallible inferences — since the premises do not logically *entail* the conclusion — so from a* logical* point of view, inference to the best explanation is a weak mode of inference. But if the arguments put forward are strong enough, they can be warranted and give us justified true belief, and hence, knowledge, even though they are fallible inferences. As scientists we sometimes — much like Sherlock Holmes and other detectives that use inference to the best explanation reasoning — experience disillusion. We thought that we had reached a strong conclusion by ruling out the alternatives in the set of contrasting explanations. But — what we thought was true turned out to be false.

That does not necessarily mean that we had no good reasons for believing what we believed. If we cannot live with that contingency and uncertainty, well, then we are in the wrong business. If it is deductive certainty you are after, rather than the ampliative and defeasible reasoning in inference to the best explanation — well, then get in to math or logic, not science.

What exactly is the

inferencein ‘inference to the best explanation’, what are the premises, and what the conclusion? …

It is reasonable to believe thatthe best available explanation of any fact is true.

F is a fact.

Hypothesis H explains F.

No available competing hypothesis explains F as well as H does.

Therefore,it is reasonable to believe thatH is true.This scheme is valid and instances of it might well be sound. Inferences of this kind are employed in the common affairs of life, in detective stories, and in the sciences …

People object that the best available explanation might be false. Quite so – and so what? It goes without saying that any explanation might be false, in the sense that it is not necessarily true. It is absurd to suppose that the only things we can reasonably believe are necessary truths …

People object that being the best available explanation of a fact does not prove something to be true or even probable. Quite so – and again, so what? The explanationist principle – “It is reasonable to believe that the best available explanation of any fact is true” – means that it is reasonable to believe or think true things that have not been shown to be true or probable, more likely true than not.

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A couple of weeks ago yours truly had a review of Diane Coyle’s

Cogs and Monstersin WEA Commentaires. As I wrote, there’s a lot in the book to like, but unfortunately also some things very hard to swallow. James Galbraith seems to argue along the same lines in his Project Syndicate review: