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Lars Pålsson Syll

Lars Pålsson Syll

Professor at Malmö University. Primary research interest - the philosophy, history and methodology of economics.

Articles by Lars Pålsson Syll

Ett ljus i radiomörkret

22 hours ago

Ett ljus i radiomörkret

I dessa tider — när ljudrummet dränks i den kommersiella radions pubertalflams — har man nästan gett upp.
Men det finns ljus i mörkret.
I programmet Text och musik med Eric Schüldt — som sänds på söndagsförmiddagarna i P2 mellan klockan 11 och 12 — kan man lyssna på seriös musik och en programledare som verkligen har något att säga och inte bara låter foderluckan glappa. Att få höra någon med intelligens och känsla tala om saker som vi alla går och bär på djupt inne i våra själar — men nästan aldrig vågar prata om — är en lisa för själen.
Jag har i flera år nu lyssnat på Erics program varje söndag. En helg utan hans tänkvärda och ofta lite melankoliska funderingar och vemodiga musik har blivit otänkbart.
I dag kunde man bland

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Me and Jane Austen in Karlsbad (personal)

1 day ago

Me and Jane Austen in Karlsbad (personal)

Back in the 80’s yours truly had the pleasure of studying German in Vienna. A wonderful town full of history and Kaffeehäuser.
A couple of years ago, I was invited to give a series of lectures at University of Vienna and at Vienna University of Economics and Business Administration. I spent an absolutely fabulous week with visits to Café Central, Hofburg, Vienna State Opera, Belvedere, Pratern, etc., etc. 
Afterwards, yours truly — of course — could not resist the temptation to make a stopover in Karlsbad (Karlovy Vary). If you like to walk right into a novel by Jane Austen — and your wallet isn’t too thin — it’s a highly recommendable place. Hopefully,​​ when the present pandemic is all over, I will get time off

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On the limits of ‘mediation analysis’ and ‘statistical causality’

3 days ago

From Lars Syll
“Mediation analysis” is this thing where you have a treatment and an outcome and you’re trying to model how the treatment works: how much does it directly affect the outcome, and how much is the effect “mediated” through intermediate variables …
In the real world, it’s my impression that almost all the mediation analyses that people actually fit in the social and medical sciences are misguided: lots of examples where the assumptions aren’t clear and where, in any case, coefficient estimates are hopelessly noisy and where confused people will over-interpret statistical significance …
More and more I’ve been coming to the conclusion that the standard causal inference paradigm is broken … So how to do it? I don’t think traditional path analysis or other multivariate methods

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On the limits of ‘mediation analysis’ and ‘statistical causality’

3 days ago

“Mediation analysis” is this thing where you have a treatment and an outcome and you’re trying to model how the treatment works: how much does it directly affect the outcome, and how much is the effect “mediated” through intermediate variables …
In the real world, it’s my impression that almost all the mediation analyses that people actually fit in the social and medical sciences are misguided: lots of examples where the assumptions aren’t clear and where, in any case, coefficient estimates are hopelessly noisy and where confused people will over-interpret statistical significance …
More and more I’ve been coming to the conclusion that the standard causal inference paradigm is broken … So how to do it? I don’t think traditional path analysis or other multivariate methods of

Read More »

Att tjäna pengar på sjuka — en riktigt sjuk idé

3 days ago

Att tjäna pengar på sjuka — en riktigt sjuk idé

Personal på Attendos äldreboende Långbroberg i södra Stockholm har larmat om missförhållanden – utan att de känner att de får gehör hos cheferna.
Ett tiotal anställda väljer nu att berätta om:
■ Obemannade avdelningar nattetid, där boende skriker av smärta och det dröjer innan de får hjälp.
■ Blaskig soppa, frysta måltider och ont om frukost, vilket gör att brukare är hungriga och rasar i vikt.
■ Boende som läggs för natten redan vid 16-tiden och får äta middag i sängen.
– Jag kastar mig hellre framför ett tåg än bli gammal om det ska vara så här, säger undersköterskan Maria Norstad Pantén, 60.
Karin Sörbring/Expressen

Många som är verksamma inom skolvärlden eller vårdsektorn har haft svårt att förstå

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Causality and the need to reform the teaching of statistics

4 days ago

Causality and the need to reform the teaching of statistics

I will argue that realistic and thus scientifically relevant statistical theory is best viewed as a subdomain of causality theory, not a separate entity or an extension of probability. In particular, the application of statistics (and indeed most technology) must deal with causation if it is to represent adequately the underlying reality of how we came to observe what was seen … The network we deploy for analysis incorporates whatever time-order and independence assumptions we use for interpreting observed associations, whether those assumptions are derived from background (contextual) or design information … Statistics should integrate causal networks into its basic teachings and indeed into

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The elite illusion

5 days ago

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A great set of lectures — but yours truly still warns his students that regression-based averages is something we have reasons to be cautious about.
Suppose we want to estimate the average causal effect of a dummy variable (T) on an observed outcome variable (O). In a usual regression context one would apply an ordinary least squares estimator (OLS) in trying to get an unbiased and consistent estimate:
O = α + βT + ε,
where α is a constant intercept, β a constant ‘structural’ causal effect and ε an error term.
The problem here is that although we may get an estimate of the ‘true’ average causal effect, this may ‘mask’ important heterogeneous effects of a causal nature. Although we get the right answer of the average causal effect being 0, those who are

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Keynes only regret

7 days ago

Your’s truly won’t have to share Keynes regret.

Champagne is one of the few things in life he never says no to.

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What are the key assumptions of linear regression models?

7 days ago

What are the key assumptions of linear regression models?

In Andrew Gelman’s and Jennifer Hill’s Data Analysis Using Regression and Multilevel/Hierarchical Models the authors list the assumptions of the linear regression model. The assumptions — in decreasing order of importance — are:
1. Validity. Most importantly, the data you are analyzing should map to the research question you are trying to answer. This sounds obvious but is often overlooked or ignored because it can be inconvenient. . . .
2. Additivity and linearity. The most important mathematical assumption of the regression model is that its deterministic component is a linear function of the separate predictors . . .
3. Independence of errors. . . .
4. Equal variance of errors. . . .
5.

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Boken jag aldrig ger bort

9 days ago

Boken jag aldrig ger bort

Just nu håller min institution på och flyttar till nya lokaler nere vid hamnbassängen i Malmö.
Flyttar är bra tillfällen att passa på och göra sig av med, eller ge bort, en massa papper och böcker som med tiden bara kommit att värma tjänsterummets hyllor. Ett och annat skönlitterärt alster har också fått göra bekantskap med soplårorna. Men en bok som jag alltid haft på hedersplats i mitt rum varken slängs eller ges bort. Den boken lämnar mig först när den sista resan står för dörren.
Malmö, staden där jag föddes och växte upp i, har kanske inte så många fina skildrare som exempelvis Stockholm. Men vi har några stycken — Torbjörn Flygts Underdog, Mats Olssons De ensamma pojkarna,  Fredrik Ekelunds Malmö stuv, kom! och Kristian

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How statistics can be misleading

9 days ago

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from Lars Syll
From a theoretical perspective, Simpson’s paradox importantly shows that causality can never be reduced to a question of statistics or probabilities.
To understand causality we always have to relate it to a specific causal structure. Statistical correlations are never enough. No structure, no causality.
Simpson’s paradox is an interesting paradox in itself, but it can also highlight a deficiency in the traditional econometric approach towards causality. Say you have 1000 observations on men and an equal amount of observations on women applying for admission to university studies, and that 70% of men are admitted, but only 30% of women. Running a logistic regression to find out the odds ratios (and probabilities) for men and women on admission,

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Causal inference from observational data

10 days ago

From Lars Syll
Researchers often determine the individual’s contemporary IQ or IQ earlier in life, socioeconomic status of the family of origin, living circumstances when the individual was a child, number of siblings, whether the family had a library card, educational attainment of the individual, and other variables, and put all of them into a multiple-regression equation predicting adult socioeconomic status or income or social pathology or whatever. Researchers then report the magnitude of the contribution of each of the variables in the regression equation, net of all the others (that is, holding constant all the others). It always turns out that IQ, net of all the other variables, is important to outcomes. But … the independent variables pose a tangle of causality – with some

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Yours truly on The Top Economics Blogs list

11 days ago

Yours truly on The Top Economics Blogs list

Mainstream economics has sadly made economics increasingly irrelevant to the understanding of the real world. Trying to contribute in making economics a more realist and relevant science, yours truly launched this blog in March 2011.
Now, ten years later and with millions of page views on it, yours truly is — together with people like e.g. Greg Mankiw and Paul Krugman — ranked on INOMICS’ The Top Economics Blogs list.
I am — of course — truly awed, honoured and delighted.

There are many excellent economics blogs out there … The blogs we’ve listed — in no particular order — are the ones we here at INOMICS turn to when we’re looking for interesting, informative, and occasionally offbeat articles on a wide

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How statistics can be misleading

12 days ago

How statistics can be misleading

.[embedded content]
From a theoretical perspective, Simpson’s paradox importantly shows that causality can never be reduced to a question of statistics or probabilities.
To understand causality we always have to relate it to a specific causal structure. Statistical correlations are never enough. No structure, no causality.
Simpson’s paradox is an interesting paradox in itself, but it can also highlight a deficiency in the traditional econometric approach towards causality. Say you have 1000 observations on men and an equal amount of observations on women applying for admission to university studies, and that 70% of men are admitted, but only 30% of women. Running a logistic regression to find out the odds ratios (and

Read More »

Causal inference from observational data

13 days ago

Causal inference from observational data

Researchers often determine the individual’s contemporary IQ or IQ earlier in life, socioeconomic status of the family of origin, living circumstances when the individual was a child, number of siblings, whether the family had a library card, educational attainment of the individual, and other variables, and put all of them into a multiple-regression equation predicting adult socioeconomic status or income or social pathology or whatever. Researchers then report the magnitude of the contribution of each of the variables in the regression equation, net of all the others (that is, holding constant all the others). It always turns out that IQ, net of all the other variables, is important to outcomes. But … the

Read More »

Is causality only in the mind?

14 days ago

Is causality only in the mind?

I make two main points that are firmly anchored in the econometric tradition. The first is that causality is a property of a model of hypotheticals. A fully articulated model of the phenomena being studied precisely defines hypothetical or counterfactual states. A definition of causality drops out of a fully articulated model as an automatic by-product. A model is a set of possible counterfactual worlds constructed under some rules. The rules may be the laws of physics, the consequences of utility maximization, or the rules governing social interactions, to take only three of many possible examples. A model is in the mind. As a consequence, causality is in the mind.
James Heckman

So, according to this ‘Nobel prize’ winning

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