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Truth and probability

November 15, 2018 2 comments

from Lars Syll

uncertainty-7Truth exists, and so does uncertainty. Uncertainty acknowledges the existence of an underlying truth: you cannot be uncertain of nothing: nothing is the complete absence of anything. You are uncertain of something, and if there is some thing, there must be truth. At the very least, it is that this thing exists. Probability, which is the science of uncertainty, therefore aims at truth. Probability presupposes truth; it is a measure or characterization of truth. Probability is not necessarily the quantification of the uncertainty of truth, because not all uncertainty is quantifiable. Probability explains the limitations of our knowledge of truth, it never denies it. Probability is purely epistemological, a matter solely of individual understanding. Probability does not exist in things; it is not a substance. Without truth, there could be no probability.

William Briggs’ approach is — as he acknowledges in the preface of his interesting and thought-provoking book — “closely aligned to Keynes’s.”

Almost a hundred years after John Maynard Keynes wrote his seminal A Treatise on Probability (1921), it is still very difficult to find statistics textbooks that seriously try to incorporate his far-reaching and incisive analysis of induction and evidential weight.  Read more…

Take a hard look at the skeletons in the mainstream closet!

November 14, 2018 10 comments

from Lars Syll

lieberAlthough prepared to admit that our empirical research procedures may be based on some very shaky assumptions, [some thoughtful scholars see] no point in saying much about this unless superior alternatives are presented. I understand this concern … Nevertheless, a hard look at the skeletons in the closet is beneficial, especially when there is a propensity to keep the door locked. Nothing is gained by avoiding that which the discipline must face up to sooner or later. If a current procedure appears to be patently wrong, I have not hesitated to indicate this, even if the alternatives remain to develop.

Like Stanley Lieberson, those of us in the economics community who are impolite enough to dare to question the preferred methods and models applied in mainstream economics and econometrics are as a rule met with disapproval. But although people seem to get very agitated and upset by the critique, defenders of “received theory” always say that the critique is “nothing new”, that they have always been “well aware” of the problem, “what Syll points out, we all know; there is nothing new in it; the real issue is to find out the alternative,” and so on, and so on.  Read more…

Econometrics: The Keynes-Tinbergen controversy

November 11, 2018 6 comments

from Lars Syll

Mainstream economists often hold the view that Keynes’ criticism of econometrics was the result of a sadly misinformed and misguided person who disliked and did not understand much of it.

This is, however, nothing but a gross misapprehension.

To be careful and cautious is not the same as to dislike. Keynes did not misunderstand the crucial issues at stake in the development of econometrics. Quite the contrary. He knew them all too well — and was not satisfied with the validity and philosophical underpinning of the assumptions made for applying its methods.

poofKeynes’ critique is still valid and unanswered in the sense that the problems he pointed at are still with us today and ‘unsolved.’ Ignoring them — the most common practice among applied econometricians — is not to solve them.

To apply statistical and mathematical methods to the real-world economy, the econometrician has to make some quite strong assumptions. In a review of Tinbergen’s econometric work — published in The Economic Journal in 1939 — Keynes gave a comprehensive critique of Tinbergen’s work, focusing on the limiting and unreal character of the assumptions that econometric analyses build on:  Read more…

Richard Feynman om mathematics

November 9, 2018 21 comments

from Lars Syll

In a comment on one of yours truly’s posts last week, Jorge Buzaglo wrote this truly interesting comment:

Nobel prize winner Richard Feynman on the use of mathematics:

Mathematicians, or people who have very mathematical minds, are often led astray when “studying” economics because they lose sight of the economics. They say: ‘Look, these equations … are all there is to economics; it is admitted by the economists that there is nothing which is not contained in the equations.

510935-Richard-P-Feynman-Quote-If-all-of-mathematics-disappeared-physics

The equations are complicated, but after all they are only mathematical equations and if I understand them mathematically inside out, I will understand the economics inside out.’ Only it doesn’t work that way. Mathematicians who study economics with that point of view — and there have been many of them — usually make little contribution to economics and, in fact, little to mathematics. They fail because the actual economic situations in the real world are so complicated that it is necessary to have a much broader understanding of the equations.

I have replaced the word “physics” (and similar) by the word “economics” (and similar) in this quote from Page 2-1 in: R. Feynman, R. Leighton and M. Sands, The Feynman Lectures on Physics, Volume II, Addison-Wesley Publishing, Reading, 1964,

 

Calibration — an economics fraud kit

November 8, 2018 7 comments

from Lars Syll

In his well-written and interesting article The Trouble with Macroeconomics, Paul Romer goes to a ​frontal attack on the theories that have put macroeconomics on a path of ‘intellectual regress’ for three decades now:

Macroeconomists got comfortable with the idea that fluctuations in macroeconomic aggregates are caused by imaginary shocks, instead of actions that people take, after Kydland and Prescott (1982) launched the real business cycle (RBC) model …

fraud-kitIn response to the observation that the shocks are imaginary, a standard defence invokes Milton Friedman’s (1953) methodological assertion from unnamed authority that “the more significant the theory, the more unrealistic the assumptions.” More recently, “all models are false” seems to have become the universal hand-wave for dismissing any fact that does not conform to the model that is the current favourite.

The noncommittal relationship with the truth revealed by these methodological evasions and the “less than totally convinced …” dismissal of fact goes so far beyond post-modern irony that it deserves its own label. I suggest “post-real.”

Paul Romer

There are many kinds of useless ‘post-real’ economics held in high regard within mainstream economics establishment today. Few — if any — are less deserved than the macroeconomic theory/method — mostly connected with Nobel laureates Finn Kydland, Robert Lucas, Edward Prescott and Thomas Sargent — called calibration.

Read more…

Debunking mathematical​ economics

November 6, 2018 14 comments

from Lars Syll

The belief in the power and necessity of formalizing economic theory mathematically has thus obliterated the distinction between cognitively perceiving and understanding concepts from different domains and mapping them into each other.quote-too-large-a-proportion-of-recent-mathematical-economics-are-mere-concoctions-as-imprecise-as-the-john-maynard-keynes-243582 Whether the age-old problem of the equality between supply and demand should be mathematically formalized as a system of inequalities or equalities is not something that should be decided by mathematical knowledge or convenience. Surely it would be considered absurd, bordering on the insane, if a surgical procedure was implemented because a tool for its implementation was devised by a medical doctor who knew and believed in topological fixed-point theorems? Yet, weighty propositions about policy are decided on the basis of formalizations based on ignorance and belief in the veracity of one kind of one-dimensional mathematics.

K. Vela Velupillai

Indeed. As social researchers, we should never equate science with mathematics. All science entail human judgement, and using mathematical models do not relieve us of that necessity. They are no substitutes for doing real science.   Read more…

Modern economics is sick

November 2, 2018 7 comments

from Lars Syll

mark-blaug-900pxModern economics is sick. Economics has increasingly become an intellectual game played for its own sake and not for its practical consequences for understanding the economic world. Economists have converted the subject into a sort of social mathematics in which analytical rigour is everything and practical relevance is nothing …

If there is such a thing as “original sin” in economic methodology, it is the worship of the idol of the mathematical rigour invented by Arrow and Debreu in 1954 and then canonized by Debreu in his Theory of Value five years later, probably the most arid and pointless book in the entire literature of economics.

The result of all this is that we now understand almost less of how actual markets work than did Adam Smith or even Léon Walras …

Indeed, much of modern microeconomics might be fairly described as a kind of geography that consists entirely of images of cities but providing no maps of how to reach a city either from any other city or from the countryside.

Mark Blaug

Mark Blaug (1927-2011) did more than any other single person to establish the philosophy and methodology of economics a respected subfield within economics. His path-breaking The methodology of economics (1980) is still a landmark (and the first textbook on economic methodology yours truly ever read).  Read more…

Economic reality — a virulent virus afflicting mainstream economics

October 30, 2018 9 comments

from Lars Syll

The WHO today warned of a virulent new virus affecting vulnerable groups in the Mid‐West and Eastern USA. The outbreak, which began in the Mid‐West’s extensive Great Lakes “Freshwater” river system, has recently jumped the “Saltwater” barrier, meaning that the entire population of its target species—“Mainstream” economists—is now at risk.

suzukiSpeaking on behalf of the WHO, Dr Cahuc explained that the virus works by turning off the one genetic marker that distinguishes this species from the rest of its genus, the Human Race. This is the so‐called “Milton” gene (Friedman, 1953), which goes dormant in other Humans as they pass through puberty. Its inactivity reduces their imaginative capacity, making it impossible for them to continue believing in such endearing infantile fantasies as the Tooth Fairy and Santa Claus. While regrettable, this drop in imagination is necessary to prepare Humans for the adult phase of their existence.

“Professor Milton Friedman found a way to re‐activate this gene during PhD training, using his ‘as if’ gene splicing technique”, Dr Zylberberg elaborated. “This enabled a wonderful outpouring of imaginative beliefs by Mainstream Economists, which gave birth to concepts like NAIRU, Money Neutrality, Rational Expectations, and eventually even DSGE models. This wealth of imagination was regarded by Mainstream Economists as a more than sufficient compensation for returning to the child‐like phase of the Human species.”

Steve Keen

Looking at what famous mainstream economists — like e.g. Paul Samuelson and Gerard Debreu — have come up with, there is no indication at all they produce rigorous and successful explanations or predictions of real-world phenomena. In physics, it’s all different. Read more…

Wren-Lewis — the flimflam anti-pluralist

October 30, 2018 7 comments

from Lars Syll

Again and again, Oxford professor Simon Wren-Lewis rides out to defend orthodox macroeconomic theory against attacks from heterodox critics. In one of his latest attacks on heterodox economics and students demanding pluralist economics education he writes:

mainstreampluralismThe danger in encouraging plurality is that you make it much easier for politicians to select the advice they like, because there is almost certain to be a school of thought that gives the ‘right’ answers from the politicians point of view. The point is obvious once you make the comparison to medicine. Don’t like the idea of vaccination? Pick an expert from the anti-vaccination medical school. The lesson of the last seven years, in the UK in particular, is that we want mainstream economists to have more influence on politicians and the public, and not to dilute this influence through a plurality of schools of thought.

And  a couple of years ago he wrote the following:   Read more…

Simon Wren-Lewis’ warped view of ​modern macroeconomics

October 27, 2018 3 comments

from Lars Syll

kThere is something that just does not sit very well with Oxford macroeconomist Simon Wren-Lewis’ view of modern macroeconomics. On more than one occasion has this self-proclaimed ‘New Keynesian’ macroeconomist approvingly written about the ‘impressive’ theoretical insights New Classical economics has brought to macroeconomics. In one of his latest blog posts he once again  shows how devoted  he is to the Chicago übereconomists and their modelling endeavours (emphasis added):

DSGE models are firmly entrenched in academic macroeconomics, and in pretty well every economist that has done a PhD, which is why the Bank of England’s core model is DSGE … Have a look at almost any macro paper in a top journal today, and compare it to a similar paper before the NCCR, and you can see we have been through a methodological revolution … If you are expecting me at this point to say that DSGE models where were macroeconomics went wrong, you will be disappointed … Moving to DSGE involved losses as well as gains. It inevitably made models less rich and moved them further away from the data in areas that were difficult but not impossible to model in a theoretically consistent way. The DSGE methodological revolution set out so clearly in Lucas and Sargent’s paper changed the focus of macroeconomics away from things we now know were of critical importance.

If moving to DSGE meant not being able to tackle things of “critical importance,” and makes economic models “less rich” and further away from real-world data, why still ultimately defend it? And does “consistency” really trump every other model​ consideration? You do, of course, expect that of New Classical Chicago economists. But a ‘Keynesian’ macroeconomist?   Read more…

Wren-Lewis insults medical science

October 26, 2018 5 comments

from Lars Syll

In a discussion today on twitter one discussant was questioning if economics really could be considered a science, adding that in physics — contrary to economics — “there are no different school of thoughts on ‘Newton’s Laws of Motion’. To this Simon Wren-Lewis answered:

Exactly the same is true of mainstream economics. There are also groups who cannot live with the mainstream who form schools of thought, like MMT. But mainstream economics is a science, like medicine.

But that is simply not true as Steve Keen also notes in a reply to Wren-Lewis. Economics is in no way a science similar to physics, Newtonian mechanics or medicine!

‘Laws’ in economics only hold ceteris paribus. That fundamentally means that these laws/regularities only hold when the right conditions are at hand for giving rise to them. Unfortunately, from an empirical point of view, those conditions are only at hand in artificially closed nomological models purposely designed to give rise to the kind of regular associations that economists want to explain. But, really, since these laws/regularities do not exist outside these ‘socio-economic machines,’ what’s the point in constructing these non-existent laws/regularities? When the almost endless list of narrow and specific assumptions necessary to allow the ‘rigorous’ deductions are known to be at odds with reality, what good do these models do?

Take ‘The Law of Demand.’  Read more…

Econometrics and causality

October 25, 2018 26 comments

from Lars Syll

Judea Pearl’s and Bryant Chen’s Regression and causation: a critical examination of six econometrics textbooks — published in Real-World Economics Review no. 65 — addresses two very important questions in the teaching of modern econometrics and its different textbooks — how is causality treated in general, and more specifically, to what extent they use a distinct causal notation.

causation

The authors have for years been part of an extended effort of advancing explicit causal modelling (especially graphical models) in applied sciences, and this article examines to what extent these endeavours have found their way into econometrics textbooks (and Pearl has later come back to the theme in his The Book of Why (2018))

Although the text partly is of a rather demanding ‘technical’ nature, yours truly definitely recommend it for reading, especially for social scientists with an interest in causality.  Read more…

The connection between cause and probability

October 22, 2018 5 comments

from Lars Syll

huntCauses can increase the probability​ of their effects; but they need not. And for the other way around: an increase in probability can be due to a causal connection; but lots of other things can be responsible as well …

The connection between causes and probabilities is like the connection between a disease and one of its symptoms: The disease can cause the symptom, but it need not; and the same symptom can result from a great many different diseases …

If you see a probabilistic dependence and are inclined to infer a causal connection from it, think hard about all the other possible reasons that that dependence might occur and eliminate them one by one. And when you are all done, remember — your conclusion is no more certain than your confidence that you really have eliminated all​ the possible alternatives.

Causality in social sciences — and economics — can never solely be a question of statistical inference. Causality entails more than predictability, and to really in-depth explain social phenomena require theory. Analysis of variation — the foundation of all econometrics — can never in itself reveal how these variations are brought about. First, when we are able to tie actions, processes or structures to the statistical relations detected, can we say that we are getting at relevant explanations of causation.  Read more…

The connection between cause and probability

October 20, 2018 13 comments

from Lars Syll

huntCauses can increase the probability​ of their effects; but they need not. And for the other way around: an increase in probability can be due to a causal connection; but lots of other things can be responsible as well …

The connection between causes and probabilities is like the connection between a disease and one of its symptoms: The disease can cause the symptom, but it need not; and the same symptom can result from a great many different diseases …

If you see a probabilistic dependence and are inclined to infer a causal connection from it, think hard about all the other possible reasons that that dependence might occur and eliminate them one by one. And when you are all done, remember — your conclusion is no more certain than your confidence that you really have eliminated all​ the possible alternatives.

Causality in social sciences — and economics — can never solely be a question of statistical inference. Causality entails more than predictability, and to really in-depth explain social phenomena require theory. Analysis of variation — the foundation of all econometrics — can never in itself reveal how these variations are brought about. First, when we are able to tie actions, processes or structures to the statistical relations detected, can we say that we are getting at relevant explanations of causation.  Read more…

Too much of ‘we controlled for’

October 18, 2018 1 comment

from Lars Syll

The gender pay gap is a fact that, sad to say, to a non-negligible extent is the result of discrimination. And even though many women are not deliberately discriminated against, but rather self-select into lower-wage jobs, this in no way magically explains away the discrimination gap. As decades of socialization research has shown, women may be ‘structural’ victims of impersonal social mechanisms that in different ways aggrieve them. Wage discrimination is unacceptable. Wage discrimination is a shame.

You see it all the time in studies. “We controlled for…” And then the list starts. The longer the better. Income. Age. Race. Religion. Height. Hair color. Sexual preference. Crossfit attendance. Love of parents. Coke or Pepsi. The more things you can control for, the stronger your study is — or, at least, the stronger your study seems. Controls give the feeling of specificity, of precision. But sometimes, you can control for too much. Sometimes you end up controlling for the thing you’re trying to measure …

paperAn example is research around the gender wage gap, which tries to control for so many things that it ends up controlling for the thing it’s trying to measure. As my colleague Matt Yglesias wrote:

“The commonly cited statistic that American women suffer from a 23 percent wage gap through which they make just 77 cents for every dollar a man earns is much too simplistic. On the other hand, the frequently heard conservative counterargument that we should subject this raw wage gap to a massive list of statistical controls until it nearly vanishes is an enormous oversimplification in the opposite direction. After all, for many purposes gender is itself a standard demographic control to add to studies — and when you control for gender the wage gap disappears entirely!” …   Read more…

Does using models really make economics a science?​

October 14, 2018 12 comments

from Lars Syll

The model has more and more become the message in modern mainstream economics. Formal models are said to help achieve ‘clarity’ and ‘consistency.’ Dani Rodrik — just to take one prominent example — even​ says, in his Economics Rules, that “models make economics a science.”

bbEconomics is more than any other social science model-oriented. There are many reasons for this — the history of the discipline, having ideals coming from the natural sciences (especially physics), the search for universality (explaining as much as possible with as little as possible), rigour, precision, etc.

Mainstream economists want to explain social phenomena, structures and patterns, based on the assumption that the agents are acting in an optimizing (rational) way to satisfy given, stable and well-defined goals.

The procedure is analytical. The whole is broken down into its constituent parts so as to be able to explain (reduce) the aggregate (macro) as the result of interaction of its parts (micro).

Modern mainstream economists ground their models on a set of core assumptions — basically describing the agents as ‘rational’ actors — and a set of auxiliary assumptions. Together they make up the base model of all mainstream economic models. Based on these two sets of assumptions, they try to explain and predict both individual (micro) and — most importantly — social phenomena (macro).  Read more…

Paul Romer’s critique of ‘post-real’ economics

October 12, 2018 8 comments

from Lars Syll

 blah_blahIn practice, what math does is let macro-economists locate the FWUTVs [facts with unknown truth values] farther away from the discussion of identification … Relying on a micro-foundation lets an author say, “Assume A, assume B, …  blah blah blah … And so we have proven that P is true. Then the model is identified.” …

Distributional assumptions about error terms are a good place to bury things because hardly anyone pays attention to them. Moreover, if a critic does see that this is the identifying assumption, how can she win an argument about the true expected value the level of aether? If the author can make up an imaginary variable, “because I say so” seems like a pretty convincing answer to any question about its properties.

Paul Romer

Yes, indeed, modern mainstream economics — and especially its mathematical-statistical operationalization in the form of econometrics — fails miserably over and over again. One reason why it does, is Read more…

At last – Paul Romer got his ‘Nobel prize’​

October 11, 2018 17 comments

from Lars Syll

Among Swedish economists, Paul Romer has for many years been the favourite candidate for receiving the ‘Nobel Prize’ in economics. This year the prediction turned out right. Romer got the prize (together with William Nordhaus).

The ‘Nobel prize’ in economics has almost exclusively gone to mainstream economists, and most often to Chicago economists. So how refreshing it is that we for once have a winner who has been brave enough to openly criticize the ‘post-real’ things that emanate from the Chicago ivory tower!

Adam Smith once wrote that a really good explanation is “practically seamless.”

Is there any such theory within one of the most important fields of social sciences — economic growth?

Paul Romer‘s theory presented in Endogenous Technological Change (1990) – where knowledge is made the most important driving force of growth – is probably as close as we get.

Knowledge – or ideas – are according to Romer the locomotive of growth. But as Allyn Young, Piero Sraffa and others had shown already in the 1920s, knowledge is also something that has to do with increasing returns to scale and therefore not really compatible with neoclassical economics with its emphasis on decreasing returns to scale.

Increasing returns generated by nonrivalry between ideas is simply not compatible with pure competition and the simplistic invisible hand dogma. That is probably also the reason why neoclassical economists have been so reluctant to embrace the theory whole-heartedly.  Read more…

Chicago economics — utterly and completely wrong

October 9, 2018 7 comments

from Lars Syll

Savings-and-InvestmentsEvery dollar of increased government spending must correspond to one less dollar of private spending. Jobs created by stimulus spending are offset by jobs lost from the decline in private spending. We can build roads instead of factories, but fiscal stimulus can’t help us to build more of both. This form of “crowding out” is just accounting, and doesn’t rest on any perceptions or behavioral assumptions.

John Cochrane

The problem with this view is, of course, that it is utterly and completely wrong!

What Cochrane is reiterating here is nothing but Say’s law, basically saying that savings are equal to investments and that if the state increases investments, then private investments have to come down (‘crowding out’). As an accounting identity, there is, of course, nothing to say about the law, but as such, it is also totally uninteresting from an economic point of view. As some of my Swedish forerunners — Gunnar Myrdal and Erik Lindahl — stressed more than 80 years ago, it’s really a question of ex-ante and ex-post adjustments. And as further stressed by a famous English economist about the same time, what happens when ex-ante savings and investments differ, is that we basically get output adjustments. GDP changes and so makes saving and investments equal ex-post. And this, nota bene, says nothing at all about the success or failure of fiscal policies!  Read more…

New Keynesian nonsense ‘proofs’

October 7, 2018 8 comments

from Lars Syll

New Keynesians use mathematics to ‘prove’ some very odd stuff … Take, for example, a paper by Campbell Leith and Simon Wren-Lewis entitled Electoral Uncertainty and the Deficit Bias in a New Keynesian Economy. The thrust of the paper is that our particular form of party-based democracy naturally leads to ‘deficit bias’ … The authors identify the root problem to be one of ‘heterogeneity’ — the fact that different political parties will have different views about how to run the country. Let’s look at a snippet from the paper to see how they use maths to support this earth-shattering discovery:

Read more…