The future — something we know very little about

18 February, 2018 at 19:54 | Posted in Economics | Leave a comment

All these pretty, polite techniques, made for a well-panelled Board Room and a nicely regulated market, are liable to collapse. At all times the vague panic fears and equally vague and unreasoned hopes are not really lulled, and lie but a little way below the surface.

check-your-assumptionsPerhaps the reader feels that this general, philosophical disquisition on the behavior of mankind is somewhat remote from the economic theory under discussion. But I think not. Tho this is how we behave in the marketplace, the theory we devise in the study of how we behave in the market place should not itself submit to market-place idols. I accuse the classical economic theory of being itself one of these pretty, polite techniques which tries to deal with the present by abstracting from the fact that we know very little about the future.

I dare say that a classical economist would readily admit this. But, even so, I think he has overlooked the precise nature of the difference which his abstraction makes between theory and practice, and the character of the fallacies into which he is likely to be led.

John Maynard Keynes

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The Bayesian folly

16 February, 2018 at 18:18 | Posted in Economics | 1 Comment

Assume you’re a Bayesian turkey and hold a nonzero probability belief in the hypothesis H that “people are nice vegetarians that do not eat turkeys and that every day I see the sun rise confirms my belief.” For every day you survive, you update your belief according to Bayes’ Rule

P(H|e) = [P(e|H)P(H)]/P(e),

where evidence e stands for “not being eaten” and P(e|H) = 1. Given that there do exist other hypotheses than H, P(e) is less than 1 and so P(H|e) is greater than P(H). Every day you survive increases your probability belief that you will not be eaten. This is totally rational according to the Bayesian definition of rationality. Unfortunately — as Bertrand Russell famously noticed — for every day that goes by, the traditional Christmas dinner also gets closer and closer …

Neoclassical economics nowadays usually assumes that agents that have to make choices under conditions of uncertainty behave according to Bayesian rules — that is, they maximize expected utility with respect to some subjective probability measure that is continually updated according to Bayes theorem. If not, they are supposed to be irrational.

bayes_dog_tshirtBayesianism reduces questions of rationality to questions of internal consistency (coherence) of beliefs, but — even granted this questionable reductionism — do rational agents really have to be Bayesian? As I have been arguing repeatedly over the years, there is no strong warrant for believing so.

The nodal point here is — of course — that although Bayes’ Rule is mathematically unquestionable, that doesn’t qualify it as indisputably applicable to scientific questions. As one of my favourite statistics bloggers —  Andrew Gelman — puts it:

The fundamental objections to Bayesian methods are twofold: on one hand, Bayesian methods are presented as an automatic inference engine, and this raises suspicion in anyone with applied experience, who realizes that different methods work well in different settings … Bayesians promote the idea that a multiplicity of parameters can be handled via hierarchical, typically exchangeable, models, but it seems implausible that this could really work automatically. In contrast, much of the work in modern non-Bayesian statistics is focused on developing methods that give reasonable answers using minimal assumptions.

The second objection to Bayes comes from the opposite direction and addresses the subjective strand of Bayesian inference: the idea that prior and posterior distributions represent subjective states of knowledge. Here the concern from outsiders is, first, that as scientists we should be concerned with objective knowledge rather than subjective belief, and second, that it’s not clear how to assess subjective knowledge in any case.

bayesfunBeyond these objections is a general impression of the shoddiness of some Bayesian analyses, combined with a feeling that Bayesian methods are being oversold as an all-purpose statistical solution to genuinely hard problems. Compared to classical inference, which focuses on how to extract the information available in data, Bayesian methods seem to quickly move to elaborate computation. It does not seem like a good thing for a generation of statistics to be ignorant of experimental design and analysis of variance, instead of becoming experts on the convergence of the Gibbs sampler. In the short term this represents a dead end, and in the long term it represents a withdrawal of statisticians from the deeper questions of inference and an invitation for econometricians, computer scientists, and others to move in and fill in the gap …

Bayesian inference is a coherent mathematical theory but I don’t trust it in scientific applications. Subjective prior distributions don’t transfer well from person to person, and there’s no good objective principle for choosing a noninformative prior (even if that concept were mathematically defined, which it’s not). Where do prior distributions come from, anyway? I don’t trust them and I see no reason to recommend that other people do, just so that I can have the warm feeling of philosophical coherence …

As Brad Efron wrote in 1986, Bayesian theory requires a great deal of thought about the given situation to apply sensibly, and recommending that scientists use Bayes’ theorem is like giving the neighborhood kids the key to your F-16 …

Economics education — teaching cohorts after cohorts of students useless theories

15 February, 2018 at 20:17 | Posted in Economics | 3 Comments

Nowadays there is almost no place whatsoever in economics education for courses in the history of economic thought and economic methodology.

This is deeply worrying.

A science that doesn’t self-reflect and asks important methodological and science-theoretical questions about the own activity, is a science in dire straits.

How did we end up in this sad state?

Philip Mirowski gives the following answer:

phil After a brief flirtation in the 1960s and 1970s, the grandees of the economics profession took it upon themselves to express openly their disdain and revulsion for the types of self-reflection practiced by ‘methodologists’ and historians of economics, and to go out of their way to prevent those so inclined from occupying any tenured foothold in reputable economics departments. It was perhaps no coincidence that history and philosophy were the areas where one found the greatest concentrations of skeptics concerning the shape and substance of the post-war American economic orthodoxy. High-ranking economics journals, such as the American Economic Review, the Quarterly Journal of Economics and the Journal of Political Economy, declared that they would cease publication of any articles whatsoever in the area, after a prior history of acceptance.

Once this policy was put in place, and then algorithmic journal rankings were used to deny hiring and promotion at the commanding heights of economics to those with methodological leanings. Consequently, the grey-beards summarily expelled both philosophy and history from the graduate economics curriculum; and then, they chased it out of the undergraduate curriculum as well. This latter exile was the bitterest, if only because many undergraduates often want to ask why the profession believes what it does, and hear others debate the answers, since their own allegiances are still in the process of being formed. The rationale tendered to repress this demand was that the students needed still more mathematics preparation, more statistics and more tutelage in ‘theory’, which meant in practice a boot camp regimen consisting of endless working of problem sets, problem sets and more problem sets, until the poor tyros were so dizzy they did not have the spunk left to interrogate the masses of journal articles they had struggled to absorb.

Methodology is about how we do economics, how we evaluate theories, models and arguments. To know and think about methodology is important for every economist. Without methodological awareness it’s really impossible to understand what you are doing and why you’re doing it. Dismissing methodology is dismissing a necessary and vital part of science.

Already back in 1991, a commission chaired by Anne Krueger and including people like Kenneth Arrow, Edward Leamer, and Joseph Stiglitz, reported from own experience “that it is an underemphasis on the ‘linkages’ between tools, both theory and econometrics, and ‘real world problems’ that is the weakness of graduate education in economics,” and that both students and faculty sensed “the absence of facts, institutional information, data, real-world issues, applications, and policy problems.” And in conclusion, they wrote that “graduate programs may be turning out a generation with too many idiot savants skilled in technique but innocent of real economic issues.”

Not much is different today. Economics — and economics education — is still in dire need of a remake.

Twenty-five years ago, Phil Mirowski was invited to give a speech on themes from his book More Heat than Light at my economics department in Lund, Sweden. All the mainstream neoclassical professors were there. Their theories were totally mangled and no one — absolutely no one — had anything to say even remotely reminiscent of a defence. Being at a nonplus, one of them, in total desperation, finally asked: “But what shall we do then?”

rethinkYes indeed — what shall they do when their emperor has turned out to be naked?

More and more young economics students want to see a real change in economics and the way it’s taught. They want something other than the same old mainstream neoclassical catechism. They don’t want to be force-fed with useless mainstream neoclassical theories and models.

Ask the mountains

14 February, 2018 at 08:47 | Posted in Economics, Varia | Leave a comment

 

How central banks create money

12 February, 2018 at 11:10 | Posted in Economics | 5 Comments

shake the money tree
Have you ever asked yourself how central banks create money? BBC Radio gives the answer.

New Classical macroeconomists — people having their heads fuddled with nonsense

11 February, 2018 at 11:10 | Posted in Economics | 3 Comments

McNees documented the radical break between the 1960s and 1970s. The question is: what are the possible responses that economists and economics can make to those events?

robert_solow4One possible response is that of Professors Lucas and Sargent. They describe what happened in the 1970s in a very strong way with a polemical vocabulary reminiscent of Spiro Agnew. Let me quote some phrases that I culled from the paper: “wildly incorrect,” “fundamentally flawed,” “wreckage,” “failure,” “fatal,” “of no value,” “dire implications,” “failure on a grand scale,” spectacular recent failure,” “no hope” … I think that Professors Lucas and Sargent really seem to be serious in what they say, and in turn they have a proposal for constructive research that I find hard to talk about sympathetically. They call it equilibrium business cycle theory, and they say very firmly that it is based on two terribly important postulates — optimizing behavior and perpetual market clearing. When you read closely, they seem to regard the postulate of optimizing behavior as self-evident and the postulate of market-clearing behavior as essentially meaningless. I think they are too optimistic, since the one that they think is self-evident I regard as meaningless and the one that they think is meaningless, I regard as false. The assumption that everyone optimizes implies only weak and uninteresting consistency conditions on their behavior. Anything useful has to come from knowing what they optimize, and what constraints they perceive. Lucas and Sargent’s casual assumptions have no special claim to attention …

It is plain as the nose on my face that the labor market and many markets for produced goods do not clear in any meaningful sense. Professors Lucas and Sargent say after all there is no evidence that labor markets do not clear, just the unemployment survey. That seems to me to be evidence. Suppose an unemployed worker says to you “Yes, I would be glad to take a job like the one I have already proved I can do because I had it six months ago or three or four months ago. And I will be glad to work at exactly the same wage that is being paid to those exactly like myself who used to be working at that job and happen to be lucky enough still to be working at it.” Then I’m inclined to label that a case of excess supply of labor and I’m not inclined to make up an elaborate story of search or misinformation or anything of the sort. By the way I find the misinformation story another gross implausibility. I would like to see direct evidence that the unemployed are more misinformed than the employed, as I presume would have to be the case if everybody is on his or her supply curve of employment. Similarly, if the Chrysler Motor Corporation tells me that it would be happy to make and sell 1000 more automobiles this week at the going price if only it could find buyers for them, I am inclined to believe they are telling me that price exceeds marginal cost, or even that marginal revenue exceeds marginal cost, and regard that as a case of excess supply of automobiles. Now you could ask, why do not prices and wages erode and crumble under those circumstances? Why doesn’t the unemployed worker who told me “Yes, I would like to work, at the going wage, at the old job that my brother-in-law or my brother-in-law’s brother-in-law is still holding”, why doesn’t that person offer to work at that job for less? Indeed why doesn’t the employer try to encourage wage reduction? That doesn’t happen either. Why does the Chrysler Corporation not cut the price? Those are questions that I think an adult person might spend a lifetime studying. They are important and serious questions, but the notion that the excess supply is not there strikes me as utterly implausible.

Robert Solow

No unnecessary beating around the bush here.

The always eminently quotable Solow says it all.

The purported strength of New Classical macroeconomics is that it has firm anchorage in preference-based microeconomics, and especially the decisions taken by inter-temporal utility maximizing ‘forward-loooking’ individuals.

To some of us, however, this has come at too high a price. The almost quasi-religious insistence that macroeconomics has to have microfoundations – without ever presenting neither ontological nor epistemological justifications for this claim – has put a blind eye to the weakness of the whole enterprise of trying to depict a complex economy based on an all-embracing representative actor equipped with superhuman knowledge, forecasting abilities and forward-looking rational expectations. It is as if – after having swallowed the sour grapes of the Sonnenschein-Mantel-Debreu-theorem – these economists want to resurrect the omniscient Walrasian auctioneer in the form of all-knowing representative actors equipped with rational expectations and assumed to somehow know the true structure of our model of the world.

That anyone should take that kind of stuff seriously is totally and unbelievably ridiculous. Or as Solow has it:

4703325Suppose someone sits down where you are sitting right now and announces to me that he is Napoleon Bonaparte. The last thing I want to do with him is to get involved in a technical discussion of cavalry tactics at the battle of Austerlitz. If I do that, I’m getting tacitly drawn into the game that he is Napoleon. Now, Bob Lucas and Tom Sargent like nothing better than to get drawn into technical discussions, because then you have tacitly gone along with their fundamental assumptions; your attention is attracted away from the basic weakness of the whole story. Since I find that fundamental framework ludicrous, I respond by treating it as ludicrous – that is, by laughing at it – so as not to fall into the trap of taking it seriously and passing on to matters of technique.

Robert Solow

Economath — a device designed to fool the feebleminded

7 February, 2018 at 14:36 | Posted in Economics | 4 Comments

Many American undergraduates in Economics interested in doing a Ph.D. are surprised to learn that the first year of an Econ Ph.D. feels much more like entering a Ph.D. in solving mathematical models by hand than it does with learning economics. Typically, there is very little reading or writing involved, but loads and loads of fast algebra is required. Why is it like this?

The first reason is that mathematical models are useful …

A second beneficial reason is signalling. This reason is not to be discounted given the paramount importance of signalling in all walks of life … Smart people do math. Even smarter people do even more complicated-looking math …

ecoA third reason to use math is that it is easy to use math to trick people. Often, if you make your assumptions in plain English, they will sound ridiculous. But if you couch them in terms of equations, integrals, and matrices, they will appear more sophisticated, and the unrealism of the assumptions may not be obvious, even to people with Ph.D.’s from places like Harvard and Stanford, or to editors at top theory journals such as Econometrica. A particularly informative example is the Malthusian model proposed by Acemoglu, Johnson, and Robinson in the 2001 version of their “Reversal of Fortune” paper …

What’s interesting about the Acemoglu et al. Malthusian model is that they take the same basic assumptions, assign a particular functional form to how population growth is influenced by income, and arrive at the conclusion that population density (which is proportional to technology) will be proportional to income …

The crucial assumption, unstated in words but there in greek letters for anyone to see, was that income affects the level of population, but not the growth rate in population. Stated differently, this assumption means that a handful of individuals could and would out-reproduce the whole of China and India combined if they had the same level of income … Obviously, this is quite a ridiculous assumption when stated in plain language. A population can grow by, at most, a few percent per year. 100 people can’t have 3 million offspring. What this model does successfully is reveal how cloaking an unrealistic assumption in terms of mathematics can make said assumption very hard to detect, even by tenured economics professors at places like MIT. Math in this case is used as little more than a literary device designed to fool the feebleminded …

Given that this paper then formed part of the basis of Acemoglu’s Clark medal, I think we can safely conclude that people are very susceptible to bullshit when written in equations …

Given the importance of signaling in all walks of life, and given the power of math, not just to illuminate and to signal, but also to trick, confuse, and bewilder, it thus makes perfect sense that roughly 99% of the core training in an economics Ph.D. is in fact in math rather than economics.

Douglas L. Campbell

Indeed.

No, there is nothing wrong with mathematics per se.

No, there is nothing wrong with applying mathematics to economics.

amathMathematics is one valuable tool among other valuable tools for understanding and explaining things in economics.

What is, however, totally wrong, are the utterly simplistic beliefs that

• “math is the only valid tool”

• “math is always and everywhere self-evidently applicable”

• “math is all that really counts”

• “if it’s not in math, it’s not really economics”

• “almost everything can be adequately understood and analyzed with math”

Knut-WicksellOne must, of course, beware of expecting from this method more than it can give. Out of the crucible of calculation comes not an atom more truth than was put in. The assumptions being hypothetical, the results obviously cannot claim more than a vey limited validity. The mathematical expression ought to facilitate the argument, clarify the results, and so guard against possible faults of reasoning — that is all.

It is, by the way, evident that the economic aspects must be the determining ones everywhere: economic truth must never be sacrificed to the desire for mathematical elegance.

Neoclassical mainstream economists have wanted to use their hammer, and so have decided to pretend that the world looks like a nail. Pretending that uncertainty can be reduced to risk and that all activities, relations, processes and events can be adequately converted to pure numbers, have only contributed to making economics irrelevant and powerless when confronting real-world financial crises and economic havoc.

How do we put an end to this intellectual cataclysm? How do we re-establish credence and trust in economics as a science? Five changes are absolutely decisive.

(1) Stop pretending that we have exact and rigorous answers on everything. Because we don’t. We build models and theories and tell people that we can calculate and foresee the future. But we do this based on mathematical and statistical assumptions that often have little or nothing to do with reality. By pretending that there is no really important difference between model and reality we lull people into thinking that we have things under control. We haven’t! This false feeling of security was one of the factors that contributed to the financial crisis of 2008.

(2) Stop the childish and exaggerated belief in mathematics giving answers to important economic questions. Mathematics gives exact answers to exact questions. But the relevant and interesting questions we face in the economic realm are rarely of that kind. Questions like “Is 2 + 2 = 4?” are never posed in real economies. Instead of a fundamentally misplaced reliance on abstract mathematical-deductive-axiomatic models having anything of substance to contribute to our knowledge of real economies, it would be far better if we pursued “thicker” models and relevant empirical studies and observations.

(3) Stop pretending that there are laws in economics. There are no universal laws in economics. Economies are not like planetary systems or physics labs. The most we can aspire to in real economies is establishing possible tendencies with varying degrees of generalizability.

(4) Stop treating other social sciences as poor relations. Economics has long suffered from hubris. A more broad-minded and multifarious science would enrich today’s altogether too autistic economics.

(5) Stop building models and making forecasts of the future based on totally unreal micro-founded macromodels with intertemporally optimizing robot-like representative actors equipped with rational expectations. This is pure nonsense. We have to build our models on assumptions that are not so blatantly in contradiction to reality. Assuming that people are green and come from Mars is not a good – not even as a ‘successive approximation’ – modelling strategy.

The flawed premises of mainstream​ economic theory

5 February, 2018 at 18:44 | Posted in Economics | 3 Comments

Misbehaving.inddYou know, and I know, that we do not live in a world of Econs. We live in a world of Humans. And since most economists are also human, they also know that they do not live in a world of Econs …

Nevertheless, this model of economic behavior based on a population consisting only of Econs has flourished, raising economics to that pinnacle of influence on which it now rests. Critiques over the years have been brushed aside with a gauntlet of poor excuses and implausible alternative explanations of embarrassing empirical evidence …

It is time to stop making excuses. We need an enriched approach to doing economic research, one that acknowledges the existence and relevance of Humans. The good news is that we do not need to throw away everything we know about how economies and markets work. Theories based on the assumption that everyone is an Econ should not be discarded. They remain useful as starting points for more realistic models. And in some special circumstances, such as when the problems people have to solve are easy or when the actors in the economy have the relevant highly specialized skills, then models of Econs may provide a good approximation of what happens in the real world. But as we will see, those situations are the exception rather than the rule.

Modern economics — confusing models with reality

2 February, 2018 at 16:51 | Posted in Economics | 1 Comment

What does concern me about my discipline … is that its current core — by which I mainly mean the so-called dynamic stochastic general equilibrium approach — has become so mesmerized with its own internal logic that it has begun to confuse the precision it has achieved about its own world with the precision that it has about the real one …

While it often makes sense to assume rational expectations for a limited application to isolate a particular mechanism that is distinct from the role of expectations formation, this assumption no longer makes sense once we assemble the whole model. Agents could be fully rational with respect to their local environments and everyday activities, but they are most probably nearly clueless with respect to the statistics about which current macroeconomic models expect them to have full information and rational information.

bThis issue is not one that can be addressed by adding a parameter capturing a little bit more risk aversion about macro-economic, rather than local, phenomena. The reaction of human beings to the truly unknown is fundamentally different from the way they deal with the risks associated with a known situation and environment … In realistic, real-time settings, both economic agents and researchers have a very limited understanding of the mechanisms at work. This is an order-of-magnitude less knowledge than our core macroeconomic models currently assume, and hence it is highly likely that the optimal approximation paradigm is quite different from current workhorses, both for academic and policy​ work. In trying to add a degree of complexity to the current core models, by bringing in aspects of the periphery, we are simultaneously making the rationality assumptions behind that core approach less plausible …

The challenges are big, but macroeconomists can no longer continue playing internal games. The alternative of leaving all the important stuff to the “policy” type​ and informal commentators cannot be the right approach. I do not have the answer. But I suspect that whatever the solution ultimately is, we will accelerate our convergence to it, and reduce the damage we do along the transition, if we focus on reducing the extent of our pretense-of-knowledge syndrome.

Ricardo J. Caballero

A great article that also underlines — especially when it comes to forecasting and implementing economic policies  — that the future is inherently unknowable, and using statistics, econometrics, decision theory or game theory, does not in the least overcome this ontological fact.

It also further underlines how important it is in social sciences — and economics in particular — to incorporate Keynes’s far-reaching and incisive analysis of induction and evidential weight in his seminal A Treatise on Probability (1921).

treatprobAccording to Keynes we live in a world permeated by unmeasurable uncertainty – not quantifiable stochastic risk – which often forces us to make decisions based on anything but “rational expectations.” Keynes rather thinks that we base our expectations on the confidence or “weight” we put on different events and alternatives. To Keynes, expectations are a question of weighing probabilities by “degrees of belief,” beliefs that often have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents as modelled by “modern” social sciences. And often we “simply do not know.”

How strange that social scientists and mainstream economists, as a rule, do not even touch upon these aspects of scientific methodology that seems to be so fundamental and important for anyone trying to understand how we learn and orient ourselves in an uncertain world. An educated guess on why this is a fact would be that Keynes concepts are not possible to squeeze into a single calculable numerical “probability.” In the quest for measurable quantities one puts a blind eye to qualities and looks the other way.

So why do economists, companies and governments continue with the expensive, but obviously worthless, activity of trying to forecast/predict the future?

Some time ago yours truly was interviewed by a public radio journalist working on a series on Great Economic ThinkersWe were discussing the monumental failures of the predictions-and-forecasts-business. But — the journalist asked — if these cocksure economists with their “rigorous” and “precise” mathematical-statistical-econometric models are so wrong again and again — why do they persist wasting time on it?

In a discussion on uncertainty and the hopelessness of accurately modelling what will happen in the real world — in M. Szenberg’s Eminent Economists: Their Life Philosophies — Nobel laureate Kenneth Arrow comes up with what is probably the most plausible reason:

It is my view that most individuals underestimate the uncertainty of the world. This is almost as true of economists and other specialists as it is of the lay public. To me our knowledge of the way things work, in society or in nature, comes trailing clouds of vagueness … Experience during World War II as a weather forecaster added the news that the natural world as also unpredictable. cloudsAn incident illustrates both uncer-tainty and the unwilling-ness to entertain it. Some of my colleagues had the responsi-bility of preparing long-range weather forecasts, i.e., for the following month. The statisticians among us subjected these forecasts to verification and found they differed in no way from chance. The forecasters themselves were convinced and requested that the forecasts be discontinued. The reply read approximately like this: ‘The Commanding General is well aware that the forecasts are no good. However, he needs them for planning purposes.’

Economics’ pretence of knowledge

1 February, 2018 at 19:08 | Posted in Economics | Leave a comment

hayek_coloresWhile in the physical sciences the investigator will be able to measure what, on the basis of a prima facie theory, he thinks important, in the social sciences often is treated as important that which happens to be accessible to measurement. This is sometimes carried to the point where it is demanded that our theories must be formulated in such terms that they refer only to measurable magnitudes. It can hardly be denied that such a demand quite arbitrarily limits the facts which are to be admitted as possible causes of the events which occur in the real world.

Friedrich Hayek

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