Endless regress

My estimable co-blogger Delusional Economics showed he was anything but delusional with his penetrating commentary on economics as an ideology (Economic Ideologies). It is a point made all too rarely. That economics purports to be an unbiased way of understanding financial and commercial behaviour when it is in fact riven with political assumptions and beliefs. It is a “discipline” concerned with human behaviour and so political biases are, in some form, inevitable. These extend far beyond the obvious materialism of economics: the belief, and it is a belief, that something is only real if a transaction occurs. For instance, economic ideologies contain implicit assumptions about work place value: capital’s value versus labour’s value, that are a priori (before the fact). Such values are political in nature, and there are many of them. I do differ from Delusional, however, in one respect. He states the often held view that the incompleteness and shortcomings of economics might one day be fixed if only computational power can be improved, or the ideas can be sharpened up.

He says this:

But economics is not a science no matter how much it tries to be. It is a fascinating and somewhat frustrated mix of mathematics, psychology, culture, astrophysics, chaos theory and random number generation.

Which is true. But then he says this:

Maybe one day, somewhat like the weather, we will have the computational processing power to be able to build models of this system, but until we do we are all just weathermen watching the clouds and claiming we can predict rain.

For me personally one of the most interesting things about economics, like any complex system where the basis of truth is misunderstood and/or unknown are the ideologies that grow around it. Somewhat like religion we have people who have very strong beliefs about how the system supposedly works. Yet the reality is that no one really understands everything. This is one of the major reasons I was attracted to this field.

Which is not true.

Economic behaviour will never be like the weather. No matter how great processing power becomes, it will never be enough to achieve predictive validity. No human being will ever be able to pick himself off the ground by pulling on his or her shoelaces, no matter how hard they yank. It is a simple category mistake to think so.

Why? Because human beings are not just observable phenomena. They think, and they know things. And they can think about economic theories; they can know what they are. Such knowledge and thinking cannot be included in the theory, because it happens after the theory has been formulated. So even if a theory is compelling, traders will start to exploit it for gain by taking positions against it. At which point the theory will fail. Exhilarating as it is to chase one’s tail, one never goes anywhere.

This much any decent philosopher could tell you (especially if they are fond of the nineteenth century idealists). But here is where I get somewhat frustrated. A question I think is important is not asked. If economics is not a science, and it does not meet the basic conditions of a science, then what is it? Surely the answer has to be: a specialised language. A way of talking about the world, especially of transactions, that has the strengths and weaknesses of technical languages. It allow you to track things, to know what is happening. It enables one to “talk about it”, as it were. But languages contain all sorts of assumptions and biases that the truly educated understand when they use them. So one learns to “talk about talking about” as it were.

Here is an example of what I mean with share trading. A report on the theories of trading in the Australian market by the Royal Bank of Scotland:

Pure value

Simple value metrics do not perform well in growth markets such as Australia because they tend to bet against growth and price momentum. Back-test performance is considerably improved when we remove this bias with regression analysis.

Dynamic investing adds value

Individual valuation ratios such as earnings yield, dividend yield, etc, can go in and out of favour, but value investing overall continues to deliver as a sensible strategy. We believe a dynamic combination of valuation ratios can provide more consistent outperformance.

Avoiding the value trap

A value trap is a stock that’s been beaten down in price to the point where it starts looking like a bargain, only to become even cheaper and/or remain stagnant for a long period of time. Our analysis shows that – on average – it is beneficial to wait for such a stock to first stabilise before investing.

Better value

Recent academic studies show that the success of value investing is related to firm-level investment activities rather than financial distress risk. We show that value stocks outperform more strongly when they have high operational leverage, while those in financial distress are usually poor investments.

The report is worth reading, it is below. Now let’s examine the assumptions in this language. One is that the past is a good predictor of the future. Maybe, probably not. Another is that “value” is static, and there is something that contrasts with it that is “dynamic” (i.e. presumably not static). A questionable distinction, although the fact that many traders are using such a distinction might make it useful. Another assumption is that share market sentiment can be observed as phenomena and understood using things like pattern recognition. Again, questionable. Empathy with crowd behaviour might be a better approach.

By looking at the language it is usually possible to predict how people will behave when they all use the same language and assumptions. When everyone speaks econo-speak, they will tend to develop similar behaviours because language does predicate behaviour. The same for share market traders who use “fundamental” analyses, for instance. By looking at the language, it is possible to get some sense of that. But who treats it as language? Instead, it is treated as flawed science. It is not flawed science, it is non-science.

RBS

Comments

  1. Deus Forex Machina

    An excellent piece…fwiw, I reckon economics is either a pseudo-science or Nomenclature…I have found the most useful insights that I have gained in my career to have been from the ancient fathers of economics none of whom held an economics degree as far as I know and also from Daniel Kahneman and Amos Tversky work.
    The character of both these sets of “teachers” for me is that they are observerers of behaviour and then translate that observation into a theory or behavioural expectation.
    They do/did not, as economists tend to do, assume a closed system with rational actors so that they can solve their scientific equations and earn their Phd’s in Economics or Finance.
    Indeed Justin Fox in his book “The Myth of the Rational Market”, quotes Harry Markowitz (one of the fathers of modern day finance for his work on portfolio allocation under uncertainty) and his response to academic students and the markets interpretation of his work. Markowitz said “People just didn’t read my book”.
    When the gods of economics come down from their posts and start walking among the people we might get better outcomes.
    Thanks again SoN…one of my favourite topics

    • DFM

      By coincidence watched an interesting discussion between Daniel Kahneman and Nicholas Nassim Taleb just yesterday. Here’s the link, if interested:
      http://www.edge.org/3rd_culture/kahneman_taleb_DLD09/kahneman_taleb_DLD09_index.html
      And even more extraordinarily, this with breakfast today!
      http://www.ted.com/talks/daniel_kahneman_the_riddle_of_experience_vs_memory.html

      For a psychologist, he’s not too bad! Admired by Taleb. My only concern is that psychology suffers problems similar to economics – the endless quest to become a ‘real’ science by modelling, charts and stats, stats, stats. He has attempted to combine the two – and provide a greater insight into the nature of the ‘human’ in economics.

      • Deus Forex Machina

        Brilliant thanks very much…i’m not overly familiar with the scientific pretensions of psychology (althought the odd pyschiatrist is always horrified if I call them a psychologist, which is always fun – 🙂 )
        But i do know that the theories that these guys have come up with have often been tested in experiments and Kahneman and Vernon Smith, who is a very rare breed of economist in that he conducts “actual” experiments, won the Nobel Prize for economics a few years back.
        Personally I know from my own experience I know that I have benefitted greatly from their insights.
        cheers…DFM

  2. yet it is interesting how the title of ‘economist’ seems to garner alot of respect (even followings) among the general public – and especially the investor public. As if whatever forecasts they utter are good enough to bet your house on. No wonder the banking sector now uses their ‘econonmists’ at the frontlines of their PR machine. Was a time when banking economists were kept in rooms out the back compiling reports for their institutions. Now they go on spruiker roadshows and head up MSM articles because they are Economists (more often with doctorates) and therefore a gold standard.

  3. My favorite article of the week. Excellent. Thought-provoking and what’s more, true. I think I fall into the camp of a language – with many dialects! Thanks.

    I linked to this previously, but here’s a sweetener:

    Physics Envy and the Abandonment of Common Sense

    It has been said that economists suffer from ‘physics envy’, and we get confirmation of this truism nearly every day (see e.g. our brief critique of the approach taken by Alan Blinder to justify Big Government). Modern macro-economics has been invaded by mathematical modeling and subjected to the very ‘scientist approach’ that Friedrich Hayek warned about in his famous Nobel lecture on the ‘Pretence of Knowledge’. One would think that if economics could really be improved by attempting to press the complex gestalt of millions, even billions, of individual human economic actors into a system of mathematical equations, there would soon be agreement on what it all means.

    Alas, modern day econometricians squabble even more over economic policy prescriptions than theoretical physicists do over how to best arrive at the GUT (the ‘grand unified theory’). We find it notable that one of the greatest books on economics ever written, Ludwig von Mises’ ‘Human Action’, appears to be able to make do without a single mathematical equation (if you want to be picky, there are a few passages where von Mises elucidates concepts by using place-holders, as for example in the chapter on capital goods, where he writes: ‘We may call p the total supply of capital goods available on the eve of the credit expansion, and g the total amount of consumers’ goods which these p could, over a definite period of time, make available for consumption without prejudice to further production.’…and so forth. Alas, that is how far as it goes). The point we want to make is merely that in their urge to make the social science of economics more ‘scientific’, to bring it closer to the natural sciences and their ‘hard truths’ by adopting mathematical modeling, many economists have ceased to see the forest for the trees.

    Consider for instance the fact that a large percentage of today’s preeminent economists failed to predict an economic crisis that anyone with a smattering of common sense could detect well in advance. Surely this serves as proof for how useless all their ‘modeling’ really is when it comes to real life. In this context, note the comments made by Wharton professors Franklin Allen and Sidney Winter on this topic after the crisis had arrived:”

    To continue, follow the link:
    “http://www.acting-man.com/?p=4741

    • “Science is the belief in the ignorance of experts” – Richard Feynman, Nobel prize-winning *physicist*.

  4. Deus,

    “The character of both these sets of “teachers” for me is that they are observerers of behaviour and then translate that observation into a theory or behavioural expectation.”

    Observe. Translate observation into (testable) theory.

    Sounds just like what *used to be* the definition of the Scientific Method 😉

  5. Thank you so much for your thoughts SoN.

    One of my favorite articles on the subject of economic science is: “The Autistic Economist” written by Stanley Alcorn and Ben Solarz (Yale Univeristy, USA)

    Quote:
    ‘How many economists does it take to change a lightbulb?

    * Two: One to change the bulb and one to assume the existence of a ladder.
    * Eight: One to screw in the light bulb and seven to hold everything else constant.
    * None: They are all waiting for an invisible hand.

    The caricature of the economist – bumbling, impractical, disconnected from the object of his work – underpins a set of surprisingly sophisticated criticisms leveled against the discipline, particularly its realism, method, and ideology. None of these critiques is particularly new, nor is any entirely unique to economics. But over the last few years, they have been asserted against the dominant economic pedagogy in general and the neoclassical framework in particular with new force – a force strong enough to be labeled a movement. An amalgamation of unorthodox academics, discontented students, and skeptical non-economists, this movement may not always be unified in its diagnosis, but is certainly unified in their discontent. If only because one of the many criticisms is of the discipline’s aloofness, the jokes as well as the criticisms should be heard.

    “We wish to escape from imaginary worlds!” proclaimed a group of French economics students in 2000, petitioning for broad changes in their economics curricula. “We no longer want to have this autistic science imposed upon us.”

    http://www.paecon.net/PAEReview/issue38/AlcornSolarz38.htm

  6. One of my favourite topics as well (along with behavioural economics). The best paper I’ve seen on the topic is from MIT’s Andrew Lo “WARNING: Physics Envy May Be Hazardous To Your Wealth!” (a bit of math involved but nothing heavy duty, and he also introduces an interesting taxonomy of “uncertainty” as a way of thinkng about risk). There’s also an online lecture he gave on the topic, on the MIT website. This is a topic worth spending a bit of time on for any serious investor….links below:

    http://www.scribd.com/doc/31402372/Physics-Envy

    mitworld.mit.edu/video/794

    And, IMHO, the last word on why we’ll never be able to model economics goes to Jim Grant (of Grant’s Interest Rate Observer)…”Progress is cumulative is science and engineering but cyclical in finance

    Cheers
    JM

  7. Ties in with personal observation: Before I left the uk, it was the case that id you were doing a B.A. (Econ.) you were regarded as a bit of a demi-god, whereas if you were doing a B.Sc. in Mathematics – even Applied Mathematics, you were reagarded as “a bit of a nutter”.

    Obviously as the general population are now finding out the hard way (lost investment opportunity), image is not always everything . . . .

  8. I think the realization made regarding Chaos Theory and trying to predict the weather (i.e. significantly increased computational power will not help you predict future outcomes) may equally well apply to economics. The following info, taken from mises.org explains it better than I ever could.

    Two decades ago, Edward Lorenz, a meteorologist at MIT stumbled onto chaos theory by making the discovery that ever so tiny changes in climate could bring about enormous and volatile changes in weather. Calling it the Butterfly Effect, he pointed out that if a butterfly flapped its wings in Brazil, it could well produce a tornado in Texas.

    Since then, the discovery that small, unpredictable causes could have dramatic and turbulent effects has been expanded into other, seemingly unconnected, realms of science.

    The conclusion, for the weather and for many other aspects of the world, is that the weather, in principle, cannot be predicted successfully, no matter how much data is accumulated for our computers. This is not really “chaos” since the Butterfly Effect does have its own causal patterns, albeit very complex. (Many of these causal patterns follow what is known as “Feigenbaum’s Number.”)

    ….

    Chaos theory is even more challenging when applied to human events such as the workings of the stock market. Here the chaos theorists have directly challenged orthodox neoclassical theory of the stock market, which assumes that the expectations of the market are “rational,” that is, are omniscient about the future. If all stock or commodity market prices perfectly discount and incorporate perfect knowledge of the future, then the patterns of stock market prices must be purely accidental, meaningless, and random (“random walk”), since all the underlying basic knowledge is already known and incorporated into the price.

    The absurdity of believing that the market is omniscient about the future, or that it has perfect knowledge of all “probability distributions” of the future, is matched by the equal folly of assuming that all happenings on the real stock market are “random,” that is, that no one stock price is related to any other price, past or future. And yet a crucial fact of human history is that all historical events are interconnected, that cause and effect patterns permeate human events, that very little is homogeneous, and that nothing is random.

    With their enormous prestige, the chaos theorists have done important work in denouncing these assumptions, and in rebuking any attempt to abstract statistically from the actual concrete events of the real world. Thus, the chaos theorists are opposed to the common statistical technique of “smoothing out” the data by taking twelve-month moving averages of monthly data-whether of prices, production, or employment. In attempting to eliminate jagged “random elements” and separate them out from alleged underlying patterns, orthodox statisticians have been unwittingly getting rid of the very real-world data that need to be examined.

    • Chaos theory has little application to markets. The reflexive involvement of market participants is makes them unstable, and they lack the deterministic dynamics that would be necessary for chaos theory be relevant.

      For some good background on what chaos theory is – and, more importantly, is not – I recommend Stephen Kellert’s _In the Wake of Chaos_. See my review at http://dannyreviews.com/h/Wake_of_Chaos.html

  9. I can understand the approach Delusional was taking with weatherman approach.
    Do you take an umbrella to work in the morning based on what the weatherman indicates? Again would you choose to alter monetary policy when the economy is indicating stress?
    As with the weather, and in economics, time seems to be the most important variable, are we talking about 2 days or 2 years…..I know which one I would rather try to predict….

  10. Good stuff – the oft-neglected field of ‘meta-economics’… For those who haven’t, a reading of 19th century philosopher Leo Strauss is a must in looking deeper into this area of thought (particularly the rejection of the fact/value distinction). Many mainstream economics departments at universities across the english-speaking world are mistaken in their dogmatic belief in ‘economics-as-science’ (and I’ve been involved with a few of them as both a student and a staff member).

  11. Just catching up with this discussion.

    I have been examining neoclassical economics from the point of view of a scientist (me). The answer is very clear – it is pseudo-science. It is built on patently absurd assumptions, such as that we can all predict the future, there are no economies of scale, there are no fashions, we are all rational, and so on. The big trouble is not just that these assumptions are ridiculous, but that if you change any one of them, your prediction shifts from a lovely steady General Equilibrium to a system full of instabilities – a self-organising system that manifests complexity, if not chaos. The real-world economy looks much more like an erratic complex system than a general equilibrium to me, especially during the not-infrequent market crashes.

    Neoclassical economists also have a century-long confusion that because they use fancy mathematics they are doing science. But real scientists not infrequently use very simple estimates. They are not interested in the mathematical tools used, they want to know if the theory’s implications (“predictions”) fit what we can observe. The objective is a theory that is a useful guide to what we can observe. Economists forgot the bit about comparing with observations, so they’ve been stuck in mathematical wanking for a century or so.

    You can see more of this on my blog Better Nature http://betternature.wordpress.com/. In particular, Neoliberal Pseudo-Science http://betternature.wordpress.com/2009/03/13/ neoliberal-pseudo-science/ or The Nature of the Beast http://betternature.wordpress.com/2010/07/28/nature-of-the-beast/. Also my book from 2004: Economia.

    Much of the interest on this site is of course in financial market behaviour, and SoN’s comments about constant adaptation of behaviour are very pertinent. Sounds like Danny Yee might be the reigning expert here so far on chaos, or not. However the larger economy can probably be regarded as a complex system, not so erratic as a chaotic system, but still unpredictable in detail.

    In any case SoN’s comments about economics not being science are spot on, as are DE’s comments about the highly selective vision of many mainstream economists.

  12. The ability of humans to be Creative (out of nothing) and to Choose screws up Economics (and other human-mind dependent systems) from qualifying as empirical science.

    They (incl Economics) have elements in common with the empirical/operational sciences, such that elements can be analogously modelled accordingly, with sufficiently simplifying and limited axioms/presuppositions; but they are not Sciences.

    Not that even the hard sciences can escape Philosophical assumptions/axioms (they can’t, and no human intellectual consideration can, i’m afraid!), but at least they don’t have to deal with human Choice actually being a part of the very system they are trying to describe!

    As a scientist, engineer and Philosopher of Science, I truly do feel sorry for Economists!!

    • PS…Economics (etc), as described in my above post, are, IMHO, better understood as complex moral systems.

      As I like to say: “From Values comes value”…

      …and Economics is the study of how value is expressed in its many forms – but the roots are in Values (which have their roots in “Worldviews”…but that is another discussion!)

  13. Timely article. But I’m bothered by the argument that Economics can never be a Science. That position justifies sloppy thinking, the application of unproven hypotheses, etc., etc.

    As the GFC illustrated, we HAVE to do better than that.

    There are many aspects of science that deal with statistical systems, uncertainty and even chaos, and are able to produce valid, useful results. The trick seems to be not just knowing what you don’t know, but knowing how to work around what you don’t know.

    And I appreciate I am asking an awful lot from s “discipline” that doesn’t yet know what it doesn’t know.

  14. As a science, one of the big problems with physics is that it models time intuitively, not physically. The present doesn’t move along an external vector from past to future. It is the changing configuration of what exists that turns future into past. The earth doesn’t travel the fourth dimension from yesterday to tomorrow. Tomorrow becomes yesterday because the earth rotates. Time is an effect of motion, not the geometric basis for it. That makes time(rate of change) more like temperature(level of activity) than space.
    It is the collapse of probabilities(future) that results in actualities(present). The past is deterministic, because all input is calculated by the occurrence of the event, while the future is indeterministic, since the cone of potential input does not exist prior to the event. All input may be approaching the point of occurrence, but it is only at the point of occurrence that it is fully implemented and calculated. Otherwise you end up with multiworlds, as you try to push a deterministic past onto an indeterministic future. As both are true, the only option is to overlay them and you have a cat that is both alive and dead.

    The main problem with economics is that we treat currency as a commodity, when it is a contract. While a debt based currency made sense when there were few economic statistics to determine how much was necessary, it also has its serious side-effects. Since the supply of wealth able to be stored is determined by the demand for debt, there is pressure to create as much debt as possible. Unfortunately those with the supply of wealth have political leverage over those seeking to borrow it and use this to drain value into their pockets. The problem is that while the lenders are the fuel tank of the economy, the borrowers are the engine. As my father used to say, “You can’t starve a profit.” Those with the capital eventually find there are no productive investments left and all they can do is speculate as to where the next bubble with blow up.
    Paul Volcker didn’t cure inflation by raising interest rates, because you don’t cure an oversupply by rewarding supply and damaging demand. Inflation was cured by increased Federal debt. The Treasury can issue far more fresh debt than the Federal Reserve can sell old debt and then use it to prop up the private sector, further increasing demand for capital. That trick is not available this time.
    If we start treating money as the public utility it has become, given the extent to which taxpayers support its value, there will be reluctance to convert any and all intangible wealth into currency, so that people will invest more in their environment and social networks, which would result in a less atomized society and healthier environment.
    There was a time when politics was private, but when monarchs lost sight of their larger social functions and became obsessively self centered, they were replaced by public political systems. Private banking has reached that same inflection point. A market needs a medium of exchange. When that medium is privately held, then the rest of the market is subservient to that private party.
    Politics is like the central nervous system of society, while banking is its economic circulatory system. With plants the nervous system and circulatory system are essentially the same, but with complex fauna, they are separate. I think a successful social and economic structure can have semi-distinct public governance and banking systems. Just as democracy functions by devolving power down to the level it is most effective and responsive, so to would a public banking system have to have an equally solid foundation of local banks that funded public services from profit generated within the community. The regional and national networks would grow out of this, until it is both globalized and decentralized. With the obvious understanding that value has to be effectively recycled back into sustainable environments, not drained away to form huge storm clouds of surplus wealth, hanging over an otherwise parched economy and degraded society and environment.

  15. John M, A very stimulating response, I shall think on it. My view is that physics measures time as space because it can’t deal with time — as time. This is in part because of science’s methodology and assumptions. A law of science can’t work at one time and not another (assumption). Experimentation is repeated many times to prove that time can be eliminated as a problem, that the claim is timeless (methodology). Ergo, time must be pushed to the side. Will be following up on Geoff D’s comments, too.

    • s.o.n,
      Thank you for the considerate and considered response. Suffice to say that when I raise this issue on physics forums, the responses are generally negative, as it does raise serious questions with many of the current models.
      The fact though, is that it goes much deeper than that. The basis of rationality is the linear cause and effect narrative, from the times we were sitting around the campfire, telling stories of the day’s hunt. Consider the extent to which civil movements, from religions to nations, build their foundation on a collective narrative.
      Both directions, the present moving from past to future and future potential collapsing into past effect, are valid in their own context. Much as we now know it’s the earth rotating west to east, rather than the sun actually moving across the heavens from east to west, we still see it as the sun moving.
      Since your perspective is one of business, one way to consider this relationship is of a factory. While the products go from initiation to completion, the process, the production line, goes the other direction, consuming raw material and expelling finished product. So as the particular products go from being in the future to being in the past, the process moves toward the future, expelling the past.
      If we compare this to an analog clock, the hand(s) represent the present, while the face represents events. Since clocks evolved from sundials, we naturally have the hands moving, much as the sun moves, but the present is the constant, so it’s actually the events going future to past. If we had a clock to represent this, the hands would be still and the face would rotate.
      Our brain operates in this manner as well. The thoughts being the products that coalesce out of the future and fade into the past, as the mind moves onto the next. It should be noted that the left, linear side of the brain is a clock, that registers sequence, while the right, intuitive side is a thermostat, that measures and responds to non-linear variations in energy. E.O.Wilson described the insect brain as a thermostat, but it has been shown that they are able to count steps as a function of navigation, as well. Essentially our right brains process context, while our left brain navigates direction. Scientists, being extremely rational, value time over temperature.
      Our lives as well move from being in the future to being in the past, as life moves onto the next generation.
      The question then, is how does one use this relationship to predict the future?
      What these two directions represent are energy and information. This eternal constant of the present is energy. The forms it manifests and which define it are information. Old information is erased by the creation of new information. “You can’t have your cake and eat it too.”
      So what defines the future is where the energy goes, when those probabilities collapse. Old forms can continue to grow and prosper, as long as they can absorb more energy than they loose. This places them within the parameters of being too rigid to absorb new energy and the dislocations required and being so flexible that new input breaks them apart. When they cannot absorb fresh energy, it builds up outside of them and the future becomes a reaction to the past, rather than a continuation of it. We seem to be approaching one of those points on a world wide scale.
      What will emerge from this collapse of the old system will have to be one that can more efficiently manage the energies of the people and resources. Those who simply hope to hold on to what they have, will have to contend with a tidal wave of change. It is best to be riding that wave, than be in front of it, because the world is about to be turned upside down and inside out.
      Rather than being one narrative, reality is a tapestry of poly-narrative and this intermingling is how we emerge as one larger system, not by having everyone marching in the same direction.
      “For every action, there is an equal and opposite reaction.” To this I would add that the action is linear, but the reaction is non-linear. So while our actions might get us quite far, we have to take into account the reaction, or it overwhelms us.
      Hope this helps some.
      Regards,
      JBMJr.

  16. Some of the discussion of science seems to require science to make detailed, accurate predictions. Anything else, by implication, would then not be science. I think this is much too narrow a view of science.

    Science, most broadly, seeks to create descriptions of the world that are useful guides to how the world works.

    Such a description might be highly accurate, or it might be a rough back-of-the-envelope estimate. The latter can still (sometimes) be very useful.

    Such a description might be statistical, but it can still be very useful.

    Such a description might even be qualitative, and still be very useful. For example “an economy is a far-from-equilibrium complex self-organising system, not a near-equlibrium system. This can lead us to abandon equilibrium-based tools like neoclassical models. It can lead us to stop trying to predict details and to start looking at the general character of the system’s behaviour. It can lead us to look for key internal feedbacks that govern the system’s self-organisation.

    In this sense, there certainly can be a science of economies. Neoclassical economics is not that science, and not a science at all. It is a pre-scientific amalgam of beliefs that is patently not a useful description of economies.

    • Good summation Geoff.
      Steve Keen’s “Debunking Economics” is coming out later this year in a second edition. As its subtitle suggests “the Naked Emperor of the Social Sciences” he goes into the scientific reasons why the neoclassical synthesis is not a science at all, but a dogmatic belief system.
      He also has a good review of the other “schools” (e.g Austrian, Post-Keynesian) and quite rightly shows their flaws as well.

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