Rethinking economics

15 Nov, 2021 at 17:53 | Posted in Economics | 7 Comments

marquesThe incorporation of new information makes sense only if the future is to be similar to the past. Any kind of empirical test, whatever form it adopts, will not make sense, however, if the world is uncertain because in such a world induction does not work. Past experience is not a useful guide to guess the future in these conditions (it only serves when the future, somehow, is already implicit in the present) … I believe the only way to use past experience is to assume that the world is repetitive. In a non-repetitive world in which relevant novelties unexpectedly arise testing is irrelevant …

Conceiving economic processes like sequences of events in which uncertainty reigns, where consequently there are “no laws”, nor “invariants” or “mechanisms” to discover, the kind of learning that experiments or last experience provide is of no use for the future, because it eliminates innovation and creativity and does not take into account the arboreal character and the open-ended nature of the economic process … However, as said before, we can gather precise information, restricted in space and time (data). But, what is the purpose of obtaining this sort of information if uncertainty about future events prevails? … The problem is that taking uncertainty seriously puts in question the relevance the data obtained by means of testing or experimentation has for future situations.

Marqués’ book is a serious challenge to much of mainstream economic thinking and its methodological and philosophical underpinnings. A must-read for anyone interested in the foundations of economic theory, showing how far-reaching the effects of taking Keynes’ concept of genuine uncertainty really are.

treatprobScience according to Keynes should help us penetrate to “the true process of causation lying behind current events” and disclose “the causal forces behind the apparent facts.” Models can never be more than a starting point in that endeavour. He further argued that it was inadmissible to project history on the future. Consequently, we cannot presuppose that what has worked before, will continue to do so in the future. That statistical models can get hold of correlations between different ‘variables’ is not enough. If they cannot help us get at the causal structure that generated the data, they are not really ‘identified.’

How strange then that economics textbooks 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 quantities one puts a blind eye to qualities and looks the other way and hopempeople will forget about Keynes’ fundamental insight

Robert Lucas once wrote — in Studies in Business-Cycle Theory — that “in cases of uncertainty, economic reasoning will be of no value.”  Now, if that was true, it would put us in a tough dilemma. If we have to consider — as Lucas — uncertainty incompatible with economics being a science, and we actually know for sure that there are several and deeply important situations in real-world contexts where we — both epistemologically and ontologically — face genuine uncertainty, well, then we actually would have to choose between reality and science.

That can’t be right. We all know we do not know very much about the future. We all know the future harbours lots of unknown unknowns. Those are ontological facts we just have to accept — and still go for both reality and science, in developing a realist and relevant economic science.

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  1. 《landing a rocket on a fast-moving asteroid for instance》
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    If you try to use the same physics model to send a probe to another star, will you have to posit an ether-like dark matter?
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    《So how/where does economics proceed?》
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    Stop prescribing tight money to treat inflation (first, do no harm)?
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    《we can gather precise information, restricted in space and time (data)》
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    How precise is that data? Is GDP half imputed, and are standard errors for the surveys that comprise the other half simply thrown out? How can you measure “Investment”, when so much of the data is private? Did Keynes know that there are lies, damned lies, and statistics?
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    《a realist and relevant economic science.》
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    Why should output and employment be goals when their assumed benefits are so uncertain and non-ergodic?

    • GDP has no vectors so what are you banging on about …

      • Would a different wage survey sample result in a different GDP estimate? Isn’t that uncertainty what standard error attempts to capture? Why throw away the standard errors in the surveys used to compile GDP? Is this an “emperor’s new clothes” type of no-brainer?

        • We’re right back to the reoccurring problem with models experiencing the human tool user problem e.g. the original model of GDP was authored as a stand alone curiosity, which might be used with others in providing a perspective of how the economy was functioning, but it was never intend to become the carrot others decided it to be. In fact the original author was adamant that this was a bastardization of its intended purpose – are you starting to see a trend here – historically I mean. Worse still it can be used not unlike the maths Nash, McNamara, Newman, used for policy formation and its endless failures.

          .

          Bit like the old joke that “friends don’t let friends use built in Excel functions for policy formation”. I question the functionality of such devices in delving into the more complex human condition in whether or not society is in good or bad health. I think its reasonable to look at say the private health system in the U.S. and its currant issues with dealing with Covid or its ability to compile facts and then disseminate them due to incentives which are contra to this occurring.

  2. Prof.Syll somehow concludes that “we just have … go for both reality and science, in developing a realist and relevant economic science.”
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    “Realist” here presumably refers to his his own Critical Realist philosophy. Unfortunately this is not relevant to empirical science:
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    “The CR concept of reality … includes the world of concepts, including false concepts, and all the products of illusion and of imagination, virtualisation and hyperrealisation, including never anywhere existents (fictive beings in their semantic and psycho-social identity).”
    “Dictionary of Critical Realism”, page 400:
    https://b-ok.cc/book/3554116/32e12f

  3. Lars says:
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    “Those are ontological facts we just have to accept — and still go for both reality and science, in developing a realist and relevant economic science.”
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    Is this possible?
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    Not if you accept Marques’ logic.
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    He says:
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    “The problem is that taking uncertainty seriously puts in question the relevance the data obtained by means of testing or experimentation has for future situations.”
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    According to this thesis, economists cannot reliably measure reality. History cannot be prologue. The present cannot support reliable conceptions of the future.
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    He also says:
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    “But, what is the purpose of obtaining this sort of information if uncertainty about future events prevails? …”
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    If you believe in uncertainty then any reliance on the past or present conditions as a vector to the future is fraught with danger.
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    Lars argues that neoclassical models are riddled with untenable assumptions and yield predictions which cannot be trusted. Who can argue with this?
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    But then he claims that the future is utterly uncertain. Who can argue with this?
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    So how/where does economics proceed? It seems it is totally emasculated.
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    I would argue that all there is of any value in economics is the various micro and macro models that exist and can be devised. While they are essentially useless for rendering the future predictable they can at least be a basis, if not a weak basis, for thinking about economic problems.
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    A weak basis is better than no basis at all. It would appear this is the best we can expect.

  4. This is very useful and enlightening. I think that economics has to integrate some insights from sociology, the theory of action, and economic and social history, and psychology, and it has to integrate feedbacks – the things Soros and others write about – and if one is going to have a “deep theory” of underlying causation, then it will be historical, which means that – in dealing with the “real world” – economics will never be a “science” in the sense of physics or chemistry where the underlying mechanisms remain largely constant and where one can therefore make very precise predictions – landing a rocket on a fast-moving asteroid for instance – predictions which are beyond the range of economics and I suspect will forever be beyond the range of economics. The surge in consumer spending – on house renovations for example – during COVID was unpredictable inside any economic model that I know of since the situation that created the surge was, in many of its aspects, unprecedented. As is the present supply chain crisis, since supply chains, in their present form, are new, and since these new lean-and-mean supply chains have never confronted a COVID crisis before and have never confronted the type of massive emergency government fiscal and monetary response before.


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