7 thoughts on “Economists – know your limits!”

  1. Posted 18/07/2017 at 04:02 | Permalink

    Interesting. I would have thought that a model could be tested against historical values where the outcome is know to check the model.

  2. Posted 18/07/2017 at 18:31 | Permalink

    Chaos theory has some things to say about the limits of predictability, but I think Paul Ormerod is the only economist who takes that seriously. Perhaps the maths is too difficult. As to Steven Procter’s comment, this illustrates perfectly the gap in understanding of the general public. (I don’t want to be mean!) If the dynamic system that is the economy goes into a different regime, then all historical data will be invalid. What do you test on then? Chaotic systems have “pockets of predictability”, periods where they look like there’s a pattern, and then they change completely and are off somewhere else. Even the simplest chaotic systems do this. This leads people to believe they understand more than they really do. Then they end up stymied. Exactly the same ting has just happened to the pollsters. The answer is to embrace 20th century maths rather than 19th. Professor Booth is definitely heading in that direction.

  3. Posted 19/07/2017 at 08:09 | Permalink

    Philip, I, of course, agree with you and it is refreshing to hear comments like yours, debunking so called “experts” who have failed miserably applying flawed econometric models based on invented data, who tell us what will happen in absolute terms. Forecasting makes sense only when it is based on stochastic models, and probability confidence levels of a particular scenario occurring are clearly set. While I don’t subscribe to most of John K. Galbraith thought, I wholeheartedly agree with him when he declared: “The only function of economic forecasting is to make astrology look respectable”

  4. Posted 19/07/2017 at 17:02 | Permalink

    A good critique. In my experience, the first question in response to any forecast should be: on what assumptions is it made? I was taught that the value of a forecasting process is not the numbers that appear at the end of it but the whole chain of reasoning and evaluation of the various factors, drivers, relationships, correlations and risks which are associated with making a forecast.

  5. Posted 19/07/2017 at 17:41 | Permalink

    Some decades ago George Box said:

    “All models are wrong, but some are useful”

    And in Mervyn King’s recent book he says:

    “It is better to be roughly right than precisely wrong.”

    Models are approximations of what could happen if – and only if – all the assumptions used in the model prove to be correct, AND if the model includes all, or nearly all the required assumptions. That can be just about right enough to send a spacecraft to Venus, but it is obviously nowhere near true when modeling complex, chaotic, non-linear systems such as economies or climates.

  6. Posted 19/07/2017 at 18:08 | Permalink

    The economist Victor Zarnowitz taught me in the 1960s at Chicago University that in economics “next year will be the same as this year” is as good as it gets. That served me well for decades in financial roles in the USA and U.K. It is gratifying to hear that it is still true!

  7. Posted 19/07/2017 at 20:31 | Permalink

    The truth is that, unlike the rest of economics, macroeconomics is still stuck in a state like Moliere’s 17th century doctors, mumbling to each other in their own language, making their unscientific diagnoses and prescribing their patent remedies with no perceptible benefit to the patient whose death is greeted with an insouciant shrug of the shoulders. In the same way, the failure to foresee or even to attach a nonzero possibility to the 2008 crash has prompted little soul-searching and certainly no sign of a crisis in the world of academic macro, with colleagues quite relaxed about their failure, as if it is only the ignorance of the public (who mostly pay their wages) – not to mention the Queen – that leads them to question the usefulness of a profession that can do little more than give us a slightly better-than-evens guess as to whether next year’s growth will be 1% or 1.5%.

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