Monday Message Board

Another Monday Message Board. Post comments on any topic. Civil discussion and no coarse language please. Side discussions and idees fixes to the sandpits, please.

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8 thoughts on “Monday Message Board

  1. The nonsense associated with the US mid-term elections, namely the allegations of fraud and corruption, the toxic smears, the calls to bring in the police and to impound ballots, and the rampant gerrymandering, have me once again thinking that Americans are an inferior and uncivilised people.

    I think we should seriously consider building a wall to keep ‘Merkins out of Oz.

  2. People are people. American behavior emerges from their system. People made the system. Now the system makes their behavior… badly. They need to remake their system. Will they? It’s anyone’s guess.

  3. Hugo : you should have said “Republicans”. The accusations of fraud and gerrymandering by Democrats are based on evidence, not smears. The majority of American voters supported them in 2016 and 2018. The trouble is that they are trying to run a 21st century superpower using a rulebook written by a bunch of clever 18th- century slaveowners, designed to prevent democracy.

  4. I thought it was obvious that my comments were directed at GOP antics. It’s hard to do satire on the net.

  5. hmm.

    blaming the system.

    yers, can be done and no doubt is applicable.

    personal ethics come into it too.

    check out the phenomenon specific to the US PoW in the Pacific theatre of WW11, known as “rice trading”.

  6. JQ, you may tell those pesky physicists that Farmer said: “Economics is a lot harder than physics because people can think.” Farmer is the guy who “turned out to be the first wearable digital computer. We were the first people to take a computer into a casino and successfully predict the outcome of roulette and make a profit.” “Norman and I started a company called Prediction Company, which predicted the stock market.” And played safe but smarter. Just like my examole below. Farmer got out to do bigger things as this article shows. Do read the linked article even if my anecdotes make you shy away. It has more info than quoted below.

    Once upon a time I had a model of f1-11 preparedness (no you cant see it), a complete web aware system dynamics modelling software (in 1993! Thanks Majola), and a handle on ‘indicators’. Lincoln Indicators in particular. An acquaintance had been turfed from Maquarie ($5m golden parachute and don’t come back) started an invoice funding house. He knew about indicators more than me. I asked ” why don’t you use Australian data such as lincoln”? “Because our backer is in the US, and if it passes their zeta model we are covered”. 

    No fine grain, no locality, no dynamic of local market. Just bankruptcy score. Financials for 3-24 mths with equity as backing anyway. Could they lose? Not really. His new driveway is costing $300,000. And still in coterie of very old established stock market traders and investors. And still they cover their arses and would never go near developmental risk. Their models, asymetric information and intuitions make money. But they could never and would never be climate modellers. Just bet (shovel) on the weather tomorrow and own the shovel.

    So it was refreshing to read J. Doyne Farmer & rebuttal by Don Ross here:

    In Farmers’ reply to rebuttal  by Don Ross, Farmer gives the example of gravitational constant;
    …”The elephant sitting in the room is the problem of statistical estimation. Models always have free parameters, i.e. numbers that are needed to complete a model, which can only be determined by comparison to data. The law of gravity, for example, depends on a parameter called the gravitational constant, which tells us how much gravitational attraction there is for a mass of a given size (in a sense it is the ratio of gravity to inertia). This number doesn’t come from the theory: We have to measure it.  Fortunately there is a lot of matter in the universe, and we can measure positions very precisely, so the data tells us the value of this parameter to an incredible degree of precision. But this is an exception. Most of the time the biggest limit to our understanding of the world is the lack of data and our inability to correctly estimate the parameters of our models.”…

    We. Have. To. Measure. It.
    And what we have a hard time measuring will, i believe, come from big data, and the ‘holes’, contrast or counterintuitive measures discovered. Known unknowns?

    And if Don Ross wants to keep using; 
    “As Farmer says, the Fed and other central banks now use enriched “DSGE+” models that incorporate financial market variables. Thanks to Bernanke’s successful rescue of the overall system, the Fed has taken on the institutional mission of worrying about, and thus modeling, financial asset dynamics. Its job description having been widened, it has added suitable new kit to its toolbox.”… Really. That is it. DGSE +. The Fed! What does NATSEM use these days? Is ‘enriched’ defined in any economic modellers books?

    There is more by Ross, …”But over-reliance on lots of data to compensate for gaps in theory—instead of identifying and repairing the gaps—will only make such failures of foresight worse. And big data, in the form of unmodeled statistical correlations that are discovered by computers, will be part of the problem to be solved, not tools toward the solutions.”

    Personally I hope Farmer develops economic ‘climate’ forecasting, and Ross bets his hard earned on ‘dgse+ enriched’ models. And keeps ‘repairing the gaps’ which will lead him to what Farmer says in rebuttal reply… “Even if we correctly navigate the bias variance tradeoff, and find the model that is “just right,” the combination of the complexity of the structure of the problem and the limitations on the availability of data pose a fundamental limit on our ability to predict. If we only have a little data then the best model is necessarily very simple. If the problem we are solving is complicated, and requires a better model with more structure, we are stuck. The only way to make a better model is to find more data.”

    Ernestine, I’d love to hear your reponse to Farmer & Ross.

  7. The latest version (number 12) of Lazards’ survey of US electricity generating costs is out (**** Basically it says the same as all the previous versions: wind and solar keep getting cheaper. It’s pretty high quality (investment bank that does not have an axe to grind, reputable and influential so that big companies will take their calls). They still use a WACC of 9.6% which has become ridiculously high, so the numbers greatly understate the true cost advantage of wind and PV. The news is that the cost of wind and solar now overlaps the running costs of old coal plants, which explains why a good number are being retired early.

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