Are You a Debt Denier?

By Grant Davies

I'm coining a new term, "Debt Denier." It describes people who are certain that the climate is changing because people live on earth and that it will cause problems at some point in the distant future based on some computer models.

They are the same people who don't think that the national debt is a problem even though every computer program that can calculate (and even a pencil and paper) show that the country is headed for financial calamity if nothing is done about spending.

If you think man made climate change is a problem but man made fiscal insanity is not, you might be a Debt Denier.

6 comments:

  1. Debt Denier...I like it! I believe back in old Psych 101, they called it "cognitive dissonance". Funny how libs will believe a computer model based on multiple guesses and assumptions about climate, that have never proven out in the real world, is to be trusted, but financial projections based on hard number crunching never dents their consciousness. Something about being "math impaired" I guess.

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  2. I am employed in a role that requires the use of statistical models. They can be very powerful. But they are dependent on the parameters they are given as much as by the data itself. Every modeler knows the basic notion of Garbage In, Garbage Out. Climate models are no different.

    Debt on the other hand is simple math. 17 trillion, is not subject to manipulation (unfunded liabilities aside). It is what it is. Debt Deniers be damned.

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    1. I wish I could remember where I heard it, but supposedly, the computer models that predicted climate change predicted torrential rains and flooding in California. Of course, now that there is a drought here, THAT's what's caused by global warming!

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    2. The most interesting model I ever heard of was from a statistician who was better able to predict outstanding or poor wine vintages than the best wine-tasters, using data like rainfall, moisture content, soil quality etc. Models can work amazingly, if you build and use them properly. They can also prove to be useless.

      I'll tell you where models do work quite well though - human behavior. Maybe it's alarming to some, but things like the likelihood to buy a specific brand of soap, or to go delinquent on a mortgage can be predicted with amazing accuracy. It's no secret that the Obama team were very effective in leveraging voter turnout models in 2008 and even more so in 2012. It's how they won. They used finely tuned strategic targeting based on those models and you can see the result.

      I've argued for years that it's something we should be using in election cycles all the time. Maybe we'll catch up at some point.

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  3. I agree Dean. But I would make the point that if the model proved flawed and the results were unexpected (like the climate change models) the model would be reworked and corrected until it produced rational provable results instead of tweaking the data until you get the desired conclusion. These models are not science, they are merely parts of the scientific method.

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    1. I think where the science fails is when the data is tweaked instead of the model. The model process is based on mathematics; sound statistical principles. I agree, the process of honing the model is a scientific method principle. But I've worked with models that have consistently predicted customer behaviors very accurately. But even the ones that work, decay over time and need to get rebuilt from scratch - that's normal.

      So when someone has a model that predicts something 5 years out and it doesn't ever change, the model itself has decayed and that has not been acknowledged. Also, the further out the model forecasts, the less accurate it becomes. Tomorrow's weather forecast is more likely very accurate than a prediction of global meltdown in 100 years (or 10, Al Gore).

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