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Thu Aug 2 09:19:25 EDT 2018
Slept from eleven-thirty to seven-thirty. Woke a couple of times in the night.
High of eighty-four today.
Work:
- Schedule Yardi 7S demo (one-hour limit, by video conference, focused on resident mobile app, especially for work orders)
No.
- Finish PO report, send to Heidi
Yes.
Ten-minute walk at lunch.
Nice-ish day. Partly sunny, a few clouds, a little warm.
Pulled Cat6 cables for our upcoming fiber connection.
Home:
- Return or exchange squeaky shoes
Done.
- Go to bed early
More or less.
https://arstechnica.com/science/2018/08/physicists-simple-spanks-economists-complex-in-economic-growth-forecasts/#p3
> […] the word complex has a specific meaning in this case.
> Imagine that you are on mountainous terrain. Your movement through the terrain depends on your current direction of motion, the slope of the terrain, and your current position. If I could look down on this from above, I could measure these and predict your route through the terrain.
> If everything was linear and _not complex_, then if I am inaccurate in my measurement, it won’t matter too much. My predictions will never be exactly correct, but they'll be close enough that I will find you. In a _complex_ system, a small initial error will amplify, and pretty soon, I will be looking for you on a hilltop while you are trudging through a stream two valleys over. There are a whole bunch of techniques that have been developed to allow us to extract some modicum of predictability from these sorts of systems.
> They reduced the number of parameters in their model to just two: economic fitness and gross domestic product, the idea being that if the economic fitness and GDP are measured at a given time, then the change in GDP can be predicted.
> So what is the economic fitness? It is, in short, a measure of the complexity of a country’s exports. The idea is that exports represent the products from a country that are competitive with like products from the rest of the world. The larger the variety of exported products, the fitter an economy is.
> Now, it is important to realize that no one really has a model (in the physical sense) of the link between economic fitness and GDP. But we do have statistical data that can be used to infer how the two are linked. We can estimate from the averages in the dataset how high the economic fitness of an economy has to be to support a given GDP and use that to determine if the GDP will increase or decrease.
> They found that their model was better than the IMF model, especially when they also took into account the trajectory of the economic fitness. Furthermore, a close analysis of how the IMF model and their dynamical model predictions differed showed that the sources of inaccuracy were different. That meant that combining the two models led to predictions that were even more accurate.
> Another important factor is that there is a kind of self-similar behavior in trajectories. Even though the total size of the economy might be different, countries with similar ratios (I’m simplifying here) of economic fitness to GDP experienced similar trajectories. And a final point: the model also shows where predictability fails. Countries with a very low economic fitness are incredibly difficult to predict. This is true of both the IMF model and their model, but it highlights that the poorer you are, the more subject you are to the random buffeting of economic noise.
Lunch: coffee, pho
Dinner: pretzels
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