>the simple models taught to undergrads are simple, elegant - and they don't work too well in practice
Also they have been very ideological for a long time.
The idea that real economic behavior will converge on a particular model as the real actors approach the assumed behavior of the actors in that model is a good way to think about models. The idea that distance from model behavior in real actors will smooth out to insignificance over the long term or at a larger scale is common, but denies the existence of nonlinearities and feedback effects resulting from the interactions between the differences between real behavior and model behavior. The effects of those nonlinearities can (and often do) subsume the model behavior entirely.
Hence, the importance of natural experiments. You can use them to find important deviations and build a new model. Unless you're from the Chicago school, in which case deviations are your cue to start hand-waving and appealing to nature, justice, and the character building nature of hard work.
Some very old and very well established models performed very well during all of the recent economic shocks. What they couldn't do was compete with a bunch of cornpone wisdom about spending within your means that was easily understood by people who have trouble with math.
Interesting. What's the best study you have, with scatterplots, that shows that the "very old" models performed "very well"? Insofar as we have seen actual quantitative predictive modeling by Keynesians of macroeconomic quantities, the plots tend to look like this:
Neither seem particularly textbook, but you're obviously thinking of something. Given that people who think differently from you invented Bitcoin (and thus have at least a glancing familiarity with advanced mathematics, if the solution of the Byzantine Generals problem means anything) it would be great to see some plots to the contrary. Not just models, but X/Y plots or tables in which Keynesians predict something and nail it. It's not hard, after all to find many examples of Krugman, Bernanke, Goolsbee, or Orszag making quantitative predictions that turned out flagrantly wrong [1].
It's very difficult for me to figure out what you're trying to say here. The first graph seems to be about Obama, the second a time series of the monetary base, and the link in the footnote long statements from random people. Only the last mentions a model, and only in terms of how well it worked[1].
>Given that people who think differently from you invented Bitcoin (and thus have at least a glancing familiarity with advanced mathematics, if the solution of the Byzantine Generals problem means anything) it would be great to see some plots to the contrary.
I don't know what Bitcoin has do do with anything, or what it is being presented as an example of.
>Not just models, but X/Y plots or tables in which Keynesians predict something and nail it.
You're the first person to mention Keynesians, I mentioned economists. If you want to find something that Krugman nailed, though, try the unemployment rate from your first graph.
Ha. Methinks you doth protest too much. But I'll be very precise. Show me the equations and code that Krugman wrote in 2009 that predicted the unemployment curve over the last four years. OMB (full of economists!), to their credit, at least essayed a quantitative prediction. As the first graph showed, it was completely wrong.
So: what "very old" models performed "very well"? You must be thinking of something here. I'm not talking about a Krugman blog post where he says the stimulus was too small. I'm talking about an actual scatterplot, a time series prediction with the X axis as time, the Y axis as the dependent variable, and actual empirical measurements plotted vs. the predictions of theory.
You can see the graph halfway down the page, with theoretical predictions as the red line and actual empirical measurements as the black line. The Nature article admits they don't match well. But in other fields they do match well. For example:
In ballistics the predicted time series match experimental results very closely. So I ask again: what "very well established models" in economics performed "very well"? Which of them nailed the curve?
Also they have been very ideological for a long time.
The idea that real economic behavior will converge on a particular model as the real actors approach the assumed behavior of the actors in that model is a good way to think about models. The idea that distance from model behavior in real actors will smooth out to insignificance over the long term or at a larger scale is common, but denies the existence of nonlinearities and feedback effects resulting from the interactions between the differences between real behavior and model behavior. The effects of those nonlinearities can (and often do) subsume the model behavior entirely.
Hence, the importance of natural experiments. You can use them to find important deviations and build a new model. Unless you're from the Chicago school, in which case deviations are your cue to start hand-waving and appealing to nature, justice, and the character building nature of hard work.
Some very old and very well established models performed very well during all of the recent economic shocks. What they couldn't do was compete with a bunch of cornpone wisdom about spending within your means that was easily understood by people who have trouble with math.