Excellent and highly recommended.
https://www.worldcat.org/title/debunking-economics-the-naked...
Besides, which heterodox viewpoint are you going to argue for? The Marxist? Austrian? Both of these are more clearly 'marketing pitches for a set values' than 'mainstream' economics. If an excessive emphasis on the free market is a pet-peeve of yours then you certainly don't want the latter.
part of his whole thing is that economics isn't something too complicated for the average person to understand. too much mathiness and touted as an absolute certain science
>The ideas of economists and political philosophers, both when they are right and when they are wrong are more powerful than is commonly understood. Indeed, the world is ruled by little else. Practical men, who believe themselves to be quite exempt from any intellectual influences, are usually slaves of some defunct economist.
Can you explain the difference between an "exact science" and the other thing?
Physics is a simple science. It studies the most basic of phenomena, and can isolate them pretty well for experiments. Chemistry is a more difficult science, biology even more so - at each step the phenomena get an order of magnitude more complex (in computational sense), and thus more difficult to study. Then there's psychology, social sciences and economics - all of which are even more complex, as they no longer deal with lots of simple machines, but results of sentient minds interacting in the complex world.
Point being, the "softer" a science is, the more difficult it is. That the "hard" sciences spawn so clear predictions and mathematical models is a consequence of their simplicity. The proper approach here is humility - economics and social sciences are so difficult that we barely begun to figure anything out. That's also why there's so much bullshit in "soft" sciences - they're so difficult that you can plausibly say almost anything, and it's hard to tell if you're wrong, or how much.
And sure, maybe you believe that economics has more untested models, but that doesn't mean there aren't many tested models in economics.
Edit: reply button is locked out for some reason so replying here.
>And look at how much it costs, how unreliable the results are, and how even after full batch of successful trials, we have no clue why a drug works.
And yet we still do solid pharmacology that results in reliable medicine, just like we can do solid economics that results in models with high predictive power.
>If you take a large enough sample and apply enough statistics to it, you can see something that looks sort of like evidence to your hypothesis. In the end, you're not much closer to knowing why it happens (and why it happens only some percentage of the time). Compare that to hard sciences, where most of the time, you can design experiments based on first principles, and you can connect the results back to fundamental theories through a string of formal math.
The idea of statistical approximation does not distinguish between controlled experiments and observational study at all. We were able to statistically model the relationship between speed and energy before we could explain gravity, i.e. we were able to figure something out before we could explain why. And most experiments in physics resulted in approximation, such as newtonian physics, that works well enough at low speeds but breaks down at high speeds. Our current model of gravity was made in the 1970s, yet before 1970 we could explain that when you jump you fall to the earth. The fact that approximation is used is not remarkable in the slightest. That's what modeling is. A model that is too complicated is useless, a model that is too simple is inaccurate. All models are approximations to some level.
>Again, "tested" in physics vs. "tested" in economics are apples-to-oranges.
Yeah, that's why newton discovered relativity, right? No, we have areas of clear evidence and areas outside of our ability to measure for every field. Just becomes some areas of a field are difficult doesn't mean every area is difficult. Just because we couldn't model what happens to a ball thrown at 0.9c in the 1700s, doesn't mean we couldn't model a ball thrown at 0.9 m/s.
>Ultimately, my main point is that economics is so hard that even our best results are pretty bad, and marginally useful.
Look on the IGM site for policy recommendations that we have clear economic consensus on. ]If a country chooses to ignore economics, e.g. zimbabwe and greece, the results are very predictable.
And look at how much it costs, how unreliable the results are, and how even after full batch of successful trials, we have no clue why a drug works. This is because medicine, as a practical ofshoot of biology, is a field so complex, it defies reasoning from first principles. We don't have a full model of how things work, so we rely on the "shotgun approach" - statistics.
Same thing happens in psychology, sociology and economics. If you take a large enough sample and apply enough statistics to it, you can see something that looks sort of like evidence to your hypothesis. In the end, you're not much closer to knowing why it happens (and why it happens only some percentage of the time).
Compare that to hard sciences, where most of the time, you can design experiments based on first principles, and you can connect the results back to fundamental theories through a string of formal math.
> A test of a model is its ability to predict.
That I 100% agree with. And it reinforces my point. Hard sciences gives you models you can rely on. Soft sciences don't. Not because they are full of dumb people, but because the problem domains of soft sciences are orders of magnitude more complex than those of hard sciences, and all your models end up being crude approximations.
> And sure, maybe you believe that economics has more untested models, but that doesn't mean there aren't many tested models in economics.
Again, "tested" in physics vs. "tested" in economics are apples-to-oranges.
Ultimately, my main point is that economics is so hard that even our best results are pretty bad, and marginally useful.
>And look at how much it costs, how unreliable the results are, and how even after full batch of successful trials, we have no clue why a drug works.
And yet we still do solid pharmacology that results in reliable medicine, just like we can do solid economics that results in models with high predictive power.
>If you take a large enough sample and apply enough statistics to it, you can see something that looks sort of like evidence to your hypothesis. In the end, you're not much closer to knowing why it happens (and why it happens only some percentage of the time). Compare that to hard sciences, where most of the time, you can design experiments based on first principles, and you can connect the results back to fundamental theories through a string of formal math.
The idea of statistical approximation does not distinguish between controlled experiments and observational study at all. We were able to statistically model the relationship between speed and energy before we could explain gravity, i.e. we were able to figure something out before we could explain why. And most experiments in physics resulted in approximation, such as newtonian physics, that works well enough at low speeds but breaks down at high speeds. Our current model of gravity was made in the 1970s, yet before 1970 we could explain that when you jump you fall to the earth. The fact that approximation is used is not remarkable in the slightest. That's what modeling is. A model that is too complicated is useless, a model that is too simple is inaccurate. All models are approximations to some level.
>Again, "tested" in physics vs. "tested" in economics are apples-to-oranges.
Yeah, that's why newton discovered relativity, right? No, we have areas of clear evidence and areas outside of our ability to measure for every field. Just becomes some areas of a field are difficult doesn't mean every area is difficult. Just because we couldn't model what happens to a ball thrown at 0.9c in the 1700s, doesn't mean we couldn't model a ball thrown at 0.9 m/s.
>Ultimately, my main point is that economics is so hard that even our best results are pretty bad, and marginally useful.
Look on the IGM site for policy recommendations that we have clear economic consensus on. ]If a country chooses to ignore economics, e.g. zimbabwe and greece, the results are very predictable.
That’s a very interesting point. Most would consider Econ a “soft science” because it is less like physical science e.g. Chemistry. Weird how people like to flip the script for some sorta political gain. Yes, in the soft sciences it is more difficult to reach conclusions as compared to fields like biology, but should we say that makes them more harder?
What I wanted to say is that economics is a "soft science", in the same sense physics is "hard science". Also, that economics is a difficult science dealing with complex phenomena, in the same sense that physics is an easy science dealing with simple phenomena.
https://en.wikipedia.org/wiki/Econometrics
Which is a moot point because science is done without controlled experiments all of the time, e.g. astrophysics, epidemiology, sociology. One of the most famous cases in medicine is the connection of drinking water to cholera discovered using observation to connect deaths to a nearby well.
Does it involve research? Does the research produce models with predictive power? Ok, let's use it, just like every policy maker in the world pre-2016.
And you have no idea how much effort goes into randomised controlled trials and the search for good natural experiments and instrumental variables to answer economic questions, to say nothing of the actual experiments in economics done every time a price is changed or a new product appears. There is a ton of data in microeconomics. It may be hard to use and, ill fitted to the question you want to answer and difficult to get but there’s lots of data.
Macroeconomics has many fewer data points and you can’t really perform experiments but even macro, for all the pointless math worship has made progress.