We don't have consensus for cause and effect at all. What we have is a well established groupthink trying desperately to maintain its view and its power.
The 2008 crash threw all of it up in the air.
I'd recommend reading debunking economics to see the heterodox viewpoint.
Essentially there is no value free economics. That a marketing pitch for a set of values. There is only political economy.
Economics is an evolving field of study like any other. There are many different schools of thought even within the 'mainstream' position. Using disagreements and changes within the field as an argument that the entire field is flawed is what climate change deniers use when they want to dismiss evidence of climate change. There is room for disagreement on policy without dismissal of the entire field.
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.
it's not an exact science in the same way physics or chemistry were. by the arguments of market fundamentalists/etc you'd think they think economics is a deductive science
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.
I think sciences should really be classified on degree of complexity of the phenomena they're dealing with.
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.
I don't think that's true at all. Pharmacology is a very difficult science that we get wrong all the time, yet we still have medicine because we are able to test our medicines by trying them on animals and people. Likewise in economics and sociology and astrophysics we are able to test through natural experiments. A test of a model is its ability to predict. We don't accept untested models just because they're "complicated".
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.
> Pharmacology is a very difficult science that we get wrong all the time, yet we still have medicine because we are able to test our medicines by trying them on animals and people.
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.
Reply button has reappeared so copying my response here for proper flow, but now I can't remove it from my other comment because the edit button disappeared.
>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.
> Ultimately, my main point is that economics is so hard that even our best results are pretty bad, and marginally useful.
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?
Ooops, I tried so much to avoid using word "hard" for multiple meanings, and I failed.
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.
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.
Well it’s great that they do more than just design experiments and hack p-vales all day;) Geez, had no idea it was such a controversial statement. What do you want to say, every application of math or coding counts as science? https://en.m.wikipedia.org/wiki/Hard_and_soft_science
Whether something is a "real science" is based on whether or not science is done, not the difficulty of the subject matter. Spending so much time trying to narrowly semanticize science in a way that specifically excludes economics is navel gazing. The purpose of these discussions seems to be to discredit economics and discount it's predictive power by defining it as not-science, but predictive power doesn't come from the definition of the word science, it comes from the statistical methods that science uses.
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.
Epidemiology, ecology, astronomy, cosmology, botany, zoology and geology obviously don’t count as sciences then.
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.
Counterpoints notwithstanding, Economics and other social sciences should be considered distinct from the more traditional fields of science that are rooted in clear cause-and-effect as demonstrated by controlled experts. You have no idea lol, obviously.
