You cannot study economics in a vacuum...in other words you cannot conduct the "test" part of the scientific method, because the real world will always produce some other unknown imperfect variable that affects the theory.
This is why behavioral economics are so important. IMHO it's the first truly concerted attempt at isolating economics to its core science in a repeatable and testable form (albeit not perfect). For example - understanding things like anchoring, recency bias, nudging, etc.
It's tested all the time.
Add tariff, demand drops. That's also economics and works well in 2019.
This stuff is now so obvious we've forgotten it and can now argue about whether economists can predict recessions.
So it's hard to see economics as a valid science. There are no consistent theories and exceptions to everything.
“Science” is not some kind of shorthand for “ultimate understanding of the world”. It is just a process for validating and understanding the limitations of theories.
Absolutely no theory in economics passes even the most basic quantitative testing.
Really. That is an observable fact. It's not an opinion.
Empirical economics is barely even a thing, and even when it's a thing it's mostly nonsense, based on poor data and questionable methodologies.
https://www.livemint.com/Opinion/J7atYOViQO54PiBzSTdAYL/Empi...
That does not mean there aren't theories, hypotheses, experiments (usually natural experiments, or small scale pop psychology demonstrations like the dollar auction), and so there is data and you can fit models.
And in economics the hard part is getting good quality data, knowing what to try to quantize, where to start. Some folks spend decades hunting for signal. And then we get priming, and turns out it was nothing. At the same time there's SBTC (skill-biased technological change) the theory describing what happens as automation progresses. But it takes a lot of work to correctly "apply" that theory, because the effects are complex, and you have to keep in mind what else can also affect your observables. (So confounders has to be managed.)
And in the end we get high quality insights, such as the David Autor paper (Why there are still jobs?).
And there are the long and even deeper dives like the "Why nations fail?" book, which talks about the problem of public choice economics (politics) and how to model good politics, how to measure, how to quantify, etc. It's naturally less dense than a paper, but the problem and the pondering is a very important part of science. (The hypothesis generation, the abductive reasoning part.)
There's no need for correcting for local variations that are needed in econ. Or from a different perspective the fact that we have simple laws in physics, and chemistry, and engieering, is because we are only considering/using a _very_ limited part of the whole universe.
The classic CH4 + 2 O2 = CO2 + 2 H2O is a gross oversimplification, because there are a few dozen other things going on at the same time, and NASA/SpaceX/BlueOrigin has to consider those when they burn in an athmosphere. But since we rarely encounter these problems we don't often find ourselves lacking enough data to fit a better theory. (But of course that's what's happening in post standard model physics, or in cosmology, or in trying to design fusion plants, we are very early in magnetohydrodynamics, and even designing a better corrosion resistant material for use in molten salt reactors is a challenge.)
So, just as we have models for ant ecologies we have for economics of states/countries, but just as neuroscientists have trouble figuring out how exactly an ant works and when does what and where ants will go to forage next economists have trouble predicting when the next crash will happen. (See also bee hive collapse syndrome, we still don't know what causes it, yet there's a lot of hives and we could even do experiments with them easily.)
I can't remember the source for this aphorism, but it resonates a lot with your comment :-)
[disclaimer: I'm a physicist]
Well this the point. Personnal experience is flawed and unreliable. In my personnal experience, something that weight more should fall faster. This is not the case.
Which economic theory enuce clearly the subset of conditions required to be true and fit the refutability criterion? For chemistry: all of them.
Humor me… can you give a more specific example? When I took chemistry classes I don’t remember learning a theory that was completely correct, but it has been a while.
Soft science like economics, psychology, sociology will have none of the 2: conditions vary, results vary, and even if you could ensure you start with absolutely identical conditions it's very implausible that the result won't be heavily influenced later on by random factors.
That's not testing. That's just a real life interaction. You can't isolate the variables in supply & demand, so we can only theorize that supply & demand is universally true. If I mix copper and tin in a bowl, I will infinitely get bronze as a result. This can be tested again and again with no variation. I simply cannot reproduce people's behavior in a vacuum. We can only observe it in the real world and draw the conclusion. This goes for my comments about anchoring, etc. as well.
Additionally, a significant number of social scientists aren't scientists.
There is a lot of gray area, for example is medicine a science? Many treatments or diagnoses are based on probabilistic or empirical models -- that doesn't make them worthless.
Medicine is not generally considered a science.
And never was it implied that things that aren't science are worthless.
- John Kenneth Galbraith
A not-science (math) is the most critical tool in the scientific toolbox, and hence contributed more to scientific progress than any isolated branch of science.
I think the issue here is more that economics is describing human behaviour, and we don't fit well in to a mathematical formula.
In aggregate, it sometimes makes sense to model participants as rational, but this is a very simplistic model that does not always apply. There are lots of economists studying how asymmetric information or irrational participants can cause market failure or other outcomes.