[HN Gopher] A field fixes itself: the applied turn in economics
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A field fixes itself: the applied turn in economics
Author : INGELRII
Score : 41 points
Date : 2022-01-23 15:37 UTC (7 hours ago)
(HTM) web link (www.newthingsunderthesun.com)
(TXT) w3m dump (www.newthingsunderthesun.com)
| Mizza wrote:
| Modern calipers revolutionizing the field of phrenology.
| carapace wrote:
| LOL! It's hilarious that economists are talking about
| "empirical" economics. What were they doing before this?
| "Unempirical" economics?
|
| Seriously though, economics seems (has seemed) little better
| than numerology to me, so I'm glad to see the field start to
| graduate from the alchemical to the chemical stage of
| knowledge. Good for them.
| AtlasBarfed wrote:
| I like to condemn economics as only being able to predict
| value based on a very limited set of things that can be
| measured/tested.
|
| The strange thing is, even with "measurements" like
| CO2/global warming so clearly pointing to armageddon in a few
| generations, the field of economics is STILL unable to
| quantify such impacts on models, or produce effective
| economic pricing measures.
|
| Of course, because in addition to being only a crude
| "science" that basically reduces to bad accounting practice
| on a massive scale, economics is also dressed up as a
| "crystal ball science" that the oligarchical powers can trot
| out to justify their positions and current structure of
| monetary distribution as a priori destiny.
|
| So it is ALSO politically corrupt, not just computationally
| bankrupt.
|
| The reality is of course that there is plenty of money to
| deal with most of our massive structural problems. But who
| owns that money? The rich who will rather see the world
| destroyed than give it up.
| ContrarianBrit wrote:
| Very interesting - thanks
| huitzitziltzin wrote:
| Nice piece which to me reads as being an accurate account of the
| recent history of the field (as far as I know it).
|
| Short summary: 90% of the work that is taken seriously in
| economics is empirical. Moreover, we only care about cases where
| causal inference is possible and those are the papers that get
| published. (If your first complaint about a published piece in an
| economics journal is "correlation does nor imply causation," we
| know that too and the kind of work which can fall for that
| criticism is only rarely and accidentally going to make it
| through the refereeing process.)
|
| Far better than a similar, much less informed piece from Aeon
| which was shared here a few days ago...
| ackbar03 wrote:
| How do you prove causation instead of correlation exactly?
| jldugger wrote:
| Causal inference, a field I've been studying for a few
| months, is often touted as achieving this. That's not quite
| true -- the causes do not live in the data.
|
| What causal inference does is estimate the parameters of a
| given causal model, and does so by applying algorithms on the
| model to determine which variables to control for. Once the
| researcher to supply directions of causality, you can use the
| data to validate the model, or ask questions about it that
| you already know the answer to as a cross check. But there
| can be multiple valid models, and the data alone cannot help
| you select the "right" one. Worse, sometimes (often?)
| validating the "right" model requires data you do not have
| access to. But you don't need to do the experiment to find
| that out at least!
|
| Underlying all this appears to be Bayesian methods. Which
| makes sense as you are often seeking answers to conditional
| probabilities, Bayes is good for that.
| NeutralForest wrote:
| There is a whole subfield dedicated to the question called
| causal inference. You can read something like the "causal
| inference : the mixtape" https://mixtape.scunning.com/
| [deleted]
| INGELRII wrote:
| 1. Experiments, and natural experiments
|
| 2. causal discovery methods + generic assumptions
|
| Economists are really putting effort into sound methodology.
| huitzitziltzin wrote:
| First thing: all claims to have proved a causal relationship
| are relative to a set of assumptions which may or may not be
| satisfied (even in experimental sciences).
|
| Taking the experiment as an ideal we cannot reach, there are
| many settings where there is useful variation in the data
| which can approximate the random assignment to treatment
| which is the essence of experiments.
|
| Some canonical research designs which can be used here
| include differences in differences, regression discontinuity,
| synthetic control methods, or instrumental variables methods.
| They are differently appropriate to different settings but
| permit causal claims to be made. These methods are widely
| used in contemporary empirical economics (indeed this is a
| nearly exhaustive list of methods used in applied micro!).
|
| Useful, accessible references here include Angrist and
| Pischke, "mostly harmless econometrics," or "causal inference
| the mixtape" by a guy at Baylor whose name I'm forgetting,
| and the very recent "the effect" by Huntington-Klein, which I
| have not yet read.
|
| Other slightly more exotic models are used in (for example)
| industrial organization which still permit causal claims to
| be made about the effects of increasing prices or changing
| product features on demand for a product or set of products.
| civilized wrote:
| I think there is sometimes too much confidence placed in these
| results (no different than any other empirical field that makes
| heavy use of statistics and significance testing). But it's
| still a positive direction, unquestionably.
| huitzitziltzin wrote:
| Fair point and I completely agree with you. We don't yet have
| a great answer on "researcher degrees of freedom" for example
| (ie what specification is run, which one is reported).
|
| Definitely better than what came before and surely in another
| 30 years empirical standards will be even higher!
| NeutralForest wrote:
| I mean, Aeon is pretty bad
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