"Economics is a social science"

Economics is a social science

I've been told that countless times by lots of different people. Recently by John Handley; awhile ago by Maiko. Here's another another one from Sam Watts. 
[I made some updates due to some reasonable objections from John Handley. I marked these with asterisks.]

Here's Daniel Little:

... Does the phenomenon of [social phenomena] admit of a scientific treatment along the lines of Galileo, Newton, or Lavoisier? 

The answer is resoundingly no. Such a goal displays a fundamental misunderstanding of the social world. Social things and processes at every level are the contingent and interactive result of the activities of individual actors.

I even (kind of) said it here. Well, I said there are two pieces of economics: working markets and failing markets. The former's properties (in my theoretical view) derive from the properties of the state space. The latter's properties will come from social science.

But what does it mean to say economics (or aspects of it) are social science?

The "Lucas critique" 

This idea I wholeheartedly agree with: empirical regularities may suddenly fail to be empirical regularities because humans have both individual and group behaviors. This is the reason behind non-ideal information transfer. Humans can spontaneously coordinate around some event (e.g. a stock market crash) and markets will fail to be ideal. 

Economic models are qualitative 

I am sympathetic to this one (I love a good zero order theory as much as the next theorist), but the existence of quantitative models that are quantitatively compared to data invalidate this objection. These range from Mark Sadowski's VARs and the NY Fed's DSGE model to my own recent entry. You can't use "but it's qualitative" as a defense of your empirically flawed model if your model has dozens of parameters and other models have quantitative results. You can't move the goalposts. Other models are quantitative. Your qualitative model better be for something that's never been quantitatively compared to data before. That immediately excludes the anything to do with the business cycle, inflation or interest rates. 

Economics can't be explained by quantitative models 

This is a bit different from the previous one. It represents a combination of the Lucas critique, the idea that models are qualitative, and, well, basically assuming you know everything about economics. You know for a fact e.g. that economics is too complex to be represented with any model. You need to show this, not just assume it like Daniel Little does above. 

I think this one persists because it sounds serious -- in the "very serious person" (VSP) sense. Just look at the problem: it's made of millions of humans making millions of decisions with millions of dollars every hour! Obviously a tractable quantitative model doesn't exist. 

But as I've said before: your failure of imagination is not evidence of anything. Humans in prehistory probably couldn't conceive lightning could be as well understood as it is today. Imagine if people went around saying: There's no way you can understand electricity ... it's too complex to model quantitatively. It's a social science of little homunculi!

Data can't falsify economic models 

This is effectively the definition of derp. Your priors are too strong. 

*This specific objection was intended to be addressed to the Lucas and Prescott types who Sargeant recalls in an interview:  

But after about five years of doing likelihood ratio tests on rational expectations models, I recall Bob Lucas and Ed Prescott both telling me that those tests were rejecting too many good models.

A less derpy version is that data is uniformative. 

[*] The data is uninformative 

This is the weak form of "data can't falsify models". Basically it says that there is insufficient data to reject most models. However, this is a model complexity-dependent statement and if it applies generally, then generally the models are too complex for the available data. Try simpler models. If you can't reject those, try even simpler ones. At some level you'll get to log NGDP = a t + b, which is completely rejected. 

This relates "economics is a social science because the data is uninformative" to the idea that economics is assumed (as a strong derpy prior) to be complex. It is "very serious" to say such things, but it's not a reason to avoid empirical data and treat economics like philosophy. 

[*] You'll never nail down correlation vs causation 

Due to external factors (and lack of controlled experiments), this may be true. However, this is a reason not to praise an empirically successful model (e.g. this information equilibrium model) too highly. It is not a reason to accept a model that would otherwise be rejected empirically. 

If external factors always seem to confound your model rendering the originally observed correlation on which it was based moot, then the model is useless even if it is correct. Personally, I'd say the Phillips curve should be thrown out based on this.

Most mainstream economic models simply assume a causal mechanism (utility optimizing agents). Is this better or worse than assuming correlation is causation? At least the latter has some connection to the empirical data. 

In any case, this is not a reason to abandon looking at empirical data or treating economics like a "hard science". You can still reject models! 

You shouldn't use math 

I wrote a whole post against this idea. Anyone who says you shouldn't use math is trying to pull a fast one. N.b. this is not the same thing as saying you don't need math. You don't; you should be able to explain mathematical concepts in human languages as well.

Economics studies the social behavior of humans

Well, this is perfectly true. If you don't mean anything more by it, then I'm fine with it.

Have I missed any?

Economists (and everyone else out there in the econoblogosphere): time to stop hiding behind theory and qualitative analysis and start addressing the empirical data out there.