A First Lesson in Econometrics (1970) [pdf]

They're not just focusing on macro, they are confusing econometrics with economics. Econometrics has nothing to do with any specific economic theory; it is about statistical modelling.

'Econometric models' have so many levers and dials on them that they be tuned to forecast whatever their operator wants them to forecast. Hence they mainly serve as a marketing tool to defend policies that their sponsors desire to get through Congress or the next board meeting or whatever.

As far as things like model projections for NAFTA, any relatively simple search turns up dozens of references. Google Scholar isn't all that bad for this, select a custom range 1990-1994 and enter "econometric model 1992 NAFTA projections". There are dozens of results. For example:

Appendix B, Macroeconomic Simulations of NAFTA https://www.cbo.gov/sites/default/files/103rd-congress-1993-...

You can find the same for those seeking to justify the China WTO deal c.2000 but I don't recall reading much about forecasts of creating something called 'the Rust Belt' all across the once-industrial zone covering a third of the US, or the resulting job losses and economic regional malaise. Perhaps something is missing in the models?

This is way off topic but hopefully it will get allowed because I think you have the expertise to help:

It seems to me that the widely accepted practice of market stimulation by interest rate intervention has the cost of destroying price discovery. Also, that it is a primary cause of wealth inequality. These relationships seem to me actually obvious: push down DCF denominators and valuations go up, inefficient businesses stay in business and employ people digging holes. Sure, we get good jobs reports, but we also work harder to make less. Meanwhile those who hold wealth see its value increase disproportionate to 'actual' worth and common people who hold little or none can afford less and less of it. It seems like a pretty direct policy of 'rich get richer, poor get poorer'. Worse yet, as I look at the world around me, it all seems to support my hypothesis. Tesla, spacs, NFTs, housing, blackrock & vanguard & gates buying land, etc. I could go on and on with examples.

But the thing is, I got shitty grades in my college econ courses. It's laughable to me that all the highly educated people at central banks somehow haven't thought of this but I have. I'm being serious, I'm kind of a lazy idiot. By any reasonable measure, I expect that I'm wrong.

Could you point me in the direction of some primary sources that address the relationship between interest rate intervention and price discovery? I've been told to pick up an undergrad macro text, but those all just seem to say "low rates = easier to get loans = mo' jobz" without any rigor.

Open market ops and other interventions are so common and accepted, the only other people I see complaining are precious metals schizos. Surely there's a theoretical foundation for the policy/practice.

> 'Econometric models' have so many levers and dials on them that they be tuned to forecast whatever their operator wants them to forecast.

I am going to guess you have never written down an economic model, much less presented one at an economics seminar. If your model can be "tuned to forecast whatever", you are going to be annihilated. You will never be able to get away with presenting a model like that. There is no place for it in the field.

Quite on the contrary, a premium is placed on parsimonious, well-identified models.

> Appendix B, Macroeconomic Simulations of NAFTA

This is a useful piece, but to make exactly the opposite of the point you wanted to make. Right there in the executive summary it says "although the overall effect of NAFTA on the US economy would be positive, some firms would contract. Industries in the US that make intensive use of low-wage labor and are now protected by trade barriers are likely to be put at a disadvantage."

Or see the entirety of Chapter 5 in the same document, where the authors repeatedly note that there will be industries where employment decreases.

Indeed, the worst part for your uninformed initial comment is page 87, wherein the following claim is made: "In sum, despite all of the analyses that have been conducted on various aspects of NAFTA, good information for answering the question 'How many workers would be displaced if NAFTA were implemented?' simply does not exist."

A substantial fraction of their Appendix B is devoted to noting weaknesses in the then-current literature about NAFTA. These users of econometrics are well aware of the limitations of the models.

Forecasting job losses at that time and today is extremely hard, and the authors of this study acknowledge that. This is literally the opposite of what you initially claimed about econometrics.

We can make this short:

There is a continuum of causal/counterfactual techniques in economics.

This continuum ranges between "calibrated" simulation models and "econometric" models. The latter are statistical approaches, with the extreme capped by distribution free or semi-parametric "causal" estimations.

Structural dynamic econometric models, for example the estimation of parameters of auctions, hiring behavior or impacts of cost shifts, would fall in the middle of that range, featuring approaches from both areas (for example, computational fixed-point search for equilibria, re-estimation of parameters and then looping back to a new equilibrium).

The paper you cite is on the former: it is a calibrated DSGE model. It is therefore not even an econometric model.

I don't want to be mean, but it really, really seems you are on the first Dunning Kruger peak of "knowing what one is talking about" when it comes to econometrics.