Krueger’s study was highly flawed. What it amounted to, was, as one economist put it, attempting to prove that water flows uphill, by looking only at the upward movement of water in a rapids. It’s politically correct, feel good nonsense. Just because you’ve found an exception does not nullify the rule - as in chaotic systems, sometimes water does flow up hill. But economics solves this issue by studying the underlying forces.

I think of the economy as a biological extension of our species. Any attempt to control or regulate it can only result in inefficiency (beyond the obvious maintenance of contracts and outlawing of violence).

Another way to look at money is as analogous to energy - and like with energy, it cannot be created nor destroyed (which is different from growth of the economy as a whole due to innovation). So any time you see a policy which appears to “create value” by shifting it around, will create slightly more losers than winners, if you take a holistic view (eg, increase cost of labour, decrease comparative advantage and decrease spending on research and development).

“ The inverse relationship between quantity demanded and price is the core proposition in economic science, which embodies the presupposition that human choice behavior is sufficiently rational to allow predictions to be made. Just as no physicist would claim that “water runs uphill,” no self-respecting economist would claim that increases in the minimum wage increase employment. Such a claim, if seriously advanced, becomes equivalent to a denial that there is even minimal scientific content in economics, and that, in consequence, economists can do nothing but write as advocates for ideological interests. Fortunately, only a handful of economists are willing to throw over the teaching of two centuries; we have not yet become a bevy of camp-following whores.” ~James M. Buchanan, 1986 Nobel laureate in economics, writing in the Wall Street Journal on April 25, 1996

IMO Card/Krueger's results are flawed for a different reason. They rely too much on real world results meaning that if all the other factors don't stay the same, their conclusions will eventually fail too.

For example, they say immigration doesn't affect wages. In Canada our government and top banks literally all say it does. There's also a wide body of evidence that increased labour supply does put downward pressure on wages (now whether they actually fall or stagnate depends on a combination of other factors).

Card/Krueger's work is like perfectly fitting a regression line to historical data. It has predictive power until it doesn't...

I'm not sure I've heard people complain that economics got too much data. Fun. To be clear, their model is to explain, not to predict.[0]

Causal inference has progressed a lot since their paper.

[0] https://projecteuclid.org/journals/statistical-science/volum...

Just go to the thread on HN discussing their Nobel Prize. They're most known for their study on Cuban migrants to Miami, where many migrants came and wages didn't fall.

Many, many economists cite this study to say that immigration doesn't reduce wages. And it is true, often. However it's not because an influx of workers doesn't create downward pressure on wages. It's because there's other factors which keep wages rising.

Now in Canada we have a situation where our immigration levels are so high that we don't even pretend it doesn't affect wages anymore.

https://www.baystreet.ca/economiccommentary/3472/Canada-Wage... https://financialpost.com/news/economy/immigrant-influx-is-s... https://www.bloomberg.com/news/articles/2021-11-24/immigrant...

>However it's not because an influx of workers doesn't create downward pressure on wages. It's because there's other factors which keep wages rising.

So one of the main theories about that paper is that the immigrants were in a largely separate labor market in terms of skills/experience from local workers. When they raised the labor supply in their particular market, it increased entreprenurial activity and more labor was hired across many labor markets as a result.

I got you. Yeah, reduced form models will have the issue of disentangling factors. This is why diff-in-diff and synthetic control models are valuable, but identification assumptions have to be clear.