Both are hard, especially in the cases I listed.
With a good theory of (e.g.) platforms, you could likely identify a few different fundamental forces which may push in different directions. Hypothetical example: force X would benefit the platform at the expense of sellers, force Y would benefit the sellers at the expense of the platform. A priori it may not be possible in theory to put a magnitude on those effects: there may be nothing that would say "we can show that X > Y in every case."
This is where you need data. (This part is especially hard for platform markets!) You would need data on the platform side AND on the consumer side AND on the supplier side. You write down a model of (generally) consumer demand, supplier response and platform behavior (at least - probably taking a somewhat simplified approach to at least one of those sets of agents). With your estimates, you would try to answer the "Is X > Y?" question posed above.
You can also simulate the impacts of counterfactual policies, among other things.
More specifically, this is where you need data which does not and cannot exist. Specifically, an objective scale which would allow you to compare the cost or benefit of policy to the platform and the sellers. There is no such objective scale, because value is subjective and not comparable between different economic actors, or even for the same actor at different times. Any model which assigns numeric "estimates" for these costs and benefits so they can be compared is substituting the authors' own subjective valuations in place of those of those who will be affected by the policy.
This is wrong. All important work in my field in the past 25 years has been empirical.
> Any model which assigns numeric "estimates" for these costs and benefits so they can be compared is substituting the authors' own subjective valuations in place of those of those who will be affected by the policy.
Very, very wrong. You’ll never get away with picking your own parameter values in modern empirical IO.
If you don’t know the field that’s fine. I probably don’t know your field either. But don’t make these overconfident and totally wrong claims about what’s done in a field you don’t know anything about.
The problem I have with much of economic theory is that it tries to tie things back to what's beneficial or not to societies and tries to do so through a very thick utilitarian lens. There's often a heavy amount of fairly sophisticated math, statistics, and modeling parading as certainty when the fact is, there's a very high amount of uncertainty in many assumptions and in variety of economic theories that are just hand-waved away. It's not to say the problems economists face are simple, they're actually incredibly challenging and I think it's good economist continue to push for a better understanding of these systems.
My gripe arises when economists masquerade or imply current theory with certainty when in many cases, as if it were a mature science. It simply isn't and far too many use the appearance of certainty hidden in complexity of theory as certainty to push a biased personal agenda or perspective. When you overload terms like efficiency, efficiency in what context? Efficient for whom and through what perspective of the world? Very clear definitions need to be made so I don't question the motives of the attempt of quantification and can look at flaws and oversights that may exist in such metrics.
Most economic theory lacks real empirical evidence because it's just to difficult to play the experiments and interplay of micro, meso, and macroscale systems at a global scale without actually running the experiment (changing policies).
It's the politicians and voting public that are the problem.
It's easy to get massive numbers of people to vote for you by giving out is completely wrong as long as you're extremely confident in your presentation of it. It's easy for these political winners to drive the economic systems to collapse while increasing authoritarianism by said false confidence. People want to vote uncertainty away, authoritarianism is one way of doing that.
But there is no link for "socially optimal", and the phrase appears nowhere else in the article, so this definition is incomplete at best and vacuous at worst because its meaning turns entirely on the meaning of "socially optimal" but I can't think of any reasonable way to define it that is not a judgement call.
Technically Pareto optimal. Pareto optimal points are not necessarily socially optimal.
NB I was just comparing the writing style of that page (which seemed a bit odd to me) with other examples.
So where do I find these definitions? Because I am still highly skeptical that they can be defined in ways that do not conceal hidden judgement calls.
You can be skeptical, but the cure for that skepticism is something more akin to taking an undergrad course, or two.
- Lacking time stability means no one tomorrow has any incentive to stick to the policy, and means the policy is unlikely to succeed in its objectives.
- Deadweight is lost efficiency
- The only arguable one is "fairness", and to clarify I blunted the term to avoid the nuance of explaining Pareto optimality. But sure, we can also consider egalitarianism and other moral frameworks.
That's true, but time stability means that a bad policy is going to be maintained even in the face of evidence that it is bad. Deciding which is worse is, as I said, a judgement call.
> Deadweight is lost efficiency
The flip side of increased efficiency is decreased resilience. Without unused capacity (i.e. inefficiency) the slightest contingency will send the entire system into chaos. How much inefficiency you want to maintain as a hedge against contingencies is a judgement call. Different people have different risk postures.
> Pareto optimality
I think it's safe to assume that people on HN understand Pareto optimality (or are capable of looking it up). Do you really think that Pareto optimality is synonymous with "fairness"?
> we can also consider egalitarianism and other moral frameworks.
Of course we can consider these things. But that doesn't answer my question, which is how do we address them in a principled way that doesn't degenerate into a political dispute?
See: CPUs and GPUs in 2020-2021, baby formula in 2022, etc.
It can absolutely be a judgment call.
It has nothing to do with the everyday meaning of the term “deadweight”.
So everyone pays the same charge for IT costs AND market does not have an unfair advantage.