| paper | d4-journals-jet-2024-0090 |
| authors | — |
| venue | ? |
| filed under | unclassified |
| judged by | gpt-6-luna / xhigh (triple__luna__xhigh__c6r1) |
| judge confidence | medium |
| authors would recognise it | no |
Proposition 2 is the only plausible computational anchor: its proof explicitly constructs transfer amounts, so it has constructive computational character despite lacking a stated complexity bound. But in a nonatomic country population, one country’s departure has no aggregate effect; preserving the spillover that drives the proposition requires a coordinated bloc exit, a different decision problem that the proponent does not specify tightly enough to hand to a prover.
fails bit b-changes — the continuum limit changes the question
The proposed mass-exit idea concerns Proposition 2’s transfers; it does not cover Propositions 1 or 3–6, and no valid mirror survives.
I can’t identify a qualifying anchor in this paper. Its numbered results are economic propositions about equilibrium and welfare, not computational results about a problem being in \(P\), NP-hard, FPT, or similar.
The closest near-miss is Proposition 2, proved in this paper: when a country wants to exit, a set of fiscal transfers that prevents its exit and is weakly preferred by every other member exists if and only if the exit is socially inefficient. That is a substantive existence result, but it does not analyze the computational complexity of finding the transfers. Propositions 1 and 3–6 likewise establish economic conditions about union formation, exit costs, credibility, and post-exit deals.
A continuum of many small member jurisdictions could be a sensible extension: types might encode preferences, trade technologies, and shock parameters; mass would represent the share of members of each type; and the model could study exit mass and transfers. But the paper’s results concern a finite set of countries and a shock to an individual country. That extension would be a new model, not a continuous mirror of a named computational result here. So, under the requested anchor rule, there is no honest continuous problem to hand to a prover for this paper.
The strongest negative case is that there is no computational result here to continuize. Propositions 1–6 establish equilibrium and welfare claims: when unions form, when exits are efficient, whether transfers or exit costs help, and when post-exit deals benefit the parties. None states a complexity result or studies an algorithmic problem.
Proposition 2 is the closest candidate, but it proves an economic existence claim: voluntary transfers that prevent an exit exist exactly when that exit is socially inefficient. Its proof even constructs a transfer scheme from the members’ welfare changes. One could ask how to compute transfers in a new model, but that would add an algorithmic problem to the paper rather than mirror one it studies.
The best attempt at a continuous version would treat countries as a distribution of types and ask whether transfers can prevent an exiting mass from leaving. That changes the key event. A single country has an identity and its own market and exporting firm; in a nonatomic population it has zero mass, so its departure has no aggregate effect on the other members—the spillover that motivates Proposition 2 disappears. Give a type positive mass and the event becomes a bloc exit, with different effects on union policy and market access. Keep one country as a positive-mass atom and the model becomes a hybrid centered on a distinguished member. Each could support new economic analysis, but none is the continuous-population version of the proposition’s single-country exit.
A large cohort of similar jurisdictions in a voluntary standards union is a conceivable setting for that new work. That is the negative case’s weak point: the authors might recognize such an extension as relevant. But it still supplies no computational anchor in this paper. Making it a computational-social-choice project would require introducing computational questions and structure the paper does not contain.
The adversarial triple: the proponent anchors on up to three named results; the opponent sees that case and must defeat every anchor; the judge decides which case convinced it. These are the pipeline’s own outputs, generated by tools/triple_run.py — no human edited them. The paper’s own text is not reproduced here beyond the quoted statement above.