Power Fluctuations and Political Economy
Bibliographic record
Abstract
We study the constrained Pareto efficient allocations in a dynamic production economy in which the group that holds political power decides the allocation of resources.We show that Pareto efficient allocations take a quasi-Markovian structure and can be represented recursively as a function of the identity of the group in power and updated Pareto weights.For high discount factors, the economy converges to a first-best allocation in which labor supply decisions are not distorted and the levels of labor supply and consumption are constant over time (though there may be transfers from one group to another).For low discount factors, the economy converges to an invariant stochastic distribution in which distortions do not disappear and labor supply and consumption levels fluctuate over time.The labor supply of groups that are not in power are taxed in order to reduce the deviation payoff of the party in power and thus relax the political economy/sustainability constraints.We also show that the set of sustainable first-best allocations is larger when there is less persistence in the identity of the party in power.This result contradicts a common conjecture that there will be fewer distortions when the political system creates a "stable ruling group".In contrast, political economy distortions are less important when there are frequent changes in power (because this encourages compromise between social groups).Despite this result, it remains true that distortions decrease along sample paths where a particular group remains in power for a longer span of time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".