Endogenous timing and income inequality in the voluntary provision of public goods: Theory and experiment
Bibliographic record
Abstract
Abstract This study theoretically and experimentally investigates the effects of income inequality on donors' decisions regarding timing choices and contributions to public goods when contribution timing is endogenously chosen by contributors. To this end, we use the conventional voluntary provision models of Warr (1983) and Bergstrom, Blume and Varian (1986), with Cobb–Douglas preferences augmented with a two‐stage game of Hamilton and Slutsky (1990). The following results were obtained and experimentally confirmed. First, when the distribution of income is extremely unequal, donors are indifferent between the simultaneous and sequential moves in the contribution game. Second, as income inequality is decreased, the simultaneous‐move contribution game is likely to emerge because every donor prefers to act as a leader. Nevertheless, a higher‐income donor may also prefer to act as a follower without specific social preferences and uncertainty regarding the quality of public goods. Third, most theoretical predictions regarding timing decisions are supported in our laboratory experiment, provided that the participants had enough time to learn the consequences of their timing choices.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".