Not all informal payments are bad: Instrumental variable investigation of the effect of sand-the-wheels, cultural norm, and grease-the-wheels types of payments on life satisfaction
Bibliographic record
Abstract
In this study, we investigate the effect of making different types of informal payments in public services on life satisfaction. We theorize that the effect of different informal payments on life satisfaction is not universally negative. Specifically, we hypothesize that the direction of the effect depends on the specific type of motivation for making such payments. As such, we articulate three hypotheses on the effect of specific motivations for making informal payments on life satisfaction. Hypothesis 1 postulates that “sand-the-wheels” payments reduce life satisfaction. Hypothesis 2 posits that “cultural norm” payments improve life satisfaction. Hypothesis 3 proposes that “grease-the-wheels” payments improve life satisfaction. We tested these hypotheses on a large sample of 29 diverse countries in Eastern Europe and the former Soviet Union using the quasi-experimental two-stage IV technique and one-stage classic OLS regression. Hypotheses 1 and 2 are confirmed by both IV and OLS. Conversely, Hypothesis 3 cannot be confirmed by either IV or OLS. We conclude that focusing on informal payments in general, rather than on evaluating specific motivations for making them masks the true outcomes of making such payments. Hence, while designing, implementing, and studying anti-corruption policies, decision-makers and researchers should distinguish between different motivations for making informal payments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".