Exploring Association between Self-Reported Financial Status and Economic Preferences Using Experimental Data
Bibliographic record
Abstract
Research on economic behaviour of individuals in different financial statuses such as being in a good financial standing or in a threatening financial situation are inconclusive. Some evidence suggest that the culture of poverty may shape and dominate the economic preferences of those who are poor and even make them being prone to trembling and making mistakes thereby making decisions that do not maximize their utility. Other evidence suggest that the poor exercise extra caution and fail to maximize utility. This study investigates the association between self-reported financial status and economic preferences in a developing country setting using data from an incentivized experiment and a survey. Extended random effects panel probit regression models are employed as an analytical strategy. The study established a positive association between being financially broke or very broke and being risk averse. In addition, a positive association is found between being financially ‘very broke’ and impatient. Such findings illustrate the importance of psychology of poverty in economic preferences and in decision-making in general, even as poverty is temporary as represented by self-reported financial status.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".