Trust in Banks - Evidence from normal times and from times of crises
Bibliographic record
Abstract
Trust in financial institutions is of great importance for financial intermediation. Against this background, we study two questions: Has trust in banks declined during the global financial crisis and what factors determine the level of trust in banks? Employing survey evidence from Austrian households, we show that trust in banks is mainly affected by subjective variables like the individuals' assessment of the current economic and financial situation and by their future outlooks. After controlling for these variables we show that the financial crisis has caused a reduction in trust (ca. -7.5pp) which is sizable but not dramatic. Even at its lowest point (in the first quarter of 2009) 65% still report to have trust in the banking system, which is a higher percentage than for many other institutions. Furthermore, the drop is only slightly larger than the drop observed after a small, non-systemic crisis that occurred in 2006. Thus, the much-stressed notion of a genuine trust crisis is not reflected in our data. Finally, we provide evidence that the degree of individual information does not influence trust, that banking trust is contagious and that the extension of deposit insurance coverage in October 2008 had a positive effect on trust.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".