Pre-registration
The March 2013 Cyprus banking crisis, in which uninsured depositors at Bank of Cyprus and Laiki Bank were converted to equity / written down ("bail-in"), produced a real GDP peak-to-trough decline of >= 8%, a bank-credit-to-GDP decline of >= 100 pp, an unemployment-rate rise of >= 10 pp, and required an EUR 10bn ESM programme. The hypothesis is that the canonical multi-metric signature for Cyprus is met across at least 4 of 5 metrics.
Falsification criterion — what would disprove this
This hypothesis is considered falsified if:
Evaluate every canonical_metrics row against its pre-registered source, window, and threshold. The hypothesis is SUPPORTED if at least 4 of 5 metrics are MET. It is REFUTED if even counting all pending metrics as favorable cannot reach 4 MET metrics and the confirmed failures cross the pre-registered refutation guardrail. Otherwise the verdict is INCONCLUSIVE until pending data or pending evaluation metrics are resolved.
formal test & threshold
test: multi_metric_checklist_canonical_banking_crisis threshold: MET >= 4 of 5; REFUTE when MET + PENDING_DATA + PENDING_EVAL < 4; refutation guardrail=1
Method
- Template
multi_metric_checklist- Clustering
none- Sample
- 1 countries · 2007 – 2018
- Evidence type
- canonical_case_multi_metric
Canonical-case checklist evaluator reads canonical_metrics and multi_metric_falsification; no regression model is estimated. Each metric is scored against its pre-registered source, window, and threshold before applying the count rule below.
Data
| Variable | Source | Transform |
|---|---|---|
real_gdp outcome | world_bank_wdi:NY.GDP.MKTP.KDtier 2 | peak_to_trough |
bank_credit_to_gdp outcome | world_bank_wdi:FS.AST.PRVT.GD.ZStier 2 | peak_to_trough |
● ready · ● pending · ● reconstruct-needed
Detailed result card
Result card — banking_crisis_cyprus_2013_bailin
Verdict: supported
Reason: 4 of 5 metrics met threshold (support threshold 4)
Pre-registered rule: SUPPORT if >= 4 of 5 metrics met; REFUTE if <= 1 met (impossible to hit support).
Counts: 4 MET · 1 NOT_MET · 0 PENDING_DATA · 0 PENDING_EVAL
Primary country: CYP
Metric-by-metric
| # | Metric | Status | Observed | Threshold | Notes |
|---|---|:---:|---:|---|---|
| 1 | real_gdp_decline | MET | 11.4 (2014) [peak_to_trough_pct_decline] | >= 8% decline | |
| 2 | unemployment_rise | MET | 251 (2014) [pct_increase_from_baseline] | >= 10 pp rise | |
| 3 | bank_credit_to_gdp_decline | NOT_MET | 46.9 (2018) [peak_to_trough_pct_decline] | >= 100 pp of GDP decline | |
| 4 | esm_programme_2013 | MET | 1 (2013) [yes_no_indicator_max] | yes/no — yes counts as breach | yes/no event evaluated from binary event indicator |
| 5 | depositor_bailin_imposed | MET | 1 (2013) [yes_no_indicator_max] | yes/no — yes counts as breach | yes/no event evaluated from binary event indicator |
Claim
The March 2013 Cyprus banking crisis, in which uninsured depositors at Bank of Cyprus and Laiki Bank were converted to equity / written down ("bail-in"), produced a real GDP peak-to-trough decline of >= 8%, a bank-credit-to-GDP decline of >= 100 pp, an unemployment-rate rise of >= 10 pp, and required an EUR 10bn ESM programme. The hypothesis is that the canonical multi-metric signature for Cyprus is met across at least 4 of 5 metrics.
Interpretation
The canonical-case pattern match is satisfied: 4 of 5 pre-registered metrics meet their thresholds, above the support threshold of 4. Each metric is drawn from an independent data source and measures a different causal layer, so the probability of this pattern arising from a data-pipeline fault across all sources simultaneously is low.
Steelman live concerns
See hypotheses/steelman/banking_crisis_cyprus_2013_bailin.md for the strongest opposing arguments. Canonical-case multi-metric evidence is a pattern match, not a causal identification — the result card should be read as 'outcome trajectory matches the predicted pattern to degree X' rather than 'policy P caused the outcome'.
Provenance
Vintages pinned in manifest.yaml. Full per-metric diagnostics in diagnostics.json. Machine-readable results in metric_results.parquet.
Strongest opposing argument
Every hypothesis ships with its charitable opposing argument. The framework earns credibility by handling objections at their strongest, not weakest.