IESET.
Hypotheses·regulatory·banking_crisis_italy_2016_2017_mps

Italy's 2016-2017 banking-distress episode — Banca Monte dei Paschi di Siena precautionary recapitalisation in July 2017, Veneto-banks resolution in June 2017, and a peak system-wide non-performing-loan ratio above 17% — represents a protracted-NPL-overhang post-GFC banking distress case that did NOT meet the canonical full-systemic-banking-crisis threshold but DID require multiple state-aid resolution events.

The hypothesis is that Italy 2016-2017 meets a deliberately- weaker multi-metric checklist on at least 3 of 4 metrics, while explicitly NOT meeting the full Laeven-Valencia systemic-crisis threshold.

SUPPORTEDengine/runs/banking_crisis_italy_2016_2017_mps

SUPPORTED

confidence cueThis is a clear pass for the claim as written. It still applies only to this sample, period, and method.

policy briefClear support

In ordinary language

In plain terms, this asks whether the policy story survives a real-world data check from 2010 to 2020.

plain answer

The data clearly moved in the predicted direction. SUPPORTED

why it matters

This matters because regulatory claims should change belief only when they survive a pre-declared empirical test.

how the test works

It compares 1 country or place units from 2010 to 2020, using a multi metric checklist design.

what was measured
What we checked
  • Bank npl ratio
  • Bank credit to income
what this does not prove

A single test is not the whole truth. It narrows the claim under a specific sample, time period, and method. Strong policy conclusions need the pattern to survive nearby tests, alternative data, and serious objections.

verification

4 input datasets, 0 unresolved missing series, provenance status: reproducible hash verified.

Results

engine/runs/banking_crisis_italy_2016_2017_mps
1007550250201020152020ITA
illustrative sketch · run pending
No coefficients yet. When the model fires, this chart will show bank_npl_ratio across 1 sampled countries over 2010–2020.
The shapes above are stylised — none of the lines are real data.
Placeholder for banking_crisis_italy_2016_2017_mps. Published chart will be generated from engine/runs/banking_crisis_italy_2016_2017_mps/chart_data.json.

Pre-registration

pre-registered
first-spec commit 098ce96 · 2026-04-30T12:57:33Z
run generated · 2026-05-15T20:30:32Z

Italy's 2016-2017 banking-distress episode — Banca Monte dei Paschi di Siena precautionary recapitalisation in July 2017, Veneto-banks resolution in June 2017, and a peak system-wide non-performing-loan ratio above 17% — represents a protracted-NPL-overhang post-GFC banking distress case that did NOT meet the canonical full-systemic-banking-crisis threshold but DID require multiple state-aid resolution events. The hypothesis is that Italy 2016-2017 meets a deliberately- weaker multi-metric checklist on at least 3 of 4 metrics, while explicitly NOT meeting the full Laeven-Valencia systemic-crisis threshold.

Falsification criterion — what would disprove this

set before the run · honoured after

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 3 of 4 metrics are MET. It is REFUTED if even counting all pending metrics as favorable cannot reach 3 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 >= 3 of 4; REFUTE when MET + PENDING_DATA + PENDING_EVAL < 3; refutation guardrail=1

Method

Template
multi_metric_checklist
Clustering
none
Sample
1 countries · 2010 – 2020
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

VariableSourceTransform
bank_npl_ratio
outcome
world_bank_wdi:FB.AST.NPER.ZStier 2
peak_level
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_italy_2016_2017_mps

Verdict: supported

Reason: 4 of 4 metrics met threshold (support threshold 3)

Pre-registered rule: SUPPORT if >= 3 of 4 metrics met; REFUTE if <= 1 met (impossible to hit support).

Counts: 4 MET · 0 NOT_MET · 0 PENDING_DATA · 0 PENDING_EVAL

Primary country: ITA

Metric-by-metric

| # | Metric | Status | Observed | Threshold | Notes | |---|---|:---:|---:|---|---| | 1 | bank_npl_ratio_peak | MET | 18.1 (2015) [max_in_window_fallback] | >= 16% gross NPL ratio | | | 2 | mps_precautionary_recap | MET | 1 (2017) [yes_no_indicator_max] | yes/no — yes counts as breach | yes/no event evaluated from binary event indicator | | 3 | veneto_banks_resolution | MET | 1 (2017) [yes_no_indicator_max] | yes/no — yes counts as breach | yes/no event evaluated from binary event indicator | | 4 | bank_credit_to_gdp_decline | MET | 18.3 (2018) [peak_to_trough_pct_decline] | >= 15 pp of GDP decline | |

Claim

Italy's 2016-2017 banking-distress episode — Banca Monte dei Paschi di Siena precautionary recapitalisation in July 2017, Veneto-banks resolution in June 2017, and a peak system-wide non-performing-loan ratio above 17% — represents a protracted-NPL-overhang post-GFC banking distress case that did NOT meet the canonical full-systemic-banking-crisis threshold but DID require multiple state-aid resolution events. The hypothesis is that Italy 2016-2017 meets a deliberately- weaker multi-metric checklist on at least 3 of 4 metrics, while explicitly NOT meeting the full Laeven-Valencia systemic-crisis threshold.

Interpretation

The canonical-case pattern match is satisfied: 4 of 4 pre-registered metrics meet their thresholds, above the support threshold of 3. 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_italy_2016_2017_mps.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.

Authored framework. Read the transparency note.