Early warning indicators
Credit gaps, asset price growth and debt service ratios are tested for their ability to signal crises, with false alarm and missed crisis rates reported.
GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Econometrics for financial stability
Econometrics estimates relationships from data and tests whether they hold. On this platform it measures credit cycles, early warning indicators, spillovers and the effects of policy, with uncertainty and identification stated.
01Register
Econometrics for financial stability on the record.
Method recordSTEM method
- MethodEconometrics
- StewardEconomic Development
- Applied inFinancial Stability
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What econometrics does here.
Econometrics applies statistical methods to economic data to estimate relationships, test theories and forecast. It provides empirical evidence on how shocks and policies affect economic outcomes. In financial stability, risk management and systemic risk and capital markets and investment, econometric evidence estimates how disasters, pandemics and financial shocks affect output, employment and prices. It informs the economic case for risk reduction. The canonical description is on the STEM Commons.
Quantile regression for growth-at-risk
The distribution of future growth is estimated conditional on financial conditions, showing how downside risk changes.
Spillover estimation
Vector autoregressions and connectedness measures estimate how shocks in one market or country affect others.
03Stress test
How a shock to assets becomes a system loss.
The equity the system loses after interbank contagion, against the initial hit, as leverage, interconnection and recovery rates change, the core of a macroprudential stress test. Teaching model with stated illustrative values, not a prediction.
Controls
- Fall in external assets
- 2.0%
- Leverage (assets over equity)
- 10 times
- Interbank share of assets
- 10%
- Recovery on interbank claims
- 40%
- Banks in the system
- 20
- Core banks
- 20% of banks
Readouts
- Equity lost to the initial shock
- 18.0%
- Equity lost after contagion
- 45.0%
- Added by contagion (DebtRank)
- 27.0 points
- Banks in default
- 0
Numbers, methods and sources
| Round | System equity lost (%) | Banks in default |
|---|---|---|
| 0 | 18.00 | 0 |
| 1 | 28.80 | 0 |
| 2 | 35.28 | 0 |
| 3 | 39.17 | 0 |
| 4 | 41.50 | 0 |
| 5 | 42.90 | 0 |
| 6 | 43.74 | 0 |
| 7 | 44.24 | 0 |
| 8 | 44.55 | 0 |
| 9 | 44.73 | 0 |
| 10 | 44.84 | 0 |
| 11 | 44.90 | 0 |
| 12 | 44.94 | 0 |
| 13 | 44.96 | 0 |
| 14 | 44.98 | 0 |
| 15 | 44.99 | 0 |
| 16 | 44.99 | 0 |
| 17 | 45.00 | 0 |
| 18 | 45.00 | 0 |
| 19 | 45.00 | 0 |
| 20 | 45.00 | 0 |
| 21 | 45.00 | 0 |
| 22 | 45.00 | 0 |
| 23 | 45.00 | 0 |
| 24 | 45.00 | 0 |
| 25 | 45.00 | 0 |
| 26 | 45.00 | 0 |
| 27 | 45.00 | 0 |
| 28 | 45.00 | 0 |
| 29 | 45.00 | 0 |
| 30 | 45.00 | 0 |
Methods
- DebtRank Battiston and others (2012), Scientific Reports 2:541
- Differential DebtRank Bardoscia and others (2015), PLOS ONE 10
- Contagion in financial networks Gai and Kapadia (2010), Proc. R. Soc. A 466
- Clearing in financial networks Eisenberg and Noe (2001), Management Science 47
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme's own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Financial Stability in Foundry
- Tested at Financial Stability in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Financial Stability in Reports
- Taught in Faculty of Finance and Economics in Academy
04Data
What the method consumes.
Datasets and records used by econometrics on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| BIS credit statistics | Credit cycles | Published statistics |
| Financial conditions indices | Market stress | ESTIMATED |
| Crisis databases | Event dating | REPORTED |
| National accounts | Real activity | Published statistics |
05Exposure, loss and capital
What econometrics for financial stability means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in econometrics for financial stability reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
06Validation
How results are checked.
Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.
| Check | How it is done |
|---|---|
| Out-of-sample performance | Indicators are tested on periods not used to fit them |
| Robustness | Results are checked across specifications and samples |
| Signal-to-noise | False alarms are reported alongside correctly signalled crises |
Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.
07Connections
Topics that rely on this method.
08Stewardship
Who maintains the method.
Economic Development stewards econometrics for the Consortium and reviews how it is applied across platforms.
09Connected
Where this page leads across the Consortium.
10Questions
Questions and answers.
What are the limits of econometrics in this field?
Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.
How are results checked?
Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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