## Stress Testing and Calibration of Macroprudential Policy Tools

_IMF Working Papers, August 14, 2020_

## Source details

**Canonical URL:** [Stress Testing and Calibration of Macroprudential Policy Tools](https://www.imf.org/en/publications/wp/issues/2020/08/14/stress-testing-and-calibration-of-macroprudential-policy-tools-49677)

## Other formats

- [Markdown version](/en/publications/wp/issues/2020/08/14/stress-testing-and-calibration-of-macroprudential-policy-tools-49677/index.md)
- [Structured JSON version](/en/publications/wp/issues/2020/08/14/stress-testing-and-calibration-of-macroprudential-policy-tools-49677/index.json)
- [Bundle manifest](/en/publications/wp/issues/2020/08/14/stress-testing-and-calibration-of-macroprudential-policy-tools-49677/bundle-manifest.json)

## Bibliographic details
- Authors: Lucyna Gornicka, Laura Valderrama
- Published: August 14, 2020
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781513554471.001

---

### Summary
- Presents a semi-structural model of default risk as a function of loan and borrower characteristics, economic conditions, and the regulatory environment.
- Uses the model to simulate bank credit losses for stress-testing purposes and to calibrate borrower-based macroprudential tools.
- Emphasizes flexibility for situations with limited crisis history, unanticipated shocks, or structural/regulatory changes altering the loan default process.
- Applies the model to quantify mortgage lending risk in two distinct mortgage markets.
- Model features enable counterfactual analysis and evaluation of macroprudential policy interventions.

### Model and Methodology
- Core construct: semi-structural default-risk model dependent on loan characteristics, borrower characteristics, economic conditions, and regulatory environment.
- Input data: bank portfolio data broken down by risk bucket and vintage, enabling explicit account of the loan life cycle.
- Incorporates housing and economic cycles to simulate portfolio-level credit losses.
- Suitable for stress-testing and for calibrating borrower-based macroprudential tools.
- Particularly useful when:
  - There is limited history of crisis episodes.
  - Crises bring unanticipated shocks where past tail events offer little guidance.
  - Structural shocks or changes in financial regulations have altered the loan default process.

### Applications and Country-Specific Adjustments
- Applied to mortgage lending risk in two distinct mortgage markets.
- For each application, the paper demonstrates a range of modeling adjustments to capture country-specific institutional features.
- Use of vintage and risk-bucket breakdown allows:
  - Explicit loan life-cycle modeling.
  - Incorporation of housing and economic cycle dynamics.
  - Timely assessment of banks’ loss-absorbing capacity and buildup of systemic risk conditional on policy.

### Policy Relevance and Uses
- Facilitates stress-testing to estimate bank credit losses under alternative scenarios.
- Enables calibration of borrower-based macroprudential tools.
- Supports counterfactual analysis to evaluate macroprudential policy interventions.
- Helps assess systemic risk accumulation and banks’ capacity to absorb losses conditional on policy choices.

---

## Content in this bundle

- **Working Paper**
  - [Working Paper (Markdown version)](/-/media/files/publications/wp/2020/english/wpiea2020165-print-pdf.pdf.md){rel="alternate" type="text/markdown"}
  - [Working Paper (PDF)](/-/media/files/publications/wp/2020/english/wpiea2020165-print-pdf.pdf){rel="external" type="application/pdf"}

---

_Source: https://www.imf.org/en/publications/wp/issues/2020/08/14/stress-testing-and-calibration-of-macroprudential-policy-tools-49677_