## _050416 - EXECUTIVE SUMMARY

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---

### Overview
- Comprehensive analysis and management of fiscal risks can help ensure sound fiscal public finances and macroeconomic stability.
- The global financial crisis and the collapse in commodity prices illustrate the vulnerability of public finances to risk.
- Over the past quarter century, governments experienced on average an adverse fiscal shock of 6 percent of GDP once every 12 years.
- The paper provides analytical tools and best practices to assess and manage fiscal risks, including fiscal stress tests and probabilistic forecasting.
- May 4, 2016

### Key findings on the scale and nature of fiscal risks
- Conventional fiscal risk analysis often assumes risks are modest, independent, symmetric, and linear; empirical evidence challenges these assumptions.
- Fiscal shocks tend to be:
  - Large: average adverse fiscal shock of 6 percent of GDP once every 12 years; a large event (costing over 9 percent of GDP) occurring every 18 years on average.
  - Downside-biased: officials more prone to anticipate positive shocks than negative ones, leaving balance of risks skewed toward the downside.
  - Highly correlated: crises typically involve several contingent liability realizations occurring together.
  - Nonlinear in impact: larger macroeconomic shocks are disproportionately more damaging.
- Public debt levels at historic highs and interest rates at historic lows increase vulnerabilities across countries.

### Sources of fiscal risk (empirical survey of 80 countries, 1990–2014)
- Macroeconomic shocks:
  - Occur once every 12 years on average.
  - Average fiscal cost equivalent to around 9 percent of GDP.
  - Identification: nominal GDP growth falls by one standard deviation relative to its average; fiscal cost computed as loss in revenue from lost output versus five year pre-crisis average.
- Financial sector:
  - Government rescues of troubled financial institutions happen once every 24 years on average.
  - Average cost of about 10 percent of GDP; maximum observed fiscal cost 56.8 percent of GDP in the survey.
- Legal cases:
  - Average cost around 7.9 percent of GDP; maximum 15.3 percent of GDP.
- Subnational government rescues:
  - Average cost 3.7 percent of GDP; maximum 12.0 percent of GDP.
- State-owned enterprises (SOEs) bailouts:
  - Average cost 3.0 percent of GDP; maximum 15.1 percent of GDP.
- Private non-financial companies:
  - Average cost 1.7 percent of GDP; maximum 4.5 percent of GDP.
- Natural disasters:
  - Average cost 1.6 percent of GDP; maximum 6.0 percent of GDP.
- Public private partnerships (PPPs):
  - Average cost 1.2 percent of GDP; maximum 2.0 percent of GDP.
- Survey summary table:
  - Contingent Liability realizations: Number of Events 230; Events with Costs 174; Average fiscal cost 6.1 (% of GDP); Maximum 56.8 (% of GDP).

### The nature of fiscal risks (implications)
- Fiscal shocks can be very large:
  - Example: during the 2009 financial crisis, macroeconomic shocks averaged 2.4 standard deviations of their pre-2008 distribution across advanced economies for the 2008–2009 period.
- Forecast errors:
  - Average three-year ahead error for official forecasts of general government debt among EU Member States (excluding Latvia and the Czech Republic) was between 1 percent and 8 percent (percent of GDP).
- Correlation and compounding effects:
  - The average direct cost of a specific contingent liability realization is 6 percent of GDP, but the average increase in the debt-to-GDP ratio over the typical event is a much larger 15 percent of GDP because of accompanying macroeconomic deterioration and other realizations.
  - Only one third of the deterioration of debt ratios among the hardest hit countries during the global financial crisis was due to standard macro-fiscal dynamics; the remainder arose from crystallization of other fiscal risks.
- Nonlinear impacts:
  - Budget rigidities and revenue dynamics mean that larger shocks raise deficits and debts disproportionately compared to smaller shocks.

### Policy recommendations and analytical tools
- Improve fiscal risk disclosure, analysis, and data:
  - Comprehensive, reliable, and timely fiscal data covering all public entities, stocks, and flows are necessary foundations.
- Use fiscal stress tests:
  - Integrated fiscal stress tests can simulate effects of shocks on central forecasts and implications for government solvency, liquidity, and financing needs.
- Expand fiscal risk management toolkit:
  - Move beyond blunt, ad hoc limits on exposures toward instruments that transfer, share, or provision for risks.
  - Weigh benefits of reducing exposure against financial and other costs of mitigation policies.
- Adopt probabilistic forecasting:
  - Use simple probabilistic tools to map uncertainty around medium-term public debt trajectories.
  - Combine probabilistic tools with fiscal stress tests to assess probabilities of staying within debt ceilings embedded in fiscal rules.
- Tailor priorities by country group:
  - Priorities for advanced economies (AEs), emerging market economies (EMEs), and low-income countries (LICs) to improve analysis and management of fiscal risks.

### The Fund’s role
- The Fund supports improvements in fiscal risk analysis and management through:
  - Technical assistance in constructing public sector balance sheets.
  - Developing institutions and capacity to identify specific fiscal risks and quantify their potential impact.
  - Undertaking fiscal stress tests.
  - Integrating risks into the design of medium-term fiscal targets.

### Implications for fiscal policymakers (section 11 highlights)
- Policymakers require:
  - A comprehensive understanding of potential risks to public finances and their interrelationships.
  - A wider range of instruments for mitigating and managing those risks.
  - Explicit incorporation of fiscal risks when setting fiscal rules or targets.
  - Analysis of both costs and benefits of mitigating fiscal risks, informed by probabilities, macroeconomic consequences, and mitigation costs.
- State of disclosure and analysis (survey findings):
  - "Only about 30 percent of countries surveyed publish" quantitative macro-fiscal sensitivity and scenario analyses.
  - "Another 4 percent of countries have begun publishing stochastic projections of key fiscal aggregates in the form of fan charts."
  - "Only 28 percent of the surveyed countries publish" balance sheets; half of those exclude non-financial items.
  - "Two-thirds of countries surveyed include some discussion" of specific fiscal risks; "Only 16 percent surveyed publish a quantified fiscal risk statement listing the specific or 'discrete' risks."
  - "40 percent of countries surveyed publish some form" of long-term fiscal sustainability analyses.

### State of fiscal risk management (practices and instruments)
- Risk categorization:
  - Endogenous vs. exogenous; continuous vs. discrete; classification into probable/possible/remote to guide provisioning, insurance, or headroom.
- Direct controls and limits:
  - About "60 percent of countries place limits on guarantees and control their issuance."
  - "Three-quarters limit the liabilities of subnational governments or require them to comply with certain fiscal rules," but only half of these back rules with sanctions.
  - About "40 percent of countries control bank lending by imposing minimum lending standards."
  - Around one-third limit explicit liabilities to SOEs; around "10 percent of countries limit contingent liabilities from PPPs."
- Indirect measures and incentives:
  - About "three-quarters of countries regulate financial sector exposures."
  - Two-thirds impose performance targets on SOE boards; two-thirds require value-for-money assessments for PPPs.
  - "60 percent of commodity exporting countries have been able to diversify their tax base."
  - Only around "15 percent of countries charge risk-related fees to beneficiaries of government credit guarantees."
- Risk transfer and insurance:
  - Only about "one quarter of countries reinsure or securitize their credit guarantee portfolio."
  - Almost "60 percent require beneficiaries to post collateral."
  - About "5 percent of commodity exporting countries hedge commodity price risk."
  - About "20 percent impose a levy on their financial institutions."
  - About "two-thirds of countries insure public assets against the impacts of natural disasters."
- Provisioning practices:
  - More than "half of all countries have established explicit deposit insurance funds."
  - About half expense quasi-fiscal activities of SOEs in the budget and half set aside provisions for natural disasters.
  - About one-third provision for expected costs of guarantee calls or have guarantee funds.
  - Just under half of commodity exporters have established a stabilization fund.

### Fiscal Stress Test (FST): purpose and methodology
- Purpose:
  - Provide a comprehensive overview of potential shocks, capture interdependence between fiscal risks, integrate macroeconomic shocks and contingent liabilities, and examine impacts on flow and stock fiscal variables.
- Three summary indicators used by the FST:
  - Fiscal solvency: change to comprehensive net worth including present value of future revenues and expenditures.
  - Government liquidity: government gross financing needs from existing and additional new public debt issuance.
  - Government financing burden: share of interest expenditure in total government revenue.
- Two key FST elements:
  - Macroeconomic risks:
    - Model public finance reactions to a large, correlated shock to GDP, inflation, commodity prices, exchange and interest rates, housing and equity prices.
    - Base shock size and nature on realized tail-events from comparator countries.
    - Use a detailed fiscal model to account for nonlinear revenue-side effects and budget rigidities.
  - Contingent liabilities:
    - Account for explicit and implicit contingent liabilities and their interaction with macro shocks.
    - Identify and quantify contingent liabilities; assess sensitivity to macro variables; estimate likely cost under stress and potential asset recovery.

### Measuring implicit financial sector contingent liabilities (CCA approach)
- Use equity prices and balance sheet data to estimate expected losses and associated credit spreads (fair-value CDS).
- The difference between observed and fair-value CDS spreads indicates the market’s view of the implicit government guarantee (implicit subsidy).
- Empirical ranges (IMF 2014, as reported):
  - Implicit subsidy for systemically important banks: range from 15 basis points in the United States to 90 basis points in the euro area in 2013.
  - Expected value of corresponding implicit subsidy: from around $50 billion to $300 billion in 2011–12.
- Caveats:
  - CDS markets can be thin; spreads volatile in crises; calculations assume equity holders wiped out in full though in practice equity holders were sometimes bailed out.

### Illustrative FST country applications (Iceland and Peru)
- Iceland (illustrative outcomes):
  - Public debt increases by 55 percent of GDP by 2021 relative to baseline.
  - Contingent liability shock increases public debt by 18 percent of GDP (recapitalization).
  - Comprehensive net worth falls by around 70 percent of GDP.
  - Liquidity needs increase to over 25 percent of GDP.
  - Budget projected to return to surplus in 2025, before reopening to deficit due to demographic pressures.
- Peru (illustrative outcomes):
  - GDP falls 11.5 percent in real terms relative to trend growth in the first year.
  - Gross debt increases by around 50 percent of GDP by 2021.
  - Comprehensive net worth declines by 38 percent of GDP.
  - Liquidity needs peak at 15 percent of GDP in 2017.
  - Fiscal burden increases to 15 percent of revenues as interest spending rises.

### Integrating FSTs into policy
- Frequency and tailoring:
  - FSTs could be undertaken periodically and tailored to country characteristics and risk exposures.
- Data and modeling:
  - Ideally requires information on public assets and liabilities, contingent liabilities, and a detailed macro-fiscal model; can be done with simplifying assumptions when data incomplete.
- Policy uses:
  - Provide risk-based scenarios to support targeted mitigation, provisioning, and determination of fiscal headroom.

### Fiscal risk management stages (four-stage approach)
- (i) Identify sources and assess magnitude and likelihood.
- (ii) Assess whether mitigating steps should be taken to reduce exposure.
- (iii) Determine whether to budget for risks that are not mitigated.
- (iv) Determine whether additional fiscal headroom is needed to accommodate remaining risks.

### Accommodate: assessing fiscal headroom and trade-offs
- Governments should assess whether sufficient fiscal headroom exists to accommodate uninsured or unmitigated risks.
- Decision to self-insure depends on:
  - Size of risk exposure;
  - Government’s degree of risk aversion and appetite to self-insure.
- Costs and benefits:
  - Eliminating all fiscal risks or pre-funding all scenarios may be suboptimal.
  - Insurance may be preferable for high-impact, low-probability events; self-insurance may be cost-effective for moderate risks.
  - To minimize moral hazard, ensure those influencing probability/impact retain some risk (partial guarantees, deductibles).

### Institutional arrangements and country examples
- Good practices:
  - Establish a risk management policy and clear accountabilities.
  - Centralize oversight where efficient; establish central risk oversight bodies and central controls over major risks.
- Country examples:
  - New Zealand: Treasury authority over borrowing and contracting; agency monitoring; regular statement on managing fiscal risks; explicit parliamentary approval for explicit fiscal risks.
  - Australia: decentralized model; agencies report risks; Fiscal Risk Statement published with the budget.
  - United Kingdom: fiscal risk group in HM Treasury; publishes dashboard; OBR preparing in-depth fiscal risk report biennially.
  - South Africa: fiscal risk committee meets quarterly; supported by secretariat in Fiscal Policy Department.
  - United States: enterprise risk management office headed by a chief risk officer within Treasury.

### Public debt ceilings and probabilistic assessment (sections 4 and 44 highlights)
- As of 2014:
  - About 70 countries have a rules-based fiscal framework that includes an explicit cap on gross public debt.
  - More than 80 percent of countries with a debt ceiling also had binding constraints on the budget balance.
  - Most specific debt ceilings fall between 40 percent and 70 percent of GDP; clustering around 60-70 percent.
- Fiscal policy responsiveness:
  - By 2012 the primary balance tended to improve by about 0.4 percentage point for every 10 percentage points of GDP increase in the public debt ratio for EMEs; for AEs the response rose from around 0.2 to over 0.3.
- Probabilistic approach to debt ceilings:
  - Estimate probability of staying below debt ceiling by modeling distribution of macro-fiscal shocks, applying stochastic simulations, and incorporating a fiscal reaction function.
  - Illustration: emerging market in Europe with debt ceiling 60 percent of GDP and initial debt 40 percent of GDP shows a 15 percent probability that public debt exceeds 60 percent by the end of the conventional forecasting horizon.
  - For LICs, methods include multivariate joint normal draws and multivariate student-T extensions; safety margin concept defined relative to CPIA public debt threshold over a six-year horizon with 95 percent probability.

### Managing specific fiscal risks (Appendix 1 highlights)
- Financial sector:
  - Average cost of government intervention across crises over 1990–2014 amounted to 9.7 percent of GDP; maximum fiscal cost exceeding 55 percent of GDP.
  - Policy options: reduce state participation; strengthen regulation and loss-absorbing capacity; require banks to finance deposit insurance; resolution mechanisms; pre-funded deposit insurance schemes.
- Guarantees:
  - Global stock of government-guaranteed bonds estimated at US$1.4 trillion in 2012.
  - Among European countries, 11 have notional exposures in excess of 10 percent of GDP.
  - Measures: central authorizing point; quantitative limits; charge guarantee fees; require collateral; budget provisions; guarantee reserve funds.
  - Sweden example: mandatory guarantee fees equal to expected loss unless Parliament decides otherwise; fees paid into notional contingency fund; DMO prices fees.
- PPPs:
  - Risks: debt-like obligations and contingent obligations often not included in fiscal aggregates.
  - Controls: central approval, quantitative ceilings, value-for-money checks, independent review, risk allocation, transparent budgeting for lifetime costs.
  - Chile example: MoF approval required; fees charged for revenue guarantees; annual appropriation for potential loss.
- Natural disasters:
  - Between 1994 and 2013 total economic losses globally from natural disasters estimated at US$2.6 trillion.
  - Average country-specific fiscal cost across 1990–2014 sample: 1.6 percent of GDP; largest 6 percent of GDP.
  - Measures: early warning systems, reinsurance, catastrophe bonds, disaster contingency funds, mandated insurance, building codes.
  - Mexico example: annual budget provision in FONDEN with minimum 0.4 percent of the annual federal budget; parametric catastrophe bonds.
- Subnational governments:
  - Fiscal costs of subnational bailouts averaged around 3.5 percent of GDP per event over 1990–2014.
  - Measures: monitor financial health, classify municipalities by risk, impose explicit limits, credible no-bailout provisions, enforcement mechanisms.
  - Iceland example: three-year rolling balanced budget rule; limit debt to revenue ratio to 150 percent; Municipal Fiscal Oversight Committee with sanction powers.
- SOEs:
  - Average cost of government intervention in public sector enterprises over 1990–2014 amounted to about 3 percent of GDP.
  - Measures: monitor financial performance, strengthen governance, limit state participation, legislate no-bail-out clauses, require provisioning and transparent accounting.
  - South Africa example: PFMA requires corporate plans, ministerial approvals for guarantees and borrowing limits, Fiscal Liability Committee oversight.

### FST methodology and balance-sheet analysis (Appendix 2)
- FST components:
  - Macro-fiscal shock: large correlated shocks to GDP, inflation, exchange and interest rates, housing and equity prices, commodity prices (typical guidance: two to three standard deviations).
  - Contingent liability shock: identify likely realizations under stress, assess loss given default and potential recoveries; probabilistic extensions possible where data exist.
  - Balance sheet analysis: apply valuation changes to financial and non-financial assets and liabilities; include discounted future revenues and expenditures.
- Fiscal non-linearities observed:
  - Expenditure rigidities: persistent increase in expenditure-to-GDP ratio averaging 2 percent of GDP during large shocks, increasing with shock magnitude.
  - Revenue non-linearities: idiosyncratic shocks (property busts, financial crises, commodity shocks) lead to falls in revenue-to-GDP ratios averaging around 2 percent of GDP.
- Key FST outputs:
  - Solvency: change in comprehensive net financial worth.
  - Liquidity: gross financing needs (GFNs) including contingent liability assumptions.
  - Fiscal burden: interest cost relative to revenue.

### Public debt and sovereign bond yields (Appendix 3 findings)
- Sample: 31 AEs and 19 EMEs, 1990–2014.
- Main empirical findings:
  - An increase of one percentage point of GDP in gross public debt raises sovereign bond yields by about 3 bps in AEs, and by about 7 bps in EMEs.
  - An increase in government financial assets by one percentage point of GDP lowers government bond yields by about 17 bps in EMEs, but has no material impact in AEs.
- Selected coefficient estimates (as reported):
  - US 10-year bond yields (in percent): 0.478*** 0.641*** 0.032 -0.302 (standard errors: (0.130)(0.123)(0.273)(0.634))
  - VIX (index): -0.016 -0.003 0.024 -0.004 (standard errors: (0.014)(0.009)(0.019)(0.028))
  - Short-term interest rate (in percent): 0.551*** 0.451*** 0.857*** 0.820*** (standard errors: (0.082)(0.070)(0.091)(0.087))
  - Lagged gross debt (percent of GDP): 0.032** 0.027** 0.073*** 0.164** (standard errors: (0.013)(0.011)(0.016)(0.059))
  - Primary balance (percent of GDP): -0.060* -0.093*** -0.002 -0.260** (standard errors: (0.031)(0.032)(0.120)(0.104))
  - Expected inflation: 0.070 -0.024 0.168* 0.311 (standard errors: (0.110)(0.057)(0.081)(0.253))
  - Real GDP growth: -0.212* -0.125** -0.024 -0.128 (standard errors: (0.105)(0.058)(0.074)(0.138))
  - Lagged financial assets (percent of GDP): -0.021 -0.172*** (standard errors: (0.013)(0.039))
  - Constant (C): -0.220 -0.257 -3.062*** -3.561 (standard errors: (0.724)(0.364)(0.695)(2.520))
  - N: 552 363 228 99
  - R2: 0.694 0.790 0.797 0.871
  - Significance notation: Standard errors in parentheses; * p-value<0.1; ** p-value <0.05; *** p-value <0.01.
- Implications:
  - Markets price sovereign risk differently across AEs and EMEs; net debt matters more in EMEs.
  - Asset liquidity is a key caveat: many government financial assets may be illiquid and not readily liquidatable in stress.

*Source: EXECUTIVE SUMMARY, Analyzing and Managing Fiscal Risks: Best Practices (May 4, 2016).*

### EXECUTIVE SUMMARY

### _050416 - EXECUTIVE SUMMARY

### Overview
- Comprehensive analysis and management of fiscal risks can help ensure sound fiscal public finances and macroeconomic stability.
- The global financial crisis and the collapse in commodity prices illustrate the vulnerability of public finances to risk.
- Over the past quarter century, governments experienced on average an adverse fiscal shock of 6 percent of GDP once every 12 years.
- The paper provides analytical tools and best practices to assess and manage fiscal risks, including fiscal stress tests and probabilistic forecasting.
- May 4, 2016

### Key findings on the scale and nature of fiscal risks
- Conventional fiscal risk analysis often assumes risks are modest, independent, symmetric, and linear; empirical evidence challenges these assumptions.
- Fiscal shocks tend to be:
  - Large: average adverse fiscal shock of 6 percent of GDP once every 12 years; a large event (costing over 9 percent of GDP) occurring every 18 years on average.
  - Downside-biased: officials more prone to anticipate positive shocks than negative ones, leaving balance of risks skewed toward the downside.
  - Highly correlated: crises typically involve several contingent liability realizations occurring together.
  - Nonlinear in impact: larger macroeconomic shocks are disproportionately more damaging.
- Public debt levels at historic highs and interest rates at historic lows increase vulnerabilities across countries.

### Sources of fiscal risk (empirical survey of 80 countries, 1990–2014)
- Macroeconomic shocks:
  - Occur once every 12 years on average.
  - Average fiscal cost equivalent to around 9 percent of GDP.
  - Identification: nominal GDP growth falls by one standard deviation relative to its average; fiscal cost computed as loss in revenue from lost output versus five year pre-crisis average.
- Financial sector:
  - Government rescues of troubled financial institutions happen once every 24 years on average.
  - Average cost of about 10 percent of GDP; maximum observed fiscal cost 56.8 percent of GDP in the survey.
- Legal cases:
  - Average cost around 7.9 percent of GDP; maximum 15.3 percent of GDP.
- Subnational government rescues:
  - Average cost 3.7 percent of GDP; maximum 12.0 percent of GDP.
- State-owned enterprises (SOEs) bailouts:
  - Average cost 3.0 percent of GDP; maximum 15.1 percent of GDP.
- Private non-financial companies:
  - Average cost 1.7 percent of GDP; maximum 4.5 percent of GDP.
- Natural disasters:
  - Average cost 1.6 percent of GDP; maximum 6.0 percent of GDP.
- Public private partnerships (PPPs):
  - Average cost 1.2 percent of GDP; maximum 2.0 percent of GDP.
- Summary table from survey:
  - Contingent Liability realizations: Number of Events 230; Events with Costs 174; Average fiscal cost 6.1 (% of GDP); Maximum 56.8 (% of GDP).

### The nature of fiscal risks (implications)
- Fiscal shocks can be very large:
  - Example: during the 2009 financial crisis, macroeconomic shocks averaged 2.4 standard deviations of their pre-2008 distribution across advanced economies for the 2008–2009 period.
- Forecast errors:
  - Average three-year ahead error for official forecasts of general government debt among EU Member States (excluding Latvia and the Czech Republic) was between 1 percent and 8 percent (percent of GDP).
- Correlation and compounding effects:
  - The average direct cost of a specific contingent liability realization is 6 percent of GDP, but the average increase in the debt-to-GDP ratio over the typical event is a much larger 15 percent of GDP because of accompanying macroeconomic deterioration and other realizations.
  - Only one third of the deterioration of debt ratios among the hardest hit countries during the global financial crisis was due to standard macro-fiscal dynamics; the remainder arose from crystallization of other fiscal risks.
- Nonlinear impacts:
  - Budget rigidities and revenue dynamics mean that larger shocks raise deficits and debts disproportionately compared to smaller shocks.

### Policy recommendations and analytical tools
- Improve fiscal risk disclosure, analysis, and data:
  - Comprehensive, reliable, and timely fiscal data covering all public entities, stocks, and flows are necessary foundations.
- Use fiscal stress tests:
  - Integrated fiscal stress tests can simulate effects of shocks on central forecasts and implications for government solvency, liquidity, and financing needs.
- Expand fiscal risk management toolkit:
  - Move beyond blunt, ad hoc limits on exposures toward instruments that transfer, share, or provision for risks.
  - Weigh benefits of reducing exposure against financial and other costs of mitigation policies.
- Adopt probabilistic forecasting:
  - Use simple probabilistic tools to map uncertainty around medium-term public debt trajectories.
  - Combine probabilistic tools with fiscal stress tests to assess probabilities of staying within debt ceilings embedded in fiscal rules.
- Tailor priorities by country group:
  - The paper concludes with priorities for advanced economies (AEs), emerging market economies (EMEs), and low-income countries (LICs) to improve analysis and management of fiscal risks.

### The Fund’s role
- The Fund supports improvements in fiscal risk analysis and management through:
  - Technical assistance in constructing public sector balance sheets.
  - Developing institutions and capacity to identify specific fiscal risks and quantify their potential impact.
  - Undertaking fiscal stress tests.
  - Integrating risks into the design of medium-term fiscal targets.

*Source: EXECUTIVE SUMMARY, Analyzing and Managing Fiscal Risks: Best Practices (May 4, 2016).*

### 11. The size, timing, and nature of fiscal risks have important and fundamental

### 11. The size, timing, and nature of fiscal risks have important and fundamental implications for fiscal policy-making

### Implications for fiscal policymakers
- Require a comprehensive understanding of potential risks to public finances and their interrelationships.
- Require a wider range of instruments for mitigating and managing those risks.
- Must explicitly take fiscal risks into account when setting fiscal rules or targets.
- Should analyze both the costs and benefits of mitigating fiscal risks, informed by data on the probability of risks occurring, their macroeconomic consequences, and the financial and other costs of mitigation strategies.

### State of fiscal risk analysis — disclosure and analysis practices
- The Fund’s 2014 revisions to its Fiscal Transparency Code emphasize fiscal risk disclosure and analysis, but current practice often falls short; coverage and quality vary significantly by country development and risk nature.
- Survey basis: IMF’s budget institutions database for 58 countries (15 AEs, 31 EMEs, and 12 LICs), the International Budget Partnership Open Budget Survey and IMF COFA database of 158 countries.

Findings:
- Quantitative macro-fiscal sensitivity and scenario analyses:
  - "Only about 30 percent of countries surveyed publish these."
  - Most examine sensitivity to individual macroeconomic parameters; only a small number provide model-based scenario analyses exploring simultaneous shocks.
  - "Another 4 percent of countries have begun publishing stochastic projections of key fiscal aggregates in the form of fan charts."
- Balance sheets:
  - "Only 28 percent of the surveyed countries publish these."
  - Half of those cover only financial assets and liabilities, excluding non-financial items (land, mineral reserves, pension liabilities).
  - Only a handful of countries (including Australia and New Zealand) examine impacts of macro trends and policies on future government assets, liabilities, and net worth.
- Specific fiscal risks:
  - "Two-thirds of countries surveyed include some discussion of these in their budget documentation."
  - "Only 16 percent surveyed publish a quantified fiscal risk statement listing the specific or 'discrete' risks."
  - Fiscal risk statements typically disclose potential liability size but not likelihood.
- Long-term fiscal sustainability analyses:
  - "40 percent of countries surveyed publish some form of these."
  - Just over one half of this group regularly publish single long-term projections for age-related programs.
  - Some advanced countries (such as Australia, the United States, and United Kingdom) explore multiple long-term scenarios for government revenue and expenditure using a range of demographic and other assumptions.

Limitations of current approaches:
- Scenario and sensitivity analyses tend to explore only modest-sized shocks and assume independence, symmetry, and linearity.
- Balance sheet data tends to be backward-looking; few forecast asset and liability developments.
- Specific risk assessments focus on explicit contingent liabilities, underplaying or ignoring implicit liabilities (for example, to the domestic banking sector).
- Reporting and analysis are often fragmented across institutions and publications, with interrelationships between risks rarely explored.

### State of fiscal risk management — nature of risks and management practices
- Fiscal risks categorized by origin and occurrence:
  - Endogenous vs. exogenous:
    - Endogenous: generated from government activities; probability influenced by government actions; mitigated via controls on public sector activity (example: reducing credit guarantee issuance).
    - Exogenous: from outside government control; mitigation via instruments like insurance (example: natural disasters).
  - Continuous vs. discrete:
    - Continuous: regular events causing outturns to differ from forecasts; can be incorporated via conservative assumptions or state-contingent fiscal rules (example: Chile for commodity prices; Australia during recovery from the global financial crisis).
    - Discrete: irregular events; management depends on probability classification:
      - Probable: likely to materialize in near term — "expected cost of the risk should be provisioned for in the budget or medium-term forecast."
      - Possible: likely at some point but unlikely in near term — better managed via insurance, risk pooling, or buffer funds (examples: earthquake reinsurance in Turkey; World Bank Caribbean Risk Insurance Facility; deposit insurance funds).
      - Remote: potentially significant but difficult to predict (systemic financial crises or wars) — require sufficient fiscal headroom.

Fiscal risk management instruments and usage:
- Direct controls, ceilings, or caps:
  - About "60 percent of countries place limits on guarantees and control their issuance."
  - "Three-quarters limit the liabilities of subnational governments or require them to comply with certain fiscal rules," but only half of these back rules with sanctions/enforcement.
  - About "40 percent of countries control bank lending by imposing minimum lending standards."
  - Around one-third limit explicit liabilities to SOEs; around "10 percent of countries limit contingent liabilities from PPPs."
- Regulations, incentives, and other indirect measures:
  - About "three-quarters of countries regulate financial sector exposures" (leverage ratios, higher capital-adequacy for systemically important banks).
  - Two-thirds impose performance targets on SOE boards; two-thirds require value-for-money assessments for PPPs.
  - "60 percent of commodity exporting countries have been able to diversify their tax base."
  - Only around "15 percent of countries charge risk-related fees to beneficiaries of government credit guarantees."
- Risk transfer, sharing, or insurance mechanisms:
  - Utilized less frequently.
  - Only about "one quarter of countries reinsure or securitize their credit guarantee portfolio," though almost "60 percent require beneficiaries to post collateral."
  - About "5 percent of commodity exporting countries hedge commodity price risk."
  - About "20 percent impose a levy on their financial institutions."
  - About "two-thirds of countries insure public assets against the impacts of natural disasters."
- Provisioning:
  - Many countries provision by expensing expected costs, establishing contingencies, or setting aside financial assets.
  - More than "half of all countries have established explicit deposit insurance funds."
  - About half expense quasi-fiscal activities of SOEs in the budget and half set aside provisions for natural disasters.
  - About one-third provision for expected costs of guarantee calls or have guarantee funds.
  - Just under half of commodity exporters have established a stabilization fund.

Assessment:
- Current practice concentrates on direct controls over endogenous risks; instruments to discourage, share, or insure exogenous risks are underutilized.
- Risk management tends to be fragmented, ad hoc, focused on individual risk categories, with little integration across sources of risk and mitigation measures.
- Little evidence policymakers systematically weigh costs and benefits of interventions to identify cost-effective risk-reduction strategies.

### Integrating fiscal risk analysis — the Fiscal Stress Test (FST)
- Purpose:
  - Provide a comprehensive overview of potential shocks and capture interdependence between fiscal risks.
  - Integrate macroeconomic shocks and contingent liabilities using historical data.
  - Examine impacts on fiscal flow variables (revenue, expenditure, financing) and stock variables (government liabilities, assets, net worth).
  - Model a more extreme set of scenarios than existing techniques.
- Benefits:
  - Offers a more complete picture of scale, sources, and likelihood of shocks to public finances.
  - Deepens understanding of interactions among fiscal risks and helps target mitigation efforts.
  - Helps fine tune estimates of fiscal headroom needed to maintain fiscal flexibility and sustainability, especially when assessing the distribution of risks.

FST methodology — two key elements:
- Macroeconomic risks:
  - Models public finance reactions to a large, correlated shock to key fiscally relevant macro variables, typically including GDP, inflation, commodity prices, exchange and interest rates, and housing and equity prices.
  - Basing shock size and nature on realized tail-events from a range of comparator countries (acknowledging past may not predict future).
  - Uses a detailed fiscal model to account for nonlinear revenue-side effects and budget rigidities on the expenditure side.
- Contingent liabilities:
  - Accounts for the range and likelihood of explicit and implicit contingent liabilities and their interaction with large macro shocks.
  - Identifies and quantifies contingent liabilities and explores key underlying risk factors, assessing sensitivity to macro variables.
  - Estimates likely cost under stress scenarios and potential for asset recovery in later years.
  - Draws on sources such as Fiscal Transparency Evaluations, FSAP evaluations for the financial sector, and contingent claims analysis (CCA).

*Source: IMF chapter "11. The size, timing, and nature of fiscal risks have important and fundamental implications for fiscal policy-making" (ANALYZING AND MANAGING FISCAL RISKS: BEST PRACTICES).*

### 20. The FST looks at the combined impact of these shocks on the government’s

### _050416 - 20. The FST looks at the combined impact of these shocks on the government’s

### FST framework and measurement approach
- The FST examines combined shocks’ impacts on:
  - the government’s operating statement (flow impact through government revenue and expenditure), and
  - an extended “comprehensive” balance sheet (balance sheet impact through changes in the volume and value of conventional financial assets and liabilities and in the present value of future revenue and expenditures).
- Flow impacts can persist for a number of years; balance sheet impacts capture both financial positions and discounted future fiscal flows.

### Three summary indicators used by the FST
- Fiscal solvency:
  - Assessed by the change to comprehensive net worth, reflecting macro shocks and contingent liabilities on financial assets and liabilities and the present value of future revenues and expenditures.
- Government liquidity:
  - Assessed by government gross financing needs from existing and additional new public debt issuance needed in response to the shock.
- Government financing burden:
  - Assessed by the share of interest expenditure in total government revenue.

### Measuring implicit financial sector contingent liabilities (Box 1)
- Rationale:
  - Governments often implicitly support domestic financial sectors in stress periods; implicit guarantees are not on balance sheets but matter for fiscal risk.
- Contingent Claims Analysis (CCA) approach:
  - Use equity prices and balance sheet data to estimate expected losses and associated credit spreads (fair-value CDS).
  - The difference between observed and fair-value CDS spreads indicates the market’s view of the implicit government guarantee (implicit subsidy).
  - Apply the implicit subsidy estimate to the stock of outstanding debt liabilities (expected value of loss upon default) to estimate the expected value of the contingent liability.
- Empirical ranges (from IMF 2014, as reported):
  - Implicit subsidy for systemically important banks: range from 15 basis points in the United States to 90 basis points in the euro area in 2013.
  - Expected value of corresponding implicit subsidy: from around $50 billion to $300 billion in 2011–12.
- Uses of CCA information:
  - Provide market valuation of implicit government support for inclusion in a comprehensive risk-adjusted balance sheet.
  - Inform fiscal stress testing on potential cost of government support and realized costs of intervention.
  - Guide market expectations of support for particular banks.
  - Assess impact of risk management reforms (e.g., increased capital ratios, deposit insurance schemes, regulatory changes) on likelihood/cost of intervention.
- Caveats:
  - CDS markets can be thin or non-existent for many banks.
  - During crises, CDS spreads can be volatile and unreliable.
  - Calculations assume equity holders wiped out in full, but in practice equity holders were sometimes bailed out.
  - Recent regulatory changes aim for greater bail-in of creditors than in the global financial crisis.

### Illustrative country applications of the FST (Boxes 2 and 3)
- Purpose:
  - Demonstrate FST applicability across different income groups and risk exposures.

- Iceland (Box 2) — illustrative FST assumptions and outcomes:
  - Shocks assumed:
    - a three standard deviation real GDP shock,
    - a one-third fall in housing prices,
    - a fifty percent fall in equity prices,
    - increases in international interest margins,
    - large realization of contingent liabilities via recapitalization of the Housing Financing Fund.
  - Transmission:
    - Increases in unemployment, decreases in inflation and domestic interest rates (central bank response).
    - Housing-related revenue falls with house prices; large corporate losses reduce corporate tax revenues; salary and pension rigidities lift expenditure ratio.
  - Quantitative outcomes:
    - Public debt increases by 55 percent of GDP by 2021 relative to baseline.
    - Contingent liability shock temporarily increases fiscal deficit and increases public debt by 18 percent of GDP (from recapitalization).
    - Comprehensive net worth falls by around 70 percent of GDP (decline in net worth including future revenues and expenditures).
    - Budget not projected to return to surplus until 2025, before deficit opens again due to demographic pressures.
    - Liquidity needs increase sharply, to over 25 percent of GDP, despite long average maturity of existing debt (high financing needs to recapitalize Housing Financing Fund).
    - Financing needs increase to very high levels; fiscal burden increases but remains elevated and manageable.
  - Note:
    - The increase in public debt relative to baseline under the stress scenario is broadly in line with the increase experienced during the financial crisis.

- Peru (Box 3) — illustrative FST assumptions and outcomes:
  - Shocks assumed:
    - Large macroeconomic shock calibrated to largest shocks in comparator countries in the region.
    - Involves shocks to GDP, asset prices, corporate interest spreads and commodity prices (commodity exports account for around 55 percent of total exports).
    - GDP falls 11.5 percent in real terms relative to trend growth in the first year.
    - Double-headed contingent liability shock: recapitalization of some domestic banks and payout of a large international investor dispute (based on 2015 Peru Fiscal Transparency Evaluation).
    - FSGM Western Hemisphere module used for economic parameters.
  - Quantitative outcomes:
    - Gross debt increases by around 50 percent of GDP by 2021.
    - Comprehensive net worth declines by 38 percent of GDP (including impact of future revenues and expenditures).
    - Liquidity needs peak at a manageable 15 percent of GDP in 2017, reflecting relatively low existing debt burden.
    - Fiscal burden increases to 15 percent of revenues as interest spending rises against a relatively low revenue base.
  - Reasons for relatively smaller impact versus Iceland:
    - Peru’s fiscal exposure to such a shock is somewhat smaller (revenue collections less affected; less rigid budget expenditures).
    - Smaller and less risky balance sheet.
    - Lower contingent liabilities.

### Integrating FSTs into policy and policymaking
- Frequency and tailoring:
  - FSTs could be undertaken periodically by country authorities to enhance understanding of fiscal risks and inform policymaking.
  - Stress tests should be tailored to country characteristics and risk exposures.
- Data and modeling:
  - Ideally requires information on conventional public assets and liabilities, contingent liabilities and other exposures, and a detailed macroeconomic and fiscal model.
  - Even with incomplete information, stress tests can be undertaken using reasonable simplifying assumptions.
- Policy uses:
  - Provide comprehensive risk-based scenarios to support better-targeted and coordinated fiscal risk management interventions.
  - Encourage policies to mitigate risks—steps to reduce vulnerability of public accounts to macro shocks, discourage taking on contingent liabilities, and define the level of fiscal headroom needed.
  - Results can inform risk mitigation, provisioning, and decisions on fiscal headroom.

### Fiscal risk management stages (overview from the Fiscal Risk Toolkit)
- Four-stage management approach:
  - (i) Identify sources of fiscal risks and assess magnitude and likelihood of realization.
  - (ii) Assess whether mitigating steps should be taken to reduce fiscal exposure.
  - (iii) Determine whether to budget for risks that are not mitigated.
  - (iv) Determine whether additional fiscal headroom is needed to accommodate remaining fiscal risks.

### Identifying and quantifying risks
- Best practices:
  - Identify sources, quantify magnitude, and estimate probability of occurrence.
  - Quantitative estimates could include maximum possible loss (face value of guarantee) or expected fiscal impact or maximum loss at a specific confidence interval (where feasible).
  - Where quantification is difficult, classify risks into categories (e.g., probable, possible, remote) based on judgment.
  - Example practice: Australian Government’s Statement of Risks details quantifiable and unquantifiable contingent liabilities and specifies whether considered “remote.”

### Mitigating instruments and good practice (three broad categories)
- Direct controls to limit fiscal exposure:
  - Avoid engaging in certain commercial activities; limit state ownership of commercial activities; impose caps on public entities’ liabilities.
  - Examples: limits on sub-national borrowing; annual or multi-annual ceilings on issuance of government guarantees; capping payments associated with government insurance schemes.
- Indirect measures (regulation or charges) to reduce risky activities:
  - Regulate sources of risk (e.g., require banks to hold capital; building requirements in disaster-prone areas; environmental standards).
  - Discourage excessive risk-taking via incentives (e.g., eliminate debt bias in tax system; charge guarantee fees or insurance premiums to beneficiaries of government underwriting).
- Transferring/sharing risks:
  - Purchase insurance (e.g., Turkey for natural disasters), use hedging instruments (e.g., Mexico for oil prices), securitize and sell financial assets (e.g., U.K. student loans), state-contingent instruments (e.g., Mexico catastrophe bonds, Malawi weather derivatives).
  - Require beneficiaries to share risk (partial guarantees, collateral, deductibles).
  - Reinsure where feasible.

### Provisioning for unmitigated risks
- Options for provisioning:
  - Expense costs up-front in the budget (e.g., United States for credit guarantees; Australia for student loan defaults).
  - Create budget contingency for moderate-likelihood risks (e.g., Philippines for natural calamities; Colombia for expected calls on guarantees).
  - Negotiate contingent budget support (some LICs).
  - Set aside financial assets for larger risks (e.g., Chile’s stabilization fund; Canada’s deposit insurance fund).

### Fiscal Risk Management Toolkit (selected instruments and practices)
- Financial sector:
  - Quantify contingent exposures; monitor financial soundness and risk indicators; incorporate financial sector stress tests into debt sustainability analysis; require banks to fund deposit insurance schemes; resolution mechanisms (e.g., Living wills); maintain cash buffers; pre-fund deposit guarantee schemes; appropriate expected payments.
- Natural disasters and environmental risks:
  - Early warning systems; reinsurance; catastrophe bonds; cap payouts and require deductibles for government schemes; mandate insurance in high risk areas; disaster contingency funds; natural disaster funds; appropriate expended payments.
- Macro shocks (e.g., commodity prices):
  - Sensitivity analysis, alternative scenarios, probabilistic fan charts; hedging instruments (options, commodity futures); resource-based fiscal rules; prudent price assumptions; stabilization funds.
- Guarantees and PPPs:
  - Maintain central registry of guarantees and PPP commitments; assess risks at time of issue and over their life; partial guarantees; require collateral; reinsure if feasible; subject projects to sensitivity analysis; risk-sharing allocation frameworks; cap payments linked to demand; insure retained contract risks where feasible; guarantee funds; provision for expected calls.
- State-Owned Enterprises:
  - Quantify explicit exposures; monitor financial performance; scenario analysis or stress testing; explicit no-bail-out clauses; appropriate expected subsidies and QFAs; provision for cost in case of restructuring.
- Subnational government:
  - Monitor financial performance against benchmarks; establish credible no-bail-out clauses; retain authority to liquidate assets/appoint administrator; maintain appropriate expected support; rainy day funds.

*Source: International Monetary Fund (content unit provided)._

### 4. Accommodate

### 4. Accommodate

### Assessing fiscal headroom and trade-offs
- Governments should assess whether sufficient fiscal headroom exists to accommodate risks that cannot be insured or mitigated.
- Some risks may be too large to provision for, too costly to mitigate, or insufficiently known in precision.
- These risks should be taken into account when setting long-run targets for government debt or net worth (example cited: New Zealand) or by ensuring a safety margin relative to debt ceilings in fiscal rules.
- The decision to self-insure (via lower debt levels) depends on:
  - the size of the risk exposure to the public finances;
  - the government’s degree of risk aversion and appetite to self-insure.

### Costs and benefits of risk mitigation
- Reasons why eliminating all fiscal risks or maintaining buffers large enough to cover all scenarios may not be optimal:
  - Governments can often bear risk at lower cost where risks are ill defined, hard to quantify, information failures exist, or risks are catastrophic and nondiversifiable (examples: student loans, earthquakes, terrorism insurance).
  - Eliminating all risks to the financial system could require levels of deposit insurance and capital requirements that would unduly stifle credit creation and growth.
  - Governments may elect to bear risks for macroeconomic stability (e.g., automatic stabilizers, deposit guarantees to discourage bank runs).
  - Fiscal risk management must reflect societal risk aversion and rate of time preference (wealthier societies may be less concerned about low probability, high impact events; elderly populations may discount the future more highly).
- Principle: when markets are well functioning, risk should be borne by the entity best able and incentivized to manage it (IMF, 2008). Example: in PPPs, construction and design risks by private sector; regulatory and political risks possibly by government.
- Choice among bearing risk, mitigating, or provisioning should be based on costs and benefits:
  - For governments with policy flexibility and access to international credit markets, raising taxes or borrowing to meet realized costs may be less costly than ex-ante insurance.
  - Volatility in tax rates imposes costs; pre-funding through insurance vehicles or budget funds can provide tax-smoothing benefits and certainty of funding for countries lacking guaranteed market access.
  - Insurance may be more worthwhile for high-impact, low-probability events since insurance costs tend to fall with probability of loss (Cebotari, 2008).
  - Self-insurance may be more cost-effective for moderate risks.
- To minimize moral hazard when the government bears risks:
  - Ensure those influencing probability or impact bear some risk (retain “skin in the game”).
  - Use partial guarantees or require insurance deductibles.

### Institutional arrangements for fiscal risk management
- Sound institutional arrangements are needed; organizational setup depends on country specifics.
- Good practices include:
  - Establish a risk management policy outlining pre-conditions under which government will take on specific fiscal risks (loans, guarantees, PPPs).
    - Example: Canada’s guarantee and loan framework requires sponsoring public entity to demonstrate project could not be financed on reasonable terms without government loan or guarantee.
  - Define clear accountabilities: individual departments/line ministries responsible and accountable for identifying, estimating, analyzing, and monitoring specific fiscal risks within their functions.
    - Centralizing oversight (e.g., for SOEs or PPPs) in the MoF can yield economies of scale.
  - Establish a central risk oversight body to monitor aggregate risk exposures, identify systematic relationships and interactions between risks, establish risk-warning indicators, and undertake ‘war-gaming’ exercises.
    - The unit can assess adequacy of risk mitigation practices and recommend strengthening actions.
  - Establish central controls over major risks: authority to approve contracts exposing government to fiscal risks should be vested in a central authorizing entity (e.g., Minister of Finance or cabinet committee).
    - Decisions to take on risk should be assessed as part of the budget process.
    - Specific risk instruments (such as guarantees) should be benchmarked against traditional policy instruments and accounted for in agency budgets (examples: Sweden for guarantees; Australia for insurance premiums).

- Country examples (Box 5):
  - New Zealand: Treasury has ultimate authority and control over borrowing, contracting obligations and assessing fiscal risk; individual agencies primarily responsible for monitoring and provisioning; Treasury publishes a regular statement on managing fiscal risks; all explicit fiscal risks subject to parliamentary approval.
  - Australia: decentralized model; agencies manage and report risks through annual reports and contribute to a Fiscal Risk Statement published as part of the budget.
  - United Kingdom: fiscal risk group within HM Treasury chaired by the Treasury Chief Economist; produces a dashboard of fiscal risks with estimates of total exposure and rankings using a traffic light system; U.K. Office of Budget Responsibility preparing to publish an in-depth fiscal risk report every two years, in addition to semi-annual reporting.
  - South Africa: fiscal risk committee to identify and quantify major sources of fiscal risk, monitor risks, propose mitigating measures, and report internally and publicly; meets quarterly; supported by a secretariat in the Fiscal Policy Department of the Treasury.
  - United States: enterprise risk management office created, headed by a chief risk officer within the Treasury Department; considering establishing similar efforts in other agencies.

### Public debt ceilings and fiscal risk implications
- Explicit public debt ceilings are increasingly important in rules-based fiscal frameworks.
- Debt ceilings usually serve as a medium-term reference for binding constraints on the annual fiscal balance and, in some cases, on public expenditure growth.
- Debt ceilings matter because fiscal shocks can make day-to-day policy keep debt far below ceilings; frequent breaches can undermine credibility of rules-based frameworks. Well-defined escape clauses can mitigate frequent breaches but have costs (loss of credibility, implementation complexity).

A. Public Debt Ceilings: current practice
- About 70 countries worldwide currently have a rules-based fiscal framework that includes an explicit cap on gross public debt.
- As of 2014:
  - more than 80 percent of countries with a debt ceiling also had binding constraints on the budget balance;
  - among those, almost a third used expenditure ceilings as operational targets.
- Specific debt ceilings vary greatly; most fall between 40 percent and 70 percent of GDP.
  - Clustering around 60-70 percent reflects strong representation of European Union (EU) and West African Economic and Monetary Union (WAEMU) member states.
- Rules are mostly defined in terms of gross, rather than net, public debt.
  - Net debt can be more relevant when government assets can be easily liquidated, but net debt is complicated to establish, communicate, less transparent, and harder to compare across countries.

B. Fiscal policy responsiveness to public debt
- Fiscal policy in Advanced Economies (AEs) and Emerging Market Economies (EMEs) has become increasingly responsive to public debt over the last decade.
- Empirical staff estimates: by 2012 the primary balance tended to improve by about 0.4 percentage point for every 10 percentage points of GDP increase in the public debt ratio for EMEs.
  - For AEs the response rose from around 0.2 to over 0.3 over the same period.
  - No strong evidence that fiscal policy in Low-Income Countries (LICs) responded to changes in public debt.

C. Probabilistic assessments of debt ceilings
- Incorporating risk into public debt dynamics analysis helps authorities understand the probability of breaching debt ceilings.
- Probabilistic tools complement the Fiscal Stress Test (FST) by identifying the probability distribution of shocks, aiding decisions on appropriate buffer levels depending on risk aversion.
- Even if initial debt levels are above the ceiling, probabilistic analysis can inform the likelihood that policies will bring debt back to levels consistent with the debt rule and whether policy adjustments or rule changes are warranted.

*Source: _050416 - 4. Accommodate (ANALYZING AND MANAGING FISCAL RISKS: BEST PRACTICES), International Monetary Fund*

### 44. The suggested approach estimates the probability of staying below the debt ceiling,

### _050416 - 44. The suggested approach estimates the probability of staying below the debt ceiling,

### Probabilistic approach to assessing debt-ceiling breach risk
- Estimates the probability of staying below the debt ceiling by accounting for the range of shocks affecting debt dynamics and the average response of fiscal policy to these shocks.
- Estimation requires:
  - An understanding of drivers of debt dynamics over the medium-term, including the government’s capacity to generate and sustain primary balances and the uncertainty surrounding interest rates, growth, the budget itself, and other relevant variables.
  - A fiscal “reaction function” that captures the average empirical policy response to output shocks and to debt developments themselves.
  - Careful definition of the relevant timeframe: too short a horizon can understate breach risk or the probability of returning below the ceiling; too long a horizon undermines confidence in outer-year projections and produces probabilities with limited immediate relevance.

### Methodology: stochastic simulations and distributions
- Calculate probabilities of exceeding—or remaining below—the debt ceiling by:
  - Estimating the distribution of macroeconomic and fiscal shocks facing a country.
  - Performing stochastic simulations of future debt trajectories over the chosen time horizon.
  - Producing year-by-year distributions of debt realizations that allow calculation of probabilities that public debt exceeds a given threshold at any point in the projection period.
- Modeling options adapt to data availability and country type:
  - Explicit dynamic models of key drivers (appropriate for advanced economies and mature emerging markets).
  - Calibrated distributions of shocks (appropriate for frontier and low-income economies undergoing rapid structural transformation).
- Caveats:
  - Validity depends on the quality and stability of the statistical model and the relevance of relationships estimated from past data.
  - Need to ensure satisfactory goodness-of-fit and dynamic stability of VARs where used.

### Applying the probabilistic approach to Low-Income Countries (Box 6)
- Constraints and methodological novelties for LICs:
  - Volatility: country-specific volatility simulated by drawing from a multivariate joint normal distribution; as an extension, a multivariate student-T distribution (fatter tails) is also used to capture tail events.
  - Nature of shocks: simulations include standard macro variables (growth, interest rates, exchange rates) plus uncertainty regarding terms of trade (ToT) and access to external financing; median distribution of stock flow adjustments used to proxy contingent liabilities at the country level.
  - Financing mix: distinction between foreign versus domestic, and concessional versus non-concessional financing.
  - Fiscal behavior: a fiscal reaction function estimated for LICs indicates fiscal policy is often driven by financing constraints and ToT rather than by lagged debt; the primary balance does not react to lagged debt in these estimates.
- Utility:
  - Analyzes the distribution of debt under various shocks—a feature absent in the DSA framework for LICs.
  - Can assess the size of the “safety margin” needed to remain beneath DSA-indicated debt thresholds.
  - Illustration: a sample of 26 LICs shows safety margins (Percent of GDP, median); safety margins tend to be larger in commodity importers, but persistent ToT shocks can increase required safety margins for commodity exporters exponentially.
- Statistical notation and significance in Box 6:
  - Coefficient estimates displayed for a fiscal reaction function: Dependent Variable: Primary Balance (Percent of GDP).
  - Stars indicate statistical significance at one percent (three stars), five percent (two stars), and ten percent (one star).
  - Safety margin definition: distance between (i) the CPIA public debt threshold and (ii) the calibrated country-specific initial debt level that does breach the CPIA threshold under shocks over a six-year time horizon with a 95 percent probability.

### Illustration for an emerging market in Europe (Figure 9)
- Scenario:
  - Debt ceiling: 60 percent of GDP.
  - Initial debt level: 40 percent of GDP.
- Stochastic result:
  - Fan-chart projections indicate a non-trivial probability of 15 percent that public debt exceeds 60 percent by the end of the conventional forecasting horizon.
- Policy interpretation:
  - A quantitative probability informs judgment on whether risk is benign or requires policy adjustment, taking into account potential costs of adjustment.
  - Similar considerations could be formalized via escape clauses or regular reviews of the debt ceiling level.

### Incorporating low-frequency, high-impact events and contingent liabilities
- Contingent liabilities can have large fiscal impacts and are relatively frequent; example given:
  - Average financial sector intervention has entailed fiscal costs of roughly 10 percent of GDP.
- Modeling options:
  - Simulate the cost of a contingent liability shock occurring mid-projection and model its effect on public debt evolution.
  - The effect depends on factors including past fiscal behavior and historical policy responses to similar shocks.

### Key implications for fiscal risk management and policy priorities
- General guidance:
  - Risk-based fiscal policy-making benefits from probabilistic analysis; shocks are often tilted to the downside and can have highly nonlinear effects on public debt ratios.
  - Allowing debt ratios to remain too close to ceilings increases the risk of breach and can impair countercyclical and growth-enhancing policy responses.
- Priorities by country capacity and data availability:
  - Low-income countries and those with limited risk disclosure should prioritize:
    - Macro-fiscal sensitivity analysis, especially for shocks to prices and volumes of main export commodities.
    - Construction of a basic financial balance sheet focused initially on debt liabilities and liquid financial assets.
    - Improved understanding and disclosure of explicit contingent liabilities (guarantees, PPPs, disaster insurance).
  - As capacity grows:
    - Construct alternative macro-fiscal scenarios based on plausible shocks to key variables.
    - Incorporate natural resource assets and public pension liabilities into balance sheets where relevant.
    - Report and forecast government financial assets, liabilities, financial liquidity, and net worth.
    - Prepare comprehensive and quantified fiscal risk statements disclosing explicit and implicit contingent liabilities (including SOEs, subnational governments, and the financial sector).
  - Countries with comprehensive risk information and developed modelling should:
    - Disclose confidence intervals (“fan charts”) around forecasts for key variables.
    - Prepare comprehensive balance sheets of all assets and liabilities (including social benefits).
    - Publish fiscal risk statements that quantify size and, where possible, likelihood of explicit and implicit contingent liabilities.
    - Undertake periodic stress tests combining stochastic macro shocks with realizations of contingent liabilities to assess government liquidity, sustainability, and solvency; use results to inform long-term fiscal anchors and medium-term fiscal plans.
- Strengthening risk management capacity and tools:
  - Low-income countries: consider legally-binding limits and centralized authorization for guarantees, PPPs, sub-national and SOE borrowing to control creation of exposures.
  - Emerging market economies: use risk mitigation and transfer tools such as partial guarantees, risk-based fees, disaster reinsurance, and hedging instruments.
  - Advanced systems: explicitly recognize residual exposures in budgets and financial statements (expected calls on guarantees, PPP payments, subsidies to public enterprises, restitution of environmental damage).
  - All countries: strengthen macro-fiscal units in ministries of finance to monitor and analyze fiscal risks, develop mitigation policies, and feed outputs into regular senior-level discussions on emerging risks and mitigating actions.

### Role of the IMF
- IMF supports improvements in fiscal risk analysis and management by members through:
  - Assistance in constructing public sector balance sheets (key element of the G20 Data Gaps Initiative).
  - Helping develop institutions and capacity to identify and quantify fiscal risks.
  - Providing technical assistance and participation in Fiscal Transparency Evaluations to define priorities for fiscal risk disclosure and management.
  - Assisting in building integrated fiscal risk analysis frameworks like the Fiscal Stress Test and incorporating probabilistic methods into fiscal projections.
  - Integrating risk analysis into the design of medium-term fiscal targets within existing capacity development resources.

*Source: _050416 - 44. The suggested approach estimates the probability of staying below the debt ceiling,*

### Appendix 1. Managing Specific Fiscal Risks

### Appendix 1. Managing Specific Fiscal Risks

### Financial sector risks
- Findings:
  - Systemic banking crises have been associated with significant fiscal costs.
  - The average cost of government intervention in the financial sector across a sample of crises over the period 1990–2014 amounted to 9.7 percent of GDP, with the maximum fiscal cost exceeding 55 percent of GDP.
- Policy options to manage risks:
  - Directly reduce financial sector exposure by reducing state participation in banks.
  - Indirectly reduce exposure by strengthening financial sector regulation and supervision, for example by increasing bank loss-absorbing capacities and reducing excessive pro-cyclicality in banking systems through macro prudential measures, and reducing the bias that incentivizes the accumulation of debt in the tax system and attractiveness of leverage.
  - Transfer risks to others, by requiring banks to finance deposit insurance and put in place effective resolution mechanisms (living wills).
  - Ensure governments have capacity to absorb residual risk by creating buffer funds in the form of pre-funded deposit insurance schemes or through the setting of prudent debt level.

*Source: Data from Bova and others (2016); related studies referenced in the source text.*

### Guarantees
- Findings:
  - Government guarantees can expose governments to significant fiscal risks.
  - Guarantees are often not subject to the same degree of budget scrutiny as regular expenditures; potential costs are typically deferred and there has been a traditional bias towards minimal reporting.
  - The global stock of government-guaranteed bonds was estimated at US$1.4 trillion in 2012.
  - Among European countries, 11 have notional exposures in excess of 10 percent of GDP.
- Measures to manage guarantee risks:
  - Directly limit exposure by controlling issuance of guarantees through a central authorizing point and put quantitative limits on either the stock of outstanding guarantees (example: Philippines) or on the flow of new guarantees that can be issued during the year (examples: Canada and Hungary).
  - Charge risk-related guarantee fees to reduce adverse selection (see Sweden example).
  - Ensure beneficiaries share some of the risk to minimize moral hazard, e.g., require collateral or provide partial guarantees (example: Canada).
  - Ensure adequate budget provisions to meet calls on guarantees: expense cost of guarantees in the budget at the time provided (examples: US, Colombia), or include a contingency provision for expected calls on guarantees for cash-based budgets.
  - Where exposures are sizeable, consider establishment of a guarantee reserve fund (notional or actual).

Box (Sweden: managing fiscal risks from guarantees) — illustrative practices:
- Controls on issuance of guarantees; decisions integrated into the budget process and require Parliamentary approval.
- A fee must be charged for all guarantees, equal to the expected loss and other costs, unless Parliament determines otherwise.
- Where Parliament sets a lower fee or no fee, funds must be allocated from the central budget to cover the fee in the regular budget assessment.
- Guarantee fees are paid into a notional contingency fund; the government maintains a claim on the guaranteed company to recover costs if a guarantee is called.
- The Swedish Debt Management Office (DMO) assesses risks, prices the guarantee fee, monitors changes in risk, and uses rating analysis, option pricing, and simulation models to estimate expected loss.
- Note: The fee level must also reflect EU State Aid requirements.

### Public Private Partnerships (PPPs)
- Findings:
  - PPPs can improve infrastructure efficiency but can create debt-like obligations and contingent obligations often not included in fiscal aggregates.
- Controls and mitigation:
  - Ensure central controls over approval of PPPs, quantitative ceilings on overall fiscal exposure (including direct service payments and contingent liabilities) and an appropriate gatekeeping role for the Ministry of Finance (examples: Brazil, Peru, Hungary, El Salvador).
  - Systematically subject projects to careful appraisal and value-for-money checks, undertake independent review of project feasibility (example: Korea), and charge risk-related guarantee fees where provided (see Chile example).
  - Allocate risks to parties best able to control them and introduce upper bounds where payments are linked to demand.
  - Transparently identify and budget for full lifetime costs and potential fiscal exposure during decision-making.

Box (Chile: managing fiscal risks from PPPs) — illustrative practices:
- Ministry of Public Works must obtain Ministry of Finance approval at different stages of contract preparation; MoF requires identification of all project risks and evaluation of economic and social benefits.
- Minister of Finance must approve PPPs through a supreme decree together with the Minister of Public Works; comptroller, auditor-general, and President approvals required.
- Most project risks borne by SPV or transferred via insurance; where government provides minimum revenue guarantees, it charges a fee.
- PPPs subject to cost-benefit analysis and generally must have expected annual social rate of return exceeding a specified threshold.
- The MoF uses a spreadsheet-based model to estimate cost of possible guarantees, set guarantee fees, and report costs and risks.
- An annual appropriation is included in the budget to cover potential loss from contingent liabilities created by the PPP portfolio (noted as a small fraction of the budget).
- A long-term planning system covers all PPP commitments, estimates commitments under tendering or feasibility study, and provides for future contract modifications and disputes to assess budget affordability.
- All PPP contracts are published; government reports include net present value of availability payments and estimates of net present value of guarantees, plus some value-at-risk information and partial probability distribution information (reports could be better integrated into budget documentation).

### Natural disasters
- Findings:
  - Natural disasters are a significant source of fiscal risk for disaster-prone countries.
  - Between 1994 and 2013, total economic losses globally from natural disasters were estimated at US$2.6 trillion (equivalent to 4 percent of 2015 world GDP).
  - The average country-specific fiscal cost of natural disasters across a sample of events over 1990-2014 was 1.6 percent of GDP, with the largest resulting in fiscal costs of 6 percent of GDP.
  - Climate change can increase frequency and severity of natural disasters.
- Recommended national strategy components:
  - Assess natural disaster risks.
  - Establish a framework for monitoring disaster risks including early warning systems.
  - Put in place disaster preparedness and response mechanisms.
  - Identify mitigating measures to reduce exposure to risks.
- Measures to mitigate disaster fiscal risks:
  - Directly reduce exposure through sectoral planning to reduce public footprint in high-risk areas; introduce tax premia in high-risk areas to discourage concentration; specify building codes to strengthen infrastructure.
  - Transfer risks to international capital markets through traditional insurance, parametric insurance and reinsurance (examples: New Zealand, Turkey), or issue catastrophe bonds which forgive interest and principal if specified catastrophes occur (see Mexico example), or use weather derivatives triggered by temperature or rainfall thresholds.
  - Risk transfer instruments tend to be costly and may be more appropriate for remote events or where access to financing may be disrupted post-disaster.
  - Share risks by capping payments and requiring deductibles under government insurance or mandating private insurance in high-risk areas.
  - Set aside a contingency provision in the annual budget for retained risks to meet costs of moderate but frequent events.
  - Establish natural disaster funds to buffer long-term fiscal costs and ensure funds are available after larger events (examples: Mexico, New Zealand, Turkey).

Box (Mexico: managing fiscal risks from natural disasters) — illustrative practices:
- Post-disaster reconstruction costs of public assets and low income housing averaged US$880 million per year between 1999 and 2011.
- The Federal Government established a three-pronged financial risk management strategy:
  - An annual budget provision in a fund for natural disasters (FONDEN); Federal Budget Law requires a minimum 0.4 percent of the annual federal budget be set aside each year.
  - Transfer part of public-sector natural disaster risk to international reinsurance markets.
  - Use parametric catastrophe bonds to ensure funds are available when specified events occur.
- Mexico was the first sovereign to issue a parametric catastrophe bond in 2006 for earthquakes in three zones; payout triggers included an official state of emergency declaration and an earthquake of specified magnitude within predefined zones. Subsequent bonds pooled multiple risks across multiple regions.

### Subnational governments
- Findings:
  - Liabilities of subnational governments can be a source of fiscal risk for central governments.
  - Off-budget activities and contingent liabilities of subnational governments can be significant.
  - Expectations of central government bailouts can weaken market discipline and lead to excessive risk taking.
  - The fiscal costs of subnational bailouts averaged around 3.5 per cent of GDP, per event, over the period 1990–2014.
- Recommended oversight and controls:
  - Monitor financial health of sub-national governments and actively manage risks.
  - Classify local governments into different risk categories by financial soundness with varying autonomy and monitoring requirements.
  - Impose explicit limits on the stock of liabilities, debt service costs, or borrowing types (e.g., local currency only) or purposes (e.g., investment only).
  - Where financial markets are well-developed, use market-imposed discipline backed by clear and credible no-bail out provisions.
  - Enforcement mechanisms and sanctions for non-compliance can include requiring restructuring plans, withholding transfers, retaining power to liquidate assets, or appointing a financial administrator.

Box (Iceland: managing fiscal risks from sub-national governments) — illustrative reforms:
- Local Government Act of 2011 introduced:
  - A three-year rolling balanced budget rule for municipalities and a limit on the ratio of debt and other balance sheet liabilities to revenue of 150 percent.
  - A three-tier system for monitoring municipal finances based on earned autonomy; municipalities breaching fiscal rules face increased monitoring.
  - A Municipal Fiscal Oversight Committee (MFOC), an independent body with power to impose sanctions.
- Municipal classification and associated measures:
  - Category 1: Comply with both fiscal rules; minimal reporting and full autonomy within rules.
  - Category 2: Breach one rule; increased monitoring, must agree a five- to ten-year fiscal adjustment strategy with MFOC, restricted to borrowing in local currency.
  - Category 3: Excessive debt (debt in excess of 250 percent of revenues); in addition to Category 2 restrictions, must obtain approval for all major revenue, expenditure (including investment) and borrowing decisions from MFOC.
- Further sanctions available to MFOC include naming and shaming, withholding transfers, and recommending vesting of fiscal powers in a financial management board.

### Public Sector Corporations (SOEs)
- Findings:
  - Public sector corporations frequently pose fiscal risk because liabilities are often explicitly or implicitly government guaranteed and because they may undertake quasi-fiscal operations.
  - For profitable SOEs, risks relate to variability in dividends and corporate income taxes and uncertainty about future market conditions.
  - Loss-making entities can require periodic recapitalization or ongoing support.
  - The average cost of government intervention in public sector enterprises across a sample of events over 1990–2014 amounted to about 3 percent of GDP.
- Monitoring and governance measures:
  - Monitor financial performance of public corporations using common financial indicators to inform fiscal risk assessments.
  - Identify problematic entities to focus oversight on those posing largest fiscal risk; ensure monitoring activities match degree of risk.
  - Support institutional fiscal oversight with sound governance principles and accountability mechanisms (see South Africa example).
- Measures to reduce exposure:
  - Reduce overall state participation in commercial activities and scale back quasi-fiscal activities.
  - Limit exposure to contingent liabilities by defining criteria for explicit government guarantees, prohibit or control SOE guarantees to third parties, and restrict sale/use of assets as collateral where appropriate.
  - Strengthen governance: appoint independent boards through merit-based nomination, hold boards accountable for financial performance, ensure operational autonomy, legislate high standards of financial reporting, and subject annual accounts to external audit.
  - Legislate explicit no-bail out clauses to reduce expectations of government support.
  - Ensure transparent and appropriate compensation for quasi-fiscal activities and expense subsidies in the budget.
  - Maintain fiscal space to absorb retained risks, for example via a general contingency reserve to cover calls on government guarantees to public corporations or unforeseen restructuring/liquidation costs.

Box (South Africa: managing fiscal risks from SOEs) — illustrative framework:
- Public Financial Management Act (PFMA) and Treasury Regulations require SOEs to submit corporate plans annually for a three-year period covering strategic objectives, key performance indicators, a risk management plan, and a financial plan including projections of revenue, expenditure and borrowings, asset and liability management, capital expenditure programs and dividend policies.
- PFMA controls on borrowing and contingent liabilities: Minister of Finance must authorize issuance of guarantees or indemnitees; some SOEs require Minister’s approval before borrowing; all SOEs may not borrow in foreign currency above prescribed limits.
- Entities permitted to borrow must submit annual borrowing programs to National Treasury and quarterly reports on actual borrowing.
- A Fiscal Liability Committee within National Treasury advises the Minister on SOE-related matters and receives reports on SOE financial performance and compliance with fiscal support conditions; it assesses aggregate fiscal risk.
- SOEs must submit audited annual financial statements in accordance with generally accepted accounting practices within five months of financial year-end to shareholder minister and National Treasury, and submit quarterly reports to shareholder Minister.

*Italic: Source — Appendix 1. Managing Specific Fiscal Risks (excerpts).*

### Appendix 2. Fiscal Risks Stress Test Methodology

### Appendix 2. Fiscal Risks Stress Test Methodology

### Purpose and Summary Outputs
- FST applies a large, correlated macroeconomic and asset price shock combined with a contingent liability realization to assess fiscal impact during an extreme macroeconomic event.
- Three key elements:
  - A macro-fiscal shock: identify an extreme macro scenario and apply it to the fiscal forecast to account for non-linearities and budget rigidities.
  - A contingent liability shock: assess which contingent liabilities might be realized in the event of a macro crisis and their cost.
  - An assessment of the impact of the macro-fiscal shock and contingent liability realization on the government’s comprehensive balance sheet, incorporating the value of future revenues and expenditures.
- Three summary outputs provided by the FST:
  - Fiscal solvency: change in the government’s net worth or net financial worth, incorporating future fiscal flows.
  - Government liquidity needs: assessed against gross financing needs (GFNs).
  - Financing burden: interest expense relative to revenue collections.

### Macro-fiscal Shock Design and Application
- Scenario construction and application:
  - Scenarios feed through key macro variables: GDP, inflation, exchange and interest rates, housing and equity prices, commodity prices.
  - Constructed via a formal macro model (e.g., IMF’s FSGM), country authorities’ models, or rule-of-thumb relationships.
- Extreme-event focus:
  - Tests examine very large—e.g., once in twenty- or thirty-year events—rather than typical year-to-year volatility.
  - Typical shock size guidance: in the range of two to three standard deviations from average historical volatility.
  - Contrast with conventional DSA shocks: around one standard deviation (and a quarter standard deviation for the combined scenario, when primary balance, interest rates and exchange rates are all shocked simultaneously).
- Forward-looking considerations:
  - Stress scenarios should be informed by comparator-country experience and consider longer lasting or permanent shocks, given evidence that large crises leave real GDP well below pre-crisis trends.

### Fiscal Forecasting and Non-linearities
- Use detailed fiscal forecasting frameworks (e.g., Ministries of Finance files) to apply macro shocks for granular impact on revenue and expenditure categories.
- Two main fiscal non-linearities identified from AE analyses since 1990:
  - Budget rigidities on the expenditure side:
    - Expenditure cannot be significantly reduced as nominal GDP falls (difficulty adjusting down nominal wages, pensions, entitlements).
    - Leads to a persistent increase in the expenditure-to-GDP ratio, averaging 2 percent of GDP, which increases with shock magnitude (see Figure A2.1).
  - Revenue non-linearities:
    - Share of revenue to GDP often declines during crises as normal revenue elasticities break down.
    - During a typical macro shock, revenue impact is relatively small, at around half a percent point of GDP, and does not increase with shock size.
    - Idiosyncratic macro shocks (property busts, financial crises, commodity shocks) typically lead to significant falls in revenue-to-GDP ratios, averaging around 2 percent of GDP (see Figure A2.2).
    - Examples: commodity price declines affect corporate tax, royalties, dividends; falling house prices reduce transaction and capital gains taxes; equity contractions weaken capital gains taxes via loss carry-forwards.
- Practical adjustments when applying shocks:
  - Test revenue heads that have grown well in excess of nominal GDP over the past half-decade (not due to policy changes).
  - Manually increase standard revenue elasticities and include long-running loss carryforwards.
  - For expenditures, hold nominal wage and social security rates constant and apply lags to account for budget rigidity and slow annual adjustment.

### Contingent Liability Analysis
- Rationale:
  - Contingent exposures are highly correlated with macro shocks and can have large impacts on public debt when realized (e.g., public guarantees, SOE debts, international obligations).
  - Implicit guarantees to the domestic banking sector can force government recapitalizations, creation of bad banks, or takeovers, bringing liabilities into general government.
- Additional steps required by FST beyond identification and quantification:
  - Assess likelihood of realization under the stress scenario by identifying risk factors and linking them to macro variables where possible.
  - Quantify stress-scenario related costs (loss given default). Recognize reported maximum loss amounts may overstate realized costs due to existing capital buffers, potential recoveries (often realized post-event), and bail-ins.
- Probabilistic extension (data- and resource-intensive):
  - Where data exist, link fiscal risk factors to macro shock inputs to test varying degrees of contingent liability realization (probabilistic assessment).
  - Example: losses of a state-backed housing fund can be assessed against unemployment and house prices across stress scenarios.
  - Provides guidance to policymakers on required fiscal buffers conditional on risk appetite.
- Interaction with macro-fiscal and balance sheet analyses:
  - Contingent liability realizations affect deficits and public debt (macro-fiscal aggregates) and can create financing needs distinct from increases in public debt (e.g., guarantees called may result in assumed debt not immediately financed).
  - Realizations often bring accompanying assets that can partially or completely offset costs and must be accounted for on the balance sheet.

### Balance Sheet Analysis
- The comprehensive government balance sheet is subjected to the fiscal stress, incorporating:
  - Increased debt liabilities from the macro-fiscal analysis.
  - Valuation changes of existing assets and liabilities via rules of thumb tied to macro parameters (e.g., government equity holdings impacted by equity price changes; land valuations reduced by housing price and commodity declines).
- Key insights:
  - Net worth or net financial worth may vary materially; some valuation changes may offset others (e.g., lower discount rates reduce pension liabilities; exchange rate depreciation increases external asset holdings).
  - Balance sheet incorporates future discounted revenues and expenditures (the fiscal gap appears in net worth), recognizing the government’s ability to levy taxes and future costs of providing goods and services.
- Analytical capabilities enabled:
  - Incorporate cost of demographic change based on long-term fiscal projections.
  - Identify long-term discounted cost of fiscal shocks relative to baseline.
  - Provide sensitivity analysis of the balance sheet to commodity price fluctuations.

### Solvency, Liquidity, and Fiscal Burden Indicators
- Solvency:
  - Level and change in comprehensive net financial worth (or net worth where non-financial assets available) indicate current solvency under policies and long-run impact of the shock.
- Liquidity:
  - Gross financing needs (GFNs) measure liquidity risk by identifying financing needs of future fiscal deficits, amortization of existing debt, and liquidity needs from contingent liability assumption.
  - Financing needs from contingent liability assumption can differ from increases in public debt when debt is assumed rather than financed immediately.
- Fiscal burden:
  - Interest cost relative to revenue gauges burden on future taxpayers; large burdens can reduce funds available for public goods and may create political economy pressure for strategic default.

*Source: Appendix 2. Fiscal Risks Stress Test Methodology*

### Appendix 3. Public Debt and Sovereign Bond Yields—

### Appendix 3. Public Debt and Sovereign Bond Yields— Updated Evidence

### Scope, data, and empirical approach
- Sample: 31 AEs and 19 EMEs, 1990–2014.
- Objective: estimate relationship between 10-year sovereign bond yields and public debt, accounting for government financial assets and other domestic and global controls.
- Dependent variable: r = 10-year government bond yields.
- Key regressors:
  - d: lagged public debt-to-GDP ratio (percent of GDP).
  - W: government financial assets (percent of GDP).
  - X_D: domestic controls — primary balance, real GDP growth, expected inflation, short-term interest rate.
  - X*: global controls — 10-year U.S. bond yields and global risk aversion (VIX).
- Estimation: panel regressions run separately for AEs and EMEs; debt and assets enter as lagged values to mitigate reverse causality.
- Rationale for controls (summarized from source):
  - Real GDP growth: affects tax capacity and deleveraging via denominator effect; ambiguous net effect on yields.
  - Public debt-to-GDP ratio: higher debt implies higher debt-servicing needs and potential solvency concerns; expected positive coefficient.
  - Short-term interest rate: controls for monetary policy stance; expected positive relationship with long-term yields.
  - Expected inflation: raises nominal yields through inflation tax; expected positive effect.
  - Primary balance: gauges fiscal stance and sustainability; sign uncertain after controlling for debt level.
  - Government financial assets: strengthen balance sheets and, if liquid, can lower yields.
  - Global risk aversion (VIX) and U.S. 10-year yields: capture global financial conditions; effects can be positive or ambiguous depending on safe-haven flows.

### Main empirical findings
- Debt-level effects:
  - An increase of one percentage point of GDP in gross public debt raises sovereign bond yields by about 3 bps in AEs, and by about 7 bps in EMEs (after controlling for other factors).
- Government financial assets:
  - An increase in government financial assets by one percentage point of GDP lowers government bond yields by about 17 bps in EMEs, but has no material impact in AEs.
  - Implication: net debt (gross debt net of financial assets) matters for market perceptions of solvency, at least in EMEs.
  - Caveat: result does not account for asset liquidity; government financial assets may be illiquid (pension funds, equity) and not readily liquidatable in stress; liquidity data were not available.
- Other notable coefficient estimates and model statistics (preserved exactly as reported):
  - US 10-year bond yields (in percent): 0.478*** 0.641*** 0.032 -0.302 (standard errors: (0.130)(0.123)(0.273)(0.634))
  - VIX (index): -0.016 -0.003 0.024 -0.004 (standard errors: (0.014)(0.009)(0.019)(0.028))
  - Short-term interest rate (in percent): 0.551*** 0.451*** 0.857*** 0.820*** (standard errors: (0.082)(0.070)(0.091)(0.087))
  - Lagged gross debt (percent of GDP): 0.032** 0.027** 0.073*** 0.164** (standard errors: (0.013)(0.011)(0.016)(0.059))
  - Primary balance (percent of GDP): -0.060* -0.093*** -0.002 -0.260** (standard errors: (0.031)(0.032)(0.120)(0.104))
  - Expected inflation: 0.070 -0.024 0.168* 0.311 (standard errors: (0.110)(0.057)(0.081)(0.253))
  - Real GDP growth: -0.212* -0.125** -0.024 -0.128 (standard errors: (0.105)(0.058)(0.074)(0.138))
  - Lagged financial assets (percent of GDP): -0.021 -0.172*** (standard errors: (0.013)(0.039))
  - Constant (C): -0.220 -0.257 -3.062*** -3.561 (standard errors: (0.724)(0.364)(0.695)(2.520))
  - N: 552 363 228 99
  - R2: 0.694 0.790 0.797 0.871
  - Note on significance notation: Standard errors in parentheses; * p-value<0.1; ** p-value <0.05; *** p-value <0.01.

### Interpretation and implications
- Markets price sovereign risk differently across AEs and EMEs:
  - EMEs exhibit a larger sensitivity of yields to gross public debt than AEs (7 bps vs. 3 bps per 1 percentage point of GDP).
  - EMEs exhibit a materially negative sensitivity of yields to government financial assets (about -17 bps per 1 percentage point of GDP), suggesting markets in EMEs value net-asset positions more strongly.
- Flow variables matter: primary deficits raise yields beyond the stock effect of debt in some specifications.
- Global factors matter: U.S. long-term rates and global risk conditions (VIX) enter yield determination and capture international spillovers (e.g., "search for yields", taper-tantrum effects).
- Policy-relevant message: assessing solvency and market perceptions requires considering both sides of the public balance sheet — gross debt and government financial assets (net debt) — and evaluating asset liquidity.

### Methodological notes and limitations
- The effect of government financial assets on yields does not incorporate asset liquidity; many government assets may be illiquid and thus less useful to service debt quickly.
- Data limitations: sample restricted when including government financial assets due to limited asset data coverage; major oil exporters with large sovereign wealth funds were excluded from the bond-yield sample because bond-yield data are not available for those countries.
- Data sources: IMF World Economic Outlook database and the Fiscal Monitor database for most variables; VIX from Chicago Board Exchange (CBOE); U.S. 10-year government bond yields from the Federal Reserve Board.

*Source: Appendix 3. Public Debt and Sovereign Bond Yields— Updated Evidence (IMF staff analysis).*

### References

### _050416 - References

### References

- Ahmad, E., M. Albino-War, and R. Singh, 2005, “Subnational Public Financial Management: Institutions and Macroeconomic Considerations,” IMF Working Paper 05/108 (Washington: International Monetary Fund).
- Amaglobeli, D., N. End, M. Jarmuzek, and G. Palomba, 2015, “From Systemic Banking Crises to Fiscal Costs: Risk Factors,” IMF Working Paper 15/166 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2015/wp15166.pdf
- Aslan, C., and D. Duarte, 2014, “How Do Countries Measure, Manage, and Monitor Fiscal Risks Generated by Public-Private Partnerships?” World Bank Policy Research Working Paper No. 7041 (Washington: World Bank).
- Baldacci, E., M. S. Kumar, 2010 “Fiscal Deficits, Public Debt, and Sovereign Bond Yields,” IMF Working Paper No. 10/184 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2010/wp10184.pdf
- Baum, A., A. Hodge, A. Mineshima, M. Moreno Badia, and R. Tapsoba, Forthcoming, “Room to Grow? Managing Fiscal Risks in Low-Income Countries,” IMF Working Paper (Washington: International Monetary Fund).
- Beck, T., L. Klapper, and J. C. Mendoza, 2008, “The Typology of Partial Credit Guarantee Funds around the World,” World Bank Policy Research Working Paper No. 4771 (Washington: World Bank). Dataset: http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/PCG_Excel.xlsx
- Bohn, H., 1998, “The Behavior of U.S. Public Debt and Deficits,” Quarterly Journal of Economics, 87.
- Bova, E., M. Ruiz-Arranz, F. Toscani, and H. E. Ture, 2016, “The Fiscal Costs of Contingent Liabilities: A New Dataset,” IMF Working Paper 16/14 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2016/wp1614.pdf
- Budina, N., and S. van Wijnbergen, 2007, “Quantitative Approaches to Fiscal Sustainability Analysis: A New World Bank Tool Applied to Turkey,” World Bank Working Paper (Washington: World Bank).
- Cebotari, A., 2008, “Contingent Liabilities: Issues and Practice,” IMF Working Paper 08/245 (Washington: International Monetary Fund).
- Celasun, O., X. Debrun, and J. D. Ostry, 2007, “Primary Surplus Behavior and Risks to Fiscal Sustainability in Emerging Market Countries: A “Fan-Chart” Approach,” IMF Staff Papers, Vol. 53, No. 3, pp. 401–25.
- Cerutti, E., S. Claessens, and L. Laeven, 2015, “The Use and Effectiveness of Macroprudential Policies: New Evidence,” IMF Working Paper, 15/61 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2015/wp1561.pdf
- Debrun, X., M. Jarmuzek, and A. Shabunina, Forthcoming, “Public Debt: Not Safe at Any Speed,” IMF Working Paper (Washington: International Monetary Fund).
- Debrun, X., M. Jarmuzek, C. Lonkeng, S. Basu, N. End, W. Shi, J. Sin, and F. Toscani, Forthcoming, “Public Debt in Advanced Economies: The Sky Is Not the Limit,” IMF Working Paper (Washington: International Monetary Fund).
- Debrun, X., 2005, “Public Debt in South Africa: A Risk Analysis,” in Selected Issues Papers: South Africa (Washington: International Monetary Fund).
- Demirgüç-Kunt, A., E. Kane, and F. Grigoli, 2014, “Deposit Insurance Database,” IMF Working Paper 14/118 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2014/wp14118.pdf
- Escolano, J., 2010, “A Practical Guide to Public Debt Dynamics, Fiscal Sustainability, and Cyclical Adjustment of Budgetary Aggregates,” Technical Notes and Manuals, January, International Monetary Fund (Washington).
- Escolano, J., and V. Gaspar, Forthcoming, “Optimal Debt Policy Under Asymmetric Risk,” IMF Working Paper (Washington: International Monetary Fund).
- Escolano, J., L. Jaramillo, C. Mulas-Granados, and G. Terrier, 2014, “How Much is a Lot? Historical Evidence on the Size of Fiscal Adjustments”, IMF Working Paper 14/179, International Monetary Fund (Washington).
- Escolano, J., C. Kolerus, and C. Lonkeng Ngouana, 2014, “Global Monetary Tightening: Emerging Markets Debt Dynamics and Fiscal Crises,” IMF Working Paper No. 14/215 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2014/wp14215.pdf
- Eurostat, 2016, “What is the extent of contingent liabilities and nonperforming loans in the EU Member States?” Eurostat Newsrelease. http://ec.europa.eu/eurostat/documents/2995521/7143457/2-27012016-AP-EN.pdf/60f17285-93bb-4813-9bd8-bb5263703408
- Finland Ministry of Finance, 2015, “Overview of Central Government Risks and Liabilities, Ministry of Finance Publications 11b/2015.
- Frankel, J. and J. Schreger, 2013, “Bias in Official Fiscal Forecasts: Can Private Forecasts Help?,” Harvard University.
- Gray, D.F., and A. A. Jobst, 2013, “Systemic Contingent Claims Analysis: Estimating Market-Implied Systemic Risk,” IMF Working Paper No. 13/54 (Washington: International Monetary Fund).
- Gray, D., R. Merton, and Z. Bodie, 2008, “New Framework for Measuring and Managing Macrofinancial Risk and Financial Stability,” Harvard Business School Working Paper No. 09-015 (Boston, Mass.: Harvard Business School).
- Guha-Sapir, D., R. Below, and P. Hoyois, 2016, EM-DAT Database – The CRED/OFDA International Disaster Database (Brussels: Universite Catholique de Louvain).
- International Monetary Fund, 2005, Government Guarantees and Fiscal Risk (Washington: International Monetary Fund).
- ______________, 2008, Fiscal Risks: Sources, Disclosure, and Management (Washington: International Monetary Fund).
- ______________, 2011, Modernizing the Framework for Fiscal Policy and Public Debt Sustainability Analysis, IMF Policy Paper, November, (Washington: International Monetary Fund.
- _______________, 2012, “Fiscal Accountability, Transparency and Risk” (Washington: International Monetary Fund).
- _______________, 2013a, Staff Guidance Note for Public Debt Sustainability Analysis in Market-Access Countries, IMF Policy Paper, November (Washington: International Monetary Fund).
- _______________, 2013b, Review of the Implementation of Government Finance Statistics to Strengthen Fiscal Analysis, IMF Policy Paper, November (Washington: International Monetary Fund).
- _______________, 2014, Global Financial Stability Report (GFSR), April, Moving from Liquidity to Growth Driven Markets
- _______________, 2015a, “From Banking to Sovereign Stress: Implications for Public Debt,” IMF Policy Paper, (Washington: International Monetary Fund). http://www.imf.org/external/np/pp/eng/2014/122214.pdf
- _______________, 2015b, Now is the Time: Fiscal Policies for Sustainable Growth, April 2015 Fiscal Monitor (Washington).
- _______________, 2015c, Fiscal Policy and Long-Term Growth, IMF Policy Paper, June (Washington: International Monetary Fund).
- _____________, 2015d, Balance Sheet Analysis in Fund Surveillance, June (Washington).
- _______________,2015e, The Commodities Roller Coaster: A Fiscal Framework for Uncertain Times, October 2015 Fiscal Monitor (Washington).
- _____________, 2015f, Uneven Growth: Short- and Long-Term Factors, Chapter 3, World Economic Outlook, October 2015 (Washington: International Monetary Fund).
- International Monetary Fund and World Bank, 2012, Revisiting the Debt Sustainability Framework for Low-Income Countries, IMF and WB Policy Paper, January, International Monetary Fund and World Bank (Washington).
- Irish Fiscal Advisory Council, 2015, “Fiscal Assessment Report,” November.
- Irwin, T., 2015, “Getting the Dog to Bark: Disclosing Fiscal Risks from the Financial Sector,” IMF Working Paper 15/208 (Washington: International Monetary Fund).
- Irwin, T., and T. Mokdad, 2010, Managing Contingent Liabilities in Public-Private Partnerships: Practice in Australia, Chile and South Africa, World Bank, PPIAF.
- Jaramillo, L., and A. Weber, 2013, “Bond Yields in Emerging Economies: It Matters What State You Are In,” Emerging Markets Review 17, 169–185.
- Laeven, L., and F. Valencia, 2008, “Systemic Banking Crises: A New Database,” IMF Working Paper, 08/224 (Washington: International Monetary Fund).
- Mauro, P., R. Romeu, and A. Zaman, 2013, “A Modern History of Fiscal Prudence and Profligacy,” IMF Working Paper No. 13/5 (Washington: International Monetary Fund). https://www.imf.org/external/pubs/ft/wp/2013/wp1305.pdf
- OECD, 2014, Financing State-Owned Enterprises: An Overview of National Practices (Paris: OECD. http://dx.doi.org/10.1787/9789264209091-en
- OECD (2015), OECD Guidelines on Corporate Governance of State-Owned Enterprises, Paris, http://www.oecd.org/corporate/guidelines-corporate-governance-soes.htm
- Parliament of Australia, 2014, “The Sensitivity of Budget Projections to Changes in Economic Parameters,” Report No. 03/2014, Parliamentary Budget Office, Canberra.
- Frankel, J. and J. Schreger, 2013, “Bias in Official Fiscal Forecasts: Can Private Forecasts Help?,” Harvard University.
- Strauch, R., M. Hallerberg, and J. von Hagen, 2004, “Budgetary Forecasts in Europe – The Track Record of Stability and Convergence Programmes,” European Central Bank Working Paper No. 307, February.

*Source: _050416 - References*

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