## 1. Explaining Common Factor’s Dynamics

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---

### Introduction: recent developments in euro area sovereign spreads
- Since the onset of the financial crisis, sovereign risk premium differentials in the euro area have been widening; spreads on the yield on 10-year government bonds over Bunds spiked in January 2009 for various euro area members, accompanied by downgrades of sovereign debt ratings for three countries—Greece, Spain, and Portugal—and a warning for Ireland.
- The rebound in sovereign spreads follows a prolonged period of very modest differentiation across countries since the introduction of the single currency, raising questions about markets’ ability to impose fiscal discipline.
- Possible drivers of spread widening discussed:
  - Fiscal vulnerabilities and default risk concerns.
  - Relative liquidity of government bond markets and a flight to safety/liquidity (Bunds as benchmark).
  - Government exposure to weakness in the financial sector via guarantees, recapitalizations, and purchase of assets.
  - Global risk repricing linked to shifts in international risk appetite.

### Stylized facts on fiscal and financial developments (EU/euro area)
- Discretionary fiscal stimulus in the euro area is estimated to average 1.1 and 0.9 percent of GDP in 2009 and 2010, respectively.
- Immediate impact of support measures on government financing in the euro area has averaged around 3½ percent of GDP.
- Indicative estimates suggest outlays from contingent liabilities could average around 2–5 percent of GDP, cumulative for 2009–13 (based on applying expected default frequency implied CDS spreads to guaranteed amounts).
- Empirical observation: since the onset of the financial crisis, the Expected Default Frequency (EDF) of the median domestic financial institution tends to co-move with the sovereign bond spread of the corresponding issuer; example: Ireland’s sovereign spreads began to increase after the government extended a guarantee to the banking system.
- Policy tension: fiscal interventions stabilized demand and financial systems but deteriorated budget positions and increased government debt, possibly fueling market concerns about solvency and sustaining higher sovereign risk premiums until credible restructuring and long-run fiscal commitment are apparent.

### Dissecting the common risk factor: theory and identification
- Literature consensus: euro area sovereign spreads are mainly driven by a single time-varying common factor associated with shifts in international risk appetite.
- Conceptual decomposition:
  - Observable asset-specific risk premium = common price of risk (the inverse of investors’ risk appetite) × inherent asset riskiness.
  - Risk appetite depends on risk aversion (a deep parameter) and macroeconomic uncertainty; shifts in observed risk appetite are more likely to respond to changes in uncertainty.
- Estimation strategy:
  - Simple asset-pricing model: country-specific sovereign yield risk premiums jointly determined by asset-specific riskiness and a common price of risk, allowing identification and filtering of the common component.
  - Empirical specification: spreads on 10-year government bonds over Bunds for 10 euro area countries are modeled jointly within a multivariate generalized autoregressive conditional heteroskedasticity framework, capturing fat-tail noise.
  - Spreads (s_it) follow an AR(1); innovations (ε_it) follow GARCH(1,1) with variance h_it.
  - Unobservable common factor λ_t evolves as a random walk; country-specific parameter γ_i captures relative riskiness across issuers.
  - Given model nonlinearity, Kalman filters are not used; Bayesian estimation via the model’s likelihood is evaluated using a particle filter on daily observations from January 2001 to April 2009.
  - Elsewhere the paper notes using daily data between January 1999 and April 2009 to study dynamics over long and short run horizons.

### Modeling and data notes (technical)
- Model nonlinear; estimation uses Bayesian particle filter techniques.
- Econometric model includes AR(1) dynamics for spreads, GARCH(1,1) for innovations, country-specific riskiness γ_i, and a stochastic common component λ_t as a random walk.
- Daily data samples cited: January 1999–April 2009 (analysis horizon) and January 2001–April 2009 (particle-filter estimation sample).

### Key empirical findings and interpretation
- A large part of changes in sovereign default risk premiums largely mirror global risk repricing driven by shifts in cyclical conditions and uncertainty in financial markets.
  - Implication: a big chunk of the widening in government bond spreads is likely to be reversed as recession fears and uncertainty recede and international financial conditions normalize.
- Structural changes in market behavior since the crisis:
  - The sensitivity of sovereign spreads to projected debt changes has significantly increased since October 2008.
  - In a few countries, markets have grown progressively more concerned about the solvency of national banking systems, linking financial sector distress to sovereign risk.
- Liquidity effects:
  - Sovereign bond market liquidity appears to maintain a significant, albeit limited, role in explaining spreads.
- Policy relevance:
  - If spreads primarily reflect investor risk appetite and liquidity strains, liquidity provision measures could beneficially reduce governments’ marginal funding costs.
  - If spreads reflect solvency concerns from fiscal deterioration or contingent financial sector liabilities, sustained market confidence requires credible financial system restructuring and a clear commitment to long-run fiscal discipline.

### Estimated common component in sovereign spreads
- The particle filtering approach is used to extract a time-varying common factor across euro area sovereign spreads.
- The estimated common factor captures four distinct developments:
  - narrowing of risk premium differentials due to EMU convergence over 2001-02;
  - decline in financial market volatility over 2003-05;
  - abundant liquidity and muted risk aversion over 2005-07;
  - risk repricing commencing end-2007 and receding at the very end of the sample.
- The time-varying common factor is generally small: even at its peak—at the beginning and at the end of the sample—the common factor in euro area sovereign spreads remains below 20 basis points.
- Fan chart depiction: at each point in time, the 5th, the 50th and the 95th percentile of the estimated probability distribution for the expected common component are plotted; hence there is a 90 percent chance that the common spread will be inside the blue-shaded range; the central thick black line denotes the estimated median common spread.
- VDAX Index is used as the implied volatility of the German stock market (index, rhs) and is shown alongside the estimated common factor (basis points, lhs).

### Drivers and econometric findings (error correction model and short-run dynamics)
- Long-run relations (Table 1, Dependent Variable: Common factor; Sample: January 2001-April 2009; Included observations: 2153):
  - Constant: -8.46 (t-Statistic -20.63)
  - Expected inflation: -4.04 (t-Statistic -36.56)
  - Euribor spread: -1.40 (t-Statistic -25.74)
  - EMBI+ spread: 0.06 (t-Statistic 6.80)
  - VDAX: 0.92 (t-Statistic 2.23)
  - VG7 currencies: 2.45 (t-Statistic 0.92)
  - Adjusted R-squared: 0.86
  - Mean dependent variable: 0.86
  - S.E. of regression: 1.27
  - S.D. dependent variable: 8.55
  - Durbin-Watson statistics: 0.07
- Short-run dynamics (Table 1, Dependent Variable: D(Common factor); Sample: January 2001-April 2009; Included observations: 2143):
  - D(Common factor (-1)): 0.25 (t-Statistic 1.60)
  - D(Common factor (-2)): 0.16 (t-Statistic 7.41)
  - ECM(-10): 0.00 (t-Statistic -2.85)
  - D(Expected inflation): -0.11 (t-Statistic -2.17)
  - D(Euribor spread): -0.09 (t-Statistic -1.57)
  - D(VDAX): 0.00 (t-Statistic 3.00)
  - D(VG7 currencies): 0.02 (t-Statistic 2.17)
  - D(EMBI+ spread): -0.06 (t-Statistic -1.01)
  - Adjusted R-squared: 0.13
  - Mean dependent variable: 0.12
  - S.E. of regression: 0.09
  - S.D. dependent variable: 0.10
  - Durbin-Watson statistics: 2.01
- Interpretation:
  - Over the long run, a common widening of euro area sovereign bond spreads is associated with expected deflationary risks (negative coefficient on expected inflation) and declining interbank rates (negative coefficient on Euribor spread).
  - On average, inflation and wholesale money market developments appear to account for more than half of the changes in the common component.
  - Common shifts in euro-area risk premium differentials tend to be positively correlated with volatility in stock, currency, and emerging markets.
  - Over the short run, only 12 percent of the daily variation in the common component can be explained (Adjusted R-squared 0.13), most of which is induced by endogenous dynamic adjustments.

### Explaining developments in euro area sovereign risk during the crisis (panel estimates and country effects)
- Panel model: spread between ten-year sovereign bonds of ten euro area countries and Germany; monthly data; estimation periods January 2003-March 2009 and January 2003-January 2009.
- General-to-specific specification includes: D(Common Factor), D(Projected Debt), D(EDF), liquidity (market value of traded euro denominated long-term government bonds), projected growth, projected fiscal balances, projected current account balance.
- Key stylized facts:
  - Substantial widening of spreads since October 2008.
  - Expectations of fiscal deficits and debt levels have increased sharply.
  - Liquidity of country bond markets has not changed much over the sample.
  - Greek and Irish sovereign bonds were severely punished by markets—out of line with pre-crisis evidence and not fully explained by expected debt developments or bond market liquidity.
- Panel estimates (selected coefficients from Table 2):
  - D(Common Factor): 4.14, 4.11, 4.08, 4.50 (pre-October sample variants); 4.79, 4.85, 4.87, 4.66 (extended to March 2009); P-value 0.00 throughout.
  - D(Projected Debt Pre October): coefficients around 0.24-0.28 with P-values 0.02-0.03 in January 2003-January 2009; similar magnitudes in the longer sample.
  - D(Projected Debt Post October): 0.58 (P-value 0.00) in January 2003-January 2009 and 0.56 (P-value 0.02) in January 2003-March 2009.
  - D(EDF Post October) in January 2003-March 2009 sample: 6.89, 6.77, 7.39, 8.66 with P-value 0.00.
  - Liquidity Pre October: negative coefficients around -0.11 to -0.14 with P-value 0.00.
  - Liquidity Post October: larger negative coefficients (e.g., -1.64, -1.68, -1.50, -1.04) with P-values from 0.06 to 0.01.
  - Adjusted R-squared reported: 0.53, 0.52, 0.51, 0.49 for various specifications; total observations 725-746 depending on sample and specification.
- Seemingly-unrelated regression (country-specific decompositions, January 2003-January 2009; total observations: 726):
  - Significant contributions from projected debt for Greece, Ireland, Spain, and to a lesser extent Austria, Italy, Portugal.
  - Rising EDFs in the financial sector translate into increases in government spreads in Austria, Ireland, and Italy.
  - Liquidity of sovereign bond markets appears to lessen Italian government financing costs.
  - A sizable part of the actual change in spreads since September 2008 remains unexplained—particularly for Greece.
- Seemingly-unrelated regression (January 2003-March 2009; total observations: 746):
  - Investors’ risk appetite (common component) plays a much smaller role in March 2009.
  - Concerns about solvency of national financial sectors have risen particularly in Austria, Finland, Greece, and Portugal.
  - Concerns about domestic fiscal sustainability have risen in Belgium, Ireland, and Italy.
  - Liquidity of sovereign bond markets still plays a significant but limited role in a few countries.

### Policy implications and conclusions
- Fiscal policy has been used to support financial systems and aggregate demand during the crisis, but market perception of fiscal sustainability matters critically.
- Movements in sovereign spreads increasingly reflect country-specific developments: rapidly rising projected debt levels and concerns about solvency of national banking systems and their budgetary consequences.
- Markets appear to be providing greater fiscal discipline than before the crisis—sensitivity of spreads to projected debt has increased after September 2008.
- Potential adverse feedback: increasing sovereign spreads could raise governments’ marginal funding costs, partly offsetting stimulus and adding financing pressures.
- Policy recommendations:
  - Restore trust in the financial system to shape the recovery and increase effectiveness of fiscal stimulus measures while reducing future governments’ financing costs.
  - Commit to credible long-run fiscal discipline and outline a clear exit strategy from supportive policy stances as the crisis abates.
  - Cast short-term fiscal expansion within a credible medium-term framework and envisage fiscal adjustments as economic conditions improve to curb solvency concerns.
  - Implement structural reforms tackling aging-related public costs and enhancing potential growth to improve medium-term revenue prospects and reduce solvency risks.

### Key statistics and figures (extracted)
- Common factor peak: below 20 basis points.
- Table 1 (long-run): Adjusted R-squared 0.86; Mean dependent variable 0.86; S.E. of regression 1.27; S.D. dependent variable 8.55; Durbin-Watson 0.07.
- Table 1 (short-run): Adjusted R-squared 0.13; Mean dependent variable 0.12; S.E. of regression 0.09; S.D. dependent variable 0.10; Durbin-Watson 2.01.
- Panel samples and total observations: 725, 726, 745, 746 depending on specification and sample window.
- Selected panel coefficients (D(Common Factor)): 4.14, 4.11, 4.08, 4.50 (pre-October sample variants) and 4.79, 4.85, 4.87, 4.66 (extended to March 2009); P-value 0.00 throughout.
- D(Projected Debt Post October): 0.58 (P-value 0.00), 0.56 (P-value 0.02).
- D(EDF Post October) in January 2003-March 2009 sample: 6.89, 6.77, 7.39, 8.66 with P-value 0.00.
- Liquidity Pre October coefficients: around -0.11 to -0.14 (P-value 0.00); Liquidity Post October: around -1.64 to -1.04 with P-values 0.06 to 0.01.
- Figure notes: Projected change in the debt-to-GDP ratio over the next year (percent); Traded volume of government debt relative to the German bond market (percent).

*Source: IMF staff analysis as presented in "1. Explaining Common Factor’s Dynamics" (excerpt).*

### 1. Explaining Common Factor’s Dynamics.................................................................................1

### 1. Explaining Common Factor’s Dynamics

### Introduction: recent developments in euro area sovereign spreads
- Since the onset of the financial crisis, sovereign risk premium differentials in the euro area have been widening; spreads on the yield on 10-year government bonds over Bunds spiked in January 2009 for various euro area members, accompanied by downgrades of sovereign debt ratings for three countries—Greece, Spain, and Portugal—and a warning for Ireland.
- The rebound in sovereign spreads follows a prolonged period of very modest differentiation across countries since the introduction of the single currency, raising questions about markets’ ability to impose fiscal discipline.
- Possible drivers of spread widening discussed:
  - Fiscal vulnerabilities and default risk concerns.
  - Relative liquidity of government bond markets and a flight to safety/liquidity (Bunds as benchmark).
  - Government exposure to weakness in the financial sector via guarantees, recapitalizations, and purchase of assets.
  - Global risk repricing linked to shifts in international risk appetite.

### Stylized facts on fiscal and financial developments (EU/euro area)
- Discretionary fiscal stimulus in the euro area is estimated to average 1.1 and 0.9 percent of GDP in 2009 and 2010, respectively.
- Immediate impact of support measures on government financing in the euro area has averaged around 3½ percent of GDP.
- Indicative estimates suggest outlays from contingent liabilities could average around 2–5 percent of GDP, cumulative for 2009–13 (based on applying expected default frequency implied CDS spreads to guaranteed amounts).
- Empirical observation: since the onset of the financial crisis, the Expected Default Frequency (EDF) of the median domestic financial institution tends to co-move with the sovereign bond spread of the corresponding issuer; example: Ireland’s sovereign spreads began to increase after the government extended a guarantee to the banking system.
- Policy tension highlighted: while fiscal interventions were vital to stabilize demand and financial systems, they have deteriorated budget positions and increased government debt, possibly fueling market concerns about solvency and sustaining higher sovereign risk premiums until credible restructuring and long-run fiscal commitment are apparent.

### Dissecting the common risk factor: theory and identification
- Literature consensus: euro area sovereign spreads are mainly driven by a single time-varying common factor associated with shifts in international risk appetite.
- Conceptual decomposition:
  - Risk appetite depends on risk aversion (a deep parameter) and macroeconomic uncertainty; shifts in observed risk appetite are more likely to respond to changes in uncertainty.
  - Observable asset-specific risk premium = common price of risk (the inverse of investors’ risk appetite) × inherent asset riskiness.
- Estimation strategy:
  - A simple asset-pricing model assumes country-specific sovereign yield risk premiums are jointly determined by asset-specific riskiness and a common price of risk, allowing identification and filtering of the common component.
  - Empirical specification: spreads on 10-year government bonds over Bunds for 10 euro area countries are modeled jointly within a multivariate generalized autoregressive conditional heteroskedasticity framework, capturing fat-tail noise.
  - Spreads (s_it) follow an AR(1); innovations (ε_it) follow GARCH(1,1) with variance h_it.
  - The unobservable common factor λ_t evolves as a random walk; country-specific parameter γ_i captures relative riskiness across issuers.
  - Given model nonlinearity, Kalman filters are not used; Bayesian estimation via the model’s likelihood is evaluated using a particle filter on daily observations from January 2001 to April 2009.
  - (Elsewhere the paper notes using daily data between January 1999 and April 2009 to study dynamics over long and short run horizons.)

### Key empirical findings and interpretation
- A large part of changes in sovereign default risk premiums largely mirror global risk repricing driven by shifts in cyclical conditions and uncertainty in financial markets.
  - Implication: a big chunk of the widening in government bond spreads is likely to be reversed as recession fears and uncertainty recede and international financial conditions normalize.
- Structural changes in market behavior since the crisis:
  - The sensitivity of sovereign spreads to projected debt changes has significantly increased since October 2008.
  - In a few countries, markets have grown progressively more concerned about the solvency of national banking systems, linking financial sector distress to sovereign risk.
- Liquidity effects:
  - Sovereign bond market liquidity appears to maintain a significant, albeit limited, role in explaining spreads.
- Policy relevance:
  - If spreads primarily reflect investor risk appetite and liquidity strains, liquidity provision measures could beneficially reduce governments’ marginal funding costs.
  - If spreads reflect solvency concerns from fiscal deterioration or contingent financial sector liabilities, sustained market confidence requires credible financial system restructuring and a clear commitment to long-run fiscal discipline.

### Modeling and data notes (technical)
- Model nonlinear; estimation uses Bayesian particle filter techniques.
- Econometric model includes AR(1) dynamics for spreads, GARCH(1,1) for innovations, country-specific riskiness γ_i, and a stochastic common component λ_t as a random walk.
- Daily data samples cited: January 1999–April 2009 (analysis horizon) and January 2001–April 2009 (particle-filter estimation sample).

*Source: IMF staff analysis as presented in "1. Explaining Common Factor’s Dynamics" (excerpt). *

### 7. For the sake of comparison, the estimated common factor is pictured along with an index

### 7. For the sake of comparison, the estimated common factor is pictured along with an index measuring the implied volatility in the German stock market—a variable extraneous to the filtering procedure used to extract the component itself.

### Estimated common component in sovereign spreads
- The particle filtering approach is used to extract a time-varying common factor across euro area sovereign spreads.
- The estimated common factor captures four distinct developments:
  - narrowing of risk premium differentials due to EMU convergence over 2001-02;
  - decline in financial market volatility over 2003-05;
  - abundant liquidity and muted risk aversion over 2005-07;
  - risk repricing commencing end-2007 and receding at the very end of the sample.
- The time-varying common factor is generally small: even at its peak—at the beginning and at the end of the sample—the common factor in euro area sovereign spreads remains below 20 basis points.
- The fan chart depiction: at each point in time, the 5th, the 50th and the 95th percentile of the estimated probability distribution for the expected common component are plotted; hence there is a 90 percent chance that the common spread will be inside the blue-shaded range; the central thick black line denotes the estimated median common spread.
- VDAX Index is used as the implied volatility of the German stock market (index, rhs) and is shown alongside the estimated common factor (basis points, lhs).

### Drivers and econometric findings (error correction model and short-run dynamics)
- Long-run relations (Table 1, Dependent Variable: Common factor; Sample: January 2001-April 2009; Included observations: 2153):
  - Constant: -8.46 (t-Statistic -20.63)
  - Expected inflation: -4.04 (t-Statistic -36.56)
  - Euribor spread: -1.40 (t-Statistic -25.74)
  - EMBI+ spread: 0.06 (t-Statistic 6.80)
  - VDAX: 0.92 (t-Statistic 2.23)
  - VG7 currencies: 2.45 (t-Statistic 0.92)
  - Adjusted R-squared: 0.86
  - Mean dependent variable: 0.86
  - S.E. of regression: 1.27
  - S.D. dependent variable: 8.55
  - Durbin-Watson statistics: 0.07
- Short-run dynamics (Table 1, Dependent Variable: D(Common factor); Sample: January 2001-April 2009; Included observations: 2143):
  - D(Common factor (-1)): 0.25 (t-Statistic 1.60)
  - D(Common factor (-2)): 0.16 (t-Statistic 7.41)
  - ECM(-10): 0.00 (t-Statistic -2.85)
  - D(Expected inflation): -0.11 (t-Statistic -2.17)
  - D(Euribor spread): -0.09 (t-Statistic -1.57)
  - D(VDAX): 0.00 (t-Statistic 3.00)
  - D(VG7 currencies): 0.02 (t-Statistic 2.17)
  - D(EMBI+ spread): -0.06 (t-Statistic -1.01)
  - Adjusted R-squared: 0.13
  - Mean dependent variable: 0.12
  - S.E. of regression: 0.09
  - S.D. dependent variable: 0.10
  - Durbin-Watson statistics: 2.01
- Interpretation:
  - Over the long run, a common widening of euro area sovereign bond spreads is associated with expected deflationary risks (negative coefficient on expected inflation) and declining interbank rates (negative coefficient on Euribor spread).
  - On average, inflation and wholesale money market developments appear to account for more than half of the changes in the common component.
  - Common shifts in euro-area risk premium differentials tend to be positively correlated with volatility in stock, currency, and emerging markets.
  - Over the short run, only 12 percent of the daily variation in the common component can be explained (Adjusted R-squared 0.13), most of which is induced by endogenous dynamic adjustments.

### Explaining developments in euro area sovereign risk during the crisis (panel estimates and country effects)
- Panel model: spread between ten-year sovereign bonds of ten euro area countries and Germany; monthly data; estimation periods January 2003-March 2009 and January 2003-January 2009.
- General-to-specific specification includes: D(Common Factor), D(Projected Debt), D(EDF), liquidity (market value of traded euro denominated long-term government bonds), projected growth, projected fiscal balances, projected current account balance.
- Key stylized facts:
  - Substantial widening of spreads since October 2008.
  - Expectations of fiscal deficits and debt levels have increased sharply.
  - Liquidity of country bond markets has not changed much over the sample.
  - Greek and Irish sovereign bonds were severely punished by markets—out of line with pre-crisis evidence and not fully explained by expected debt developments or bond market liquidity.
- Panel estimates (selected coefficients from Table 2):
  - D(Common Factor): coefficients of 4.14, 4.11, 4.08, 4.50 with P-value 0.00 in pre-October sample (January 2003-January 2009) and coefficients 4.79, 4.85, 4.87, 4.66 with P-value 0.00 in sample through March 2009.
  - D(Projected Debt Pre October): coefficients around 0.24-0.28 with P-values 0.02-0.03 in January 2003-January 2009; similar magnitudes in the longer sample.
  - D(Projected Debt Post October): coefficients 0.58 (P-value 0.00) in January 2003-January 2009 and 0.56 (P-value 0.02) in January 2003-March 2009—indicating increased sensitivity after October 2008.
  - D(EDF Post October): large and significant in the January 2003-March 2009 sample (coefficients 6.89, 6.77, 7.39, 8.66 with P-value 0.00).
  - Liquidity Pre October: negative coefficients around -0.11 to -0.14 with P-value 0.00.
  - Liquidity Post October: larger negative coefficients (e.g., -1.64, -1.68, -1.50, -1.04) with P-values from 0.06 to 0.01.
  - Adjusted R-squared reported in the tables: 0.53, 0.52, 0.51, 0.49 for various specifications; total observations 725-746 depending on sample and specification.
- Seemingly-unrelated regression (country-specific decompositions, January 2003-January 2009; total observations: 726) highlights:
  - Significant contributions from projected debt for Greece, Ireland, Spain, and to a lesser extent Austria, Italy, Portugal.
  - Rising EDFs in the financial sector translate into increases in government spreads in Austria, Ireland, and Italy.
  - Liquidity of sovereign bond markets appears to lessen Italian government financing costs.
  - A sizable part of the actual change in spreads since September 2008 remains unexplained—particularly for Greece.
- Seemingly-unrelated regression (January 2003-March 2009; total observations: 746) shows evolving contributions:
  - Investors’ risk appetite (common component) plays a much smaller role in March 2009.
  - Concerns about solvency of national financial sectors have risen particularly in Austria, Finland, Greece, and Portugal.
  - Concerns about domestic fiscal sustainability have risen in Belgium, Ireland, and Italy.
  - Liquidity of sovereign bond markets still plays a significant but limited role in a few countries.

### Policy implications and conclusions
- Fiscal policy has been used to support financial systems and aggregate demand during the crisis, but market perception of fiscal sustainability matters critically.
- Movements in sovereign spreads increasingly reflect country-specific developments: rapidly rising projected debt levels and concerns about solvency of national banking systems and their budgetary consequences.
- Markets appear to be providing greater fiscal discipline than before the crisis—sensitivity of spreads to projected debt has increased after September 2008.
- Potential adverse feedback: increasing sovereign spreads could raise governments’ marginal funding costs, partly offsetting stimulus and adding financing pressures.
- Policy recommendations from the analysis:
  - Restore trust in the financial system to shape the recovery and increase effectiveness of fiscal stimulus measures while reducing future governments’ financing costs.
  - Commit to credible long-run fiscal discipline and outline a clear exit strategy from supportive policy stances as the crisis abates.
  - Cast short-term fiscal expansion within a credible medium-term framework and envisage fiscal adjustments as economic conditions improve to curb solvency concerns.
  - Implement structural reforms tackling aging-related public costs and enhancing potential growth to improve medium-term revenue prospects and reduce solvency risks.

### Key statistics and figures (extracted)
- Common factor peak: below 20 basis points (text statement).
- Table 1 (long-run): Adjusted R-squared 0.86; Mean dependent variable 0.86; S.E. of regression 1.27; S.D. dependent variable 8.55; Durbin-Watson 0.07.
- Table 1 (short-run): Adjusted R-squared 0.13; Mean dependent variable 0.12; S.E. of regression 0.09; S.D. dependent variable 0.10; Durbin-Watson 2.01.
- Panel samples and total observations: 725, 726, 745, 746 depending on specification and sample window.
- Selected panel coefficients (D(Common Factor)): 4.14, 4.11, 4.08, 4.50 (pre-October sample variants) and 4.79, 4.85, 4.87, 4.66 (extended to March 2009); P-value 0.00 throughout.
- D(Projected Debt Post October): 0.58 (P-value 0.00), 0.56 (P-value 0.02) indicating higher sensitivity post-October 2008.
- D(EDF Post October) in January 2003-March 2009 sample: 6.89, 6.77, 7.39, 8.66 with P-value 0.00.
- Liquidity Pre October coefficients: around -0.11 to -0.14 (P-value 0.00); Liquidity Post October: around -1.64 to -1.04 with P-values 0.06 to 0.01.
- Figure notes: Projected change in the debt-to-GDP ratio over the next year (percent); Traded volume of government debt relative to the German bond market (percent).

*Sources: Datastream; Bloomberg L.P.; Moody's Creditedge; Economist Intelligence Unit; and IMF staff calculations.*

### References

### _wp09222 - References

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*Source: _wp09222 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09222.pdf_