## 9. A Summary on the Determinants of Countercyclicality of Fiscal Policy: Distinguishing between High and Low-Debt Countries

## Source details

**Canonical URL:** [9. A Summary on the Determinants of Countercyclicality of Fiscal Policy: Distinguishing between High and Low-Debt Countries](https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023089-print-pdf.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/wp/2023/english/wpiea2023089-print-pdf.pdf.md)
- [Structured JSON version](/-/media/files/publications/wp/2023/english/wpiea2023089-print-pdf.pdf.json)

---

### I. Key findings (paper summary)
- Fiscal countercyclicality has increased over time for many economies over the last two decades.
- Countercyclicality tends to be relatively stronger during severe downturns, especially in advanced economies.
- Previously estimated countercyclicality coefficients are likely to be lower bounds.
- The discretionary and automatic components of the budget balance display countercyclical effects for advanced economies, but are not pinpointed in a statistically significant way for emerging market economies and low-income developing countries.
- Fiscal countercyclicality operates primarily through the expenditure channel, with social security benefits being the most countercyclical component.
- Financial development, government size and institutional quality matter, particularly for automatic stabilizers.

### III. Methodological framework (conceptual and estimation structure)
- Main reduced-form fiscal reaction equation:
  - f_t = α + β x_t + ε_t^s
  - where f_t signals an improvement in public finances and x_t is a measure of economic activity.
- Structural feedback (fiscal multiplier, not estimated here):
  - x_t = γ + δ f_t + ε_t^m
  - structural shocks ε_t^s and ε_t^m assumed uncorrelated with positive finite variances σ_s^2 and σ_m^2.
- Solved system (as presented):
  - f_t = α + (β γ) / (1 + δ β) · ε_t^s + (β / (1 + δ β)) · ε_t^m
  - x_t = γ + (δ α) / (1 + δ β) + (δ / (1 + δ β)) · ε_t^s + (1 / (1 + δ β)) · ε_t^m
- Degree Σ of fiscal policy stabilization:
  - Σ = 1 + δ β
  - interpretation: for δ>0, Σ increases with β; OLS estimates of β are downward biased when δ≠0.
- Time-varying coefficient specification:
  - BB_it = α_it + β_it · ∆y_it + ε_it
  - where BB_it is budget balance (percent of GDP) and ∆y_it is real GDP growth rate.
- Decomposition between discretionary and automatic components:
  - CAB_it = α + β_discretionary · ∆y_it + ε_it
  - β_total = β_discretionary + β_automatic

### III.B Measuring countercyclicality and data choices
- Budget balance (BB) expressed in percent of GDP; regressions use ∆y (real GDP growth) and OG (output gap) as activity measures.
- CAB constructed using WEO output gaps when available; Hamilton filtering used when WEO gaps are not sufficiently available.
- CAB calculation approach:
  - CAB = REV · [1/(1+OG/100)] - EXP
  - (unity elasticity of government revenues to output growth and inelastic expenditure to growth per Girouard and André, 2005)

### III.C Determinants empirical approach (regression for β coefficients)
- Second-stage regression:
  - β_hat_it = δ_i + γ_t + θ' X_it + ε_it
  - δ_i: country-fixed effects; γ_t: time-fixed effects; X_it: vector of time-varying macroeconomic, structural, institutional and political variables.
- Estimation accounts for sampling error in estimated β by using Weighted Least Squares (WLS). Explanatory variables enter with one lag.
- Macroeconomic and structural covariates included:
  - Real GDP per capita
  - Inflation
  - Financial development (proxied by credit-to-GDP ratio)
  - Trade openness (exports + imports to GDP)
  - Capital account openness (Chinn-Ito index)
  - Government size (including social expenditures as percent of GDP)
  - Financial crises (Laeven and Valencia dataset)
  - Pandemics (dummy)
  - Share of agriculture value added and informality (informality from Elgin et al. (2021))
  - Fiscal space (proxies: general government gross debt and fiscal balance, both as ratios to average tax revenues, from Kose et al. (2020))
  - Fiscal rules (dummy for existing fiscal rules)
- Institutional and political variables included:
  - Democracy and governance indices
  - Constraints on the executive (veto points), polconv (political configuration)
  - Election dummies (executive and legislative)
  - Margin of majority, proportional representation, parliamentary regimes
  - Corruption

### IV. Empirical results (degree of fiscal countercyclicality across income groups, 1980–2021)
- Sample: about 190 countries, annual, 1980–2021.
- Average fiscal policy behavior: countercyclical in all income groups; degree of countercyclicality increases with development level.
- Table 1 — Real GDP Growth coefficient estimates (with standard errors in parenthesis) and sample statistics:
  - Specification mapping: (1) AE (not excluding commodity exporters), (2) EM (not excluding commodity exporters), (3) LIC (not excluding commodity exporters), (4) AE (excluding commodity exporters), (5) EM (excluding commodity exporters), (6) LIC (excluding commodity exporters), (7) Commodity exporters.
  - Coefficients:
    - (1) 0.2981*** (0.050)
    - (2) 0.2998*** (0.055)
    - (3) 0.1332** (0.051)
    - (4) 0.3036*** (0.050)
    - (5) 0.1442*** (0.039)
    - (6) 0.1695*** (0.059)
    - (7) 0.2694*** (0.076)
  - Observations:
    - (1) 1,274
    - (2) 2,735
    - (3) 1,653
    - (4) 1,156
    - (5) 1,770
    - (6) 1,161
    - (7) 1,575
  - Number of countries:
    - (1) 37
    - (2) 93
    - (3) 56
    - (4) 34
    - (5) 61
    - (6) 39
    - (7) 52
  - R-squared:
    - (1) 0.6099
    - (2) 0.2751
    - (3) 0.2494
    - (4) 0.5655
    - (5) 0.3739
    - (6) 0.1952
    - (7) 0.3066
  - Note: Robust standard errors clustered at the country level. Symbols *, **, *** denote statistical significance at the 10, 5 and 1 percent levels. Constant terms and country and time fixed effects are included but not shown.
- Interpretation from text:
  - Excluding commodity exporters suggests fiscal stabilization coefficients are highest among AEs at 0.3, while magnitudes are about 0.14 and 0.17 for EMs and LICs, respectively.

### IV.A Addressing endogeneity in estimating fiscal countercyclicality
- Endogeneity concern: OLS β estimates are expected to be downward biased due to simultaneous feedback (fiscal multiplier).
- Estimators and instruments used:
  - Estimators: Ordinary Least Squares (OLS), Generalized Method of Moments (GMM), Two-Stage Least Squares (TSLS).
  - Instruments: (i) lagged real GDP growth; (ii) contemporaneous and lagged growth of main trading partners.
- Result summary:
  - Results confirm that, with the exception of LICs, point estimates are higher once endogeneity is addressed, especially when using TSLS.
  - (Figure note: Missing bars denote insignificant coefficients.)

### Policy-relevant implications and interpretation
- For δ>0, higher measured fiscal countercyclicality β implies greater fiscal stabilization Σ = 1 + δ β.
- OLS estimates likely understate true countercyclicality; instrumentation (TSLS/GMM) increases estimated β for advanced and emerging market economies (less so for LICs).
- Automatic stabilizers and discretionary policy both contribute to stabilization in advanced economies; in EMs and LICs the statistical significance of discretionary vs automatic components is weaker.
- Financial development, larger government size and better institutional quality are associated with stronger automatic stabilizers and greater countercyclicality.

### Additional key findings and quantified magnitudes
- The overall change in fiscal balance includes a component of 0.17 percentage point of GDP, compared to an increase of 0.12 points for the discretionary part.
- Average degree of fiscal countercyclicality by income group:
  - Advanced economies (AEs): 0.4
  - Emerging markets (EMEs): 0.3
  - Low-income countries (LICs): 0.19
- Median countercyclicality of fiscal policy over time:
  - 1990: 0.15
  - 2019: 0.25
  - 2020 (peak of the pandemic): around 0.3
- Government revenues and expenditures as a share of GDP act countercyclically:
  - A one percentage-point increase in real GDP growth is estimated to increase the revenue ratio by 0.034 percentage points.
  - A one percentage-point increase in real GDP growth is estimated to decrease the expenditure ratio by 0.2 percentage point of GDP.
- Discretionary tax policy is typically procyclical: estimates of β_disc are negative and statistically significant for all tax items.
- Investment spending is slightly procyclical.
- Countercyclicality of fiscal policies has increased over time for many economies over the last two decades, particularly for emerging market economies.
- Countercyclicality tends to be much stronger during severe downturns and statistically different from typical recessions, especially for advanced economies.
- Quantified determinants (selected estimates preserved exactly as reported):
  - Credit-to-GDP: A one percentage point increase in the ratio of credit to GDP is associated with an increase in the fiscal countercyclicality coefficient ranging between 0.14-0.24 points.
  - GDP per capita: Increasing real GDP per capita by one dollar leads to an improvement of the fiscal stabilization coefficient that ranges between 0.09-0.16 points.
    - Note: coefficient turns negative and significant at the 10 percent level when CPI inflation is introduced (specification 7), partly owing to a drop in sample size from 3,224 to 774.
  - Gross debt ratio: An additional one percentage point increase in the gross debt ratio is associated with increases in the fiscal countercyclicality coefficient of 0.02 and 0.05 (two reported estimates).
  - Political/institutional variables: Increasing the margin of majority index by 1 point is associated with a 0.06-0.1 percentage points increase in the fiscal countercyclicality coefficient. Reducing government fractionalization by 1 point is associated with a 0.06-0.1 percentage points increase in the fiscal countercyclicality coefficient.
  - Banking crises are positively related to fiscal countercyclicality.
- Cross-group heterogeneity:
  - Advanced economies: higher financial and economic development, larger government sizes, and better institutional quality explain relatively higher countercyclicality coefficients; trade and capital account openness are negatively correlated with fiscal countercyclicality in AEs.
  - Emerging markets and developing economies: trade and capital account openness are positively associated with fiscal countercyclicality; government size tends to have a larger effect in AEs than in developing economies, while the opposite is true for the level of economic and financial development.
  - High-debt vs low-debt countries: differences in signs and significance across explanatory variables for overall stabilization and automatic stabilization by debt status are reported (Table 9 summary referenced).

### Time variation, distribution and crisis asymmetry
- Panel (1) estimated over 10-year rolling windows shows a slow upward trend of countercyclicality since 1990, with a more notable upward movement during 2000-10.
- Country-by-country regressions (for countries with at least 20 continuous observations) reveal:
  - EMs show larger dispersion with greater density toward the lower half of the distribution.
  - AEs show a distribution tilted to the higher end.
- Asymmetry during recessions and crises:
  - Recession groupings:
    - (i) Typical recessions: growth below the country’s own average of the previous three years.
    - (ii) Global financial crisis (2008-10).
    - (iii) COVID-19 pandemic (2020-21).
  - Fiscal policy tends to be more countercyclical during severe crises than in normal recessions, particularly during the Global Financial Crisis (2008-10) and the COVID-19 pandemic (2020-21).
- More than 70 percent of AEs conducted a more aggressive countercyclical fiscal policy during the GFC and COVID-19 pandemic than in a typical recession.

### Robustness and limitations
- Robustness checks using alternative indicators, exclusion of country and/or time fixed effects, and splitting sample into high-debt versus low-debt countries yield results largely consistent with baseline specification.
- Limitation: the paper does not provide a benchmark for the optimal degree of fiscal countercyclicality.

*Source: IMF Working Paper — Revisiting the Countercyclicality of Fiscal Policy (chapter 9 content provided).*

### References .............................................................................................................

### References

### Figures
- 1. Addressing Potential Endogeneity in Estimating Fiscal Countercyclicality Coefficients ................................. 12
- 2. Components of Fiscal Countercyclicality, 1980-2021 ..................................................................................... 13
- 3. Distribution Fiscal Countercyclicality Coefficients by Income Groups ............................................................. 14
- 4. Interquartile Range of Time-Varying Fiscal Countercyclicality ........................................................................ 14
- 5. Fiscal Countercyclicality in Large Crises ......................................................................................................... 15

### Tables
- 1. Overall Fiscal Countercyclicality, 1980-2021 .................................................................................................. 12
- 2. Countercyclical Properties of Government Revenues .................................................................................... 15
- 3. Countercyclical Properties of Government Expenditures ................................................................................ 16
- 4. Key Determinants of the Countercyclicality of Fiscal Policy, 1990-2021 ........................................................ 17
- 5. Determinants of Fiscal Stabilization for Advanced Economies, 1990-2021 .................................................... 18
- 6. Determinants of Fiscal Stabilization for Emerging Markets and Developing Economies, 1990-2021 ............. 19
- 7. Determinants of Automatic Stabilizers, 1990-2021 ......................................................................................... 20
- 8. Determinants of Countercyclicality of Fiscal Policy, Robustness check with Alternative Specifications ......... 21

*Content from: wpiea2023089-print-pdf - References ......................................................................................................... 25*

### 9. A Summary on the Determinants of Countercyclicality of Fiscal Policy: Distinguishing between High and

### 9. A Summary on the Determinants of Countercyclicality of Fiscal Policy: Distinguishing between High and Low-Debt Countries

### I. Key findings (paper summary)
- Fiscal countercyclicality has increased over time for many economies over the last two decades.
- Countercyclicality tends to be relatively stronger during severe downturns, especially in advanced economies.
- Previously estimated countercyclicality coefficients are likely to be lower bounds.
- The discretionary and automatic components of the budget balance display countercyclical effects for advanced economies, but are not pinpointed in a statistically significant way for emerging market economies and low-income developing countries.
- Fiscal countercyclicality operates primarily through the expenditure channel, with social security benefits being the most countercyclical component.
- Financial development, government size and institutional quality matter, particularly for automatic stabilizers.

### III. Methodological framework (conceptual and estimation structure)
- Main reduced-form fiscal reaction equation (in general form):
  - f_t = α + β x_t + ε_t^s
  - where f_t signals an improvement in public finances (e.g., budget balance, fiscal revenues, the negative of government expenditure) and x_t is a measure of economic activity.
- Fiscal multiplier (structural feedback, not estimated in this paper):
  - x_t = γ + δ f_t + ε_t^m
  - structural shocks ε_t^s and ε_t^m assumed uncorrelated with positive finite variances σ_s^2 and σ_m^2.
- Solving the system yields:
  - f_t = α + (β γ) / (1 + δ β) · ε_t^s + (β / (1 + δ β)) · ε_t^m  (as presented in paper)
  - x_t = γ + (δ α) / (1 + δ β) + (δ / (1 + δ β)) · ε_t^s + (1 / (1 + δ β)) · ε_t^m
- Degree Σ of fiscal policy stabilization:
  - Σ = 1 + δ β
  - interpretation: for δ>0, Σ increases with β; OLS estimates of β are downward biased when δ≠0.
- Time-varying coefficient specification:
  - BB_it = α_it + β_it · ∆y_it + ε_it
  - where BB_it is budget balance (percent of GDP) and ∆y_it is real GDP growth rate.
- Decomposition between discretionary and automatic components:
  - CAB_it = α + β_discretionary · ∆y_it + ε_it
  - β_total = β_discretionary + β_automatic

### III.B Measuring countercyclicality and data choices
- Budget balance (BB) expressed in percent of GDP, regressions use ∆y (real GDP growth) and OG (output gap) as activity measures.
- CAB (cyclically adjusted balance) constructed using WEO output gaps when available; Hamilton filtering used to obtain output gaps consistently across a wide set of countries when WEO gaps are not sufficiently available.
- CAB calculation approach (as described):
  - CAB = REV · [1/(1+OG/100)] - EXP
  - (unity elasticity of government revenues to output growth and inelastic expenditure to growth per Girouard and André, 2005)

### III.C Determinants empirical approach (regression for β coefficients)
- Second-stage regression for estimated β coefficients (using Hamilton-filtered output gaps for panel availability):
  - β_hat_it = δ_i + γ_t + θ' X_it + ε_it
  - δ_i: country-fixed effects; γ_t: time-fixed effects; X_it: vector of time-varying macroeconomic, structural, institutional and political variables.
- Estimation accounts for sampling error in estimated β by using Weighted Least Squares (WLS). Explanatory variables enter with one lag to reduce reverse causality.
- Macroeconomic and structural covariates included (explicit list preserved):
  - Real GDP per capita
  - Inflation
  - Financial development (proxied by credit-to-GDP ratio)
  - Trade openness (exports + imports to GDP)
  - Capital account openness (Chinn-Ito index)
  - Government size (including social expenditures as percent of GDP)
  - Financial crises (Leaven and Valencia dataset)
  - Pandemics (dummy)
  - Share of agriculture value added and informality (informality from Elgin et al. (2021))
  - Fiscal space (proxies: general government gross debt and fiscal balance, both as ratios to average tax revenues, from Kose et al. (2020))
  - Fiscal rules (dummy for existing fiscal rules)
- Institutional and political variables included (explicit list preserved):
  - Democracy and governance indices
  - Constraints on the executive (veto points), polconv (political configuration)
  - Election dummies (executive and legislative)
  - Margin of majority, proportional representation, parliamentary regimes
  - Corruption

### IV. Empirical results (degree of fiscal countercyclicality across income groups, 1980–2021)
- Sample: about 190 countries, annual, 1980–2021.
- Average fiscal policy behavior: countercyclical in all income groups; degree of countercyclicality increases with development level.
- Table 1 (Overall Fiscal Countercyclicality, 1980-2021) — main coefficient estimates and sample statistics (preserved exactly):
  - Specification columns correspond to: (1) AE (not excluding commodity exporters), (2) EM (not excluding commodity exporters), (3) LIC (not excluding commodity exporters), (4) AE (excluding commodity exporters), (5) EM (excluding commodity exporters), (6) LIC (excluding commodity exporters), (7) Commodity exporters.
  - Real GDP Growth coefficient estimates (with standard errors in parenthesis):
    - (1) 0.2981*** (0.050)
    - (2) 0.2998*** (0.055)
    - (3) 0.1332** (0.051)
    - (4) 0.3036*** (0.050)
    - (5) 0.1442*** (0.039)
    - (6) 0.1695*** (0.059)
    - (7) 0.2694*** (0.076)
  - Observations:
    - (1) 1,274
    - (2) 2,735
    - (3) 1,653
    - (4) 1,156
    - (5) 1,770
    - (6) 1,161
    - (7) 1,575
  - Number of countries:
    - (1) 37
    - (2) 93
    - (3) 56
    - (4) 34
    - (5) 61
    - (6) 39
    - (7) 52
  - R-squared:
    - (1) 0.6099
    - (2) 0.2751
    - (3) 0.2494
    - (4) 0.5655
    - (5) 0.3739
    - (6) 0.1952
    - (7) 0.3066
  - Note (from table): Robust standard errors clustered at the country level. Symbols *, **, *** denote statistical significance at the 10, 5 and 1 percent levels. Constant terms and country and time fixed effects are included but not shown.
- Interpretation highlighted in text:
  - Excluding commodity exporters suggests fiscal stabilization coefficients are highest among AEs at 0.3, while magnitudes are about 0.14 and 0.17 for EMs and LICs, respectively (as shown in the table and text).

### IV.A Addressing endogeneity in estimating fiscal countercyclicality
- Endogeneity concern: OLS β estimates are expected to be downward biased due to simultaneous feedback (fiscal multiplier).
- Alternative estimators applied and instruments used:
  - Estimators: Ordinary Least Squares (OLS), Generalized Method of Moments (GMM), Two-Stage Least Squares (TSLS).
  - Instruments: (i) lagged real GDP growth; (ii) contemporaneous and lagged growth of main trading partners.
- Result summary (from Figure 1 note and accompanying text):
  - Results confirm that, with the exception of LICs, point estimates are higher once endogeneity is addressed, especially when using TSLS.
  - (Figure note: Missing bars denote insignificant coefficients.)

### Policy-relevant implications and interpretation (preserved from text)
- For a given positive fiscal multiplier (δ>0), higher measured fiscal countercyclicality β implies greater fiscal stabilization Σ = 1 + δ β.
- OLS estimates likely understate true countercyclicality; instrumentation (TSLS/GMM) increases estimated β for advanced and emerging market economies (less so for LICs).
- Automatic stabilizers and discretionary policy both contribute to stabilization in advanced economies; in EMs and LICs the statistical significance of discretionary vs automatic components is weaker.
- Financial development, larger government size and better institutional quality are associated with stronger automatic stabilizers and greater countercyclicality.

*Source: IMF Working Paper — Revisiting the Countercyclicality of Fiscal Policy (chapter 9 content provided).*

### 0.17 percentage point of GDP, compared to an increase of 0.12 points for the discretionary part. The

### wpiea2023089-print-pdf - 0.17 percentage point of GDP, compared to an increase of 0.12 points for the discretionary part. The

### Key findings on countercyclicality
- The overall change in fiscal balance includes a component of 0.17 percentage point of GDP, compared to an increase of 0.12 points for the discretionary part.
- Average degree of fiscal countercyclicality by income group:
  - Advanced economies (AEs): 0.4
  - Emerging markets (EMEs): 0.3
  - Low-income countries (LICs): 0.19
- Median countercyclicality of fiscal policy over time:
  - 1990: 0.15
  - 2019: 0.25
  - 2020 (peak of the pandemic): around 0.3

### Components and statistical notes
- The study decomposes fiscal response into discretionary component and automatic stabilizers.
- For two components, coefficients are similar in the case of EMs, though they are not statistically significant individually.
- The point estimates suggest procyclical behavior for LICs in Figure 2, a result that contrasts with Table 1; this discrepancy is attributed to differences in samples across the two exercises.
- Panel regressions are estimated in an unbalanced sample across income groups.
- Left chart specification: cyclically adjusted budget balance (CAB) from the IMF WEO as dependent variable, regressed against real GDP growth.
- Right chart specification: difference between the overall budget balance and the CAB (devoted to automatic stabilizers) as dependent variable.
- Lighter bars in figures denote statistically insignificant coefficient estimates at the 10 percent level.
- Country and time fixed effects are included in regressions; robust standard errors clustered at the country level are used.

### Country-level distribution and dispersion
- Country-by-country regressions are estimated individually for countries with at least 20 continuous observations.
- Dispersion patterns:
  - EMs show larger dispersion with greater density toward the lower half of the distribution.
  - AEs show a distribution tilted to the higher end.

### Time-varying behavior and rolling windows
- Panel (1) is also estimated over 10-year rolling windows to explore time variation.
- Estimation results indicate a slow upward trend of countercyclicality since 1990, with a more notable upward movement during 2000-10 (confirming Furceri and Jalles 2018, who showed data only until 2014).

### Asymmetry during recessions and crises
- Recessions are grouped into three categories for asymmetry analysis:
  - (i) Typical recessions: periods when an individual country’s growth is below the country’s own average of the previous three years.
  - (ii) Global financial crisis (2008-10).
  - (iii) COVID-19 pandemic (2020-21).
- Fiscal policy tends to be more countercyclical during severe crises than in normal recessions, particularly during:
  - the Global Financial Crisis (2008-10)
  - the COVID-19 pandemic (2020-21)

*IMF Working Paper excerpt from the provided PDF content.*

### conclusion by calculating the share of countries in each income group that have displayed a larger

### V. Conclusions

### Overview and dataset
- Novel dataset: time-varying measures of fiscal countercyclicality for a large and unbalanced panel of advanced and emerging market and developing economies between 1980 and 2021.
- Purpose: investigate scope, time trend, cross-country variation, role of discretionary policy vs automatic stabilizers, budget-component effects, and macroeconomic/structural determinants.
- Methodological advantage: time-varying measures account for country-specific and global factors and different effects during severe crises.

### Key empirical findings
- More than 70 percent of AEs conducted a more aggressive countercyclical fiscal policy during the GFC and COVID-19 pandemic than in a typical recession.
- Both government revenues and expenditures as a share of GDP act countercyclically:
  - A one percentage-point increase in real GDP growth is estimated to increase the revenue ratio by 0.034 percentage points.
  - A one percentage-point increase in real GDP growth is estimated to decrease the expenditure ratio by 0.2 percentage point of GDP.
- Discretionary tax policy is typically procyclical: estimates of β_disc are negative and statistically significant for all tax items.
- Countercyclicality of fiscal policy operates primarily through the expenditure side; social benefits are the most countercyclical component.
- Investment spending is slightly procyclical.
- The countercyclicality of fiscal policies has increased over time for many economies over the last two decades, particularly for emerging market economies.
- Countercyclicality tends to be much stronger during severe downturns and statistically different from typical recessions, especially for advanced economies.
- Previously estimated coefficients on countercyclicality are likely to be lower bounds.
- The discretionary and automatic components of the budget balance display countercyclical effects for advanced economies, but cannot be pinpointed in a statistically significant way for emerging market economies and low-income countries.

### Quantified determinants and magnitudes
- Financial and economic development, government size, and institutional quality matter for the degree of countercyclicality.
- Credit-to-GDP:
  - A one percentage point increase in the ratio of credit to GDP is associated with an increase in the fiscal countercyclicality coefficient ranging between 0.14-0.24 points.
- GDP per capita:
  - Increasing real GDP per capita by one dollar leads to an improvement of the fiscal stabilization coefficient that ranges between 0.09-0.16 points.
  - Note: coefficient turns negative and significant at the 10 percent level when CPI inflation is introduced (specification 7), partly owing to a drop in sample size from 3,224 to 774.
- Gross debt ratio:
  - An additional one percentage point increase in the gross debt ratio is associated with increases in the fiscal countercyclicality coefficient of 0.02 and 0.05 (two reported estimates).
- Political/institutional variables:
  - Increasing the margin of majority index by 1 point is associated with a 0.06-0.1 percentage points increase in the fiscal countercyclicality coefficient.
  - Reducing government fractionalization by 1 point is associated with a 0.06-0.1 percentage points increase in the fiscal countercyclicality coefficient.
- Banking crises are positively related to fiscal countercyclicality.
- Automatic stabilizers:
  - The impact of financial and economic development on automatic stabilizers is relatively less pronounced than for the overall coefficient.
  - Government size and gross debt ratio have a more pronounced impact on automatic stabilization.

### Cross-group heterogeneity
- Advanced economies (AEs):
  - Higher levels of financial and economic development, larger government sizes, and better institutional quality explain relatively higher countercyclicality coefficients.
  - Trade and capital account openness are negatively correlated with fiscal countercyclicality in AEs.
- Emerging markets and developing economies:
  - Trade and capital account openness are positively associated with fiscal countercyclicality.
  - Government size tends to have a larger effect in AEs than in developing economies, while the opposite is true for the level of economic and financial development.
- High-debt vs low-debt countries:
  - Summary table (Table 9) indicates differences in signs and significance across explanatory variables for overall stabilization and automatic stabilization by debt status (signs and statistical significance preserved as reported).

### Robustness and limitations
- Robustness checks:
  - Alternative indicators, exclusion of country and/or time fixed effects, and splitting sample into high-debt versus low-debt countries yield results largely consistent with baseline specification.
- Limitation:
  - The paper does not provide a benchmark for the optimal degree of fiscal countercyclicality.

*IMF WORKING PAPERS — Revisiting the Countercyclicality of Fiscal Policy. INTERNATIONAL MONETARY FUND*

### References

### References

### Citations
- Acemoglu,  D.,  S.  Naidu,  P.  Restrepo,  and  J.  A.  Robinson  (2013),  “Democracy  Does  Cause  Growth”,  NBER  
  Working Paper 20004.
- Afonso, A., and D. Furceri. (2010), “Government Size, Composition, Volatility and Economic Growth”, European 
  Journal of Political Economy, 26 (4): 517–32.
- Afonso,  A.,  and  J.  T.  Jalles.  (2013),  “The  Cyclicality  of  Education,  Health,  and  Social  Security  Government  
  Spending”, Applied Economics Letters, 20 (7): 669–72.
- Aghion, P. and I. Marinescu (2008), “Cyclical Budgetary Policy and Economic Growth: What Do We Learn from 
  OECD Panel Data?”, NBER Macroeconomics Annual, Volume 22
- Aghion,  P.,  G.  Angeletos,  A.  Banerjee  and  K.  Manova  (2005),  “Volatility  and  Growth:  Credit  Constraints  and  
  Productivity Enhancing Investment,” NBER Working Paper 11349.
- Alonso-Ortiz, J., and R. Rogerson (2010). “Taxes, Transfers and Employment in an Incomplete Markets Model”. 
  Journal of Monetary Economics, 57 (8), 949–958.
- Auerbach, A. J. and L. J. Kotlikoff (1987). “Dynamic Fiscal Policy”. Cambridge: Cambridge University Press.
- Auerbach, (2008). “How Much Should We Rely on Fiscal Stimulus?”, Presentation at Federal Reserve Bank of 
  San Francisco Symposium).
- Auerbach, A. J. and Feenberg, D. (2000). “The Significance of Federal Taxes as Automatic Stabilizers”. Journal 
  of Economic Perspectives, 14, 37–56.
- Auerbach, A. (2009), “Implementing the new fiscal policy activism”, American Economic Review, 99(2), 543-549.
- Baunsgaard, T. and Symansky, S. A. (2009). “Automatic Fiscal Stabilizers”. IMF Staff Position Note 09/23.
- Berman,  N,  Eymard,  L,  Aghion,  P,  Askenazy,  P,  and  G.  Cette  (2007),  “Credit  Constraints  and  Cyclical  R&D  
  Investment: Evidence from French Firm-Level Panel Data”, mimeo Banque de France.
- Blanchard, O. (1993), “Suggestions for a New Set of Fiscal Indicators.” In The Political Economy of Government 
  Debt, edited by H. A. A. Verbon and F. A. A. M. Van Winden. Amsterdam: Elsevier Science.
- Blanchard, O. J. (1985), “Debt, Deficits and Finite Horizons”, Journal of Political Economy, 93(2), 223–47.
- Blanchard, O. J., and L. H. Summers (1984), “Perspectives on High World Real Interest Rates”, Brookings Papers 
  on Economic Activity, 2, 273–334.
- Blinder,  A.  S.  (1975):  “Distribution  Effects  and  the  Aggregate  Consumption  Function,”  Journal  of  Political  
  Economy, 83 (3), 447–475.
- Brown, E. C. (1955). “The Static Theory of Automatic Fiscal Stabilization”, Journal of Political Economy, 3 (5), 
  427–440.
- Brunila, A., M. Buti, and J. in’t Veld (2003), “Fiscal Policy in Europe: How Effective are Automatic Stabilisers?”, 
  Empirica, Vol. 30: 1-24.
- Challe, E., and X. Ragot (2015). “Precautionary Saving Over the Business Cycle”. Economic Journal, 126(590), 
  135–164.
- Chinn, Menzie D. and Hiro Ito (2006), "What Matters for Financial Development? Capital Controls, Institutions, 
  and Interactions," Journal of Development Economics, 81(1), 163-192.
- Christiano,  L.  J.  (1984),  “A  Reexamination  of  the  Theory  of  Automatic  Stabilizers,”  Carnegie-Rochester  
  Conference Series on Public Policy, 20 (1), 147–206.
- Darby, J., Melitz, J. and Masten, I. (2008), “Social Spending and Automatic Stabilizers in the OECD,” Economic 
  Policy, 23(56), 715-756.
- Debrun,  X.  and  R.  Kapoor  (2011),  “Fiscal  Policy  and  Macroeconomic  Stability:  New  Evidence  and  Policy  
  Implications”, Nordic Economic Policy Review, 1(1), 35-70.
- Debrun,  X.,  Pisani-Ferry,  J.,  Sapir,  A.  (2008),  “Government  Size  and  Output  Volatility:  Should  We  Forsake  
  Automatic Stabilization?”, International Monetary Fund, IMF Working Paper 08/122, May 2008.
- Dolls, M., Fuest, C., and Peichl, A. (2016). "Automatic Stabilizers, Economic Crisis and Income Distribution in 
  Europe" In Who Loses in the Downturn? Economic Crisis, Employment and Income Distribution.
- Dolls, M., Fuest, C. and Peichl, A. (2012a), "Automatic stabilizers and economic crisis: US vs. Europe", Journal 
  of Public Economics, 96, 279-294.
- Dolls, M., Fuest, C., and Peichl, A. (2012b). Automatic stabilization and discretionary fiscal policy in the financial 
  crisis. IZA Journal of Labor Policy, 1:4.
- Drazen,  A.  (2000),  “The  Political  Business  Cycle  after  25  Years.”  In:  B.  Bernanke  and  K.  Rogoff,  eds.  NBER  
  Macroeconomics Annual 2000. Cambridge, MA: MIT Press.
- Elgin,  C.,  M.  A.  Kose,  F.  Ohnsorge,  and  S.  Yu.  2021.  “Understanding  Informality.”  CERP  Discussion  Paper  
  16497, Centre for Economic Policy Research, London.
- European Commission (2017b), “Automatic stabilisers in the euro area: A model-based assessment”, European 
  Economic Forecast Autumn 2017, 65-68.
- Fatás,  A.  and  I.  Mihov  (2001),  “Government  size  and  automatic  stabilizers:  international  and  intranational  
  evidence”, Journal of International Economics, 55(1), 3-28.
- Fatas, A. and I. Mihov (2003), “The Case for Restricting Fiscal Policy Discretion”, Quarterly Journal of Economics, 
  118: 1419-1447.
- Fatas, A. and I. Mihov (2013), “Policy Volatility, Institutions, and Economic Growth”, Review of Economics and 
  Statistics, 95, 362-376.,
- Fatás, A. and I. Mihov (2012), “Fiscal Policy as a Stabilization Tool”, The B.E. Journal of Macroeconomics, 12(3), 
  1-68.
- Floden, M. (2001). “The Effectiveness of Government Debt and Transfers as Insurance”. Journal of Monetary 
  Economics, 48 (1), 81–108.
- Frankel, J., C. Vegh and G. Vuletin (2011), “On graduation from fiscal procyclicality,” NBER Working Paper No. 
  17619 (November).
- Furceri, D.  and J. T. Jalles (2019), "Fiscal counter-cyclicality and productive investment: evidence from advanced 
  economies," The B.E. Journal of Macroeconomics, 19(1), 1-15.
- Furceri, D. (2010), “Stabilization effects of social spending: Empirical evidence from a panel of OECD countries”, 
  North American Journal of Economics and Finance, 21(1), 34-48.
- Furceri,  D.,  Karras,  G.  (2007),  “Country  Size  and  Business  Cycle  Volatility:  Scale  Really  Matters”,  Journal  of  
  Japanese and International Economies, 21(4), 424-434.
- Galí, J. (1994), “Government Size and Macroeconomic Stability”, European Economic Review, 38, 117–32
- Galeano,  L.,  Izquierdo,  A.,  Puig,  J.,  Vegh,  C.,  Vuletin,  G.  (2021).  “Can  automatic  government  spending  be  
  procyclical?”, NBER working paper 28521.
- Ilzetzki,  E.  and  Vegh,  C.  (2008).  “Procyclical  fiscal  policy  in  developing  countries:  Truth  or  Fiction?”  NBER  
  Working Paper No. 14191
- Imbs, J. (2007), “Growth and volatility”, Journal of Monetary Economics, 54 (7), 1848-1862.
- IMF, 2015. World Economic Outlook, October.
- IMF, 2015. Fiscal Monitor, April 2015: Now Is the Time: Fiscal Policies for Sustainable Growth.
- IMF, 2022. Fiscal Monitor, October 2022: Helping People Bounce Back.
- Knieser and Ziliak (2002), “Tax reform and automatic stabilization”, American Economic Review, 45(1), 1-28.
- Kose, M. A., Kurlat, S., Ohnsorge, F., Sugawara, N. (2022). “A cross-country database of fiscal space”. Journal 
  of International Money and Finance, 128, 102682.
- Kumhof, M., and D. Laxton, (2009), “Simple, Implementable Fiscal Policy Rules”, IMF Working Paper 09/76.
- Laeven,  L.  and  Valencia  F.,  (2020),  “Systemic  Banking  Crises  Database  II”,  IMF  Economic  Review,  68,  307–
  361.
- Lane,  P.  R.  (2003),  “The  Cyclical  Behaviour  of  Fiscal  Policy:  Evidence  from  the  OECD”,  Journal  of  Public  
  Economics, 87(12), 2661–2675.
- Ma, C. Rogers, J., and Zhou, S. (2020). “Modern Pandemics: Recession and Recovery”.
- McKay, A. and Reis, R. (2016). “The Role of Automatic Stabilizers in the U.S. Business Cycle”. Econometrica, 
  84(1), 141–194.
- McKay, A. and Reis, R. (2021). “Optimal Automatic Stabilizers”. Review of Economic Studies, 0, 1–32
- Mohl,  P.;  Mourre,  G.;  Stovicek,  K.  (2019).  “Automatic  Fiscal  Stabilisers  in  the  EU:  Size  and  Effectiveness”.  
  Economic Brief 042. European Commission.
- Oh, H., and R. Reis (2012): “Targeted Transfers and the Fiscal Response to the Great Recession,” Journal of 
  Monetary Economics, 59, S50–S64.
- Persson,  T.  and  G.  Tabellini  (2000),  “Political  Economics:  Explaining  Economic  Policy”,  Cambridge,  MA:  MIT  
  Press
- Ramey,  G.  and  V.  A.  Ramey  (1995),  “Cross-Country  Evidence  on  the  Link-Between  Volatility  and  Growth”,  
  American Economic Review, 85, 1138–51.
- Ratto M, W. Roeger and J. in’t Veld (2009). “QUEST III: An Estimated Open-Economy DSGE Model of the Euro 
  Area with Fiscal and Monetary Policy”, Economic Modelling, 26, 222-233.
- Rodrik, D. (1998), “Why Do More Open Economies Have Bigger Governments”, Journal of Political Economy, 
  106, 997-1032.
- Seidman, L. S and Lewis, K. W. (2002). “A New Design for Automatic Fiscal Policy”. International Finance 5(2), 
  2002: pp. 251–284
- Talvi,  E.,  and  C.  Vegh.  (2005).  “Tax  Base  Variability  and  Procyclical  Fiscal  Policy”,  Journal  of  Development  
  Economics, 78, 156-90
- Taylor, J. B. (2000). “Reassessing Discretionary Fiscal Policy”. Journal of Economic Perspectives14(3),21–36.
- Tödter, K., and M. Scharnagl (2004), “How effective are automatic stabilisers? Theory and empirical results for 
  Germany and other OECD countries”, Deutsche Bundesbank Discussion Paper, 21.
- van den Noord, P. (2000). “The Size and Role of Automatic Fiscal Stabilizers in the 1990s and Beyond”, OECD 
  Working Paper 230.

*Revisiting the Countercyclicality of Fiscal Policy Working Paper No. WP/2023/089*

---


_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023089-print-pdf.pdf_