## _afr1604 — Chapter 1. Introduction

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---

### Scope and structure
- Chapters cover measurement, extent, determinants, and country case studies of fiscal procyclicality in Sub-Saharan Africa:
  - Chapter 2. How to Measure the Degree of Fiscal Procyclicality
  - Chapter 3. To What Extent Has the Fiscal Policy Been Procyclical among Sub-Saharan African Countries?
    - The Business Cycle in Sub-Saharan Africa
    - The Fiscal Policy Stance
    - Fiscal Policy Procyclicality
  - Chapter 4. What Explains the Degree of Fiscal Policy Procyclicality among Sub-Saharan African Countries?
  - Chapter 5. Country Case Studies (Nigeria; Botswana; Chile)
  - Chapter 6. Conclusion
  - Appendix I. Data Sources and Definition of Variables
  - Appendix II. Endogeneity Concern: Do Output Shocks Drive Fiscal Policy, or Do Fiscal Policy Shocks Cause Output Shocks?
- Empirical materials referenced include figures and tables such as:
  - Figure 1. GDP Growth Rates by Country Groups, 2000–14
  - Figure 2. Output Gaps by Country Groups, 2000–14
  - Figures and tables documenting fiscal impulses, cyclically adjusted balances, sensitivity estimates, and cross-country GMM results.

### Key findings: overall results and stylized facts
- General findings:
  - Sub-Saharan African countries ran procyclical fiscal policies in general during 2000–14.
  - Procyclicality was particularly pronounced among oil exporters.
  - Procyclicality intensified after the global financial crisis (2009), especially for oil exporters.
- Drivers found to reduce procyclicality:
  - Deeper financial markets (financial depth).
  - Higher reserves coverage (gross international reserves, GIR).
- Institutional quality (IQ) was not statistically significant in cross-country regressions for this sample—likely due to limited cross-country variation in IQ among these countries.
- Public investment played a large and increasing role in the fiscal stance of oil-exporting countries.
- Business cycle stylized facts (2000–14):
  - Four subperiods: 2000–04; 2005–08 (acceleration); 2009 (sharp fall after global financial crisis); 2010–14 (recovery but below 2005–08 levels).
  - Output gaps average positive for 2005–08 and 2010–14; average negative for 2000–04 and 2009.
  - Oil exporters experienced more extreme average gaps and greater dispersion than mineral exporters and other countries.

### Measurement and econometric approach
- Sample and period:
  - Country sample: 43 sub-Saharan African countries (all sub-Saharan African countries excluding South Sudan and Zimbabwe).
  - Sample period: 2000 to 2014, except Cabo Verde (2002‒14), Chad (2004‒14), Malawi (2002‒14), Niger (2006‒14), São Tomé and Príncipe (2001‒14).
- Fiscal stance measures:
  - For resource-rich countries: cyclically adjusted nonresource primary balance measured in percent of nonresource GDP.
  - For other countries: cyclically adjusted standard primary balance measured in percent of GDP.
- Cyclical adjustment:
  - Output gap estimated with Hodrick-Prescott (H-P) filter on annual (total or nonresource) real GDP.
  - capb = (R*(YP/Y) – G) / Y, with elasticity of nonresource revenues = 1 and primary expenditure elasticity = 0.
  - Fiscal expansion when Δcapb < 0; contraction when Δcapb > 0. Countercyclical if expansion accompanies negative change in output gap (and vice versa); procyclical if expansion accompanies positive change in output gap (and vice versa).
- Regression specifications:
  - Panel regressions with dependent variables: cyclically adjusted (nonresource) primary balance (% of nonresource GDP) or (nonresource) primary balance (% of nonresource GDP).
  - Key independent variables: nonresource output gap or nonresource real GDP growth.
  - Endogeneity addressed with instrumentation and panel GMM.

### Empirical estimates and key statistics
- Panel regressions (examples reported):
  - Table 3a (Output Gap regressions):
    - Output Gap coefficient, 2000-14 = –0.16 (t-stat 1.01)
    - Output Gap coefficient, 2005-08 = –0.66 (t-stat 0.41)
    - Output Gap coefficient, 2010-14 = –2.9 (t-stat 2.77)
  - Table 3b (Real GDP Growth regressions):
    - Real GDP Growth, 2000-14 = –2.03*** (t-stat 0.56)
    - Real GDP Growth, 2005-08 = –0.84*** (t-stat 0.15)
    - Real GDP Growth, 2010-14 = –3.84** (t-stat 1.64)
  - Interpretation: coefficients largely negative, indicating procyclical fiscal response; magnitude of negative coefficient increased over time, particularly after 2009.
- Resource-interaction results:
  - Table 4b (Real GDP Growth * Oil Exporters Dummy):
    - Coefficients: –5.86*** for 2000-14 (t-stat 0.86); –17.70*** for 2010-14 (t-stat 2.30)
    - Indicates stronger procyclical bias among oil exporters, increasing over time.
- Cross-country GMM (determinants) — Table 7:
  - Dependent: sensitivity of cyclically adjusted primary balance to output gap.
  - Financial depth coefficient = 0.031, t-statistic = 2.043 (**)
  - IQ average coefficient = –1.079, t-statistic = –1.489 (not significant)
  - Foreign reserves coverage coefficient = –0.014, t-statistic = –0.228 (not significant)
  - Hansen's J-statistic = 4.522 [0.104]; Number of countries = 43
- Cross-country GMM — Table 8:
  - Dependent: sensitivity of primary balance to real GDP growth.
  - Foreign reserves coverage coefficient = 0.063, t-statistic = 2.738 (***) 
  - Other variables (including IQ and financial depth) not significant in this specification
  - Hansen's J-statistic = 1.085 [0.581]; Number of countries = 43
- Panel GMM causality and robustness:
  - Panel GMM estimation (instrumenting cyclical real GDP by trading-partner real output growth, change in TOT, change in real interest rate on six-month U.S. Treasury bills):
    - Coefficient on cyclical component of real output = 1.857 (t-statistics 2.227) **
    - Constant = -0.194 (t-statistics -0.879)
    - Hansen's J-statistics = 3.512 [0.173]
    - Number of observations (unbalanced panel) = 826
    - Number of countries = 43
  - Pairwise panel causality tests (Dumitrescu-Hurlin):
    - Null: Real government primary spending cycle does not Granger-cause real GDP cycle — Zbar = -0.762; p-value = 0.446
    - Null: Real GDP cycle does not Granger-cause real government primary spending cycle — Zbar = 2.054; p-value = 0.040 ** 
    - Number of observations = 860

### Determinants: variables and measurement
- Key explanatory variables (period averages unless noted):
  - Institutional quality (IQ): average of six normalized Worldwide Governance Indicators; range –2.5 to +2.5; period average used (2002–12).
  - Financial depth: credit to private sector as percent of GDP (average 2001–13).
  - Financial openness: Chinn-Ito index (average 2001–11).
  - Output volatility: variance of cyclical component of (nonresource) real GDP during 2001–13.
  - Public debt-to-GDP ratio: average 2001–13.
  - Gross international reserves (GIR): months of imports (average 2001–13).
  - Terms-of-trade volatility and trading partners’ output volatility used as instruments for output volatility.
- Interpretation from regressions:
  - Greater financial depth causally linked to less fiscal procyclicality.
  - Ample GIR holdings significantly help reduce fiscal procyclicality in some specifications.
  - IQ not statistically significant in this sample, possibly due to limited variation in IQ across these countries.

### Country case studies and lessons
- Nigeria:
  - Fiscal framework since 2004: budget reference oil price and Excess Crude Account (ECA).
  - ECA successful in 2004–08; buffers used for expansionary stance in 2009.
  - Since 2010, the oil price rule and ECA lost traction; discretionary withdrawals and weak institutionalization led to depleted buffers by end-2014 and contractionary stance in 2015.
  - Weaknesses: budget reference price not formally instituted; ECA subject to discretionary withdrawals across federal, state, local layers; fiscal responsibility laws do not cover subnational governments that receive >50 percent of oil revenues.
- Botswana:
  - Despite mineral revenue dependence (over 35 percent of government revenue), Botswana ran countercyclical or cyclically neutral fiscal policies over the past decade.
  - Built foreign reserves and fiscal cushions in booms and used them in busts (notably 2009) while avoiding debt accumulation.
  - Institutional features: normative principles and the Pula Fund; expenditure cap at 40 percent of GDP; debt ceilings at 20 percent of GDP domestic and foreign (public debt remained <25 percent of GDP).
- Chile:
  - Fiscal rule formalized since 2001: structural balance target linking spending to cyclically adjusted copper and noncopper revenue; two SWFs with clear rules; potential GDP and long-term copper prices determined by independent expert committees.
  - During the 2003–08 copper boom ran surpluses and saved in SWFs; used savings to increase spending in 2009 recession; later clawed back stimulus and used buffers again in 2015 copper price decline.
  - Lesson: holistic fiscal rule with integration of SWFs and budget anchoring enabled effective smoothing.

### Policy implications and recommendations
- Deepen financial markets:
  - Progress in financial deepening could enhance macroeconomic stability and allow less procyclical fiscal policies, mitigating boom–bust cycles and improving medium-term growth prospects.
- Build international reserves buffers:
  - Ample reserves coverage may reduce default risks and permit less procyclical fiscal policy (avoiding abrupt fiscal consolidation in downturns).
- Save revenue windfalls:
  - Accumulate financial savings for rainy days (overall fiscal surpluses) out of revenue windfalls during booms to promote financial depth and build reserves.
- Design and support special fiscal institutions (SFIs) with strong commitment:
  - Fiscal rules or SWFs alone do not guarantee reduced procyclicality; SFIs need strong transparency, accountability, and political commitment to be effective.
  - Country experiences (Botswana, Chile, Nigeria) illustrate that institutional strength and holistic fiscal frameworks improve prospects for smoothing spending and saving for rainy days.
- Practical policy sequence emphasized:
  - Save part of revenue windfalls in good times (run overall fiscal surpluses).
  - Use savings to build GIR and deepen financial markets.
  - Establish credible fiscal rules/SWFs integrated with budget anchors and supported by independent technical inputs and political commitment.

### Data sources and key variable definitions
- Main data source: IMF’s 2015 Spring World Economic Outlook database, except for institutional quality and trading partners’ output volatility.
- Key variable definitions:
  - GDP: NGDP for nonresource countries; Nonresource GDP for resource-rich countries.
  - Output gap: actual real GDP minus potential real GDP as percent of potential GDP (H-P filter trend).
  - Primary fiscal balance: Government revenue excluding grants minus primary expenditure.
  - Nonresource primary fiscal balance: Government revenue excluding grants and commodity revenue minus primary expenditure.
  - Institutional quality (IQ): World Bank’s Worldwide Governance Indicators (1996‒2012).
  - Financial depth: Credit to the private sector in percent of GDP.
  - Financial openness: Chinn-Ito index (2001‒11 data used).
  - Debt-to-GDP: Total general government debt in percent of GDP at end of year.
  - Foreign reserves coverage: Gross international reserves in months of imports in the current year.
  - Terms-of-trade volatility: Variance of TT from 2015 Spring WEO during 2001‒13.
  - Trading partners’ output volatility: Variance of index of real GDP growth of five biggest trading partners, weighted by export shares.

*Source: _afr1604 - Chapter 1. Introduction (PDF).*

### Chapter 1. Introduction ................................................................................................

### Chapter 1. Introduction

### Scope and Structure
- The document is organized into chapters covering measurement, extent, determinants, and country case studies of fiscal procyclicality in Sub-Saharan Africa:
  - Chapter 2. How to Measure the Degree of Fiscal Procyclicality
  - Chapter 3. To What Extent Has the Fiscal Policy Been Procyclical among Sub-Saharan African Countries?
    - The Business Cycle in Sub-Saharan Africa
    - The Fiscal Policy Stance
    - Fiscal Policy Procyclicality
  - Chapter 4. What Explains the Degree of Fiscal Policy Procyclicality among Sub-Saharan African Countries?
  - Chapter 5. Country Case Studies (Nigeria; Botswana; Chile)
  - Chapter 6. Conclusion
  - Appendix I. Data Sources and Definition of Variables
  - Appendix II. Endogeneity Concern: Do Output Shocks Drive Fiscal Policy, or Do Fiscal Policy Shocks Cause Output Shocks?
- Empirical materials referenced include figures and tables such as:
  - Figure 1. GDP Growth Rates by Country Groups, 2000–14
  - Figure 2. Output Gaps by Country Groups, 2000–14
  - Figures and tables documenting fiscal impulses, cyclically adjusted balances, sensitivity estimates, and cross-country GMM results.

### Key Findings
- Excessively procyclical fiscal policy can be harmful.
- This paper investigates the degree of fiscal procyclicality in Sub-Saharan African countries in recent years and the reasons for cross-country differences.
- Main empirical findings:
  - A tendency for procyclical fiscal policy was particularly pronounced among oil exporters.
  - Procyclicality was particularly pronounced after the global financial crisis.
  - There is a statistically significant causal link running from deeper financial markets and higher reserves coverage to lower fiscal policy procyclicality.
- Empirical approaches referenced include sensitivity of cyclically adjusted (nonresource) primary balance to (nonresource) output gap and sensitivity of (nonresource) primary balance to (nonresource) growth, as well as cross-country GMM and panel GMM estimates.

### Determinants and Policy Implications
- Determinants identified:
  - Deeper financial markets are associated with lower fiscal policy procyclicality.
  - Higher reserves coverage is associated with lower fiscal policy procyclicality.
- Policy-relevant implications highlighted:
  - Fiscal rules supported by strong political commitment and institutions seem to be key to facilitating progress toward deeper financial markets and stronger reserves coverage.
- Country case studies (Nigeria, Botswana, Chile) are used to illustrate experiences and policy choices related to fiscal cyclicality and stabilization.

*Source: _afr1604 - Chapter 1. Introduction (PDF).*

### Introduction

### _afr1604 - Introduction

### Introduction: scope and research questions
- Focus: cyclical behavior of fiscal policy in sub-Saharan African countries during 2000–14.
- Motivation: many sub-Saharan African countries depend on commodity exports or have gained access to volatile international capital markets; highly procyclical fiscal policy can amplify booms and exacerbate busts.
- Objectives: assess fiscal expansion/contraction and cyclical stance, identify determinants of fiscal procyclicality, and derive policy lessons.
- Three central questions:
  - How expansionary or contractionary was fiscal policy in sub-Saharan African countries in recent years, and to what extent was the policy procyclical or countercyclical?
  - What factors explain different degrees of fiscal procyclicality among sub-Saharan African countries?
  - What policy lessons can be applied to run less procyclical fiscal policy?

### Key findings (overview)
- General finding: sub-Saharan African countries ran procyclical fiscal policies in general; oil exporters’ policies tended to be more procyclical than those of other countries.
- Determinants (robust to endogeneity controls): financial depth and international reserves buffers significantly reduce fiscal policy procyclicality.
- Institutional quality: unlike results for advanced and emerging markets in other studies, institutional quality is not statistically significant in explaining cross-country differences in procyclicality within the sub-Saharan African sample (likely because IQ shows little variation across these countries).
- Role of public investment: public investment was an important driver of the fiscal stance in oil-exporting countries, with a large and increasing role.

### How the paper measures fiscal procyclicality
- Time period: analysis of fiscal policy stance and business cycle between 2000 and 2014.
- Two alternative fiscal stance measures:
  - For resource-rich countries: cyclically adjusted nonresource primary balance measured in percent of nonresource GDP.
  - For all other countries: cyclically adjusted standard primary balance measured in percent of GDP.
- Cyclical adjustment methodology:
  - Output gap estimated using the Hodrick-Prescott (H-P) filter applied to annual (total or nonresource) real GDP series.
  - Cyclically adjusted (nonresource) primary balance (capb) formula:
    - capb = (R*(YP/Y) – G) / Y
      - where R = (nonresource) revenues excluding grants, Y = (nonresource) GDP, YP/Y = ratio of potential (nonresource) output to actual output, G = primary expenditure.
  - Assumptions: elasticity of nonresource revenues = 1; primary expenditure elasticity = 0.
- Definitions:
  - Fiscal policy expansionary when Δcapb < 0; contractionary when Δcapb > 0.
  - Fiscal stance classified as countercyclical if expansionary policy accompanies negative change in output gap (and vice versa), procyclical when expansionary policy accompanies positive change in output gap (and vice versa).
- Robustness check: unadjusted (nonresource) primary balance linked to changes in real (nonresource) GDP growth.

### Business cycle stylized facts, 2000–14
- Four subperiods identified by growth dynamics: 2000–04; 2005–08 (acceleration); 2009 (sharp fall after global financial crisis); 2010–14 (recovery but below 2005–08 levels).
- Output gaps (H-P filter): average positive for 2005–08 and 2010–14; average negative for 2000–04 and 2009.
- Oil-exporting countries experienced more extreme average gaps and greater dispersion than mineral exporters and other countries.

### Fiscal stance and procyclicality evidence
- Fiscal impulse by subperiod (summary observations):
  - Most oil-exporting countries ran an expansionary fiscal policy between 2005 and 2008.
  - All mineral-exporting countries had an expansionary fiscal stance in 2009.
  - No clear bias across other country groups in subperiods.
- Panel regression approaches:
  - (a) Dependent: cyclically adjusted (nonresource) primary balance (% of nonresource GDP); independent: nonresource output gap.
  - (b) Dependent: (nonresource) primary balance (% of nonresource GDP); independent: nonresource real GDP growth.
- Regression results:
  - Table 3a: coefficient on output gap largely negative (except 2005–08) but not statistically significant across periods.
    - Example reported coefficients: Output Gap for 2000-14 = –0.16 (t-stat 1.01); 2005-08 = –0.66 (t-stat 0.41); 2010-14 = –2.9 (t-stat 2.77). Constant terms significant.
  - Table 3b: coefficient on (nonresource) real GDP growth significantly negative over full sample and subsample periods; magnitude of negative coefficient increased over time.
    - Example reported coefficients: Real GDP Growth 2000-14 = –2.03*** (t-stat 0.56); 2005-08 = –0.84*** (t-stat 0.15); 2010-14 = –3.84** (t-stat 1.64). Constants reported.
  - Interpretation: overall procyclical fiscal policies during 2000–14, with increasing procyclicality over time, particularly after the global financial crisis.
- Resource-specific results:
  - Interaction terms show procyclicality bias particularly strong among oil exporters.
    - Table 4b: Real GDP Growth * Oil Exporters Dummy coefficients significantly negative in all periods and becoming more negative over time (e.g., –5.86*** for 2000-14, t-stat 0.86; –17.70*** for 2010-14, t-stat 2.30).
  - Mapping of country outcomes and figures for oil exporters highlight predominance of procyclical bias for many oil-exporting countries across subperiods.
  - Country-level cyclicality summaries (examples):
    - Oil exporters: varying classification across periods; some countries (Angola, Cameroon, Gabon, Nigeria, Equatorial Guinea) often classified as procyclical in certain subperiods; others like Chad and Republic of Congo show mixed patterns across periods.
    - Mineral exporters: mixed procyclical/countercyclical classifications across periods (Table 6).

### Determinants of fiscal policy procyclicality (cross-country analysis)
- Dependent variable: country-level degree of fiscal procyclicality measured two ways (sensitivity of cyclically adjusted primary balance to output gap; sensitivity of primary balance to real GDP growth).
- Explanatory variables (averages/period measures):
  - Institutional quality (IQ): average of six normalized Worldwide Governance Indicators; range –2.5 to +2.5; period average used (2002–12).
  - Financial depth: ratio of credit to private sector to GDP (average 2001–13).
  - Financial openness: Chinn-Ito index (average 2001–11).
  - Output volatility: variance of cyclical component of (nonresource) real GDP during 2001–13.
  - Public debt-to-GDP ratio (average 2001–13).
  - Gross international reserves (GIR) in months of imports (average 2001–13).
- Endogeneity addressed by instrumentation:
  - Instruments include lagged or earlier-period averages/levels for IQ, financial depth, financial openness, debt-GDP, GIR; output volatility instrumented by terms-of-trade volatility and trading partners’ output volatility measures.
- Cross-country GMM results (Tables 7 and 8):
  - Table 7 (Dependent: sensitivity of cyclically adjusted primary balance to output gap):
    - Financial depth coefficient = 0.031, t-statistic = 2.043 (**), positive and significant at 5 percent.
    - IQ average coefficient = –1.079, t-statistic = –1.489 (not significant).
    - Foreign reserves coverage coefficient = –0.014, t-statistic = –0.228 (not significant).
    - Hansen's J-statistic = 4.522 [0.104]; Number of countries = 43.
  - Table 8 (Dependent: sensitivity of primary balance to real GDP growth):
    - Foreign reserves coverage coefficient = 0.063, t-statistic = 2.738 (***), positive and significant at 1 percent.
    - Other variables (including IQ and financial depth) not significant at conventional levels in this specification.
    - Hansen's J-statistic = 1.085 [0.581]; Number of countries = 43.
- Interpretation of determinants:
  - More financial depth causally linked to less fiscal procyclicality among sub-Saharan African countries.
  - Ample GIR holdings significantly help reduce fiscal procyclicality.
  - Institutional quality not statistically significant in this sample—likely due to limited cross-country variation in IQ among sample countries; VIF and pairwise correlations do not indicate severe multicollinearity.

### Policy implications and recommendations
- Deepen financial markets:
  - Progress in deepening financial markets could enhance macroeconomic stability and allow less procyclical fiscal policies, mitigating boom–bust cycles and improving medium-term growth prospects.
- Build international reserves buffers:
  - Ample reserves coverage may reduce default risks and permit less procyclical fiscal policy (avoiding abrupt fiscal consolidation in downturns).
- Save revenue windfalls:
  - Accumulate financial savings for rainy days (overall fiscal surpluses) out of revenue windfalls during booms to promote financial depth and build reserves.
- Design and support special fiscal institutions (SFIs) with strong institutions:
  - Fiscal rules or SWFs alone do not guarantee reduced procyclicality; SFIs need strong transparency, accountability, and political commitment to be effective.
  - Country experiences (Botswana, Chile, Nigeria) illustrate that institutional strength and holistic fiscal frameworks improve prospects for smoothing spending and saving for rainy days.

### Country case studies: lessons from Nigeria, Botswana, Chile
- Nigeria:
  - Fiscal framework since 2004: budget reference oil price and Excess Crude Account (ECA).
  - ECA successful 2004–08; buffers used to run expansionary stance in 2009.
  - Since 2010, the oil price rule and ECA lost traction: discretionary withdrawals, weak institutionalization, and lack of coverage of state/local governments led to depleted buffers by end-2014 and necessitated contractionary stance in 2015.
  - Identified weaknesses: budget reference price not formally instituted; ECA subject to discretionary withdrawals across federal, state, local layers; fiscal responsibility laws do not cover subnational governments that receive >50 percent of oil revenues.
- Botswana:
  - Despite mineral revenue dependence (over 35 percent of government revenue), Botswana ran countercyclical or cyclically neutral fiscal policies over the past decade.
  - Built foreign reserves and fiscal cushions in booms and used them in busts (notably 2009) while avoiding debt accumulation.
  - Normative principles and the Pula Fund: rules aiming to finance current spending from nonmineral revenue, use resource revenues for investment or savings; expenditure cap at 40 percent of GDP (met when accounting for mineral cycle); debt ceilings at 20 percent of GDP domestic and foreign (public debt remained <25 percent of GDP).
- Chile:
  - Fiscal rule (formalized since 2001): structural balance target linking spending to cyclically adjusted copper and noncopper revenue; two SWFs with clear rules; potential GDP and long-term copper prices determined by independent expert committees.
  - During 2003–08 copper boom, ran surpluses and saved in SWFs; used savings to increase spending in 2009 recession; later clawed back stimulus and again used buffers in 2015 copper price decline.
  - Lesson: holistic fiscal rule with integration of SWFs and budget anchoring enabled effective smoothing.

### Concluding practical lessons
- Adoption of well-designed fiscal rules or resource funds (SFIs) can help save in good times but is insufficient without strong institutions and political commitment.
- Progress in financial depth and reserves accumulation should be policy priorities to reduce fiscal procyclicality.
- Chile and Botswana offer instructive models: rules that link spending to smoothed revenue estimates, clear SWF integration with fiscal anchors, independent technical inputs, and institutional commitment facilitate effective saving for rainy days.

*Source: _afr1604 - Introduction (IMF staff analysis and estimations, 2000–14 sample).*

### Conclusions

### Conclusions

### Main findings
- Sub-Saharan African countries have in general run procyclical fiscal policies since 2000.
- Procyclicality is pronounced among resource-rich countries and was exacerbated after the global financial crisis in 2009, particularly among sub-Saharan African oil exporters.
- This exacerbation is concerning given the prospect that these countries may face a prolonged period of low international commodity prices with depleted policy buffers.

### Determinants of fiscal procyclicality (empirical results)
- Deep domestic financial markets and ample international reserves coverage are associated with less procyclical fiscal policies.
  - Lack of financial depth and reserves buffers constrains a country’s ability to pursue expansionary fiscal policy during downturns.
  - To promote financial depth and build reserves buffers, countries should accumulate financial savings (through overall fiscal surpluses) based on part of revenue windfalls in good times.
- Regressions in this paper do not find a statistically significant role for institutional strength in reducing fiscal procyclicality. Nevertheless, country case studies and existing literature suggest that special fiscal institutions—fiscal rules and stabilization/saving funds—supported by strong political commitment and institutions should help build savings for rainy days.
- The experiences of Botswana and Chile are cited as offering useful lessons for many sub-Saharan African countries.

### Policy implications and recommendations
- Build domestic financial depth to allow countercyclical fiscal responses.
- Accumulate international reserves coverage to reduce the need for procyclical fiscal adjustments.
- Save part of revenue windfalls in good times (run overall fiscal surpluses) to create buffers for downturns.
- Consider establishing and credibly supporting fiscal rules and stabilization/saving funds, backed by political commitment and institutional capacity, to smooth fiscal policy across cycles.

### Robustness and econometric evidence
- The paper addresses endogeneity concerns and provides evidence that output shocks drive fiscal policy among sub-Saharan African countries.
- Panel GMM estimation (instrumenting cyclical real GDP by weighted trading-partner real output growth, change in terms of trade, and change in real interest rate on six-month U.S. Treasury bills) yields:
  - Coefficient on cyclical component of real output: 1.857 (t-statistics 2.227) **
  - Constant: -0.194 (t-statistics -0.879)
  - Hansen's J-statistics: 3.512 [0.173]
  - Number of observations (unbalanced panel): 826
  - Number of countries: 43
  - Notes: Estimations are performed using panel GMM with country-fixed effects. *, **, and *** indicate statistically significant at 10 percent, 5 percent, and 1 percent levels, respectively. Dependent Variable: Cyclical components of real government primary spending. Instrumented Variable: Cyclical components of real GDP. Instruments: Weighted average of real GDP growth of trading partners; Change in TOT; Change in real interest rate on 6-month U.S. Treasuries.
- Pairwise panel causality tests (Dumitrescu-Hurlin approach) report:
  - Null: Real government primary spending cycle does not Granger-cause real GDP cycle — Zbar statistics: -0.762; p-value: 0.446
  - Null: Real GDP cycle does not Granger-cause real government primary spending cycle — Zbar statistics: 2.054; p-value: 0.040 **
  - Number of observations: 860
  - Notes: *, **, and *** indicate statistically significant at 10%, 5%, and 1% levels, respectively.

### Data, sample, and key variable definitions
- Country sample: 43 sub-Saharan African countries (all sub-Saharan African countries excluding South Sudan and Zimbabwe).
- Sample period: 2000 to 2014 for all countries, except:
  - Cabo Verde (2002‒14)
  - Chad (2004‒14)
  - Malawi (2002‒14)
  - Niger (2006‒14)
  - São Tomé and Príncipe (2001‒14)
- Main data source: IMF’s 2015 Spring World Economic Outlook database, except for institutional quality and trading partners’ output volatility.
- Key variable measurements as used in the analysis:
  - GDP: Series Nominal Gross Domestic Products (NGDP) for non-resource countries; Nonresource GDP for resource-rich countries (GDP excluding value added of the commodity sector).
  - Output gap: Difference between actual real GDP and potential real GDP in percent of potential GDP. NGDP is deflated by the GDP deflator; potential real GDP is the trend from the Hodrick-Prescott filter.
  - Nonresource output gap: Analogous definition using nonresource GDP and deflator.
  - Primary fiscal balance: Government revenue excluding grants minus primary expenditure (total expenditure and net lending minus interest payments).
  - Nonresource primary fiscal balance: Government revenue excluding grants and commodity revenue minus primary expenditure.
  - Institutional quality (IQ): World Bank’s Worldwide Governance Indicators for 1996‒2012 (index construction explained in Chapter 4).
  - Financial depth: Credit to the private sector in percent of GDP (see Chapter 4).
  - Financial openness: Chinn-Ito financial openness index (Chinn and Ito 2006); data cover the period 2001‒11. (Database of Chinn-Ito index updated in 2013 is used for this paper.)
  - Debt-to-GDP ratio: Total general government debt in percent of GDP at end of year.
  - Foreign reserves coverage: Gross international reserves at end of year in months of imports of goods and services in the current year.
  - Terms-of-trade volatility: Variance of TT (terms of trade, goods, and services) from 2015 Spring WEO database during 2001‒13.
  - Trading partners’ output volatility: Variance of an index of real GDP growth of each country’s five biggest trading partners, weighted by export shares from IMF Direction of Trade Statistics and deflated by the country’s average ratio of exports to GDP over the sample period.

*Source: Conclusions and appendices from the provided IMF content unit.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/dp/2016/_afr1604.pdf_