## 1. Countries with IMF Programs and Expenditure Conditionality

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### I. Introduction
- Immediate goals of an IMF program:
  - restore macroeconomic stability,
  - create conditions for sustainable growth,
  - improve balance of payment viability,
  - in low-income countries (LIDCs) also reduce poverty.
- Program conditionality:
  - made up of benchmarks and indicative targets reflecting prevailing macroeconomic conditions,
  - typically applied on both the revenue and expenditure side.
- Revenue conditionality focus: structural tax measures in four areas: taxation of goods and services, value-added tax (VAT), and income and trade taxes.
- Expenditure conditionality:
  - utilization has increased in Fund programs in the last decade.
  - LIDCs have the largest number of expenditure conditions on average, followed by EMs and AEs.
  - comprises quantitative ceilings or floors on overall or specific government expenditures (including social spending, wages and public investment), and public financial management measures (strengthening public investment processes, fiscal transparency, budget preparation, minimizing fiscal risks).
- Debates:
  - Critics argue IMF programs/conditionality have failed to increase social sector spending; austerity and wage-bill conditionality may lower such spending.
  - Counterarguments: IMF-supported programs can increase social spending via higher growth raising revenues, safeguards protecting social spending, and catalyzing foreign aid and investment.
  - Empirical findings cited in text: some studies find education and health spending increases faster in IMF-supported countries; some find long-term growth benefits to program participation.

### II. Purpose and Contributions of the Paper
- Research objectives:
  - investigate impact of different types of expenditure conditions in IMF programs on key expenditure components: health, education, public investment, wage bill.
  - assemble a dataset on expenditure conditionality in IMF programs since 1992, disaggregated by type of condition and specific targets.
- Main contributions:
  - analyze short- and long-term impact of different types of expenditure conditionality on wage, health, education, public investment, and total general government expenditures;
  - examine possible trade-offs associated with implementing conditionality.

### III. Data and Stylized Facts
- Sample and dataset:
  - Annual unbalanced panel of 106 emerging market and low-income countries over the period 1992-2016 (countries that had at least one IMF program over the sample period).
  - The 9 advanced countries are excluded from quantitative analysis.
  - Data sources include WEO, WDI, IMF Investment and Capital Stock Dataset (2017), IMF internal dataset on Government Compensation and Employment (2016), and MONA database for conditionality.
  - The data are unreliable prior to 1992; starting point is 1992.
  - Number of lags set to 2 for consistency across estimations.
- Types of IMF program conditions (definitions preserved):
  - Quantitative performance criteria (QPC)
  - Indicative targets (IT)
  - Structural benchmarks (SB)
  - Prior actions (PA)
- Aggregate patterns 1992-2016 (average):
  - Quantitative performance criteria: 46 percent of total conditions.
  - Structural benchmarks: 31 percent of total conditions.
- Patterns 2005-2015 (average proportions):
  - Structural benchmarks: 42 percent of all conditions.
  - Quantitative performance criteria: 22 percent of all conditions.
- Implementation success:
  - More than 80 percent of expenditure conditions were met on average during the full sample period.
  - ITs, QPCs, and SBs: 76 percent of the conditions met on average across all spending categories.
  - PAs nearly always met (percent met entries indicate nearly 100 percent).
  - PFM conditions have approximately 82 percent of conditions met on average across all PFM categories.
- Focus shift in conditionality:
  - from general government spending ceilings to improving budget execution and control, public investment, social and priority spending.

### IV. Empirical Approach
- Primary econometric frameworks:
  - CS-DL (cross-sectionally augmented distributed lag)
  - CS-ARDL (cross-sectionally augmented autoregressive distributed lag)
- Advantages: address cross-sectional dependence and common factors; robust to endogeneity, structural break, reverse causality and omitted common effects bias.
- Main variable Xit: indicator whether a certain expenditure conditionality was met. Mean-group long-run effect denoted by ɵ̄.
- Dependent variables:
  - education and health as share of GDP and share of total government expenditure,
  - wage outlays as share of GDP,
  - public investment in log per capita terms.
- Regressions repeated for three samples: full sample, emerging markets (EM), low-income developing countries (LIDC).

### V. Key Empirical Findings — Health and Education Spending
- Structural conditionality (PFM: accounting and financial reporting, arrears containment, budget execution and control) has lasting long-run impact on social spending composition.
- Specific magnitudes and findings:
  - Improving accounting and financial reporting, and containing the accumulation of arrears through IMF programs have helped countries improve education share of government expenditures by about 0.9-2 percent in the long run.
  - Conditions on enhancing public investment have reduced the budget share of health spending by between 1.5-2.8 percent.
- Income-group heterogeneity:
  - Preventing further accumulation of arrears helped both low-income and emerging economies.
  - Long-run benefits of conditions on budget execution and control, and accounting and financial reporting are mainly felt in low-income countries.

### VI. Key Empirical Findings — Wage Spending
- Direct ceilings on the wage bill often statistically insignificant in the long run; structural reforms play a more significant role in containing wage spending.
- Statistically significant structural conditions associated with containing wage spending include:
  - Legislative framework,
  - Preventing accumulation of arrears,
  - Budget execution and control (in emerging markets).
- In LIDCs, structural conditionality coefficients are sometimes negative but often statistically insignificant.

### VII. Key Empirical Findings — Public Investment
- Structural reforms effective in boosting public investment in the long run.
- Successful implementation of conditionality related to:
  - Accounting and financial reporting,
  - Budget execution and control,
  - Budget preparation,
  have played crucial roles in enhancing public investment.
- Quantitative magnitude:
  - Implementation of IMF structural conditionality could help an emerging market country to increase its public investment by between 10 and 19 percent (range obtained based on the size of statistically significant coefficients).
- Selected example coefficients (All Countries / EM / LIDC reported in Appendix):
  - All Countries ɵ̄ examples: 0.039, 0.059*, 0.089*, 0.108**, 0.192*** (various specifications).
  - Emerging Markets ɵ̄ examples: 0.102**, 0.141**, 0.122**, 0.192** (selected specifications).
  - Low-income Developing Countries ɵ̄ example: 0.133* (selected specification).

### VIII. Key Empirical Findings — Total Government Expenditure
- Measures that prevent accumulation of arrears, improve accounting and financial reporting, strengthen budget execution and control, and enhance legislative framework have long-lasting impacts on total government spending as a share of GDP—effects observed more significantly in emerging market countries.
- Merely limiting overall government spending without accompanying structural reforms did not prove as effective.
- Selected coefficients (Full Sample, Lags 1 and 2, examples from Table 5):
  - Full Sample ɵ̄: 0.007* (Lags 1), 0.008 (Lags 2) for Gov. Exp. conditionality; -0.014*** and -0.017*** for Arrears Acc. (Lags 1 and 2).
  - Emerging Markets: significant negative long-run effects for Arrears Acc. and Budget Exe. (e.g., -0.017***, -0.021***).
  - Low Income Countries: some significant effects (e.g., 0.006* for Gov. Exp. at Lags 1), and -0.018** for Budget Exe. at Lags 2 in one specification.

### IX. Short-run Effects (CS-ARDL results)
- Direct expenditure conditionality achieves short-term objectives even when long-run effects are not durable.
- Table 6 — Short-run and Long-run estimates (Dependent Variable as percent of GDP; Conditionality: Direct measure). Short-run coefficients with standard errors in brackets:
  - Short Run:
    - Education Spending: 0.000  [0.001]
    - Health Spending: 0.002***  [0.000]
    - Wage: -0.001  [0.001]
    - Public Investment: 0.003**  [0.002]
  - Long Run:
    - Education Spending: -0.000  [0.006]
    - Health Spending: -0.002  [0.011]
    - Wage: 0.008  [0.005]
    - Public Investment: 0.003  [0.009]
  - Observations: Education 965; Health 1862; Wage 1017; Public Investment 1869.
- Interpretation: Minimum floors for certain types of spending can ensure adequate short-term allocations for poverty and growth-enhancing programs in tight fiscal environments.

### X. Appendix Figure 1 — Classification, Frequency and Success Rates (selected counts and percents preserved)
- Aggregate sample sizes:
  - Number of countries: 106
  - Number of programs: 212
- Spending-category condition counts (selected excerpts):
  - IT total snippet: "IT 29"
  - QPC total snippet: "QPC 381"
  - SB total snippet: "SB 3" (table excerpts contain category-level breakdowns)
  - PA total snippet: "PA 0" (category-level entries vary in table)
- Spending-category percent met (excerpts as presented in table):
  - IT percent met: "IT 69   63 61"
  - QPC percent met: "QPC 70 90 70 56 64 65"
  - SB percent met: "SB 100 86 88 81 78 100"
  - PA percent met: "PA   100 97 100 100"
- PFM-category counts and percent met (selected excerpts):
  - QPC counts across PFM categories: "... 1352" (total excerpt)
  - SB counts across PFM categories: "... 1204" (total excerpt)
  - PA counts across PFM categories: "... 377" (total excerpt)
  - IT percent met excerpt: "IT 71 86 86 80   82 ... 75         65"
  - QPC percent met excerpt: "QPC 72 79 81 78   85 ... 100     75   72"
  - SB percent met excerpt: "SB 85 91 88 75 81 79 ... 82 75 88 84 78 82"
  - PA percent met excerpt: "PA 100 100 100 100 100 100 ... 100 100 100 100 100 100"

### XI. Conclusions and Policy Implications
- Expenditure conditionality has shifted toward protecting growth-friendly and pro-poor spending and addressing structural issues: spending floors on social spending and public investment, improving budget execution and control, and preventing domestic arrears.
- Structural conditionality (accounting & financial reporting, arrears containment, budget execution/control) is most effective over the longer term in improving the composition of government spending—particularly increasing the share of health and education.
- Trade-offs and caveats:
  - Floors on specific spending (e.g., public investment) can boost those expenditures but may exert pressure on other budget areas (e.g., health).
  - Binding constraints on one expenditure type may distort short-term resource allocation under limited fiscal space.
  - The mere existence of expenditure conditionality does not lead to improved outcomes; implementation (i.e., meeting conditions) is crucial.
- Policy recommendations:
  - Combine short-term spending protection measures (spending floors for health, education, public investment) with long-term structural conditionality focused on public financial management reforms.
  - Prioritize strong implementation and monitoring of conditionality to achieve desired compositional improvements in government spending.
  - Focus structural reforms with a medium-term perspective to support increases in social sector spending and progress toward the SDGs.
- Suggestions for future research:
  - Study impact of conditionality on sectoral outcomes in education and health (expenditure increases do not necessarily translate to better outcomes if inefficiencies persist).
  - Investigate whether different types of conditionality (structural, revenue, or expenditure) are complements or substitutes in achieving long-term macroeconomic improvement.

*Source: wp18255 - 1. Countries with IMF Programs and Expenditure Conditionality; Appendix A; Appendix Figure 1 (excerpts as provided).*

### 1. Countries with IMF Programs and Expenditure Conditionality __________________________________ 4

### 1. Countries with IMF Programs and Expenditure Conditionality

### I. Introduction
- Immediate goals of an IMF program:
  - restore macroeconomic stability,
  - create conditions for sustainable growth,
  - improve balance of payment viability,
  - in low-income countries (LIDCs) also reduce poverty.
- Program policies designed in consultation with authorities; fiscal adjustment often central to programs.
- Program conditionality:
  - made up of benchmarks and indicative targets reflecting prevailing macroeconomic conditions,
  - typically applied on both the revenue and expenditure side.
- Revenue conditionality has focused on structural tax measures in four areas: taxation of goods and services, value-added tax (VAT), and income and trade taxes (Crivelli and Gupta 2016).
- Expenditure conditionality:
  - utilization has increased in Fund programs in the last decade (Figure 1).
  - LIDCs have the largest number of expenditure conditions on average, followed by EMs and AEs (Figure 2).
  - comprises quantitative ceilings or floors on overall or specific government expenditures (including social spending, wages and public investment), and public financial management measures (strengthening public investment processes, fiscal transparency, budget preparation, minimizing fiscal risks).
- Debates in the literature:
  - Critics: IMF programs and conditionality have failed to deliver increases in social sector spending; austerity and wage-bill conditionality may lower such spending (Ooms and Hammonds 2009, Rowden 2009, MacDonald 2007); other studies contend IMF conditionality reduced fiscal space for health spending in African countries (Kentikelenis, Stubbs and King 2015, 2016; Baker 2010; Benton and Dionne 2015; Stubbs and others 2017).
  - Counterarguments: IMF-supported programs can potentially increase social spending via three channels:
    - higher growth during program raising domestic revenues,
    - safeguards in programs protecting social spending from austerity (Gupta and others 2000; Gupta 2010),
    - catalyzing foreign aid and investment during the program period.
  - Empirical findings: Clements, Gupta and Nozaki (2013) find education and health spending increases faster in IMF-supported countries than in other developing economies without IMF programs.
  - Some studies find long-term growth benefits to program participation (Bas and Stone 2014; Bal-Gunduz and others 2013), with long-term users benefiting most; Newiak and Willems (2017) find even IMF-monitored programs without financing helped promote growth and FDI and lower inflation; Atoyan and Conway (2006) find growth benefits materialize after program conclusion and note contemporaneous improvements in fiscal and current account balances.
- Gaps in literature:
  - Limited research on impact of specific IMF conditionality on composition of public expenditure.
  - Concerns that productive expenditures used in excess can become unproductive (Devarajan, Swaroop, and Zou 1996; Paternostro, Rajaram and Tiongson 2007).
  - Composition matters for growth: higher share of capital and nonwage goods and services linked to higher growth; larger wage-bill share linked to lower output growth (Gupta and others 2005).
  - Cordella and Dell’Ariccia (2002): spending floors (social spending, public investment) need to balance benefits with costs from distorted resource allocation.
  - Quality of spending matters: higher spending does not necessarily mean better outcomes; Pritchett’s (1996) “white elephant” hypothesis on inefficiency of some public investment in developing countries.

### II. Purpose and Contributions of the Paper
- Research objectives:
  - investigate impact of different types of expenditure conditions in IMF programs on key expenditure components: health, education, public investment, wage bill.
  - assemble a dataset on expenditure conditionality in IMF programs since 1992, disaggregated by type of condition and specific targets.
- Two main contributions:
  - analyze short- and long-term impact of different types of expenditure conditionality on wage, health, education, public investment, and total general government expenditures;
  - examine possible trade-offs associated with implementing conditionality.

### III. Key Empirical Findings (as reported in text)
- Structural conditionality (classified under Public Financial Management) has been most effective over the longer term in improving composition of government spending by increasing the share of growth-friendly and poverty-reducing spending on health and education.
- Short-term effects:
  - Spending floors on health, education or public investment may help achieve short-term objective of protecting such spending during the adjustment period.
  - However, such spending floors might exert pressure on the rest of the budget and limit allocations to other expenditures.
- Policy design implication:
  - Programs should combine short-term conditionality on specific expenditure components with long-term structural conditionality covering public financial reforms.
- Implementation:
  - Strong implementation of conditionality is crucial for achieving superior outcomes.
- Relevance:
  - Findings are relevant to policy makers targeting the Sustainable Development Goals (SDGs); structural reforms with a medium-term perspective can help achieve significant increases in social sector spending.

### IV. Data and Stylized Facts
- Types of IMF program conditions:
  - Quantitative performance criteria (QPC): under government control and measurable by economic indicators (examples: maximum level of domestic financing, minimum level of international reserves, certain range for fiscal balance). Unmet QPCs require formal waiver from the Executive Board to mark the review as complete.
  - Indicative targets (IT): quantitative measures set in addition to QPCs to assess progress; sometimes set when QPCs cannot be met due to data unreliability; may be converted into QPCs later.
  - Structural benchmarks (SB): not quantifiable; critical markers to assess program implementation (examples: measures to strengthen public financial management, improve social safety nets); assessed in context of overall program and do not require formal waiver if unmet.
  - Prior actions (PA): actions authorities agree to take before IMF Executive Board approval (examples: bank reconciliation, elimination of price controls).
- Data source:
  - Expenditure conditionality constructed from IMF’s Monitoring of Fund Arrangements (MONA) database, which provides detailed information on expenditure conditionality in each program and whether conditions were met or not.
- Appendix references:
  - Appendix A contains details on classification of conditionality under Public Financial Management.
  - Appendices A and B provide a full list of conditions and their incidence, and methodology for constructing the expenditure conditionality dataset.

### V. Policy Recommendations (implied by findings)
- Combine short-term spending protection measures (spending floors for health, education, public investment) with long-term structural conditionality focused on public financial management reforms.
- Prioritize strong implementation and monitoring of conditionality to achieve desired compositional improvements in government spending.
- Focus structural reforms with a medium-term perspective to support increases in social sector spending and progress toward the SDGs.
- Be mindful of trade-offs: protect specific social expenditures while ensuring broader budgetary balance to avoid crowding out other essential expenditures.

*Source: wp18255 - 1. Countries with IMF Programs and Expenditure Conditionality (excerpt as provided).*

### Appendix A.

### wp18255 - Appendix A

### Dataset and sample
- Annual unbalanced panel of 106 emerging market and low-income countries over the period 1992-2016, countries that had at least one IMF program over the sample period.
- The 9 advanced countries are excluded from quantitative analysis.
- Data sources: IMF World Economic Outlook (WEO), World Bank World Development Indicators (WDI), IMF Investment and Capital Stock Dataset (2017), IMF internal dataset on Government Compensation and Employment (2016).
- The data are unreliable prior to 1992; the study’s starting point is 1992.
- For consistency across different estimations, the number of lags is set to 2.

### Patterns of expenditure conditionality
- Over 1992-2016, conditionality composition (average):
  - Quantitative performance criteria: 46 percent of total conditions.
  - Structural benchmarks: 31 percent of total conditions.
- Over 2005-2015 (average proportions):
  - Structural benchmarks: 42 percent of all conditions.
  - Quantitative performance criteria: 22 percent of all conditions.
- Indicative targets and prior actions have remained stable or increased slightly since 2010.
- More than 80 percent of expenditure conditions were met on average during the full sample period.
- The focus of expenditure conditionality shifted from general government spending ceilings to improving:
  - Budget execution and control,
  - Public investment,
  - Social and priority spending.

### Empirical approach
- Primary econometric frameworks: CS-DL (cross-sectionally augmented distributed lag) and CS-ARDL (cross-sectionally augmented autoregressive distributed lag) to address cross-sectional dependence and common factors by incorporating cross-sectional averages of the dependent variable, regressors, and their lags.
- CS-DL and CS-ARDL advantages:
  - Robust to endogeneity, structural break, reverse causality and omitted common effects bias (Chudik and others 2016).
  - CS-DL uses mean-group estimation; consistent when no feedback effect from lagged dependent variable to regressors (simultaneity may cause bias).
- Specification details:
  - Main variable of interest Xit = indicator whether a certain expenditure conditionality was met. Mean-group long-run effect denoted by ɵ̄.
  - Dependent variables include spending on education, health, public investment, and wage outlays.
  - Health and education expressed as share of GDP and as share of total government expenditure.
  - Wage outlays expressed as share of GDP; public investment expressed in log per capita terms.
  - Regressions are repeated for three samples: full sample, emerging markets (EM), low-income developing countries (LIDC).

### Main findings — health and education spending
- Structural conditionality covering the budget process has lasting impact on social spending.
- Improvements in accounting and financial reporting and containing expenditure arrears have statistically significant long-run impacts on improving health and education expenditures.
- Conditionality on general government expenditure (less used in past decade) had long-run benefits on health spending.
- Conditionality on public investment is associated with pressures on other expenditures:
  - Negative and statistically significant coefficient attached to the share of health spending in the budget, implying tradeoffs across spending categories.
- Quantitative magnitudes reported:
  - Improving accounting and financial reporting, and containing the accumulation of arrears through IMF programs have helped countries improve education share of government expenditures by about 0.9-2 percent in the long run.
  - Conditions on enhancing public investment have reduced the budget share of health spending by between 1.5-2.8 percent.
- Income-group heterogeneity (Table 2):
  - Preventing further accumulation of arrears helped both low-income and emerging economies.
  - Long-run benefits of conditions on budget execution and control, and accounting and financial reporting are mainly felt in low-income countries.

### Main findings — wage spending
- Direct ceilings on the wage bill often statistically insignificant in the long run; structural reforms play a more significant role in containing wage spending.
- Statistically significant structural conditions associated with containing wage spending include:
  - Legislative framework,
  - Preventing accumulation of arrears,
  - Budget execution and control (in emerging markets).
- In LIDCs, structural conditionality coefficients are sometimes negative but often statistically insignificant.
- Table 3 (selected pattern): In Emerging Markets, some structural conditions show negative and statistically significant coefficients (e.g., Arrears Acc., Leg. Framework, Budget Exe. at various specifications).

### Main findings — public investment
- Structural reforms have been effective in boosting public investment in the long run.
- Successful implementation of conditionality related to:
  - Accounting and financial reporting,
  - Budget execution and control,
  - Budget preparation,
  have played crucial roles in enhancing public investment.
- Quantitative magnitude:
  - Implementation of IMF structural conditionality could help an emerging market country to increase its public investment by between 10 and 19 percent (range obtained based on the size of statistically significant coefficients).
- Table 4 highlights positive long-run ɵ̄ coefficients for public investment associated with accounting, budget execution, and budget preparation across All Countries, EM, and LIDC samples (example figures):
  - All Countries ɵ̄: 0.039, 0.059*, 0.089* (various specifications); 0.108**, 0.192*** (account/budg prep cases).
  - Emerging Markets ɵ̄: 0.102**, 0.141**, 0.122**, 0.192** (selected specifications).
  - Low-income Developing Countries ɵ̄: 0.133* (selected specification).

### Main findings — government expenditure (total)
- Measures that prevent accumulation of arrears, improve accounting and financial reporting, strengthen budget execution and control, and enhance legislative framework have long-lasting impacts on total government spending as a share of GDP—effects observed more significantly in emerging market countries.
- Merely limiting overall government spending without accompanying structural reforms did not prove as effective.
- Selected coefficients from Table 5 (Full Sample, Lags 1 and 2):
  - Full Sample ɵ̄: 0.007* (Lags 1), 0.008 (Lags 2) for Gov. Exp. conditionality; -0.014*** and -0.017*** for Arrears Acc. (Lags 1 and 2).
  - Emerging Markets show significant negative long-run effects for Arrears Acc. and Budget Exe. (e.g., -0.017***, -0.021***).
  - Low Income Countries show some significant effects (e.g., 0.006* for Gov. Exp. at Lags 1), and -0.018** for Budget Exe. at Lags 2 in one specification.

### Short-run effects (CS-ARDL)
- Direct expenditure conditionality achieves short-term objectives even when long-run effects are not durable.
- Table 6 — Short-run and Long-run estimates (Dependent Variable as percent of GDP; Conditionality: Direct measure):
  - Short Run:
    - Education Spending: 0.000  [0.001]
    - Health Spending: 0.002***  [0.000]
    - Wage: -0.001  [0.001]
    - Public Investment: 0.003**  [0.002]
  - Long Run:
    - Education Spending: -0.000  [0.006]
    - Health Spending: -0.002  [0.011]
    - Wage: 0.008  [0.005]
    - Public Investment: 0.003  [0.009]
  - Observations (Table 6): Education 965; Health 1862; Wage 1017; Public Investment 1869.
- Interpretation: Minimum floors for certain types of spending can ensure adequate short-term allocations for poverty and growth-enhancing programs in tight fiscal environments.

### Conclusions and policy implications
- Expenditure conditionality has shifted toward protecting growth-friendly and pro-poor spending and addressing structural issues: spending floors on social spending and public investment, improving budget execution and control, and preventing domestic arrears.
- Structural conditionality (accounting & financial reporting, arrears containment, budget execution/control) is most effective over the longer term in improving the composition of government spending—particularly increasing the share of health and education.
- Trade-offs and caveats:
  - Floors on specific spending (e.g., public investment) can boost those expenditures but may exert pressure on other budget areas (e.g., health).
  - Binding constraints on one expenditure type may distort short-term resource allocation under limited fiscal space.
  - The mere existence of expenditure conditionality does not lead to improved outcomes; implementation (i.e., meeting conditions) is crucial.
- Suggestions for future research:
  - Study impact of conditionality on sectoral outcomes in education and health (expenditure increases do not necessarily translate to better outcomes if inefficiencies persist).
  - Investigate whether different types of conditionality (structural, revenue, or expenditure) are complements or substitutes in achieving long-term macroeconomic improvement.

*Source: wp18255 - Appendix A (Appendix A of the study; dataset and empirical results for 1992-2016).*

### Appendix Figure 1. Average Number of Expenditure Conditionality by Category

### wp18255 - Appendix Figure 1. Average Number of Expenditure Conditionality by Category

### Overview of expenditure conditionality types and categorization
- Expenditure conditionality in the MONA database is classified into:
  - Quantitative measures (either a floor or ceiling). Note: "All quantitative measures are ceilings except for social protection (social spending) and payment of arrears."
  - General public financial management (PFM) measures.
- Expenditure conditions are separated into nine spending categories and seven PFM categories.

### Spending categories (definitions preserved)
- General/central government expenditure: Conditions related to minimizing the total amount of government spending  
- Subsidies: Conditions related to minimizing government spending on subsidies  
- Wage bill: Conditions related to minimizing the government’s wage bill  
- Social protection: Conditions related to increasing spending on or transfers to health, education, or pro-poverty sectors  
- Pensions: Conditions related to minimizing civil service pensions and social security spending  
- Public investment and public private partnerships (PPPs): Conditions related to increasing government spending on public investment  
- Arrears: Conditions related to increasing arrears payments or decreasing the stock of arrears  
- Extra-budgetary expenditure: Conditions related to the limiting level of extra-budgetary spending  
- Specific expenditure: Conditions related to country-specific spending measures

### Public Financial Management (PFM) categories (definitions preserved)
- Accounting and financial reporting: Conditions related to budget classification, chart of accounts, or conceptual design  
  - Example: Adopt accounting standards for the government and a comprehensive chart of accounts. Ministry of Finance to publish quarterly reports on the stock of unpaid bills of all government entities contained in the central government votes.
- Budget execution and control: Conditions related to commitment controls, internal control standards, guidelines for public expenditure management, or treasury single accounts  
  - Examples: Ceiling on the amount of the budgetary float. Complete an external audit by a reputable international audit company.
- General public financial management reform: Conditions related to budget system reform, fiscal transparency, performance measurement, and budget institution reform  
  - Examples: Develop a PFM strategy covering the next three years, to be attached to the budget. Adoption by the Government of a strategy for a better monitoring of operations and financial performance of public enterprises.
- Institutional design: Conditions related to extra-budgetary funds, fiscal decentralization and government guarantees  
  - Examples: Centralization of all public revenues and execution of all public payments by the Treasury. Establish a Public Procurement Authority. Adopt, in consultation with donors, a new budget nomenclature, including a functional classification.
- Legislative framework: Conditions related to fiscal federalism and legislation in the budget process  
  - Example: Adoption by the Parliament and promulgation of the law on government finance.
- Macrofiscal/budget preparation: Conditions related to budget preparation and fiscal risks  
  - Examples: Submission of government budget. Approval of government budget.
- Public investment: Conditions related to efficient public investment and implementing public investment programs  
  - Examples: Submit revised National Investment Policy to Cabinet. Complete a three-year public investment plan, fully integrated with the budget process, to be submitted with the budget.

### Frequency, types, and success rates of expenditure conditions (selected counts and percent met)
- Aggregate sample sizes:
  - Number of countries: 106
  - Number of programs: 212

- Spending-category conditions: total counts by condition type (IT = Indicative Target, QPC = Quantitative Performance Criterion, SB = Structural Benchmark, PA = Prior Action)
  - IT: Total number by category (excerpt): IT 29 total; breakdown shown as "IT 29 0 19 231 0 0" (columns correspond to spending categories in the table).
  - QPC: QPC 381 total; breakdown shown as "QPC 381 20 178 25 14 34".
  - SB: SB 3 total; breakdown shown as "SB 3 14 58 97 86 4".
  - PA: PA 0 total; breakdown shown as "PA 0 6 30 29 29 0".
- Spending-category percent met (percent met by condition type and category; entries as in source table)
  - IT percent met: "IT 69   63 61" (table shows 69 percent overall for IT and 63, 61 for some categories)
  - QPC percent met: "QPC 70 90 70 56 64 65"
  - SB percent met: "SB 100 86 88 81 78 100"
  - PA percent met: "PA   100 97 100 100" (prior actions nearly all met)

- PFM-category conditions: total counts by condition type (selected excerpts)
  - IT: "IT 7 7 7 5 0 17 ... 12 0 0 0 0 334" (IT counts across PFM categories and total)
  - QPC: "QPC 444 24 16 9 0 13 ... 1 0 0 193 0 1352" (QPC counts across PFM categories and total)
  - SB: "SB 26 33 25 12 100 229 ... 144 108 102 105 58 1204" (SB counts across PFM categories and total)
  - PA: "PA 12 16 4 2 24 65 ... 43 13 37 60 7 377" (PA counts across PFM categories and total)

- PFM-category percent met (percent met by condition type and category; entries as in source table)
  - IT percent met: "IT 71 86 86 80   82 ... 75         65"
  - QPC percent met: "QPC 72 79 81 78   85 ... 100     75   72"
  - SB percent met: "SB 85 91 88 75 81 79 ... 82 75 88 84 78 82"
  - PA percent met: "PA 100 100 100 100 100 100 ... 100 100 100 100 100 100"

- Core descriptive findings regarding types and success rates:
  - The most common types of expenditure conditions are quantitative performance criteria (QPCs).
  - The second most common type of condition is indicative targets (ITs); ITs, QPCs, and structural benchmarks (SBs) tend to include social protection and priority spending and wage bill conditions.
  - ITs, QPCs, and SBs have relatively high success rates in implementation, with 76 percent of the conditions met on average across all spending categories.
  - Prior actions (PAs) are nearly always met.
  - PFM conditionality focuses on accumulation and stock of arrears, accounting and budgeting, and institutional and legislative frameworks; PFM conditions have approximately 82 percent of conditions met on average across all PFM categories.

### Data sources and independent variables (selected)
- MONA database: provides data for construction of dummy variables on IMF-supported programs and expenditure conditionality; starting year of a program is the year in which it was approved; end year is the year in which the program expired.
- Health expenditure (percent of GDP): World Development Indicators (World Bank)
- Education expenditure (percent of GDP): World Development Indicators (World Bank)
- Investment expenditure (constant 2011 international dollars): IMF Investment and Capital Stock Dataset (2017)
- Nominal GDP (LCU): World Economic Outlook, October 2016
- Population: World Economic Outlook, October 2016
- Social expenditure (LCU): World Economic Outlook, October 2016
- Social expenditure (percent of GDP): The Atlas of Social Protection Indicators of Resilience and Equity (World Bank)
- Total expenditure (percent of GDP): World Economic Outlook, October 2016
- Expenditure on compensation of government employees (percent of GDP): IMF Government Compensation and Employment Dataset, 2016
- Expenditure on compensation of government employees (percent of total expenditure): IMF Government Compensation and Employment Dataset (2016)

### Notes on variable definitions (preserved)
- Public health expenditure consists of recurrent and capital spending from government (central and local) budgets, external borrowings and grants (including donations from international agencies and nongovernmental organizations), and social (or compulsory) health insurance funds.
- General government expenditure on education (current, capital, and transfers) is expressed as a percentage of GDP and includes expenditure funded by transfers from international sources to government.
- Social expenditure is defined as transfers in cash or in kind to protect the entire population or specific segments of it against certain social risks; classified according to the type of scheme governing their payment and consist of social security benefits, social assistance benefits, and employer social benefits (GFSM 2001, paragraphs 6.67-6.72). The payment of pensions and other retirement benefits through employer social insurance schemes are not expense; they are treated as reductions in liabilities.

*Source: wp18255 - Appendix Figure 1. Average Number of Expenditure Conditionality by Category*

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_Source: https://www.imf.org/-/media/files/publications/wp/2018/wp18255.pdf_