A. Program Goals, Instruments, and Conditionality: Focus and Alignment

14. Program instruments were aligned with key program objectives (Figure 1).¹⁴ All programs identified external and macro-economic stability as overarching goals. GRA-supported programs (hereafter GRA programs) centered on external and macro-economic stability; an increasing number of programs included growth objectives (from 40 to 60 percent of programs between 2008 and 2011), reflecting mounting concerns about growth in emerging market (EM) and advanced market (AM) program countries. Almost all PRGT-supported programs (hereafter PRGT programs) aimed also to achieve poverty reduction and economic growth.¹⁵ Fiscal and monetary policies were the most frequently used instruments in support of program goals, with some differences across program types.^16,17 GRA programs relied more strongly on financial sector policies, while PRGT programs demonstrated their emphasis on growth and poverty reduction by employing a wider set of pro-growth and social sector policies. Program goals, program instruments, and structural conditionality also were more focused for countries with weaker initial conditions (Box 1).

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Program Goals and Instruments, 2006-2011

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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15. Structural conditionality was in general broadly aligned with program goals and tailored to country circumstances (Boxes 1 and 2 and BP2). PRGT programs included more wide-ranging structural reform agendas, while capital account challenges, along with concerns about the size of spillovers and systemic risks, in some GRA programs were reflected in higher access levels. Program design took into account political economy considerations (see summary of EPAs/EPEs in BP4) and spillover effects of the global financial crisis (see BP2).

Box 2.

Structural Conditionality Alignment and Tailoring

This box assesses whether conditionality was appropriately aligned and programs properly tailored in a sample of program countries.¹⁹ The main conclusions are that (1) program conditionality was generally well aligned with program goals and reform strategies, although there was room for improvement; and (2) programs were generally tailored to country-specific circumstances.

In most cases structural measures were in line with the programs’ stated objectives, though not all objectives were covered by structural measures (Box Table).²⁰ This was equally true for GRA and PRGT countries; for both sets around 80 percent of conditions on average could be linked to specific objectives.²¹ By contrast, not all objectives were covered by structural reforms: In PRGT countries, about 60 percent of objectives were addressed by structural reforms and 70 percent in GRA countries. Full coverage would not be expected given that certain objectives, like reducing inflation or the deficit, are achieved with QPCs and not structural measures. Nonetheless, there is a large variation across countries, with as little as one third of objectives covered by structural measures in some countries.

Generally, program design and conditionality were focused and tailored to country circumstances. Structural conditionality was typically specific to the country’s policy and institutional setting. When programs were designed in close coordination with other institutions and donors, Fund conditionality was focused on areas within its core area of responsibility. In particular:

• The particular lending facility chosen for the program depended on the scope and nature of the needed reform agenda. The Fund offers a variety of lending facilities, catering to the specific needs of members. Some allow for more time than others to implement an ambitious structural reform agenda, notably the ECF for PRGT-eligible countries, and the EFF for GRA countries. The FCL and the PLL (formerly PCL) offer support to relatively stronger performers with a commensurate reduction in conditionality. Countries may move from one facility to another, e.g., in 2009, Seychelles from a SBA to an extended arrangement and Armenia from a SBA to an ECF-EFF blend arrangement.

• Program duration and the timing of conditionality were in line with country characteristics. Among case study countries, PRGT programs tended to have more structural measures than GRA programs in the original program design, reflecting their heavier structural agendas. However, the number of conditions to be implemented in the first three months was lower than in GRA programs (2 compared to 3); this, together with the longer time span on PRGT programs and typically semi-annual reviews, facilitated program implementation in a context of weaker administrative capacities.

• Past performance and political cycles played a role in designing program conditionality. The 2007 Burkina Faso program followed 10 years of strong program implementation (according to the EPA), which was reflected in lower fiscal adjustment, no reliance on PAs, a number of structural conditions close to the average for the sample, and the need for only small access. The one-year 2006 Uganda PSI was to be replaced by a multi-year PSI later in the year, so as to promote ownership by delaying discussions on substantive medium-term policies until after the elections. In contrast, the 2007 Gambia program, which was approved after several programs with mixed success (attributed by the EPA to a lack of ownership), had three PAs and an above average number of structural measures.

• Program conditionality usually covered multiple policy areas, but there were instances of strong focus responding to the diagnosis of the problems and priorities. For instance, conditionality for the 2008 Armenia program heavily emphasized tax reforms, the 2008 Iceland one stressed banking reforms, and the January 2006 Uganda one stressed domestic arrears.

Alignment of Objectives and Structural Conditionality

Source: MONA and staff calculations.

Alignment of Objectives and Structural Conditionality

	Objectives		Measures			Alignment
	Number of		Number of			Percent
	Goals	Strategies	PAs	SBs/SPCs	First 3 months	Conditions/Goals	Goals/conditions
Averages
GRA	3	4	2	6	3	81	70
PRGT	2	5	2	9	2	87	61
All programs	2	5	2	8	3	84	65

Source: MONA and staff calculations.

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Alignment of Objectives and Structural Conditionality

	Objectives		Measures			Alignment
	Number of		Number of			Percent
	Goals	Strategies	PAs	SBs/SPCs	First 3 months	Conditions/Goals	Goals/conditions
Averages
GRA	3	4	2	6	3	81	70
PRGT	2	5	2	9	2	87	61
All programs	2	5	2	8	3	84	65

Source: MONA and staff calculations.

16. While EPAs and EPEs generally confirm that conditionality was well-aligned with the key program objectives, there were important exceptions (BP4). In some instances, EPAs and EPEs saw scope to align the reform agenda more consistently with program objectives, and to sequence reforms in order to overcome capacity constraints (Sierra Leone). In other cases, they assessed that the macro-criticality of structural measures could have been demonstrated more clearly in order to ensure focus on core areas of Fund expertise and provide a better sense of direction for policy makers (Benin, Burundi). In a few countries, EPAs and EPEs considered that better diagnostics of underlying institutional and political constraints would have enhanced the effectiveness of conditionality (Belarus, Ukraine, and Kyrgyz Republic). These ex-post exercises also deemed that some programs suffered from lack of appropriate follow-up conditionality, once the initial set of reforms had been completed.

17. Survey results also point to the alignment of program conditionality with program objectives (Figure 2). While Fund staff and country authorities generally agreed that conditionality had been geared toward critical program objectives, responses from donor agencies were more cautious, suggesting room to explain the criticality of Fund conditionality more coherently.

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Program Objectives and Conditionality

Outcome from questionnaires (percent of respondents)

Statement: The structural conditions in the program only covered reforms that were critical for program objectives, design and implementation

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

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Source: MONA and staff calculations.Probabilities In these charts show the probability of finding a program with corresponding structural conditionalrty In the full sample. Different lines represent conditional probabilities where the conditions are having different reform strategies. The 13 MONA categories for reform strategies are aggregated into 5 categories: Fiscal (Public Expenditures and Fiscal Revenue). Monetary (Monetary stability, stable inflation. Central Bank Reform, and Exchange Rate issues). Financial Sector Reform, Public Enterprises, and Others (Trade Reform. ProKjrowth Regime. Social Outcomes. Economic Governance, and Other).

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B. Focus of Structural Conditionality

18. To an increasing extent, structural conditionality has focused on core areas of Fund expertise (Figure 3).²² In principle, conditionality can be applied to areas beyond core Fund expertise if critical for program success. However, the Guidelines state that conditionality that would be critical to program success “will normally consist of macroeconomic variables and structural measures that are within the Fund’s core area of responsibility” (Guidelines, ¶7 (b)). The trend toward conditionality focusing on core Fund competencies picked up in recent years, particularly for GRA programs, reflecting an increasing focus on fiscal-related conditionality.

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Breakdown of Structural Conditions into Fund Competencies

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

source: MOMA and staff calculations.¹ Includes SPCs. SACs. SBs. and priar actions.

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19. Fiscal conditionality has dominated the structural reform agenda in Fund-supported programs, with much of it drawn from the Fund’s technical assistance (Figure 4). In PRGT programs, in particular, government-related structural measures accounted for about 58 percent of total structural conditionality during 2008-2011, an increase of more than 7 percentage points compared to the preceding three-year period. Financial sector reforms were the second most important area of structural reforms, notably in GRA programs. As the crisis moved from a financial crisis to a deeper, real-sector crisis, the focus on the financial sector peaked at the onset of the global financial crisis, after which fiscal issues increased in prominence, including in the European Union and Iceland programs (Figure 5).

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Focus of Structural Conditionality

Distribution of conditions by sector, in percent of total conditions per review

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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Fiscal and Financial Sector Conditionality in GRA-Supported Programs¹

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ EU programs include Iceland, Greece, Hungary, Ireland, Latvia, Portugal, and Romania.

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20. The breakdown of structural conditionality by sector was determined by the extent of vulnerabilities and the availability of fiscal space (Table 1 and Appendix 2). For instance, general-government or fiscal related conditionality in GRA programs was more likely to be higher with better economic conditions (lower inflation, higher growth), while conditionality in the financial sector was more likely to be important when there are larger exposures (total assets and liabilities) and smaller fiscal deficits. In PRGT programs, more general government conditions were more likely with higher debt levels, lower reserves, and smaller fiscal deficits.

Table 1.

Determinants of the Probability of a High Number of Structural Conditions ¹

¹This table summarizes the results of probit models relating the probability of setting a large number of conditions (defined as a number of conditions belonging to the highest quartile of the distribution) to macroeconomic conditions at program approval. Probit models are run separately on the main categories of structural conditionality. Only statistically significant variables are summarized. Detailed results appear in Appendix 2.

Table 1.

Determinants of the Probability of a High Number of Structural Conditions ¹

	GRA	PRGT
General government	Inflation (-) Growth (+)	Fiscal balance (+) Debt/GDP (+) Reserves (-)
Central bank	Trade openness (-)	Inflation (+) Reserves (-) Assets and liabilities (-)
Public employment	Current account (-) Growth (-)
Pensions and social sector		Trade openness (+)
Public enterprise		Debt/GDP (-) Fiscal balance (+)
Financial sector	Assets and liabilities (+) Fiscal balance (+)	Inflation (-)
Other		Growth (+)

¹This table summarizes the results of probit models relating the probability of setting a large number of conditions (defined as a number of conditions belonging to the highest quartile of the distribution) to macroeconomic conditions at program approval. Probit models are run separately on the main categories of structural conditionality. Only statistically significant variables are summarized. Detailed results appear in Appendix 2.

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Table 1.

Determinants of the Probability of a High Number of Structural Conditions ¹

	GRA	PRGT
General government	Inflation (-) Growth (+)	Fiscal balance (+) Debt/GDP (+) Reserves (-)
Central bank	Trade openness (-)	Inflation (+) Reserves (-) Assets and liabilities (-)
Public employment	Current account (-) Growth (-)
Pensions and social sector		Trade openness (+)
Public enterprise		Debt/GDP (-) Fiscal balance (+)
Financial sector	Assets and liabilities (+) Fiscal balance (+)	Inflation (-)
Other		Growth (+)

¹This table summarizes the results of probit models relating the probability of setting a large number of conditions (defined as a number of conditions belonging to the highest quartile of the distribution) to macroeconomic conditions at program approval. Probit models are run separately on the main categories of structural conditionality. Only statistically significant variables are summarized. Detailed results appear in Appendix 2.

21. Efforts to enhance the focus of programs can be seen in conditions set on public financial management (PFM), macro-social conditionality, and wages. PFM conditionality has typically been sequenced to address the most important vulnerabilities (Box 3). Conditionality on macro-social critical reforms, while remaining parsimonious, has gained in importance in recent years (Box 4). Finally, refocusing conditionality on areas critical to macroeconomic stability also applied to public wage ceilings. While ceilings— specifically, QPCs—on civil service wages were included in programs in the early 2000s, this practice was discontinued in 2007 given concerns about their impact on poverty-reducing spending (Box 5).

Box 4.

Macro-Social Structural Conditionality in Fund-Supported Programs

The focus on macro-social issues in Fund-supported programs has increased recently. An analysis of all macro-social structural conditions over 2002-2011 showed that, in line with the call for parsimony and focus on macro-critical conditions in programs, structural conditionality directly related to macro-social issues represented a small share of all structural conditions. Macro-social conditionality had been declining since the early 2000s, but started to increase again at the end of the review period. GRA programs have typically included more macro-social conditions, with a greater relative focus on reforms to pensions, social sectors, and labor markets. By contrast and also reflecting labor market characteristics in these countries, civil service reforms are relatively more common in PRGT programs, but conditionality related to pensions or labor markets outside public employment is very limited (Box Figure).

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Macro-Social Conditions, by Type of Fund-Supported Program

Share of total structural conditions

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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What are the short and long-term outcomes? Several Fund-supported programs include measures aimed at lowering fiscal expenditure in the short term and/or improving productivity through structural reforms. While these measures contribute to resolving balance-of-payments difficulties and are likely to result in longer term gains, they may also have short-term costs in terms of employment or income. In some countries, programs included deeps cuts in public sector employment, public sector wages (e.g., Latvia and Greece), and pensions (Greece), reflecting the depth of the fiscal trouble and the need for rapid and strong adjustment. In the case of Latvia, for example, safety measures were introduced, such as extension of employment benefits, public works programs, and higher housing benefits. A close look at these measures suggests that:

• On labor markets: many measures involved social partners in the decision-making process, helping build ownership for reforms and thereby supporting successful program implementation. While many of these conditions could have short-term costs, they were also likely to improve the functioning of labor markets and make them more inclusive over the longer term.

• On the civil service and public employment: some conditions could result in lower public employment or lower wages in the short-term. However, measures that aim at enhancing productivity need not have short-term negative effects, and have positive longer-term effects in terms of public sector efficiency. These measures are more common in PRGT programs.

• On pensions and other social sector reforms: almost half of conditions aimed at improving the social safety net either through higher social spending or through better targeting of benefits. In some instances where programs supported reforms of energy subsidies, conditionality helped mitigate the impact of higher energy prices on the poor.

Box 5.

Wage Bill Ceilings in PRGT Programs²³

In 2007, the Executive Board requested that wage bill ceilings in LICs be used only in exceptional cases and with sufficient flexibility in programs. This guidance followed a discussion on the implications of aid inflows for Fund advice and program design in LICs.²⁴ Wage ceilings had come under criticism from both civil society organizations and the IEO, because they could prevent LICs from using donor resources for expanding employment in poverty-reducing sectors, such as health and education. A review by Fund staff found that while wage bill ceilings were used with some flexibility and were tailored to country circumstances, they also created a number of problems: they tended to persist in programs, were difficult to monitor, and distracted governments from efforts to strengthen institutions for better controlling wage spending.²⁵

An analysis of conditionality at program approval showed that the policy on wage bill ceilings for LICs was well followed. There were no QPCs set on wage bills starting in 2007, although there were a few instances of monitoring through ITs. For example, this reflected high wage bills in Djibouti and Moldova compared to similar countries in the region, and the need to reorient spending towards pro-poor spending in Cote d’Ivoire. Structural conditionality related to wage bill ceilings also dropped significantly—the last PRGT program with structural conditionality on wage bills was Moldova with an SPC in 2006 and a PA in 2009 (Box Table).

Use of Wage Ceilings in IMF LIC Program Conditionality

Use of Wage Ceilings in IMF LIC Program Conditionality

Year of program approval		2002	2003	2004	2005	2006	2007	2008	2009	2010	2011
Quantitative PCs or ITs
Nicaragua	PRGF	QPC
Dominica	PRGF		QPC
Ghana	PRGF		QPC
Kenya	PRGF		QPC
Honduras	PRGF			QPC
Chad	PRGF				QPC
Benin	PRGF				IT
Malawi	PRGF				QPC
Central African Republic	PRGF					QPC
Moldova	PRGF					IT
Sierra Leone	PRGF					IT
Nicaragua	PRGF						IT
Burundi	PRGF							IT
Djibouti	PRGF							IT
Cote d’Ivoire	PRGF								IT
Moldova	ECF-EFF									IT
PAs, SPCs, SBs
Number of programs with structural conditionality implying wage bil ceiling		2	4	2	2	1			1
Memorandum item: Number of LIC programs approved		8	10	7	9	13	7	11	7	19 2

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Use of Wage Ceilings in IMF LIC Program Conditionality

Year of program approval		2002	2003	2004	2005	2006	2007	2008	2009	2010	2011
Quantitative PCs or ITs
Nicaragua	PRGF	QPC
Dominica	PRGF		QPC
Ghana	PRGF		QPC
Kenya	PRGF		QPC
Honduras	PRGF			QPC
Chad	PRGF				QPC
Benin	PRGF				IT
Malawi	PRGF				QPC
Central African Republic	PRGF					QPC
Moldova	PRGF					IT
Sierra Leone	PRGF					IT
Nicaragua	PRGF						IT
Burundi	PRGF							IT
Djibouti	PRGF							IT
Cote d’Ivoire	PRGF								IT
Moldova	ECF-EFF									IT
PAs, SPCs, SBs
Number of programs with structural conditionality implying wage bil ceiling		2	4	2	2	1			1
Memorandum item: Number of LIC programs approved		8	10	7	9	13	7	11	7	19 2

C. Focus of Quantitative Conditionality

22. Quantitative conditionality focused on external and fiscal stability, reflecting the key objectives of Fund-supported programs (Figure 6). Following a focus on debt in the earlier part of the review period, monitoring in GRA programs was shifted toward fiscal consolidation during the global financial crisis in line with the growing fiscal consolidation needs in a number of programs. In PRGT programs, the mix of QPCs remained broadly unchanged with emphasis on external debt, also reflecting the Fund’s involvement in debt-reduction exercises for LICs (BP4). Fiscal and monetary stability were monitored in almost all programs, and all PRGT programs included targets on external debt. The use of reserves targets was, however, limited in countries with no autonomous exchange rate policy (currency unions and currency boards constitute the totality of programs with no reserves target).

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Quantitative Conditionality in Fund-Supported Programs, 2002-2011¹

Number of conditions per review

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ External debt includes ceiling on external arrears (including no new arrears), medium and long term external debt, and short term debt. Monetary and fiscal stability includes credit to government, domestic arrears, fiscal deficit, and total domestic credit.

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23. Indicative targets have mostly been used to monitor fiscal performance and “social sector” indicators (Figure 7). Assessments of ITs are used to complement QPCs (or QACs) in monitoring quantitative performance. They are mostly used to provide guidance on the expected values of QPCs later in the program (these targets are normally turned into QPCs, with appropriate modifications; these are not reviewed here as they do not provide additional information compared with QPCs). They can also be set on variables that provide important additional information about program performance (such as the primary fiscal deficit, base money, and the change in net credit of the banking system to the public sector), or on variables that are seen as critical but may be difficult to assess with sufficient precision to qualify as QPCs.²⁶ Over the period under review, the largest share of ITs was related to the fiscal deficit in PRGT programs. In GRA programs, there was a shift toward fiscal ITs in the latter part of the period, reflecting concerns about fiscal sustainability. The use of wage ceilings declined both in GRA and PRGT programs (see also Box 4). “Social” ITs—typically floors for priority (such as social or poverty-related) spending—were used to monitor performance in fiscal expenditure in these areas. Following the revamping of facilities for LICs in 2009, which mandated monitoring of poverty-related spending, the use of poverty-related ITs increased in PRGT programs.

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Quantitative and Social-Related Indicative Targets, 2006-2011

(In percent of total)

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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D. Volume of Conditionality

24. The number of conditions set over the course of a program is often used as measure of parsimony. Parsimony implies containing the number of conditions in a program to the minimum necessary to achieve program objectives, as noted above. This paper counts conditionality on the basis of the year when conditions were reviewed (review-year approach; Box 6).²⁷

25. The number of QPCs has been stable, at around five to six per review (Figure 8). Macroeconomic frameworks drive the number of monitored variables and the variance in the number of QPCs by program is limited (the inter-quartile range is between four and six QPCs in GRA programs and between five and seven in PRGT programs). The number of ITs, which are used to facilitate the monitoring of program implementation, was broadly steady overall during 2006-11 (Figure 9).

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Number of Structural and Quantitative Conditions per Review, 2002-2011

All programs, average and median

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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Number of Indicative Targets per Review, 2006-2011

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ No data for 2006. There was only one GRA program in 2005, with 5 ITs.

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26. The discontinuation of SPCs in March 2009 had a sizeable impact on the number of structural conditions per review, notably in GRA programs.³⁰ This impact was further reinforced by the decline in SBs and PAs (both at program approval and during reviews) over most of the period (Figure 10).³¹ Moreover, the distribution across programs of the number of structural conditions per review narrowed during the latter part of the period, pointing to an effort across the board to further parsimony (Figure 11). The number of structural conditions however stabilized after 2009. Conditions per review would be even lower if arrangements under the FCL and PCL were included, given there is no ex-post conditionality under the FCL and limited ex-post conditionality under the PCL (BP4).³²

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Structural and Quantitative Conditionality in Fund-Supported Programs, 2002-2011

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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Distribution of Structural Conditions per Review, 2002-2011¹

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and Staff calculations.Source: MONA and Staff calculations.¹ The white line refers to the median value; grey boxes contain values within the 25th and 75th percentiles; whiskers indicate the dispersion between the lower and upper adjacent values; dots are the outside values. Adjacent values defined as follows: the upper adjacent value (UAV) is the largest data value that is less than or equal to the third quartile (Q3) plus 1.5 times the interquartile range (IQR): UAV = Q3 + [(Q3 - Q1) × 1.5]. The lower adjacent value (LAV) is the smallest data value that is greater than or equal to the first quartile (Q1) minus 1.5 times the IQR: LAV = Q1 - [(Q3 - Q1) × 1.5].

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27. The drive towards parsimony may have reached a plateau at the very end of the review period. The number of conditions per review remained comparatively low in both GRA and PRGT programs, but in GRA programs a steady increase in the number of SBs per review was noticeable (Figure 10). The number of reviews with a relatively larger number of conditions tended to increase between 2009 and 2011, likely reflecting the need to tackle deeper-rooted issues, such as competitiveness or large debt burdens (Figure 11). This shift was not limited to a small number of countries, but was rather widespread across all types of GRA programs. As a consequence, the total number of conditions per year picked up modestly starting in 2010, reflecting both an increase in the number of conditions per review (GRA programs) and a greater frequency of reviews per year (GRA and PRGT) (Figure 12).³³ These developments may be appropriate giving the changing circumstances in recent programs—especially the greater need for growth-enhancing structural reforms. However, they also point to the importance of continued monitoring of structural conditionality, to ensure that these are the minimum necessary to meet program goals.

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Reviews with more than 4 and 5 conditions

(In percent of total reviews)

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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Total Number of Conditions per Year of Ongoing Programs, 2002-2011¹

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ Prior actions refer to review prior actions. PRGT includes PSI.

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28. More frequent adjustments in structural conditionality point to an ongoing fine-tuning of programs, and maybe a need to better leverage surveillance. Fine-tuning of programs is expected as reviews proceed, especially as new unforeseen circumstances can require policy responses, including adjustments and additions to conditionality and, as the imperative of addressing quickly, a crisis situation may crowd out important structural measures in initial program design. In recent programs with advanced countries (namely, Iceland, Greece and Ireland), adjustments and additions to conditionality were relatively higher during the third and subsequent reviews, compared with other cases (Figure 13). While the changes had been agreed upfront with the authorities in some cases (e.g., Iceland), this could also indicate that conditionality may have become relatively more complex as these programs progressed. In some cases, lags in fully developing the reform agenda could point to some disconnect between Fund surveillance and program design. This suggests surveillance could be better leveraged in program design by relating more systematically program conditionality to the vulnerabilities identified during surveillance exercises, including through enhanced prioritization of recommendations during surveillance (Box 7 and Appendix 3).

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Number of New Conditions Set , 2008-2011

Average by review number

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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E. Depth of Structural Conditionality

29. The impact of structural conditionality depends not only on numbers of conditions but also on the depth of those conditions, where depth is defined as the degree and durability of structural change that would likely occur if the condition was implemented. As detailed in BP4, the notion of depth refers to the durability of structural change. It does not imply any assessment of (1) the difficulty of implementing conditionality on the part of authorities or (2) the criticality of structural measures agreed upon in a program. The analysis of programs during 2006-11 pointed toward an increase in depth of structural conditionality. There was significant variance among countries and regions, and on average, programs with advanced market economies were structurally deeper than programs with emerging markets. GRA programs with European countries demonstrated the highest degree of structural depth. The structural depth of recent programs with euro area countries (especially Greece) surpassed the average structural depth for other programs. While programs with LICs accounted for the largest number of conditions, structural depth in these programs was lower than that for the other two country groups.

30. Regression analysis indicates that there was a trade-off between the number and the depth of conditions. This suggests that streamlining may have led to a balancing in the burden of conditionality between the number of conditions and their depth (Box 8). In particular, the number of conditions per review correlated negatively with the average depth of conditionality per review in both GRA and PRGT programs during 2006-11.

Box 8.

Number of Conditions and Depth

A mere reduction in the number of conditions would not necessarily satisfy the principle of parsimony.

For example, a given condition can either be relatively easy or very demanding to implement. Measuring the structural burden of conditionality therefore requires taking into account both the number and the depth of conditionality.

The trade-off between the number of conditions and the depth of conditionality is estimated using a fixed-effects panel regression. The total number of conditions per review, for each program, was regressed against the average depth of conditionality. In order to avoid biases related to outliers, the first and last percentiles (in terms of depth of conditionality) were omitted from the regression. The estimated equation was:

$N_{\mathit{\text{ir}}}=\alpha {\text{Depth}}_{\mathit{\text{ir}}}+c+u_i+w_r+{\epsilon }_{\mathit{\text{ir}}}$

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Where i is the arrangement, r the review, N the number of total conditions per review (SPC, SB, or PA) and Depth is the weighted average depth of conditionality per review (where the weights for low, medium and high structural depth are set respectively at 1, 2 and 3). u and w_r are fixed effects for arrangements and reviews respectively, and s_ir is the residual.

Results point to a statistically significant tradeoff between the depth of conditionality and the number of conditions set by review, with a one standard deviation increase in the depth of conditionality correlated with a reduction in the number of conditions by 1.2 and .7 in GRA and PRGT programs respectively.

¹*** and ** refer to a 1 percent and 5 percent significance level respectively. The period covered is 2006-2011 and includes all conditions with test dates up to September 30, 2011.

	GRA	PRGT
Depth1	-2 23***	-1.43**
Adjusted R-squared Number of obs.	0.27 111	0.21 187

¹*** and ** refer to a 1 percent and 5 percent significance level respectively. The period covered is 2006-2011 and includes all conditions with test dates up to September 30, 2011.

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	GRA	PRGT
Depth1	-2 23***	-1.43**
Adjusted R-squared Number of obs.	0.27 111	0.21 187

¹*** and ** refer to a 1 percent and 5 percent significance level respectively. The period covered is 2006-2011 and includes all conditions with test dates up to September 30, 2011.

A. Ownership

31. Ownership is crucial to successful implementation of Fund-supported programs. According to the Guidelines, the primary responsibility for the selection, design, and implementation of economic and financial policies rests with member countries. Through a collaborative process, the Fund should aim to reach understanding with country authorities on a mutually acceptable path for achieving program goals, taking into account economic priorities, the political economy framework, the specific context for a program request, including the causes of the balance of payments need, and the member country’s capacity to implement reforms within the specified time horizon. The Fund also should encourage members to seek to broaden and deepen support for sound policies to enhance likelihood of implementation.

32. Streamlined and tailored programs, through parsimonious conditionality, support ownership. EPAs and EPEs noted that lack of ownership was sometimes exacerbated by the complexity of measures and capacity constraints in public administration. They also suggest that consideration of both political and capacity constraints was essential to program effectiveness (BP4 and Box 2).When slower-than-expected implementation of structural reforms reflects capacity constraints and/or limited ownership in implementing some of the “stronger” structural measures, a more prioritized approach in defining the reform may be required.

33. The Fund’s outreach to both the authorities and a broader group of stakeholders can help build ownership. Some EPEs and EPAs suggested that extensive outreach efforts, in combination with focused conditionality and flexible implementation, helped achieve a higher degree of ownership. Moreover, the review of country cases indicates that outreach served to facilitate some program negotiations (see also Box 9). While active interactions with civil society organizations were frequent, they were not the rule, reflecting both the fact that the main counterparts in program negotiations are the country authorities and possibly political sensitivity on issues related to outreach in some countries (Figure 14, and BP4). The recording of outreach activities in support of ownership in program documents was uneven, possibly reflecting staffs efforts to produce concise staff reports. In particular, three out of the nine GRA case studies did not report outreach activities, although there was evidence that outreach was undertaken.

Box 9.

Ownership, Program Implementation, and the Use of PAs

PAs can be used when program implementation concerns lead the Fund to look for frontloaded implementation of measures that are particularly critical for program success. In that context, PAs are both a screening device used to ensure that the minimum necessary level of ownership is present for program success and a tool to support implementation of conditionality.

Simple regression analysis suggests that the use of PAs at program approval was related to future implementation issues in GRA programs, pointing to the role of PAs as a screening device. A higher number of PAs at program approval was associated with a lower implementation ratio of structural conditionality over the length of the program (see Table below). This finding was only statistically significant for GRA programs with more than 2 PAs. Indeed, conditionality was much more focused when the number of PAs was limited, and largely related to fiscal measures such as adoption of budgets in line with the program agreement (Box Figure). In PRGT programs, the relation failed to be significant, suggesting that PAs were used regardless of potential implementation issues and possibly to advance important structural reforms in countries with large reform needs.

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Distribution of the Number of Prior Actions at Program Approval, 2002-2011

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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Number of Board Prior Actions and Subsequent Program Implementation, 2002-2011

Source: MONA and staff calculations.

¹Includes a dummm for Romania (2004 program) p-values in brackets.

^*p<0.1,

^**p<0.05,

^***p<0.01

Number of Board Prior Actions and Subsequent Program Implementation, 2002-2011

	Up to 2 PAs			More than 2 PAs
	All programs	GRA	PRGT	All programs	GRA1	PRGT
Implementation of structural conditionality over the life of the program	-0.298	-0.988	0.172	-5.481***	-7.928**	-3.156
Constant	0.933**	1.441**	0.602	9.183***	11.05***	7.353***
Adjusted R-squared	-0.008	0.017	-0.018	0.513	0.624	0.021
N	87	32	55	57	28	29

Source: MONA and staff calculations.

¹Includes a dummm for Romania (2004 program) p-values in brackets.

^*p<0.1,

^**p<0.05,

^***p<0.01

View Table

Number of Board Prior Actions and Subsequent Program Implementation, 2002-2011

	Up to 2 PAs			More than 2 PAs
	All programs	GRA	PRGT	All programs	GRA1	PRGT
Implementation of structural conditionality over the life of the program	-0.298	-0.988	0.172	-5.481***	-7.928**	-3.156
Constant	0.933**	1.441**	0.602	9.183***	11.05***	7.353***
Adjusted R-squared	-0.008	0.017	-0.018	0.513	0.624	0.021
N	87	32	55	57	28	29

Source: MONA and staff calculations.

¹Includes a dummm for Romania (2004 program) p-values in brackets.

^*p<0.1,

^**p<0.05,

^***p<0.01

The use of PAs during program implementation (or reviews) underlined their role as implementation tools. In particular, probit analysis indicated that the probability for a given review to include a PA was related to the implementation record of previous reviews.³⁴ In GRA programs, a better track record of current and past implementation lowered the likelihood that a PA was set for a given review. An improvement in program implementation by one percent in the current review reduced the likelihood of having a PA at that review by 0.6 percent. Concurrently, an improvement in implementation in the previous review by one percent reduced the likelihood of a PA by 0.5 percent (see Table to right).

PAs in PRGT programs were determined by the track record of the current review, while implementation in the previous review failed to have an impact. An improvement in the implementation ratio by 1 percent during the current review reduced the likelihood of having a PA at that review by 0.89 percent.

Probit Results for Prior Actions and Implementation ¹

Source: MONA and staff calculations.

¹The table reports marginal effects. P(y=1) denotes a review with at least one prior action

Probit Results for Prior Actions and Implementation ¹

	GRA	PRGT
Implementation ratio (t)	-0.0062**	-0.0089**
Implementation ratio (t-1)	-0.0077**	0.0011
Actual P	35.55	32.75
Predicted P	32.91	29.39
P error	-2.64	-3.36

Source: MONA and staff calculations.

¹The table reports marginal effects. P(y=1) denotes a review with at least one prior action

View Table

Probit Results for Prior Actions and Implementation ¹

	GRA	PRGT
Implementation ratio (t)	-0.0062**	-0.0089**
Implementation ratio (t-1)	-0.0077**	0.0011
Actual P	35.55	32.75
Predicted P	32.91	29.39
P error	-2.64	-3.36

Source: MONA and staff calculations.

¹The table reports marginal effects. P(y=1) denotes a review with at least one prior action

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Ownership - Results of the Survey of Fund Staff and Country Authorities

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

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34. Fund policies to support ownership of programs seemed to have brought some success. There are indications that ownership may have improved over 2002-2010 for GRA programs, as evidenced by less use of a large number of PAs at program approval (Box 9). Supporting this view, survey results indicated that Fund staff has confidence in country ownership. The MEFPs, which form the basis of program documents and describe the authorities’ economic policies, were designed with the active contribution of authorities. Drafting, however, remained mostly done by Fund staff, suggesting room for further improvement towards ownership (Figure 14).

35. The survey results, however, point to some difficulties in conveying Fund efforts to enhance ownership (BP4). For instance, the discontinuation of SPCs, which was designed partly to accommodate countries’ specific timelines in the implementation of structural conditionality, had a limited impact on the sense of ownership, as conveyed by Fund staff. Similarly, stigma attached to programs appeared to have not been significantly reduced.

36. In cases of limited ownership, specific instruments can enhance program implementation. Staff-monitored programs, for instance, can be used to assess the potential for a future Fund-supported program with UCT-quality conditionality, thereby gauging both implementation capacity and the degree of ownership by the authorities. PAs at program approval could also be used as screening devices for the degree of ownership. EPAs/EPEs suggested that a flexible approach to program conditionality, with regard to implementation timelines, was found to enhance ownership, while the discontinuation of SPC did not have a noticeable impact (Appendix 4).

37. However, conditionality cannot substitute for ownership. For example, a higher number of PAs did not systematically result in more successful program implementation (Box 9). In some programs—for example, with Ukraine—program success was reduced by weak ownership despite many PAs (BP4). Lessons from recent GRA programs also showcase the importance of ownership and the difficulty of gauging ownership through simple measures of implementation (Box 10).

B. Tailoring

38. In tailoring conditionality, programs need to strike a balance between consideration of country circumstances and evenhandedness among countries.³⁵

Program design needs to accommodate a broad spectrum of initial conditions. For instance, countries with wide-ranging structural reform agendas may require deeper structural changes than countries suffering from short-term liquidity shocks. Large-scale disbursements may justify a different type of conditionality than more limited disbursements. The Fund takes a liberal view to requests for transactions within the first credit tranche, provided that the member itself is making reasonable efforts to solve its problem. Conditionality should also be adapted to countries’ capacity and track record.

Capacity

39. Conditionality needs to reflect implementation capacity. In countries with low implementation capacity, program design entails tradeoffs between an ambitious structural reform agenda that ultimately would help the country to develop capacity, and a realistic set of conditions, possibly divided into small, achievable modules. Within the capacity-determined framework, conditionality could thus be somewhat less complex for low-capacity countries, and more ambitious for countries where stronger institutions allow for a higher degree of implementation.

40. Case study analysis suggests that capacity considerations did affect the design and sequencing of structural conditionality. The 2006 Sierra Leone program presented an example of a carefully paced structural agenda reflecting the country’s post-conflict nature. Similarly the structural agenda in the 2008 Togo program took into account the country’s capacity constraints after its long political crisis and donor disengagement, with no measures for the first six months of the program other than two PAs.

41. The burden of conditionality was tailored to the challenges facing low-capacity countries.³⁶ The correlation between country capacity at the time of program approval and the total number of conditions per program was positive and statistically significant (Figure 15).³⁷ The depth of conditionality was also adjusted to the capacity of countries: conditions of high structural depth tended to be set more frequently in countries with a higher Country Policy and Institutional Assessment (CPIA) rating.

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Number of Structural Conditions and CPIA Rating, 2005-2009¹

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Sources: MONA; World Bank; and staff calculations.¹ Includes SBs, SPCs, and PAs. The positive relation between the number of conditions and the County Policy and Institutional Assessment (CPIA) rating is significant at the 1 percent level for programs with CPIA rating equal or lower than 4.

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Access

42. Reflecting the need to safeguard Fund resources, conditionality was tailored to the access level under an arrangement. With differences across types of programs, access was related to the number of PAs for Board approval in PRGT programs and to the number of deep conditions in GRA programs (Figure 16). These results may be linked to capacity issues in PRGT countries, leading to a focus on measures that can be achieved prior to program approval. In GRA programs where capacity was usually stronger, higher access was correlated with deeper structural change, as higher BOP needs translated into both a higher access and a greater need for structural reforms to bring down large macro-imbalances.

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Structural Conditionality and Access in GRA and PRGT Programs, 2002-2011¹

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ For PRGT programs, the sample is limited to programs with at least one prior action at program approval, and non-zero access levels.

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43. The level of access impacted on the focus of conditionality (as defined in Section II). GRA and PRGT programs in the upper quartile of the access distribution for each group had structural conditionality that was more focused than average on financial sector reforms, reflecting more mature economic systems with greater financial difficulties. On the quantitative side, the monitoring of arrangements involving higher access was focused on fiscal issues. This was true for high exceptional access GRA-supported arrangements (access over 1000 percent of quota), as well as for PRGT-supported arrangements in the upper half of the access distribution, reflecting the need to ensure fiscal sustainability in a context of rising external debt (Figure 17).

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Focus of Conditionality and Access, 2008-2011

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ Includes review PAs, SBs, and SPCs. High exceptional access denotes access over 1,000 percent of Quota.

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44. Tailoring also applied to the specification of debt limits in programs with LICs. These programs typically included external debt limits, seeking to prevent the build-up of unsustainable debt, while allowing for adequate external financing. With the new guidelines on debt limits in place since December 2009, the Fund moved away from a single design for concessionality requirements toward a menu of options, taking better account of differences among LICs regarding their debt vulnerability and their macroeconomic and public financial management capacity (BP4).

45. According to survey results, conditionality was generally viewed as both tailored and flexible. While Fund staff were more convinced of the appropriateness of program design and flexibility, both country authorities and donors broadly shared the positive assessment (Figure 18).

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Tailoring and Flexibility of Fund Programs - Survey Results

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: Survey of IMF staff and stakeholders.

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46. However, some programs were affected by weaknesses in the design of conditionality. As noted in the EPAs and EPEs, inappropriate diagnostics of underlying problems reduced the effectiveness of some programs. In a few cases, critical conditionality or conditionality following-up on initial reforms did not form part of the program.

C. Coordination

47. Fund collaboration with partner institutions is essential for program success. The Guidelines underscore the need for coordination with other multilateral institutions— especially the World Bank—in designing and monitoring conditionality. While coordination has also been important with other international organizations—for example, bilateral and multilateral donors—the need for coordination with new partners, such as regional institutions, has grown in recent years, including to reduce the risks of duplication and overstretched capacity. EPAs and EPEs pointed to the essential role of coordination with the World Bank and other institutions in macro-critical areas of structural reform beyond the areas of core responsibility of the Fund, such as decentralization and energy sector reform.³⁸

48. Prominent examples of Fund coordination with other institutions include (BP4):

• Sub-Saharan Africa: The survey of Fund stakeholders and views from Fund country teams suggest that the coordination process with multilateral and regional institutions—notably with the World Bank—was effective (BP4). Coordination focused in areas of joint or overlapping responsibilities, supporting the streamlining of Fund conditionality and avoiding the duplication of conditionality across different organizations. Responsibilities were shared according to the “lead agency” principle, with the Fund focusing on macro-critical conditionality. Coordination was supported by the Joint-Management Action Plan and World Bank-Fund Collaboration (JMAP), but informal and formal coordination tended to be equally important. However, as noted in some of the EPAs and EPEs, on some occasions, collaboration with the World Bank met with challenges.

• Recent programs with European member countries: Coordination with the EU supported the design and monitoring of conditionality. The complementarities of Fund and EU expertise proved useful in various program areas. In fiscal policy, the Fund’s expertise was crucial in operationalizing the fiscal adjustment path and tackling fiscal risks, while European Commission (EC) expertise focused on specific fiscal areas, such as health care and pension reforms. In euro area countries, however, unlike under conventional programs, additional stakeholders added a layer of complexity in conditionality design, often resulting in extended periods of discussion and decision making. Discussions about critical issues (such as private sector involvement) also weighed on coordination as well as on program design. In addition, the large and growing number of structural reforms identified by the EU is increasingly at odds with the principle of parsimony (Box 11).

  Box 11.

  Design of Conditionality in Co-financed Euro Area Programs

  The three euro area (EA) member countries—for Greece, Ireland, and Portugal—are supported by the Fund, the European Commission (EC), and the European Central Bank (ECB), the so called “Troika.”

  Monitoring is ensured through a set of unified macroeconomic parameters and structural measures. Conditionality for Fund Board reviews is based on a standard quarterly framework of QPCs and SBs. EC conditionality is based on an overall assessment of progress against the EC structural agenda and macroeconomic targets. Joint Troika review missions and assessments support coincidental disbursements from the Fund and the EU.

  Coordination is important for these programs. It has developed in the spirit of the Guidelines and was generally guided by the core expertise of each institution (BP4).³⁹ The Fund mostly focuses on short-term macro-critical policies, while the EC covers comprehensive medium-term structural reforms. Fund conditions mainly address the fiscal and financial sectors, but also include SBs related to competitiveness in the Portugal and Greece program. The EC’s structural agenda aims at reforming areas deemed critical for medium-term recovery and is geared toward achieving compliance with EU directives; reforms bear on public administration, health, labor market, the judicial system, and sectoral competition. Within this division of labor, some overlaps between institutions exist (for instance, the EC/ECB memoranda of understanding include fiscal and financial chapters). On the quantitative side, the EC targets are designed to be consistent with the Fund’s, even though the definition of the targets may differ (e.g., fiscal targets are defined on a cash basis for the Fund, but in percent of GDP for the EC). On the structural side, EC measures are usually much more precise and detailed than the Fund’s. While this allows for a more effective division of labor, it may create ex-post inconsistency issues (e.g., Fund conditions for Greece provide for a —comprehensive pension reform that reduces the projected increase in public spending on pensions over the period 2010-60 to 2% percent of GDP,” while the EC has a set of precise measures defining the new pension system). While the assessment of the Fund’s parsimonious conditions is straightforward, the large set of EC measures calls for a broad-based assessment of implementation prior to authorizing a disbursement.

  Over time, both the Fund and the EC have increasingly ventured into areas of structural reforms initially devoted to the other institution. EC-supported measures have been more and more focused on fiscal issues, while the Fund introduced “competitiveness” conditionality in the Portugal and Greece programs. While the exact number of EC measures is difficult to establish (as they are broken down into sub-measures), it has been far less parsimonious than the Fund standard, and became even less so over time (Box Figure). Moreover, whereas EC measures set for the Greece program were initially clearly identified as conditionality, the identification became less clear-cut in following reviews or other EA programs, as some measures included both very detailed sub-actions and broad overall objectives.

  

  

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  EC structural conditionality in Euro Area programs

  Number of measures at Board approval

  Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

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49. Country authorities, Fund staff, and donor agencies viewed coordination as critical to program implementation. More than 80 percent of respondents noted intensive coordination with donors and effective coordination with the World Bank (Figure 19).

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Fund Coordination with Aid Partners - Survey Results

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: Surveyof IMF staff and stakeholders.

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D. Clarity

50. Clarity in Fund conditionality enables stakeholders to better comprehend the key elements of programs. In particular, the operational guidance notes on conditionality call for clear justification of program conditionality, as well as of the link between program goals, program instruments, and the corresponding structural conditionality. Program documents should discuss possible concerns related to implementation constraints and provide strong justification and more detailed explanation of the critical importance of conditions outside Fund core areas of expertise. Discussions with country authorities on policy options should be conveyed clearly where possible. Moreover, program conditions should be transparently distinguished from other elements of the authorities’ program in program documents and staff reports.⁴⁰ Except when otherwise indicated, the following assessment of clarity is based on the review of the country case studies (see BP4 for details).

51. Country case studies indicated that the implementation of the Guidelines with respect to clarity in conditionality has been uneven. In particular, while most staff reports reviewed provided a clear justification of the criticality of conditionality and presented implementation risks, the specific guidance on the presentation of critical structural measures and of a discussion of policy options was largely ignored (Table 2).

Table 2.

Presentation of Conditionality

In percent of case study Staff Reports meeting guidance

Source: Staff calculations, based on a sample of 18 countries.

Table 2.

Presentation of Conditionality

In percent of case study Staff Reports meeting guidance

Justification of clarity?	Clarity in IMF vs. authorities’ goals?	Link between structural conditions and program objectives?	Discussion of policy options?	Discussion of implementation difficulties?	Table of all structural and quantitative conditionality?
78	56	72	28	89	38

Source: Staff calculations, based on a sample of 18 countries.

View Table

Table 2.

Presentation of Conditionality

In percent of case study Staff Reports meeting guidance

Justification of clarity?	Clarity in IMF vs. authorities’ goals?	Link between structural conditions and program objectives?	Discussion of policy options?	Discussion of implementation difficulties?	Table of all structural and quantitative conditionality?
78	56	72	28	89	38

Source: Staff calculations, based on a sample of 18 countries.

52. Staff reports for many of the case study countries presented the proposed conditionality in a comprehensive way. The 2009 Ghana program contained a comprehensive table with measures and their macroeconomic rationale. The 2008 Togo one presented a complete set of past, immediate, and envisaged structural reforms, while the 2008 Pakistan program contained a box explaining how structural measures link to the achievement of program objectives. However, some reports could have better set out the rationale and criticality of the proposed conditionality.

53. Reports did well in justifying the macro relevance of structural conditionality, but could have done better in linking conditionality clearly to program goals. The July 2008 revision to the operational guidance note called for a clearer explanation of the choice of conditionality, in particular its macro-criticality. Much progress was made with explaining the macro criticality. Of the 19 case study programs approved in or after 2008, almost all did so, usually referring to “macro rationale”—in most cases in a structural conditionality table. However, no staff report followed the guidance note’s approach of introducing structural conditionality with an explanation of program goals, strategies/instruments, and structural conditionality. Only the documents for Armenia (2008 and 2009) grouped the structural conditionality by strategy. Hence, the intention of the 2008 guidance note of clearly presenting the mapping of structural conditionality to objectives and strategies was only partially realized. A few programs stood out by succinctly articulating program objectives and strategies in their executive summaries—2008 Hungary, 2008 Seychelles, and 2008 Togo. In combination with a table linking those to structural conditionality that approach could qualify as best practice.⁴¹

54. Programs include non-core structural conditions that could be better justified. The analysis of case study countries suggests that a number of structural measures fell outside the Fund’s core areas of expertise (Table 3).⁴² Overall roughly 40 out of 200 measures in 26 programs were non-core. Most of these had to do with state-owned enterprises, social programs, or civil service reform. One third of GRA programs had such measures, while about two thirds of PRGT programs had non-core conditionality. In one third of cases the justification for the measure was quite detailed; in the rest it was succinct and not different from the other measures. In only three cases was a partner institution mentioned that would provide technical assistance with the implementation. In sum, programs could do better in identifying measures that are not core, but nonetheless macro-critical, and therefore included in conditionality.

Table 3.

Non-Core Conditionality in Case Studies

Source: staff calculations, based on a sample of 18 countries.

Table 3.

Non-Core Conditionality in Case Studies

		Number of programs	Non Core measures
			Total	Per program	% of conditions
All programs		26	41	1.6	20.7
With Non-Core (NC)		14	39	2.8	32.8
GRA
	All	10	8	0.8	13.6
	With NC	4	8	2.0	28.6
	2006-07	0	0	0.0	0.0
	2008-11	10	8	0.8	13.6
PRGF, ECF, PSI
	All	16	33	2.1	23.7
	With NC	10	31	3.1	34.1
	2006-07	6	12	2.0	22.2
	2008-11	10	21	2.1	24.7

Source: staff calculations, based on a sample of 18 countries.

View Table

Table 3.

Non-Core Conditionality in Case Studies

		Number of programs	Non Core measures
			Total	Per program	% of conditions
All programs		26	41	1.6	20.7
With Non-Core (NC)		14	39	2.8	32.8
GRA
	All	10	8	0.8	13.6
	With NC	4	8	2.0	28.6
	2006-07	0	0	0.0	0.0
	2008-11	10	8	0.8	13.6
PRGF, ECF, PSI
	All	16	33	2.1	23.7
	With NC	10	31	3.1	34.1
	2006-07	6	12	2.0	22.2
	2008-11	10	21	2.1	24.7

Source: staff calculations, based on a sample of 18 countries.

55. Most reviewed staff reports presented the implementation risks well. Nearly 90 percent of staff reports provided a discussion of the implementation risks in a broad sense, with many also providing details about the risks for individual measures. For example, Hungary’s request for an SBA provided considerable detail about the potential risks, in terms of the domestic political situation and the external environment. Capacity constraints can present implementation risks, mitigated by a slow start up and careful pacing of the structural agenda (2008 Togo and 2006 Sierra Leone).

56. The recent European programs have usually been successful at distinguishing between Fund conditionality and other elements of the authorities’ program. In the case studies, staff reports for the Hungary and Greece programs clearly outlined the framework for cooperation between the EU and the Fund (e.g., Box 1 in the Hungary staff report), and separated Fund conditions from those set by other organizations, allowing for a clear identification of program-related conditionality. By contrast, in Iceland it was not initially clear to the public that the requirement to compensate for losses of foreign depositors was not set by the Fund.

57. The reviewed staff reports contained little information on discussions of policy options. Only a quarter of the case studies contained any record of a discussion between the staff and the authorities on the policy options considered. Survey results suggested broad satisfaction from country authorities and staff that policy options and implementation plans were being discussed, suggesting that the issue is that discussions of policy options were not being recorded in the program documents, as per the guidance (Figure 20).

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Policy Options - Survey Results

During program discussions, Fund staff provided a sufficient range of policy options and implementation plans.

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

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A. Program Interruptions

59. Program performance can be partly assessed by considering how often program interruptions were temporary or long lasting. Programs fall “off-track” when implementation is not satisfactory and agreement on corrective actions is not reached. In this paper, programs are considered to be off-track when the time elapsed between two reviews (or between the Board date and the first review) was larger than twice the planned time between reviews, i.e. more than six months for quarterly programs, and more than one year for semi-annual programs. An interruption is considered temporary when an off-track period was followed by a review that brought the program back on track. Interruptions are long lasting when a program went off-track for more than 12 months, and no review subsequently takes place before the program lapses.

60. Delays in completing reviews were infrequent. During 2002-end-September 2011, the average share of off-track programs hovered around 15 percent. Long-lasting program interruptions accounted for about 6 percent of the sample. By contrast, about 60 percent of the programs in the sample experienced no off-track period.

61. After declining earlier in the 2000s, program interruptions have become more frequent since the start of the global financial crisis (Figure 21). Overall implementation weakened progressively between 2009 and 2011 in PRGT programs, while deterioration was notable for GRA programs in 2011. Cases of off-track PSIs have been exceptional, with only one case recorded since the instrument was created (Uganda).

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Program Interruptions By Year of Review, 2002-2011

On-track and off-track programs, in percent of total

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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62. While interruptions have become more frequent, the average length of interruption has declined since 2007 (Figure 22). In PRGT programs, off-track periods amounted to about 10 percent of total program periods over 2002-2007, a proportion that fell significantly after 2007. Improvement was also observed for GRA programs. The improved record will need to be confirmed once those programs have been completed.

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Average Duration of Off-Track Periods

By year of program approval, 2002-2011 (In percent of program duration)

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.

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B. Implementation of Conditionality

63. Implementation of conditionality improved over most of the review period (Figure 23).⁴⁴ The implementation of QPCs outperformed that of structural measures in both GRA and PRGT programs, with more even and generally better implementation in PRGT programs. Implementation of structural conditionality was consistently better for SBs than for SPCs, and the discontinuation of SPCs does not seem to have affected the implementation record of structural conditionality, which remained broadly unchanged in 2010.⁴⁵ However, implementation deteriorated in 2011. In GRA programs, this worsening reflects an increase in the frequency of programs with at least one non-implemented SB. By contrast, the proportion of PRGT programs with at least one non-implemented SB has remained stable, while the average number of SBs that were not met at the time of the review increased. In both cases, these developments reflect more difficult program implementation conditions. The implementation of structural benchmarks was generally better in core Fund areas.

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Implementation of Program Conditionality¹

Implementation ratio

Citation: Policy Papers 2012, 045; 10.5089/9781498340380.007.A001

Source: MONA and staff calculations.¹ Excludes prior actions, which are always implemented. PRGT programs include PSIs. The implementation ratio is a weighted average of assessed conditions, whereby a weight of 2 is assigned to fully met conditions, a weight of 1 to partially met conditions and conditions met with delay, and a weight of zero to not met or waived conditions.

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64. Improvements in implementation were not limited to strong-performing countries, although progress in relatively poor performers was sometimes uneven. In general, countries with a good track record in the previous review tend to have better implementation (Table 4). Nevertheless, in both GRA and PRGT programs, the implementation rate of structural conditionality generally improved at a similar pace for the average of the sample, the median, and the bottom quartile, highlighting across-the-board progress in program implementation.

Table 4.

Track Record and Implementation¹

Source: MONA and staff calculations.

¹Panel probit relating the probability of a 100 percent implementation of conditionality to the implementation ratio at the previous review.

^***and ** refer to a 1 and 5 percent significance level, respectively.

Table 4.

Track Record and Implementation¹

	GRA	PRGT
Structural conditionality	-0.99	1.01**
Quantitative conditionality	2.16***	1.77**

Source: MONA and staff calculations.

¹Panel probit relating the probability of a 100 percent implementation of conditionality to the implementation ratio at the previous review.

^***and ** refer to a 1 and 5 percent significance level, respectively.

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Table 4.

Track Record and Implementation¹

	GRA	PRGT
Structural conditionality	-0.99	1.01**
Quantitative conditionality	2.16***	1.77**

Source: MONA and staff calculations.

¹Panel probit relating the probability of a 100 percent implementation of conditionality to the implementation ratio at the previous review.

^***and ** refer to a 1 and 5 percent significance level, respectively.

65. Flexible timelines for program reviews have enhanced implementation. In the majority of cases, flexibility was not required, as most structural conditions were implemented as scheduled. Nevertheless, accommodating delays in the implementation of structural conditionality was helpful in ensuring that agreed reforms were implemented, as about 50 percent of measures that were reset for a future date were eventually met (Table 5).⁴⁶

Table 5.

Flexibility in the Timeline and Implementation Record

Status of implementation of structural conditions, 2002-2011

Source: MONA and staff calculations.

Table 5.

Flexibility in the Timeline and Implementation Record

Status of implementation of structural conditions, 2002-2011

	On the initially scheduled test date	On the rescheduled test date (when rescheduled)
Share of conditions (in percent)
Met	74	49
Not met	15	23
Pending	11	27
	100	100

Source: MONA and staff calculations.

View Table

Table 5.

Flexibility in the Timeline and Implementation Record

Status of implementation of structural conditions, 2002-2011

	On the initially scheduled test date	On the rescheduled test date (when rescheduled)
Share of conditions (in percent)
Met	74	49
Not met	15	23
Pending	11	27
	100	100

Source: MONA and staff calculations.

66. Implementation was supported by parsimony and not impaired by deeper structural conditionality (Table 6). A panel regression of the implementation ratio against the number of conditions (by review) showed that a larger number of conditions in a given review tended to have a negative correlation with overall implementation. However, implementation appeared to be unrelated to the depth of conditionality, pointing to the importance of other determinants—such as capacity or ownership. In particular, the combination of low capacity and a large number of conditions was linked to worse implementation (Table 6, last column).

Table 6.

Determinants of Implementation by Review, 2006-2011

Panel data estimate¹

Source: MONA and staff calculations.

¹Excludes prior actions at Board approval. t-statistics in parentheses;

^*p<0.1,

^**p<0.05,

^***p<0.01

Table 6.

Determinants of Implementation by Review, 2006-2011

Panel data estimate¹

	All programs	GRA	PRGT
	(1)	(2)	(3)	(4)
Number of conditions	-0.018***	-0.019**	-0.015**	-
Number of conditions χ CPIA	-	-	-	-0.004*
Constant	0.778***	0.782***	0.728***	0.705***
Review fixed effects	Yes	Yes	Yes	Yes
N	295	110	185	111
R-squared (within)	0.10	0.18	0.09	0.01

Source: MONA and staff calculations.

¹Excludes prior actions at Board approval. t-statistics in parentheses;

^*p<0.1,

^**p<0.05,

^***p<0.01

View Table

Table 6.

Determinants of Implementation by Review, 2006-2011

Panel data estimate¹

	All programs	GRA	PRGT
	(1)	(2)	(3)	(4)
Number of conditions	-0.018***	-0.019**	-0.015**	-
Number of conditions χ CPIA	-	-	-	-0.004*
Constant	0.778***	0.782***	0.728***	0.705***
Review fixed effects	Yes	Yes	Yes	Yes
N	295	110	185	111
R-squared (within)	0.10	0.18	0.09	0.01

Source: MONA and staff calculations.

¹Excludes prior actions at Board approval. t-statistics in parentheses;

^*p<0.1,

^**p<0.05,

^***p<0.01

67. In programs facing implementation challenges, PAs provided limited support for program execution. PAs ensure that some critical structural measures are implemented by the time of program approval or review. Econometric analysis confirmed that programs with lower implementation ratios faced a higher probability of having a PA at the current or next review. However, a higher number of PAs did not necessarily translate into improved overall implementation, suggesting that the effect of PAs on program execution was limited (Box 8).