A. Measuring Program Implementation

We analyzed the implementation of 170 IMF-supported programs approved between 1992 and 1998 (Table 1). The choice of the time period was determined by the availability of information on conditionality in the MONA database⁴ and the difficulty in assessing programs approved after 1998, some of which are still ongoing. The largest collection of programs (about 48 percent of the total) in the sample were Stand-By Arrangements (SBAs). The second largest group of programs (38 percent) were programs under concessional facilities,⁵ followed by programs under the Extended Fund Facility (EFF)(15 percent).

^{Table 1.}

Program^*Implementation by Type of Arrangement

^*Multiyear arrangements are treated as one program. This is a sample of programs approved between 1992 and 1998 and available from MONA database (our sample is missing 16 SBAs, one ESAF, and one EPF program approved in 1992). The sample of EFF programs is quite small to make reliable conclusions regarding relative performance of EFF compared to ESAF and SBA programs.

^1/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than six months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were canceled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^2/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

^3/The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

^4/The Structural Implementation Index for a given structural condition is equal to 100 percent if structural condition was met or met with small delay for structural benchmarks; it is equal to 50 percent if structural condition was partially met or delayed for performance criteria and it is equal to zero if structural condition was not met. The Structural Implementation Index for a program then is computed as the average of Structural Implementation Indices across all structural conditions for this program.

^5/The Average Overall Implementation Index for a given program is the average of Macro and Structural Implementation indices over all conditions in this program.

^6/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^7/Sample size for implementation indices was smaller (150 programs), which corresponds to the sample constructed for “Structural Conditionality in Fund-Supported Programs,” we simply extended structural index used in this paper to macro and overall implementation indices

^8/The average share of disbursed funds was computed across the sample of programs excluding precautionary arrangements (on approval and turned into precautionary) as well as canceled and ongoing programs.

^{Table 1.}

Program^*Implementation by Type of Arrangement

Type of Arrangement	Number of Programs*	Number of Programs*excluding precautionary arrangements as well as cancelled and on-going programs 8/	Share of programs having Interruptions1/ 6/	Share of programs having Irreversible Interruptions 2/ 6/	Average Macro Implementation Index 3/ 6/ 7/	Average Structural Implementation Index 4/ 6/ 7/	Average Overall Implementation Index 5/ 6/ 7/	Average Share of Committed Funds Disbursed 8/
			(In percent)
EFF	25	13	68	40	87.0	75.4	83.3	72.1
PRGF/ESAF	64	51	73.4	45.3	77.1	71.3	72.9	77.2
SBA	81	41	67.9	43.2	81.0	60.8	76.0	63.7
Total	170	105	70.0	43.5	80.3	67.4	75.8	71.3

^*Multiyear arrangements are treated as one program. This is a sample of programs approved between 1992 and 1998 and available from MONA database (our sample is missing 16 SBAs, one ESAF, and one EPF program approved in 1992). The sample of EFF programs is quite small to make reliable conclusions regarding relative performance of EFF compared to ESAF and SBA programs.

^1/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than six months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were canceled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^2/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

^3/The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

^4/The Structural Implementation Index for a given structural condition is equal to 100 percent if structural condition was met or met with small delay for structural benchmarks; it is equal to 50 percent if structural condition was partially met or delayed for performance criteria and it is equal to zero if structural condition was not met. The Structural Implementation Index for a program then is computed as the average of Structural Implementation Indices across all structural conditions for this program.

^5/The Average Overall Implementation Index for a given program is the average of Macro and Structural Implementation indices over all conditions in this program.

^6/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^7/Sample size for implementation indices was smaller (150 programs), which corresponds to the sample constructed for “Structural Conditionality in Fund-Supported Programs,” we simply extended structural index used in this paper to macro and overall implementation indices

^8/The average share of disbursed funds was computed across the sample of programs excluding precautionary arrangements (on approval and turned into precautionary) as well as canceled and ongoing programs.

View Table

^{Table 1.}

Program^*Implementation by Type of Arrangement

Type of Arrangement	Number of Programs*	Number of Programs*excluding precautionary arrangements as well as cancelled and on-going programs 8/	Share of programs having Interruptions1/ 6/	Share of programs having Irreversible Interruptions 2/ 6/	Average Macro Implementation Index 3/ 6/ 7/	Average Structural Implementation Index 4/ 6/ 7/	Average Overall Implementation Index 5/ 6/ 7/	Average Share of Committed Funds Disbursed 8/
			(In percent)
EFF	25	13	68	40	87.0	75.4	83.3	72.1
PRGF/ESAF	64	51	73.4	45.3	77.1	71.3	72.9	77.2
SBA	81	41	67.9	43.2	81.0	60.8	76.0	63.7
Total	170	105	70.0	43.5	80.3	67.4	75.8	71.3

^*Multiyear arrangements are treated as one program. This is a sample of programs approved between 1992 and 1998 and available from MONA database (our sample is missing 16 SBAs, one ESAF, and one EPF program approved in 1992). The sample of EFF programs is quite small to make reliable conclusions regarding relative performance of EFF compared to ESAF and SBA programs.

^1/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than six months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were canceled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^2/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

^3/The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

The Macro Implementation Index for a given macro performance criterion is equal to 100 percent if macro performance criterion was met or met after modification and it is equal to zero if macro performance criterion was not met after modification, waived, or waived after modification. The Macro Implementation Index for a program then is computed as the average of Macro Implementation Indices across all macro performance criteria for this program.

^4/The Structural Implementation Index for a given structural condition is equal to 100 percent if structural condition was met or met with small delay for structural benchmarks; it is equal to 50 percent if structural condition was partially met or delayed for performance criteria and it is equal to zero if structural condition was not met. The Structural Implementation Index for a program then is computed as the average of Structural Implementation Indices across all structural conditions for this program.

^5/The Average Overall Implementation Index for a given program is the average of Macro and Structural Implementation indices over all conditions in this program.

^6/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^7/Sample size for implementation indices was smaller (150 programs), which corresponds to the sample constructed for “Structural Conditionality in Fund-Supported Programs,” we simply extended structural index used in this paper to macro and overall implementation indices

^8/The average share of disbursed funds was computed across the sample of programs excluding precautionary arrangements (on approval and turned into precautionary) as well as canceled and ongoing programs.

IMF-supported programs are complex in nature, making it difficult to arrive at a single metric of program success. In general, a program is considered to be successful if its principal macroeconomic and structural objectives are met, including the restoration of a sustainable balance of payments and a sustainable high rate of growth with low inflation. Lacking a single indicator of success for IMF-supported programs, such as the one produced by the World Bank’s Operations Evaluation Department for Bank-supported programs, in this paper we focus on the narrower issue of successful implementation of program conditionality which is a prerequisite for overall program success.

Our strategy was to construct multiple measures of implementation for each program in our sample. These measures capture essential features of program performance from different angles, using information available in MONA, data from International Financial Statistics, and program documents. ⁶Viewed from this narrower perspective, program implementation depends on the extent to which the program was completed without undue delays—whether it was interrupted—and on whether its macroeconomic and structural conditionality was met. The extent to which funds committed by the IMF under the program were disbursed is another indicator of program progress, one that is traditionally used in the literature.

Our first indicator of program implementation is a binary variable measuring program interruptions. This variable captures both major and minor interruptions and is motivated by Mecagni’s work. We say that an interruption occurred if an SBA review was delayed by more than three months or not completed at all; if a program review for EFF/PRGFs was delayed by more than six months or not completed at all; if there was an interval of more than six months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved.⁷,⁸ The second indicator is a binary variable identifying irreversible program interruptions. This measure captures programs that went off track and were not revived subsequently (i.e., were either canceled or were allowed to lapse because of policy slippages). More precisely, we say that an irreversible interruption occurred if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements). Third, we constructed a quantitative indicator of implementation of IMF conditionality, the overall implementation index, which represents the average fraction of macro and structural conditionality implemented. This indicator is an extension of the structural conditionality index developed in the IMF’s Policy Development and Review Department during the 2000-02 review of conditionality (IMF 2001c). Finally, we also computed the ratio of disbursements to commitments. The last two indicators are continuous variables that take values between zero and 100.

Each of our four indices captures an important dimension of program implementation. The macro and structural implementation indices provide quantitative information on implementation rates by type of condition. Their main drawback is that they overstate the degree of implementation because, as is well known, MONA fails to capture information on interrupted programs that were not subject to further Board reviews.⁹ The interruption dummies, which are based on MONA data and additional information from program documents, complement the macro and structural implementation indices by capturing significant program stoppages. The share of disbursed funds provides useful information on the proportion of approved assistance actually delivered for nonprecautionary arrangements and also on the actual duration of the program compared to the scheduled one. The implementation indices and interruption dummies provide useful information about precautionary programs, canceled programs, and some unusual cases where no drawings were made despite good results.

B. Descriptive Statistics

Table 1 summarizes program implementation by type of arrangement. About 44 percent of all programs experienced an irreversible interruption, while 70 percent of all programs experienced either a major or a minor interruption. Nonetheless, approximately 71 percent of committed funds were disbursed on average (excluding precautionary arrangements, cancelled and ongoing programs). The average implementation index for programs for which information is available in MONA is 76 percent. The macro implementation index is significantly higher (80 percent) than the structural implementation index (67 percent). However, implementation indices most likely overstate program performance. MONA collects data only for program test dates subject to Board approval or review. Information on later stages of some programs experiencing major interruptions is, therefore, not available. Although implementation indices do not change much over time (Figure 1), two clear peaks in irreversible interruptions are visible, corresponding to programs approved in 1994 and 1996, and two troughs in the share of disbursed funds for the same years. These are attributable to the financial crises of the mid- and late 1990s.

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Implementation of Fund Programs over Time

Citation: IMF Working Papers 2003, 008; 10.5089/9781451842531.001.A001

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The four measures of program implementation are significantly mutually correlated (Table 2).¹⁰ However, the correlation coefficients are not very high in most cases, reflecting the fact that the various implementation measures capture quite different angles of program performance. The correlation coefficient between the macro and structural implementation index is only 0.2. This is consistent with the recent finding by Buliř and Moon that the implementation of fiscal measures in IMF-supported programs was not strongly correlated with the implementation of structural measures.

^{Table 2.}

Correlations of Implementation Indices (excluding arrangements precautionary on approval)^*

Note: In brackets is 2-tailed significance level. Significant at 0.05 level are in bold.

^*Multiyear arrangements are treated as one program. These programs were approved between 1992 and 1998 and are taken from the MONA database.

^1/The Macro Implementation Index is equal to 100 percent if macro performance criteria were met or were met after modification and it is equal to zero if macro performance criteria were not met, after modification, waived, or waived after modification.

^2/The Structural Implementation Index is equal to 100 percent if structural criteria were met or met with small delay for structural benchmarks; it is equal to 50 percent if structural criteria were partially met or delayed for performance criteria and it is equal to zero if structural criteria were not met.

^3/The Average Overall Implementation Index is the average of macro and structural implementation indices over all conditions for a given program.

^4/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which IMF Executive Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^5/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than 6 months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were cancelled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^6/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

^{Table 2.}

Correlations of Implementation Indices (excluding arrangements precautionary on approval)^*

Pearson Correlation	Average Macro Implementation Index 1/ 4/	Average Structural Implementation Index 2/ 4/	Average Overall Implementation Index 3/ 4/	Interruption Index 5/	Irreversible Interruption Index 6/	Average Share of Committed Funds Disbursed
Average Macro Implementation Index 1/ 4/	1.000
Average Structural Implementation Index 2/ 4/	0.211	1.000
	(0.01)
Average Overall Implementation Index 3/ 4/	0.782	0.653	1.00
	(0.00)	(0.00)
Interruption Index 5/	−0.286	−0.050	−0.30	1.00
	(0.00)	(0.56)	(0.00)
Irreversible Interruption Index 6/	−0.263	−0.279	−0.39	0.55	1.00
	(0.00)	(0.00)	(0.00)	(0.00)
Average Share of Committed Funds Disbursed	0.211	0.346	0.38	−0.42	−0.75	1.00
	(0.01)	(0.00)	(0.00)	(0.00)	(0.00)

Note: In brackets is 2-tailed significance level. Significant at 0.05 level are in bold.

^*Multiyear arrangements are treated as one program. These programs were approved between 1992 and 1998 and are taken from the MONA database.

^1/The Macro Implementation Index is equal to 100 percent if macro performance criteria were met or were met after modification and it is equal to zero if macro performance criteria were not met, after modification, waived, or waived after modification.

^2/The Structural Implementation Index is equal to 100 percent if structural criteria were met or met with small delay for structural benchmarks; it is equal to 50 percent if structural criteria were partially met or delayed for performance criteria and it is equal to zero if structural criteria were not met.

^3/The Average Overall Implementation Index is the average of macro and structural implementation indices over all conditions for a given program.

^4/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which IMF Executive Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^5/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than 6 months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were cancelled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^6/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

View Table

^{Table 2.}

Correlations of Implementation Indices (excluding arrangements precautionary on approval)^*

Pearson Correlation	Average Macro Implementation Index 1/ 4/	Average Structural Implementation Index 2/ 4/	Average Overall Implementation Index 3/ 4/	Interruption Index 5/	Irreversible Interruption Index 6/	Average Share of Committed Funds Disbursed
Average Macro Implementation Index 1/ 4/	1.000
Average Structural Implementation Index 2/ 4/	0.211	1.000
	(0.01)
Average Overall Implementation Index 3/ 4/	0.782	0.653	1.00
	(0.00)	(0.00)
Interruption Index 5/	−0.286	−0.050	−0.30	1.00
	(0.00)	(0.56)	(0.00)
Irreversible Interruption Index 6/	−0.263	−0.279	−0.39	0.55	1.00
	(0.00)	(0.00)	(0.00)	(0.00)
Average Share of Committed Funds Disbursed	0.211	0.346	0.38	−0.42	−0.75	1.00
	(0.01)	(0.00)	(0.00)	(0.00)	(0.00)

Note: In brackets is 2-tailed significance level. Significant at 0.05 level are in bold.

^*Multiyear arrangements are treated as one program. These programs were approved between 1992 and 1998 and are taken from the MONA database.

^1/The Macro Implementation Index is equal to 100 percent if macro performance criteria were met or were met after modification and it is equal to zero if macro performance criteria were not met, after modification, waived, or waived after modification.

^2/The Structural Implementation Index is equal to 100 percent if structural criteria were met or met with small delay for structural benchmarks; it is equal to 50 percent if structural criteria were partially met or delayed for performance criteria and it is equal to zero if structural criteria were not met.

^3/The Average Overall Implementation Index is the average of macro and structural implementation indices over all conditions for a given program.

^4/The Macro and Structural implementation indices were computed from information available in MONA. Since MONA questionnaires are sent only for programs for which IMF Executive Board meetings are scheduled, implementation information is missing on many conditions for programs with noncompleted reviews. Since these were typically unsuccessful programs, the macro and structural indices may overstate program implementation. Interruption indices were constructed using additional information from country documents and other sources.

^5/An interruption occurs if an SBA program review was delayed by more than three months or not completed at all; if a program review for ESAF/PRGF programs was delayed by more than six months or not completed at all; if there was an interval of more than 6 months between two subsequent years of a multiyear arrangement; or if at least one of the annual arrangements was not approved (exceptions are programs which were cancelled and replaced by another program, in which case noncompleted reviews and nonapproved annual arrangements are not counted as interruptions).

^6/An irreversible interruption occurs if either: (i) the last scheduled program review was not completed (all programs); or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved (ESAF/PRGF arrangements).

Several differences stand out between implemented and interrupted programs (Table 3). First, countries that implemented their IMF-supported reform programs were experiencing much higher inflation at the start of the program than countries whose programs were interrupted. Although the difference in inflation rates was not statistically significant in the year in which the program was approved, inflation was significantly higher in implemented programs one year before the program started. Countries that implemented their programs started with substantially smaller budget deficits (2 ½ percent of GDP on average) as compared to countries in which programs were interrupted (4 ¾ percent of GDP on average). Terms of trade shocks were stronger in countries with interrupted programs. The strength of special interests was higher, and the degree of political cohesion was lower, in countries whose programs were interrupted. Interestingly, the effort invested by the IMF and the extent and structure of conditionality are similar in interrupted and implemented programs.

^{Table 3.}

Features of Successful and Failed Fund programs

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level.

^*The null hypothesis is stated as follows: Ho: mean (successful) - mean (failed)=0. The alternative hypothesis was different for different cases. In case when the means were significantly different we report t-statistics for the relevant one-sided alternative hypothesis (for example, for the index of political cohesion we report statistics for the null hypothesis as specified above versus alternative that the degree of political cohesion is higher for successful than for failed programs, which in fact, cannot be rejected at 5 percent significance level), otherwise we report t-statistics for alternative hypothesis that the difference in means is not equal to zero.

^** Although the average inflation rate in approval year was not significantly different for successful and failed programs in the year preceding approval year average inflation rate for successful programs was significantly higher than for unsuccessful ones

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one I if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding in more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified: religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. “We also made use of the dollar costs of resident representatives provided by OPM.

^7/Reserves here do not include gold.

^8/Average growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

^{Table 3.}

Features of Successful and Failed Fund programs

	Successful		Failed		t-test for the equality of means*
Political Economy Characteristics	Average	Number of Programs	Average	Number of Programs	t-statistics	p-value
Ethnic Fractionalization	46	58	51	50	−0.86	0.39
Political Instability 1/	4.75	67	5.68	57	−1.16	0.25
Executive Index of Electoral Competitiveness (in percent) 2/	62	86	56	66	0.69	0.49
Time in Power (years)	5.73	86	4.52	66	1.00	0.32
Strength of Special Interests 3/	16	66	25	54	−1.74	0.04
Index of Political Cohesion 4/	2.36	85	2.06	66	2.45	0.01
Quality of Bureaucracy 5/	1.72	67	1.81	57	−0.68	0.5
Change in Chief Executive (=1 if there was change in chief executive in the course of the program)	18.18	99	28.38	74	−1.59	0.11
Variables under Fund Control
Fund Effort per Program Year (in millions of US$) 6/	1.01	99	1.03	68	0.13	0.9
Total Number of Conditions per Program Year	40	95	38	65	0.48	0.63
Share of Quantitative PCs Waived (percent)	8.33	99	7.22	73	0.6	0.55
Share of Structural Conditions (percent)	37	95	40	68	−0,74	0.46
Loan Size (agreed amount in millions of SDRs)	620	95	526	69	0.3	0.76
Macro Characteristics
Initial GDP per capita per year (US dollars)	1434	98	1291	74	0.81	0.42
Initial Debt to the Fund (actual holdings as percent quota)	177	99	159	74	1.16	0.25
initial Central Government balance (in percent of GDP)	−2.5	88	−4.74	68	3.7	0
Reserve holdings (as percent of imports) 7/	36.72	81	32.98	68	0.85	0.4
Initial Inflation (percent per annum)	80	98	53	74	0.89**	0.37
Initial Current Account Balance (in percent of GDP)	−5.32	98	−5.87	74	0.42	0.67
Terms of Trade Shock (growth rate during the program period in percent) 8/	−90	98	−15	74	−1.30	0.10

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level.

^*The null hypothesis is stated as follows: Ho: mean (successful) - mean (failed)=0. The alternative hypothesis was different for different cases. In case when the means were significantly different we report t-statistics for the relevant one-sided alternative hypothesis (for example, for the index of political cohesion we report statistics for the null hypothesis as specified above versus alternative that the degree of political cohesion is higher for successful than for failed programs, which in fact, cannot be rejected at 5 percent significance level), otherwise we report t-statistics for alternative hypothesis that the difference in means is not equal to zero.

^** Although the average inflation rate in approval year was not significantly different for successful and failed programs in the year preceding approval year average inflation rate for successful programs was significantly higher than for unsuccessful ones

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one I if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding in more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified: religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. “We also made use of the dollar costs of resident representatives provided by OPM.

^7/Reserves here do not include gold.

^8/Average growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

View Table

^{Table 3.}

Features of Successful and Failed Fund programs

	Successful		Failed		t-test for the equality of means*
Political Economy Characteristics	Average	Number of Programs	Average	Number of Programs	t-statistics	p-value
Ethnic Fractionalization	46	58	51	50	−0.86	0.39
Political Instability 1/	4.75	67	5.68	57	−1.16	0.25
Executive Index of Electoral Competitiveness (in percent) 2/	62	86	56	66	0.69	0.49
Time in Power (years)	5.73	86	4.52	66	1.00	0.32
Strength of Special Interests 3/	16	66	25	54	−1.74	0.04
Index of Political Cohesion 4/	2.36	85	2.06	66	2.45	0.01
Quality of Bureaucracy 5/	1.72	67	1.81	57	−0.68	0.5
Change in Chief Executive (=1 if there was change in chief executive in the course of the program)	18.18	99	28.38	74	−1.59	0.11
Variables under Fund Control
Fund Effort per Program Year (in millions of US$) 6/	1.01	99	1.03	68	0.13	0.9
Total Number of Conditions per Program Year	40	95	38	65	0.48	0.63
Share of Quantitative PCs Waived (percent)	8.33	99	7.22	73	0.6	0.55
Share of Structural Conditions (percent)	37	95	40	68	−0,74	0.46
Loan Size (agreed amount in millions of SDRs)	620	95	526	69	0.3	0.76
Macro Characteristics
Initial GDP per capita per year (US dollars)	1434	98	1291	74	0.81	0.42
Initial Debt to the Fund (actual holdings as percent quota)	177	99	159	74	1.16	0.25
initial Central Government balance (in percent of GDP)	−2.5	88	−4.74	68	3.7	0
Reserve holdings (as percent of imports) 7/	36.72	81	32.98	68	0.85	0.4
Initial Inflation (percent per annum)	80	98	53	74	0.89**	0.37
Initial Current Account Balance (in percent of GDP)	−5.32	98	−5.87	74	0.42	0.67
Terms of Trade Shock (growth rate during the program period in percent) 8/	−90	98	−15	74	−1.30	0.10

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level.

^*The null hypothesis is stated as follows: Ho: mean (successful) - mean (failed)=0. The alternative hypothesis was different for different cases. In case when the means were significantly different we report t-statistics for the relevant one-sided alternative hypothesis (for example, for the index of political cohesion we report statistics for the null hypothesis as specified above versus alternative that the degree of political cohesion is higher for successful than for failed programs, which in fact, cannot be rejected at 5 percent significance level), otherwise we report t-statistics for alternative hypothesis that the difference in means is not equal to zero.

^** Although the average inflation rate in approval year was not significantly different for successful and failed programs in the year preceding approval year average inflation rate for successful programs was significantly higher than for unsuccessful ones

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one I if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding in more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified: religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. “We also made use of the dollar costs of resident representatives provided by OPM.

^7/Reserves here do not include gold.

^8/Average growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

C. Correlation of Implementation Measures with Macroeconomic Performance

IMF-supported programs aim to strengthen the borrowing countries’ balance of payments and overall macroeconomic performance. This section presents a preliminary assessment of whether program implementation improves macroeconomic performance, both over the course of programs and after their expiration.

Figures 2-4 show how the main macroeconomic magnitudes evolved in uninterrupted and interrupted programs from the year at which the program was approved until three years after the program ended. The variables plotted are the average changes in inflation, the ratio of reserves to imports, and real GDP growth. The eye-ball test (Figure 2) indicates that inflation for both implemented and interrupted programs continued to decline after the program ended, but the reduction in inflation (compared to the approval year) was greater for implemented than for interrupted programs. Uninterrupted programs started with significantly higher inflation as measured one year before the approval year. However this difference was significant only for the end year of the program as indicated by solid dots on the graph. The average level of inflation itself in the end year was also significantly lower for uninterrupted than for interrupted programs but was not significantly different in later years. The high variability of inflation in the data contributed to the differences in the changes in inflation being indistinguishable for implemented and interrupted programs in later years.

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Inflation Dynamics for Successful and Unsuccessful Fund programs after the Program End

Citation: IMF Working Papers 2003, 008; 10.5089/9781451842531.001.A001

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Reserves to Imports Dynamics for Successful and Unsuccessful Fund Programs after the Program End

Citation: IMF Working Papers 2003, 008; 10.5089/9781451842531.001.A001

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Real GDP Growth Dynamics for Successful and Unsuccessful Fund Programs.

Citation: IMF Working Papers 2003, 008; 10.5089/9781451842531.001.A001

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Completed programs were associated with better performance, at least as far as the evolution of the reserve coverage of imports (Figure 3). Reserves in relation to imports experienced significantly higher growth in uninterrupted programs than in interrupted ones when the year after the program ended is compared with the year in which the program was approved. Changes in the reserve cover of imports were also significantly and positively correlated with the share of disbursed funds and, in one case, with the noninterruption dummy. However, the correlation of the reserves-to-import ratio with the overall implementation index took the “wrong” sign (it was negative) although insignificant in almost all cases.

Countries that completed their IMF-supported programs started with deeper recessions (more negative GDP growth rates) but grew faster than countries where programs were interrupted, both right after the programs expired and for a couple of years after that (Figure 4). However, these differences in growth rates were not statistically significant. Once initial GDP and inflation are controlled for, only the overall implementation index was significantly positively correlated with growth in the program’s end year.

What, then, is the association between program implementation and macroeconomic performance? Although not especially strong in our sample, these results provide some evidence that countries that complete their IMF-supported programs also manage, on average, to reduce inflation, increase their relative reserve holdings, gain export competitiveness, and accelerate growth by more than countries where programs are interrupted. These results are generally consistent with those of the literature: program implementation helps countries strengthen their current account, external reserves, and balance of payments.¹¹ Economic growth, which is depressed in the short run as program reforms begin to “bite,” also improves eventually. One noteworthy difference with previous studies concerns inflation performance. Whereas previous studies generally have been inconclusive regarding the impact of IMF-supported programs on inflation, inflation performance improves with program implementation in our sample.¹²

A. Model Specification

We identify three major groups of factors that might affect the prospects of successful implementation of IMF-supported programs. These are political economy variables, variables describing the IMF’s behavior, and initial and external conditions.

On the political economy side, we collected data from various sources, namely, the Political Institutions Database at the World Bank (Beck et al., 2001), the International Country Risk Guide (ICRG), the Polity IV dataset and the CIA World Factbook. The main hypothesis that emerges from the theoretical model presented in a companion paper (Mayer and Mourmouras 2002) is that the implementation of reforms is affected by the strength of special interest groups in countries using IMF resources. In practice, it is difficult to identify and measure the strength of organized lobbies. To develop a suitable measure of the strength of special interests, we relied on the observation that in many countries political parties represented in government or the legislature (or both) sometimes represent specific interests. Legislatures are crucial players in policymaking: legislative approval is required for successful implementation of almost all key reforms.¹³ While many different organized interest groups can and do block reforms, special interest groups in parliament seem a natural candidate.

The Political Institutions Database (Beck et al., 2001) identifies four groups of parties in parliament that represent nationalistic, rural, regional, and religious special interests. Key components of the platforms of these parties are the creation or defense of a national or ethnic identity and of rural, regional, or religious issues. Sometimes, nationalistic special interests have persecuted minorities (nationalist special interests), with disastrous consequences for economic development. In any event, special interests in parliament influence government policy choices through the exercise of their political power and, perhaps, through monetary exchanges.

An important question is whether the interests of the political parties representing these interest groups run counter to the reform objectives of IMF-supported programs. While the motives of each of these four types of parliamentary groups are different, each is clearly committed to promoting the interests of only a segment of the population. As such, these parties are likely to support policies favored by the groups they represent even if they harm aggregate welfare. In short, special interests in the parliament serve as our proxy for special interest groups in the theoretical model. To test whether the presence of influential lobbies lowers the probability of successful program implementation we use the maximum share of seats in parliament held by parties that represent nationalistic, religious, rural, and regional interest groups as a measure of the strength of special interests.

Regarding the remaining political economy variables, we include political instability, ethnic fractionalization and ethnic fractionalization squared, political cohesion, and the interaction term of the quality of bureaucracy and the change in chief executive (see the Annex for more details on the definitions of the political variables and their sources). Program implementation might be jeopardized by political instability, which measures the degree of internal conflict and the extent of drastic political change, such as the installation of a new chief executive. Ethnic fractionalization may lead to tensions in society and is, therefore, a potential threat to reforms. Political cohesion emphasizes the heterogeneous nature of the government and the legislature. In countries with poor bureaucracies, changes in government tend to be traumatic as they are often accompanied by disruptions in policy formulation and day-to-day administrative functions, which can have a negative impact on program implementation. A high-quality bureaucracy has the strength and expertise to govern without drastic changes in policies and, therefore, can act as a shock absorber to reduce policy deviations from program goals when governments change. Since the importance of bureaucracy is more sharply felt in times of government change, we included only a term that interacts the strength of the bureaucracy with the dummy variable indicating a change in chief executive.¹⁴

To test how factors under the IMF’s control affect program implementation we included three major groups of factors in our regressions: (1) measures of IMF effort, (2) the extent of IMF financing, and (3) measures of the extent and structure of conditionality.

To test the hypothesis that more support from the IMF improves the prospects of programs we constructed three variables: (1) IMF effort, measured by the dollar cost of each program. This is based on (a) internal IMF data on staff hours allocated to Use of Fund Resources (UFR) work, which is program-related, and staff hours devoted to technical assistance and support tasks in member countries; (b) information on average staff salaries by grade; and (c) the costs of running the IMF’s resident representative offices in member countries with programs (data were provided by the IMF’s Office of Budget and Planning); (2) the number of IMF staff missions; and (3) the number of missions days.¹⁵

It has also been argued that the size of IMF loans may not be large enough to induce substantial changes in domestic policies. To test how the extent of IMF financing influences program implementation we included loan size as percent of quota in our regressions.

To analyze the impact of conditionality on program implementation we employed the following measures: (1) the number of conditions per program year, which measures the extent of overall conditionality; (2) the share of quantitative performance criteria waived, which measures the strength of enforcement and associated flexibility of conditionality; and (3) the share of structural conditions in the total number of conditions, which measures the weight programs put on structural reforms. As an alternative to the last measure we also included the number of structural conditions per program year in the regressions, to capture the extent of structural conditionality. As the results were unaffected, they are not reported separately.

Variables under the IMF’s control are endogenously determined. Hence, a list of appropriate instrumental variables (IVs) must be employed in order to glean the impact of IMF variables on the probability of successful implementation of IMF-supported programs. These instruments must be correlated with variables under the IMF’s control, be uncorrelated with the shocks hitting programs and not be direct determinants of program implementation. The choice of instruments is described in more detail in the box.

Another key issue is the impact of initial and external conditions and shocks on the implementation of IMF-supported programs. One possibility is that countries that start with unfavorable initial conditions or are hit by unfavorable shocks have a harder time meeting program targets. Alternatively, these countries could face stronger incentives to reform and might be more successful in implementing IMF-supported programs. A third possibility is that programs are designed and negotiated optimally, taking into consideration all the relevant factors, including initial conditions and the frequency, intensity and nature of economic and other shocks. If programs are tailored to the circumstances of each member country, differences in initial or external conditions and in exposure to shocks may not play a big role in program implementation.¹⁶ It turns out that it is not possible to distinguish empirically between these three possibilities. All we can say is that the data are consistent with the notion that initial and external conditions do not represent a major stumbling block for program implementation.

Variables included as initial conditions in our regressions were: the central government fiscal balance in relation to GDP; the current account balance in relation to GDP; the level of gross reserves at the start of the program; initial inflation; initial GDP per capita; and initial debt to the IMF in relation to a member’s IMF quota. To control for external conditions, we use the terms of trade shock, namely the difference between the growth rate of dollar export prices times the share of exports in GDP and the growth rate of dollar import prices times the share of imports in GDP.

B. Econometric Methodology

Our strategy is to relate the various indicators of implementation, either in isolation or in a pooled sample, to various right-hand side variables. These “explanatory” variables include observable characteristics of borrowing countries, such as initial conditions and features of their domestic political economy, and variables under the IMF’s control, as described in the previous section.

Our choice of econometric technique was guided by the need to make efficient use of the information contained in our implementation indicators and by data availability. One complication is that one of our indicators is a binary variable while the other two vary continuously, which makes it difficult to combine all three in a single model. Limited availability of political economy data is an additional consideration. Even though implementation measures are available for 170 programs, political economy variables are only available for about 60 programs. Crucially, some of the political economy data were not available for all former centrally planned economies.¹⁷ The limited sample also forced us to set aside problems of prolonged use of IMF resources. As some of the countries in the complete sample had multiple programs with the IMF, there is strong cross-sectional correlation between observations in the entire sample. As 56 percent of our working sample comprised countries with only one program, and only eight percent of countries in the sample had three or more programs (Table 4), it was not possible to apply a fixed effects model to our data.

^{Table 4.}

Distribution of Countries by the Number of Programs

^*/Original sample contained programs approved between 1992 and 1998 and available from MONA database; it is missing 16 SBAs, one ESAF and one EFF program approved in 1992

^**/Working sample comprised all list-wise nonmissing observations after we included our choice of political economy variables in the regression of noninterruption dummy (see Table 13).

^{Table 4.}

Distribution of Countries by the Number of Programs

Number of programs	In the Original* Sample			In the Working**Sample
	Number of countries	Percent of countries	Number of observations	Number of countries	Percent of countries	Number of observations
1	32	36.36	32	22	56.41	22
2	41	46.59	82	14	35.9	28
3	8	9.09	24	2	5.13	6
4	5	5.68	20	0	0.00	0
6	2	2.27	12	1	2.56	6
Total	88	100	170	39	100	62

^*/Original sample contained programs approved between 1992 and 1998 and available from MONA database; it is missing 16 SBAs, one ESAF and one EFF program approved in 1992

^**/Working sample comprised all list-wise nonmissing observations after we included our choice of political economy variables in the regression of noninterruption dummy (see Table 13).

View Table

^{Table 4.}

Distribution of Countries by the Number of Programs

Number of programs	In the Original* Sample			In the Working**Sample
	Number of countries	Percent of countries	Number of observations	Number of countries	Percent of countries	Number of observations
1	32	36.36	32	22	56.41	22
2	41	46.59	82	14	35.9	28
3	8	9.09	24	2	5.13	6
4	5	5.68	20	0	0.00	0
6	2	2.27	12	1	2.56	6
Total	88	100	170	39	100	62

^*/Original sample contained programs approved between 1992 and 1998 and available from MONA database; it is missing 16 SBAs, one ESAF and one EFF program approved in 1992

^**/Working sample comprised all list-wise nonmissing observations after we included our choice of political economy variables in the regression of noninterruption dummy (see Table 13).

Due to the small sample size, we estimate several specifications to check the robustness of our conclusions. Our approach is to first apply the Multiple Indicators and Multiple Causes (MIMIC)¹⁸ model (see Joreskog and Goldberger, 1975), which combines three implementation measures in one econometric model. We then reestimate models that feature each implementation measure separately using proper econometric techniques. Amemiya’s IV probit method is employed to estimate regressions where the left-hand side variable is a binary indicator. Amemiya’s IV tobit is used in regressions of the share of disbursed funds and the overall implementation index.

Formally, our model can be described as follows. If $y_i^{*}$ is the unobservable probability of successful program implementation, then

where P_i is a vector of country i political economy variables, F_i is a vector of variables under the IMF’s control, α_y, γ_y, and β_y are vectors of coefficients, and ε_yi is a stochastic disturbance term. The variables controlled by the IMF are given by

where α _F γ _F and λ _F are vectors of coefficients, ε _Fi is another error term, and Z _i is a vector of exogenous variables that are correlated with donor behavior but do not systematically influence the probability of success. Since the IMF responds to shocks hitting programs by adjusting its effort and conditionality, ε _yi and ε _Fi are correlated. We use IV techniques to obtain consistent estimates of the coefficients in equation (1).

Since we do not observe $y_i^{*}$ we cannot estimate equation (1) directly. However we have three indicators of success, which are correlated with $y_i^{*}$ . We can relate our observed measures of implementation to the unobserved probability of success as follows:

where y _i1 y _i2, and y _i3are our three implementation measures, and U _i1, U _i2, and U _i3are measurement errors which are possibly mutually correlated. Equations (l)-(5) represent a special case of MIMIC model analyzed in Joreskog and Goldberger (1975). In order to estimate this model, we first substitute equation (2) into (1) and (1) into (3)-(5) to obtain a system of equations which can be treated as seemingly unrelated regressions. This system can be estimated to obtain reduced form coefficients which we can use to recover the parameters γ _y and β _y . To calculate the variance of γ _y and β _y we employ the delta method. This approach requires normalization of one of the coefficients δ to one. Since the model is overidentified we also had to impose nonlinear constraints to obtain unique parameter estimates. Because of computational complexity we estimate the general form of the MIMIC model (l)-(5) including only one variable under the IMF’s control, namely, the IMF effort (Table 7).

A computationally convenient version of this model arises if the coefficients δ are all unity. In this case, substituting (1) into (3)-(5) and setting the δ’s to one we have:

The system (3’)-(5’) is a random effects model with random effect ε _yi . If IMF effort were not simultaneously determined with the success probability, then the random effect ε _yi would be uncorrelated with the set of regressors in F _i and be P _i . We could then obtain consistent estimates of this model by pooling the three implementation measures in one variable and regressing it on the same set of political economy and IMF effort variables for a particular program using the random effects estimator. However, since IMF effort is simultaneously determined with the probability of success, we apply the random effects IV estimator to obtain consistent estimates of the coefficients on political economy and IMF effort variables.

To summarize, we proceed as follows: we first estimate linear-in-probability and tobit regressions that combine three implementation measures in one model employing the random effects estimator (equations (3’)-(5’)). Two variants are examined, one that ignores the endogeneity of variables under the IMF’s control (Table 6) and another dealing with this endogeneity through IV techniques (Table 7). The set of IVs employed is specified in Table 5. Table 7 also reports a third, more general, version of the MIMIC model. This is specification (l)-(5) with only one endogenous variable, namely, IMF effort per program year (column 1, Table 7).¹⁹ We then reestimate our chosen specification of political economy variables with each of the implementation indices in isolation, not taking into account endogeneity of the variables under the IMF control (Table 8) and instrumenting for these variables (Tables 9-11).²⁰

^{Table 5.}

First-stage Regressions^*

^*/Estimated by CVLS with robust standard errors. Regression also included constant term, which is omitted in the table, bold figures indicate significance at the J percent level, bold and italic figures indicate significance at 10 percent level

^1/This index is computed based on the index of inlernl conflict provided by the ICRO on a scale from 0 to 12, Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Tour special interest groups are identified:religious, nationalistic, regional and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted that variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

^{Table 5.}

First-stage Regressions^*

Dependent variable:		Fund Effort per Program Year (log) 5/	Loan Size as Percent of Quota (log)	Number of Conditions per Program Year (log)	Share of Quantitative PCs Waived (percent)
Number of observations		57	57	57	57
Ethnic Fractionalization		−0.021	0.006	0.008	0.031
		−(1.56)	(0.58)	(0.84)	(0.12)
Ethnic Fractionalization (squared)		0.000	0.000	0.000	−0.002
		(1.39)	−(0.51)	(0.620)	−(0.57)
Political Instability 1/		−0.034	0.008	−0.012	0.316
		−(0.66)	(0.20)	−(0.34)	(0.34)
Other political economy variables
Strength of Special Interests 2/		0.391	−0.05	−0.042	−9.424
		(1.15)	−(0.20)	−(0.18)	−(1.51)
Index of Political Cohesion 3/		−0.008	−0.092	−0.093	−0.060
		−(0.06)	−(0.86)	−(0.98)	−(0.02)
Bureaucracy Quality Interacted with Change in Chief Executive 4/		0.007	0.009	0.055	0.391
		(0.02)	(0.04)	(0.29)	(0.08)
Variables under Fund control
Share of Structural Conditions (percent)		−0.003	0.007	0.009	0.064
		−(0.30)	(1.11)	(159)	(0.42)
Instruments
Average Share of Bilateral Aid by G-7 to the Country Before the Program Start		0.060	0.153	−0.038	3.009
		(0.49)	(1.60)	−(0.45)	(1.35)
Approval Year		0.119	0.052	0.110	−0.199
		(1.55)	(0.86)	(2.04)	−(0.14)
Expected Program Duration		0.123	0.251	0,059	−5.512
		(0.93)	(2.40)	(0.63)	−(2.27)
Fund Quota (log)		0.469	−0,128	0.219	17.421
		(2.01)	−(0.70)	(1.33)	(4.06)
Dummy for ESAF/PRGF		0.306	0.167	−1.063	16.555
		(0.80)	(0.56)	−(3.95)	(2.37)
GDP per capita (log)		−0.442	0.418	−0.218	−8.443
		−(2.45)	(2.93)	−(1.71)	−(2.55)
Latin America and Caribbean		1.095	0.784	0.313	0.303
		(2.29)	(2.08)	(0.93)	(0.03)
Sub-Saharan Africa		0.222	0.968	−0.046	13.041
		(0.40)	(2.24)	−(0.12)	(1.30)
East Asia		0.724	1,609	−0.005	18.280
		(1.31)	(3.70)	−(0.01)	(1.81)
Population (log)		−0.020	0.291	−0.121	−10.740
		−(0.11)	(2.02)	−(0.94)	−(3.21)
R2		0.56	0.75	0.57	0.549
F-statistic on Instruments		3.37	9.48	3.55	2.94
	(p-value)	0.00	0.00	0.00	0.01

^*/Estimated by CVLS with robust standard errors. Regression also included constant term, which is omitted in the table, bold figures indicate significance at the J percent level, bold and italic figures indicate significance at 10 percent level

^1/This index is computed based on the index of inlernl conflict provided by the ICRO on a scale from 0 to 12, Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Tour special interest groups are identified:religious, nationalistic, regional and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted that variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

View Table

^{Table 5.}

First-stage Regressions^*

Dependent variable:		Fund Effort per Program Year (log) 5/	Loan Size as Percent of Quota (log)	Number of Conditions per Program Year (log)	Share of Quantitative PCs Waived (percent)
Number of observations		57	57	57	57
Ethnic Fractionalization		−0.021	0.006	0.008	0.031
		−(1.56)	(0.58)	(0.84)	(0.12)
Ethnic Fractionalization (squared)		0.000	0.000	0.000	−0.002
		(1.39)	−(0.51)	(0.620)	−(0.57)
Political Instability 1/		−0.034	0.008	−0.012	0.316
		−(0.66)	(0.20)	−(0.34)	(0.34)
Other political economy variables
Strength of Special Interests 2/		0.391	−0.05	−0.042	−9.424
		(1.15)	−(0.20)	−(0.18)	−(1.51)
Index of Political Cohesion 3/		−0.008	−0.092	−0.093	−0.060
		−(0.06)	−(0.86)	−(0.98)	−(0.02)
Bureaucracy Quality Interacted with Change in Chief Executive 4/		0.007	0.009	0.055	0.391
		(0.02)	(0.04)	(0.29)	(0.08)
Variables under Fund control
Share of Structural Conditions (percent)		−0.003	0.007	0.009	0.064
		−(0.30)	(1.11)	(159)	(0.42)
Instruments
Average Share of Bilateral Aid by G-7 to the Country Before the Program Start		0.060	0.153	−0.038	3.009
		(0.49)	(1.60)	−(0.45)	(1.35)
Approval Year		0.119	0.052	0.110	−0.199
		(1.55)	(0.86)	(2.04)	−(0.14)
Expected Program Duration		0.123	0.251	0,059	−5.512
		(0.93)	(2.40)	(0.63)	−(2.27)
Fund Quota (log)		0.469	−0,128	0.219	17.421
		(2.01)	−(0.70)	(1.33)	(4.06)
Dummy for ESAF/PRGF		0.306	0.167	−1.063	16.555
		(0.80)	(0.56)	−(3.95)	(2.37)
GDP per capita (log)		−0.442	0.418	−0.218	−8.443
		−(2.45)	(2.93)	−(1.71)	−(2.55)
Latin America and Caribbean		1.095	0.784	0.313	0.303
		(2.29)	(2.08)	(0.93)	(0.03)
Sub-Saharan Africa		0.222	0.968	−0.046	13.041
		(0.40)	(2.24)	−(0.12)	(1.30)
East Asia		0.724	1,609	−0.005	18.280
		(1.31)	(3.70)	−(0.01)	(1.81)
Population (log)		−0.020	0.291	−0.121	−10.740
		−(0.11)	(2.02)	−(0.94)	−(3.21)
R2		0.56	0.75	0.57	0.549
F-statistic on Instruments		3.37	9.48	3.55	2.94
	(p-value)	0.00	0.00	0.00	0.01

^*/Estimated by CVLS with robust standard errors. Regression also included constant term, which is omitted in the table, bold figures indicate significance at the J percent level, bold and italic figures indicate significance at 10 percent level

^1/This index is computed based on the index of inlernl conflict provided by the ICRO on a scale from 0 to 12, Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Tour special interest groups are identified:religious, nationalistic, regional and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted that variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

^{Table 6.}

Random Effects Model: Linear in Probability and Tobit Regressions ^*/

Note: Bold figures indicate significance at the 3 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measure as left-hand side variables, ignoring the endogeneity of variables under the Funt’s control, The measures of program success used are: (1) a binary variable unhealing no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100%)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^1/This index, is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one 1 if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding to more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was at change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Avarage growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

^7/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by GPM.

^{Table 6.}

Random Effects Model: Linear in Probability and Tobit Regressions ^*/

Regression Number	(1)		(2)		(3)		(4)
Dependent Variable: Program Success	Linear in probability	Tobit	Linear in probability	Tobit	Linear in probability	Tobit	Linear in probability	Tobit
Number of Observations	240	240	170	170	179	179	167	167
D&S variables
Ethnic Fractionalizalion	0.12	0.31	1.07	1.99	1.16	2.14	1.31	2.45
	(0.25)	(0.34)	(2.07)	(2.34)	(2.46)	(2.64)	(2.70)	(2.94)
Ethnic Fractionalization (squared)	0.00	0.00	−0.01	−0.02	−0.01	−0.02	−0.01	−0.02
	−(0.17)	−(0.39)	−(1.34)	−(1.76)	−(2.03)	−(2.30)	−(2.38)	−(2.59)
Political Instability 1/	−039	−1.31	−1.49	−5.47	−2.85	−5.87	−3.11	−5.54
	−(0.41)	−(0.75)	−(0.69)	−(1.53)	−(1.87)	−(2.23)	−(2.03)	−(2.15)
Executive Index of Electoral competitiveness 2/	9.64	15.18	8.23	18.85	12.69	22.36	13.25	23.33
	(1.27)	(1.11)	(0.88)	(1.28)	(1.57)	(1.64)	(1.67)	(1.79)
Time in Power	0.34	1.90	1.32	3.70	1.22	3.54	2.24	4.38
	(0.30)	(0.91)	(0.73)	(1.29)	(0.78)	(1.33)	(1.46)	(1.90)
Time in Power (squared)	0.00	−0.04	−0.07	−0.18	−0.07	−0.16	−0.10	−0.20
	−(0.08)	−(0.80)	−(1.21)	−(1.92)	−(1.29)	−(1.84)	−(1.93)	−(2.35)
Other Political Economy
Strength of Special Interests 3/			−31.72	−69.73	−34.46	−68.41	−36.39	−70.49
			−(2.14)	−(2.87)	−(3.08)	−(3.53)	−(3.19)	−(3.62)
Index of Political Cohesion 4/			9.66	19.51	11.49	20.58	13.22	21.85
			(1.98)	(2.50)	(2.95)	(3.11)	(3.20)	(3.32)
Quality of Bureaucracy			12.82	33.25	16.25	31.30	20.77	36.82
Interacted with Change in Chief Executive 5/			(1.19)	(1.85)	(1.92)	(2.13)	(2.52)	(2.63)
Initial conditions
Central Government Balance (in percent of GDP)			0.93	0.98
			(0.76)	(0.50)
Level of Reserves			0.00	0.00
			(0.46)	(0.72)
Inflation			0.00	−0.27
			(0.01)	−(0.97)
Current Account Balance (in percent of GDP)			−95	−123
			−(1.26)	−(1.02)
GDP per capita (log)			5.39	4,75
			(0.81)	(0.44)
Debt to the Fund (percent of Fund Quota)			4.62	13.21
			(0.37)	(0.63)
External Conditions
Terms of Trade Shock 6/			−0.01	−0.01
			−(1.15)	−(0.34)
Variables under the Fund Control
Fund Effort per Program Year (log) 7/							3.81	11.91
							(0.78)	(1.48)
Loan Size as Percent of Quota (log)							7.0	11.45
							(1.63)	(1.55)
Number of Conditions per Program Year (log)							−6.43	−13.80
							−(0.99)	−(1.29)
Share of Quantitative PCs Waived (percent)							−0.49	−1.05
							−(1.98)	−(2.56)
Share of Structural Conditions (percent)							0.16	0.21
							(0.98)	(0.77)
Wald Chi2 statistics	2.95	5.00	34.29	42.63	33.32	38.31	45.86	48.33
p-value	0.31	0.54	0.01	0.00	0.00	0.00	0.00	0.00

Note: Bold figures indicate significance at the 3 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measure as left-hand side variables, ignoring the endogeneity of variables under the Funt’s control, The measures of program success used are: (1) a binary variable unhealing no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100%)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^1/This index, is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one 1 if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding to more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was at change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Avarage growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

^7/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by GPM.

View Table

^{Table 6.}

Random Effects Model: Linear in Probability and Tobit Regressions ^*/

Regression Number	(1)		(2)		(3)		(4)
Dependent Variable: Program Success	Linear in probability	Tobit	Linear in probability	Tobit	Linear in probability	Tobit	Linear in probability	Tobit
Number of Observations	240	240	170	170	179	179	167	167
D&S variables
Ethnic Fractionalizalion	0.12	0.31	1.07	1.99	1.16	2.14	1.31	2.45
	(0.25)	(0.34)	(2.07)	(2.34)	(2.46)	(2.64)	(2.70)	(2.94)
Ethnic Fractionalization (squared)	0.00	0.00	−0.01	−0.02	−0.01	−0.02	−0.01	−0.02
	−(0.17)	−(0.39)	−(1.34)	−(1.76)	−(2.03)	−(2.30)	−(2.38)	−(2.59)
Political Instability 1/	−039	−1.31	−1.49	−5.47	−2.85	−5.87	−3.11	−5.54
	−(0.41)	−(0.75)	−(0.69)	−(1.53)	−(1.87)	−(2.23)	−(2.03)	−(2.15)
Executive Index of Electoral competitiveness 2/	9.64	15.18	8.23	18.85	12.69	22.36	13.25	23.33
	(1.27)	(1.11)	(0.88)	(1.28)	(1.57)	(1.64)	(1.67)	(1.79)
Time in Power	0.34	1.90	1.32	3.70	1.22	3.54	2.24	4.38
	(0.30)	(0.91)	(0.73)	(1.29)	(0.78)	(1.33)	(1.46)	(1.90)
Time in Power (squared)	0.00	−0.04	−0.07	−0.18	−0.07	−0.16	−0.10	−0.20
	−(0.08)	−(0.80)	−(1.21)	−(1.92)	−(1.29)	−(1.84)	−(1.93)	−(2.35)
Other Political Economy
Strength of Special Interests 3/			−31.72	−69.73	−34.46	−68.41	−36.39	−70.49
			−(2.14)	−(2.87)	−(3.08)	−(3.53)	−(3.19)	−(3.62)
Index of Political Cohesion 4/			9.66	19.51	11.49	20.58	13.22	21.85
			(1.98)	(2.50)	(2.95)	(3.11)	(3.20)	(3.32)
Quality of Bureaucracy			12.82	33.25	16.25	31.30	20.77	36.82
Interacted with Change in Chief Executive 5/			(1.19)	(1.85)	(1.92)	(2.13)	(2.52)	(2.63)
Initial conditions
Central Government Balance (in percent of GDP)			0.93	0.98
			(0.76)	(0.50)
Level of Reserves			0.00	0.00
			(0.46)	(0.72)
Inflation			0.00	−0.27
			(0.01)	−(0.97)
Current Account Balance (in percent of GDP)			−95	−123
			−(1.26)	−(1.02)
GDP per capita (log)			5.39	4,75
			(0.81)	(0.44)
Debt to the Fund (percent of Fund Quota)			4.62	13.21
			(0.37)	(0.63)
External Conditions
Terms of Trade Shock 6/			−0.01	−0.01
			−(1.15)	−(0.34)
Variables under the Fund Control
Fund Effort per Program Year (log) 7/							3.81	11.91
							(0.78)	(1.48)
Loan Size as Percent of Quota (log)							7.0	11.45
							(1.63)	(1.55)
Number of Conditions per Program Year (log)							−6.43	−13.80
							−(0.99)	−(1.29)
Share of Quantitative PCs Waived (percent)							−0.49	−1.05
							−(1.98)	−(2.56)
Share of Structural Conditions (percent)							0.16	0.21
							(0.98)	(0.77)
Wald Chi2 statistics	2.95	5.00	34.29	42.63	33.32	38.31	45.86	48.33
p-value	0.31	0.54	0.01	0.00	0.00	0.00	0.00	0.00

Note: Bold figures indicate significance at the 3 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measure as left-hand side variables, ignoring the endogeneity of variables under the Funt’s control, The measures of program success used are: (1) a binary variable unhealing no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100%)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^1/This index, is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Dummy variable which equals one 1 if the executive index of electoral competitiveness is equal to 7 and zero otherwise. The executive index of electoral competitiveness is from the Database of Political Institutions at the World Bank. It ranges from 1 to 7, with higher values corresponding to more competitive elections.

^3/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional and rural.

^4/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See Annex 1 for a more detailed definition.

^5/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4 point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was at change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^6/Avarage growth rate of dollar export prices multiplied by the initial share of exports in GDP minus average growth rate of dollar import prices multiplied by the initial share of imports in GDP over the course of the program

^7/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by GPM.

^{Table 7.}

Random Effects (IV) */and MIMIC **/Models: Linear in Probability Regressions

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measures as left-hand side variables, uising random effects IV estimator with the set of instruments as specified in Table 9. The measures of program success used are: (1) a binary variable indicating no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100 percent)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^**/This model comprises equations (l)-(5) in the text and is essentially a system of seemingly unrelated regressions, which can be estimated to obtain reduced form parameters (since the model is overidentified we had to impose nonlinear contraints to obtain unique estimates of coefficients). Then the structural parameters were computed using estimates of reduced form parameters and their variance was estimated using delta-method. (More detailed information is available from authors upon request).

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional, and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See the Annex for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4-point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

^6/Treated as endogenous variable in this regression.

^{Table 7.}

Random Effects (IV) */and MIMIC **/Models: Linear in Probability Regressions

		Random effects IV regressions */					MIMIC Model**/
Regression number		(1)	(2)	(3)	(4)	(5)	(6)
Observations		165	165	165	165	165	165
D&S variables
Ethnic Fractionalization		1.08	0.91	0.94	1.25	0.99	2.50
		(2.09)	(1.70)	(1.75)	(2.44)	(2.05)	(3.55)
Ethnic Fractionalization (squared)		−0.01	−0.01	−0.01	−0.01	−0.01	−0.03
		−(1.76)	−(1.42)	−(1.48)	−(2.07)	−(1.68)	−(3.53)
Political Instability 1/		−3.91	−3.82	−3.93	−4.58	−4.48	−4.23
		−(2.49)	−(2.43)	−(2.50)	−(2.90)	−(2.82)	−(2.20)
Other Political Economy Variables
Strength of Special Interests 2/		−39.78	−33.86	−34.01	−45.47	−37.38	−38.69
		−(3.57)	−(2.80)	−(2.81)	−(3.99)	−(3.24)	−(2.48)
Index of Political Cohesion 3/		10.03	10.55	8.78	9.86	9.69	14.02
		(2.74)	(2.87)	(2.17)	(2.43)	(2.39)	(2.86)
Bureaucracy Quality Interacted with Change in Chief Executive 4/		21.39	21.36	22.02	24.97	24.50	21.05
		(2.68)	(2.68)	(2.75)	(3.11)	(3.02)	(2.16)
Variables under the Fund control
Fund Effort per Program Year (log) 5/ 6/		1.54	−2.14	−0.49	7.06		−9.29
		(0.23)	−(0.29)	−(0.07)	(0.99)		−(1.06)
Loan Size as Percent of Quota (log) 6/			6.89	7.35		6.58
			(1.26)	(1.33)		(1.30)
Number of Conditions per Program Year (log) 6/				−9.87	−15.77	−13.70
				−(1.05)	−(1.55)	−(1.43)
Share of Quantitative PCs Waived (percent) 6/					−0.67	−0.47
					−(1.59)	−(1.17)
Share of Structural Conditions (percent)		0.14	0.11	0.06	0.16	0.14
		(0.83)	(0.62)	(0.32)	(0.92)	(0.77)
Wald Chi 2 statistics		26.92	28.50	29.57	31.62	31.93
p-value		0.00	0.00	0.00	0.00	0.00
Over-identifying restrictions test		12.67	10.42	8.83	8.04	6.91
	(degrees of freedom)	9	8	7	7	7
	(p-value)	0.18	0.24	0.27	0.33	0.44
Hausman Test		0.38	0.92	1.04	0.84	0.83
	(p-value)	0.54	0.63	0.79	0.84	0.84

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measures as left-hand side variables, uising random effects IV estimator with the set of instruments as specified in Table 9. The measures of program success used are: (1) a binary variable indicating no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100 percent)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^**/This model comprises equations (l)-(5) in the text and is essentially a system of seemingly unrelated regressions, which can be estimated to obtain reduced form parameters (since the model is overidentified we had to impose nonlinear contraints to obtain unique estimates of coefficients). Then the structural parameters were computed using estimates of reduced form parameters and their variance was estimated using delta-method. (More detailed information is available from authors upon request).

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional, and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See the Annex for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4-point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

^6/Treated as endogenous variable in this regression.

View Table

^{Table 7.}

Random Effects (IV) */and MIMIC **/Models: Linear in Probability Regressions

		Random effects IV regressions */					MIMIC Model**/
Regression number		(1)	(2)	(3)	(4)	(5)	(6)
Observations		165	165	165	165	165	165
D&S variables
Ethnic Fractionalization		1.08	0.91	0.94	1.25	0.99	2.50
		(2.09)	(1.70)	(1.75)	(2.44)	(2.05)	(3.55)
Ethnic Fractionalization (squared)		−0.01	−0.01	−0.01	−0.01	−0.01	−0.03
		−(1.76)	−(1.42)	−(1.48)	−(2.07)	−(1.68)	−(3.53)
Political Instability 1/		−3.91	−3.82	−3.93	−4.58	−4.48	−4.23
		−(2.49)	−(2.43)	−(2.50)	−(2.90)	−(2.82)	−(2.20)
Other Political Economy Variables
Strength of Special Interests 2/		−39.78	−33.86	−34.01	−45.47	−37.38	−38.69
		−(3.57)	−(2.80)	−(2.81)	−(3.99)	−(3.24)	−(2.48)
Index of Political Cohesion 3/		10.03	10.55	8.78	9.86	9.69	14.02
		(2.74)	(2.87)	(2.17)	(2.43)	(2.39)	(2.86)
Bureaucracy Quality Interacted with Change in Chief Executive 4/		21.39	21.36	22.02	24.97	24.50	21.05
		(2.68)	(2.68)	(2.75)	(3.11)	(3.02)	(2.16)
Variables under the Fund control
Fund Effort per Program Year (log) 5/ 6/		1.54	−2.14	−0.49	7.06		−9.29
		(0.23)	−(0.29)	−(0.07)	(0.99)		−(1.06)
Loan Size as Percent of Quota (log) 6/			6.89	7.35		6.58
			(1.26)	(1.33)		(1.30)
Number of Conditions per Program Year (log) 6/				−9.87	−15.77	−13.70
				−(1.05)	−(1.55)	−(1.43)
Share of Quantitative PCs Waived (percent) 6/					−0.67	−0.47
					−(1.59)	−(1.17)
Share of Structural Conditions (percent)		0.14	0.11	0.06	0.16	0.14
		(0.83)	(0.62)	(0.32)	(0.92)	(0.77)
Wald Chi 2 statistics		26.92	28.50	29.57	31.62	31.93
p-value		0.00	0.00	0.00	0.00	0.00
Over-identifying restrictions test		12.67	10.42	8.83	8.04	6.91
	(degrees of freedom)	9	8	7	7	7
	(p-value)	0.18	0.24	0.27	0.33	0.44
Hausman Test		0.38	0.92	1.04	0.84	0.83
	(p-value)	0.54	0.63	0.79	0.84	0.84

Note: Bold figures indicate significance at the 5 percent level, bold and italic figures indicate significance at 10 percent level

^*/This model was estimated on a pooled sample of three implementation measures as left-hand side variables, uising random effects IV estimator with the set of instruments as specified in Table 9. The measures of program success used are: (1) a binary variable indicating no irreversible program interruption; (2) the share of funds committed by the Fund under an arrangement disbursed (we excluded the measure of committed funds disbursed for arrangements precautionary on approval; cancelled programs that did not have irreversible interruption and arrangements that turned precautionary were treated as fully disbursed (100 percent)); and (3) the average share of conditions implemented. Regression also included constant term, which is omitted in the table.

^**/This model comprises equations (l)-(5) in the text and is essentially a system of seemingly unrelated regressions, which can be estimated to obtain reduced form parameters (since the model is overidentified we had to impose nonlinear contraints to obtain unique estimates of coefficients). Then the structural parameters were computed using estimates of reduced form parameters and their variance was estimated using delta-method. (More detailed information is available from authors upon request).

^1/This index is computed based on the index of internal conflict provided by the ICRG on a scale from 0 to 12. Higher values of the index correspond to more internal political instability. We replaced the value of this variable by its maximum score (12) if there was a change in chief executive in the course of Fund program.

^2/Computed as the maximum share of seats in the parliament held by parties representing special interests (Political Institutions Database, World Bank). Four special interest groups are identified:religious, nationalistic, regional, and rural.

^3/The index of political cohesion is defined as follows: in presidential systems a high degree of political cohesion is said to exist if the same party is in control of the executive and legislature; in parliamentary systems a high degree of political cohesion means a one-party majority government. See the Annex for a more detailed definition.

^4/Bureaucracy quality (ICRG) measures the quality of a country’s bureaucracy on a 4-point scale. See Annex 1 for a more detailed definition. We interacted this variable with the dummy indicating that there was a change in chief executive (Political Institutions Database and CIA World Fact Book for most recent years).

^5/Fund effort is estimated dollar cost of Fund programs computed based on BRS data on hours spend by the staff on program implementation (it includes both preparation and supervision of the program) and estimated average salaries of the staff by grade. We also made use of the dollar costs of resident representatives provided by OPM.

^6/Treated as endogenous variable in this regression.