Is Fiscal Adjustment More Durable When The IMF is Involved? 1

TL;DR: In this paper, the authors investigated the impact of IMF conditionality on 112 countries during the 1990s and found that, while the overall fiscal balance improved in most of them, the composition of this improvement differed.

Abstract: This paper investigates fiscal developments in 112 countries during the 1990s. It finds that while the overall fiscal balance improved in most of them, the composition of this improvement differed. In countries without IMF-supported programmes, revenues increased modestly and expenditure declined sharply, while in programme countries both post-programme revenue and expenditure declined. However, in countries with programmes that included fiscal structural conditions, the adjustment was effected primarily through sharp expenditure compression. No evidence of a statistically significant impact of IMF conditionality was found. Moreover, fiscal developments were influenced by cyclical factors and by the general stance of macroeconomic policies.

Summary

INTRODUCTION

• This paper examines post-programme fiscal developments in countries with and without an IMF-supported programme.
• In nonprogramme countries, revenue increased modestly and expenditure declined sharply, while in programme countries both revenue and expenditure declined during the post-programme period.
• Second, the authors describe the techniques used in their estimations.

IMF PROGRAMMES AND FISCAL DEVELOPMENTS

• In the literature, three different influences have been construed.
• In other words, public sector policies are essentially the same in democracies and nondemocracies (Mulligan et al., 2003).
• In contrast, Barro and Lee (2002) reported opposite results–participation in IMF-supported programme was found to lower growth and investment.
• The macroeconomic effects of IMF-supported programmes depended, on the one hand, on borrowing countries’ domestic political economy (Ivanova et al., 2003, Khan and Sharma, 2001; Boughton and Mourmouras, 2002) and, on the other hand, on the technical design of the programme or the amount of money borrowed (Schadler et al., 1995).

What is IMF conditionality?

• Conditionality is an explicit link between the approval (or continuation) of the Fund’s financing and the implementation of certain aspects of the authorities’ policy programme (Guitián, 1981).
• While most fiscal conditions were designed as neutral vis-à-vis the overall fiscal balance, some conditions were geared towards either higher revenue or lower expenditure.
• Throughout the paper, the authors used a sample of 112 countries, of which 48 countries did not have a programme during the sample period, and 31 and 33 countries had programmes without and with structural conditions, respectively.
• More conditions required for programme continuation increase the risk of missing some of them, however, missing one of them does not stop a programme.

SPECIFICATION OF THE MODEL

• Fiscal developments are affected by various exogenous and country-specific effects and, therefore, the authors re-examine them in multivariate panel and crosscountry regressions.
• The simple model above has two drawbacks.
• The estimates of f could suffer from simultaneous equation bias: participation in IMFsupported programmes depended on past policies (Conway, 1994, 2000; Przeworski and Vreeland, 2000; Barro and Lee, 2002) and an OLS regression of (1) would underestimate the true effect of Fund programmes.
• Successful programmes were defined as those that either disbursed all committed resources without interruptions or those that were designed and executed as precautionary arrangements (following the definition of programme success in Ivanova et al., 2003).
• To this end, the authors introduced a set of variables, c, into equation (3) to test the significance of fiscal structural conditionality.

SAMPLE SELECTION AND ESTIMATION

• First, using data for nonprogramme countries only, the authors estimated the policy reaction function (equation (2)) for the relevant macroeconomic variables.
• There are a few well-known exceptions, though.
• Bulgaria in 1997 insisted on a detailed specification of structural conditionality in order to avoid domestic political confrontation about the design of reforms (International Monetary Fund, 2001).
• Comparative Economic Studies parameters, the authors simulated macroeconomic policies in programme countries to reflect what those policies would have been in the absence of an IMFsupported programme.
• The authors selected the 1993–96 period because of three considerations.

The policy reaction function

• The policy reaction function determined the stance of monetary, external, and incomes policies, respectively, as a function of the pre-announced fiscal adjustment.
• The difference between this projection and the current fiscal outcome, yij( 1), then measured the fiscal disequilibrium to which the authorities reacted with changes in policy instruments in the coming year.
• Only one political economy variable was significant, indicating that if one party controlled the government, current account balance was more likely to improve and vice versa.
• AThe abbreviations stand for the following data sources, respectively: World Economic Outlook; World Development Indicators; Database of Political Institutions, Version 3.0 (World Bank, 2001); Ivanova et al. (2003); International Financial Statistics; and the Monitoring of Fund Arrangements Database.

The generalized evaluation estimator

• The authors consider three target variables (yij) measuring fiscal developments: (i) the overall central government balance; (ii) central government revenue and grants; and (iii) central government expenditure and net lending, all expressed in percent of GDP, in 64 countries that operated under IMFsupported programmes13 and 48 nonprogramme countries during 1993–96.
• AThe superscripts ***, **, and * denote the rejection of the null hypothesis that the estimated coefficient is zero at the 1, 5, and 10 percent significance levels, respectively.
• The endogenous policy variables stemmed from the policy reaction function and the exogenous variables were 2-year averages, lagged one period: the terms of trade, GDP per capita in constant US dollars, foreign aid in percent of GDP, the rate of inflation, and real GDP growth.
• The authors wanted to measure the impact of IMF-supported programmes beyond the initial, short-term impact and, hence, they considered fiscal variables 1, 2, and 3 years after the initial programme ended, with 112, 109, and 97 observations, respectively.
• First, poor fiscal discipline or a lack of programme ownership may have caused the reversal.

Results in the full sample

• In general, the authors find that cyclical variables drove the fiscal developments and that the impact of macroeconomic policy variables was comparatively small (Tables 6–8).16.
• In all cases, the robust estimators were the autoregressive terms, real GDP growth, and the real rate of interest, the stance of monetary policy being a good measure of the general tightness of macroeconomic policies.
• In some cases, the authors also found inflation, and certain conditionality variables to be significant.
• The dummy measuring programme participation was statistically insignificant, implying that past IMF-supported programmes did not make the medium-term fiscal adjustment either softer or stronger – on average, programme countries adjusted as much as nonprogramme countries.
• The only statistically significant regional dummy was the sub–Saharan Africa dummy.

The overall balance

• Several other variables were either marginally significant or significant only in some regressions.
• One of them was the aid-to-GDP ratio, indicating 16 We present both full-blown and parsimonious estimates with statistically significant variables only.the authors.
• 17 Moderate inflation was associated with improvements in the overall balance, while countries with an average annual inflation of more than 50 percent worsened their fiscal position.
• Countries with programme stoppages did worse than the average, while those without interruptions did better.

Revenue and grants

• Revenue regressions explained much less of the variance of the dependent variable (20–30 percent), even though the results were also dominated by the pre-programme revenue levels and cyclical effects (Table 7).
• The revenue-toGDP ratio worsened in countries with larger-than-average initial revenue and it was inversely related to real GDP growth.
• On the one hand, the tax burden peaked in many countries in the late 1980s and, on the other hand, fast-growing economies did not need to increase their tax-toGDP ratio, also known as Both results were intuitive.
• The aid-to-GDP ratio was positive, but statistically insignificant in all but the 1-year-after-the-programme estimates.
• 18 Some authors argued that foreign aid causes longer-term fall in revenue by breeding corruption and creating a perverse motivation for the authorities not to collect taxes (Ziegler, 1996).

Expenditure and net lending

• The variance of the expenditure-to-GDP ratio was mostly explained by preprogramme expenditure levels, the real rate of growth, and monetary policy (20–30 percent) (Table 8).
• While the size and signs of the individual coefficients were broadly unchanged compared to Tables 6–8 their statistical significance declined predictably with the loss of degrees of freedom.
• Revenue performance in sub–Saharan Africa was better than average, although not sufficiently to offset the expenditure increase.
• These results seem to suggest that countries with structural conditionality were indeed different from the other programme countries.
• Finally, post–programme fiscal performance in those countries was driven by accelerating expenditure compression, which may not be a bad thing, provided, for example, the pre–programme level of spending was wasteful or that a statist budget was replaced with a less intrusive one.

CONCLUDING REMARKS

• This paper presents empirical tests of the relevance of IMF structural conditionality for post-programme fiscal performance in a large sample of countries during the 1990s.
• The impact of IMF-supported programmes was not statistically significant, owing to the large variance in the sample of programme countries.
• In structural conditionality countries, revenue declined slightly and expenditure declined significantly.
• The authors results highlight the difficulty in identifying the impact of structural conditionality.
• First, more work is needed to examine the role of initial shocks, structural weaknesses, political economy, and regime– specific effects, such as the choice of the exchange rate regime.

Figures

Table 1: Frequency of fiscal structural conditionality

Table 5: Estimates of the policy reaction function (heteroscedasticity-consistent, feasible GLS regression estimates, t-statistics in parentheses)a

Figure 1: Change in the overall fiscal balance 3 years after the end of the IMF-supported programme or 1999 for nonprogramme countries, compared to the initial observation. The median initial observation is 1993 and the median end-period observation is 1999 (in percent of GDP, 112 countries). Source: World Economic Outlook; authors’ calculations.

Table 4: Definitions of variables

Table 9: Fiscal developments in structural conditionality countries relative to nonstructural conditionality countriesa (Heteroscedasticity-consistent OLS regression estimates of the structural conditionality and sub-Saharan Africa dummies, t-statistics in parentheses)

Table 2: Change in fiscal outcomes 3 years after the end of IMF-supported programmesa (in percent of GDP)

Table 3: Selected characteristics of programme and nonprogramme countries

Full text

Is Fiscal Adjustment More Durable When
The IMF is Involved?
1
ALES
ˇ
BULI
´
R
ˇ
1
& SOOJIN MOON
2
1
International Monetary Fund. E-mail: abulir@imf.org;
2
Department of Economics, University of California, Los Angeles, CA, USA.
E-mail: sjmoon@ucla.edu
This paper investigates fiscal developments in 112 countries during the 1990s. It
finds that while the overall fiscal balance improved in most of them, the
composition of this improvement differed. In countries without IMF-supported
programmes, revenues increased modestly and expenditure declined sharply, while
in programme countries both post-programme revenue and expenditure declined.
However, in countries with programmes that included fiscal structural conditions,
the adjustment was effected primarily through sharp expenditure compression. No
evidence of a statistically significant impact of IMF conditionality was found.
Moreover, fiscal developments were influenced by cyclical factors and by the general
stance of macroeconomic policies.
Comparative Economic Studies (2004) 46, 373–399. doi:10.1057/palgrave.ces.8100051
Keywords: IMF-supported programmes, conditionality, fiscal policy, general
evaluation estimator
JEL Classifications: F33, H30
INTRODUCTION
What determines the composition of fiscal adjustment and does it differ
between countries with IMF-supported programmes and those without such
arrangements? Moreover, how effective is IMF structural conditionality for
post-programme fiscal developments? This paper attempts to answer these
1
The authors are indebted to Tim Lane and Alex Mourmouras for extensive discussions. We are
also grateful for helpful comments from George Anayiotos, Martin C
ˇ
iha
´
k, Christina Daseking, Kamil
Dybczak, Gervan Fearon, Rex Ghosh, Sanjeev Gupta, Javier Hamann, Eduardo Ley, Paolo Mauro,
Alex Segura Ubiergo, Kater
ˇ
ina S
ˇ
mı
´
dkova
´
, Alun Thomas, Jaroslaw Wieczorek and two anonymous
referees as well as participants at the 2002 Atlantic Economic Society conference, 2002 Czech
Economic Society conference, 2003 International Institute of Public Finance conference, and seminar
participants at the International Monetary Fund. Anna Ivanova kindly shared some data with us.
Comparative Economic Studies, 2004, 46, (373–399)
r 2004 ACES. All rights reserved. 0888-7233/04 $30.00
www.palgrave-journals.com/ces

questions by investigating the fiscal developments in 112 countries during the
1990s, some with and some without IMF-supported programmes.
A central objective of IMF-supported programmes has been to reduce
external imbalances (International Monetary Fund, 1998). This often requires
bringing the budget under control: first, fiscal profligacy often causes current
account deficits and, second, even if the initial budgetary position is
sustainable, additional fiscal tightening may be needed if the domestic
currency comes under pressure (Ghosh et al., 2002). This adjustment has
been part of broader medium–term macroeconomic programmes that also
encompass supply side structural reforms relevant for external stability.
This paper examines post-programme fiscal developments in countries
with and without an IMF-supported programme. It finds significant diff-
erences in the composition of adjustment between programme and non-
programme countries as well as large differences among programme
countries. In nonprogramme countries, revenue increased modestly and
expenditure declined sharply, while in programme countries both revenue
and expenditure declined during the post-programme period. Moreover, in
IMF-supported programmes that included structural conditions, the adjust-
ment was effected primarily through sharp expenditure compression in order
to offset revenue declines. We did not find any evidence that fiscal structural
conditions improved revenue performance after the end of the programme.
Fiscal developments were strongly affected by the business cycle and, to
some extent, by the general stance of macroeconomic policies.
This paper is organised as follows. First, we review the stylised facts and
define the sample. Second, we describe the techniques used in our estima-
tions. Third, we present and discuss our results. The final section concludes.
IMF PROGRAMMES AND FISCAL DEVELOPMENTS
How to measure the impact of IMF-supported programmes?
What is the impact of IMF-supported programmes on fiscal adjustment? In the
literature, three different influences have been construed. One view is that
these programmes provide external resources beyond the financing provided
by the IMF itself to the extent that they have a catalytic effect; thus,
adjustments take place at lower costs than in the absence of such an arrange
ment (Cottarelli and Curzio, 2002). Hence, IMF-supported programmes can
be associated with either smaller or larger fiscal deficits, depending on the
nature of the shock and the design of the programme. This description is close
to the official IMF view of its role (Dhonte, 1997; Haque and Khan, 1998; Bird,
2002; Bird and Rowland, 2002). A second view is that these programmes
A Bulı
´
r
ˇ
& S Moon
Fiscal Adjustment and the IMF
374
Comparative Economic Studies

prescribe excessively fast adjustment, by uniformly requiring monetary tightening,
expenditure cuts, and higher taxes, hurting both the poor and businesses in the
process. A third view is that IMF-supported programmes delay fundamental
reforms by merely treating the symptoms of financing needs by repeated
lending to crisis-prone and structurally unstable countries (Bird, 1996).
Which view is the closest to reality? Empirical assessments of the impact
of IMF-supported programmes are notoriously complex. Countries’ macro-
economic performance is influenced by secular forces, external shocks,
structural reforms, and temporary availability of IMF-linked financing. The
initial conditions and exogenous shocks need to be separated from the effects
of IMF-supported arrangements, because countries that do not undertake
such programmes are not an appropriate control group for IMF-programme
countries (Krueger, 1998). An appropriate technique is the general evaluation
estimator (GEE), due to Goldstein and Montiel (1986), which constructs
counterfactual economic policies first and then tests the importance of
IMF-supported programmes. This approach was successfully tested, inter
alia, by Khan (1990), Conway (1994), and Dicks-Mireaux et al. (2000).
The question asked is two-fold. First, what are the factors that lead to IMF-
supported programmes? The answer to this question is well known: economic
variables, such as the current account balance, inflation, international
reserves, debt service, GDP per capita, and so on, together with participation
in previous programmes explain reasonably well the approval of an IMF-
supported arrangement (Conway, 1994; Knight and Santaella, 1997; Bird et al.,
2000). Knight and Santaella (1997) found that policy commitments made by
recipient governments matter for the programme approval as well; if the
authorities promise stronger adjustment, the Fund is more likely to approve a
bigger loan. Barro and Lee (2002) added to the list of variables a bigger IMF
quota, more IMF professional staff of that country origin, and a closer
political/economic connection to the major shareholders of the IMF. The last
variable is intuitive – ‘better connected’ countries are likely to get more money
with fewer strings attached (Bird, 2002). In contrast, the literature found no
relationship between political economy variables (political institutions, quality
of bureaucracy, and so on) and the participation in an IMF-supported
programme. In other words, public sector policies are essentially the same in
democracies and nondemocracies (Mulligan et al., 2003).
Second, and this is the question we are interested in, what are the
macroeconomic effects of IMF-supported programmes? This strand of the
literature has a few well-established stylised facts as well. IMF-supported
programmes were found to be associated with an improved post-programme
current account balance. Inflation slowed down and real growth recovered,
however, typically by less than what was projected under the programme
A Bulı
´
r
ˇ
&SMoon
Fiscal Adjustment and the IMF
375
Comparative Economic Studies

(Conway, 1994; Schadler et al., 1995; Bird, 2002; Ghosh et al., 2002). In
contrast, Barro and Lee (2002) reported opposite results–participation in
IMF-supported programme was found to lower growth and investment.
Unfortunately, Barro and Lee controlled neither for the repeated use of Fund
loans nor for country’s adherence to the policies agreed in the programme. At
the same time, limited work has been done on longer-term fiscal effects of
IMF-supported programmes.
The macroeconomic effects of IMF-supported programmes depended, on
the one hand, on borrowing countries’ domestic political economy (Ivanova
et al., 2003, Khan and Sharma, 2001; Boughton and Mourmouras, 2002) and,
on the other hand, on the technical design of the programme (conditionality)
or the amount of money borrowed (Schadler et al., 1995). Regarding the
former, strong special interests, political instability, inefficient bureaucracies,
lack of political cohesion, and ethno-linguistic divisions weakened pro-
gramme implementation. Adjustment programmes were more successful in
countries where they augmented home-grown reforms than in countries
where the Fund and/or other donors tried to impose them on unwilling
authorities. Regarding the latter, it seems that the impact of Fund
conditionality was governed by a ‘Laffer-curve’ relationship, whereby a
few, well-targeted conditions had a positive impact on economic perfor-
mance, but too many or too intrusive conditions hindered such performance
(Collier et al., 1997; Dollar and Svensson, 2000; Goldstein, 2000; Bird, 2001).
To this end, we will use the IMF’s Monitoring of Fund Arrangements
Database (MONA) that collects information on conditionality under IMF-
supported programmes and which was first utilised in International Monetary
Fund (2001). Surprisingly, assessments of structural conditionality have been
rare and this paper is a first empirical exercise to address its role in
macroeconomic adjustment in a systematic fashion.
What is IMF conditionality?
Conditionality is an explicit link between the approval (or continuation) of the
Fund’s financing and the implementation of certain aspects of the authorities’
policy programme (Guitia
´
n, 1981). The conditions may be either quantitative
(say, a limit on reserve money growth) or structural (say, the introduction of a
value-added tax).
2
In general, conditionality is designed to encompass policy
measures that are critical to programme objectives or key internal data targets
that sound warning bells if policies veer off track. Whereas in the mid-1980s
structural conditionality in IMF-supported arrangements was rare, by the mid-1990s
2
IMF-supported programmes typically do not stipulate quantitative fiscal conditions in terms
of, say, the primary fiscal balance or domestic fiscal revenue.
A Bulı
´
r
ˇ
& S Moon
Fiscal Adjustment and the IMF
376
Comparative Economic Studies

about half of all programmes included structural conditions. The average
number of structural conditions per programme year increased from two in 1987
to more than 16 in 1997 (International Monetary Fund, 2001; Boughton, 2001).
These developments were the result of several forces. First, the IMF
gradually placed more emphasis on supply-side reforms as compared to demand
management. Second, the IMF’s involvement in low-income and transition
countries was focused on the alleviation of structural imbalances and rigidities
prevalent in these economies (Mercer-Blackman and Unigovskaya, 2000).
Finally, the experience with monetary and fiscal policies indicated that their
success depends critically on structural conditions. Indeed, most structural con-
ditions were in the core area of IMF expertise (International Monetary Fund, 2001).
In this paper, we focus on three main types of structural conditions
tabulated in the MONA database: (i) prior actions, which are stipulated as
preconditions to the approval of an IMF-supported programme, (ii) structural
performance criteria, fulfilment of which is a formal precondition for
programme continuation, and (iii) structural benchmarks, which are agreed
with the authorities and monitored by the IMF staff, but are not a formal
precondition for programme continuation. The majority of conditions were
structural benchmarks, while structural performance criteria were the least
numerous conditions. The extent of structural conditionality was in part
determined endogenously – countries with a large reform agenda or history of
poor reform performance tended to get more conditions, although no clear-cut
answers as to why some countries have many more conditions than others are
available (International Monetary Fund, 2001). If anything, distribution of
structural conditions was correlated regionally and with the length of the
programmes (quite predictably, 12-months IMF-supported programmes tend
to have fewer supply side conditions than 3-year programmes).
All but two IMF-supported programmes with structural conditionality in
our sample (33 countries during 1993–1999) contained at least one fiscal
condition.
3
Indeed, fiscal structural conditionality was the most common area
of structural conditionality, comprising about 50 percent of all conditions.
While most fiscal conditions were designed as neutral vis-a
`
-vis the overall
fiscal balance, some conditions were geared towards either higher revenue or
lower expenditure. We classify all those measures according to their expected
revenue or expenditure impact and present their summary in Table 1.
4
Based
3
Throughout the paper, we used a sample of 112 countries, of which 48 countries did not have
a programme during the sample period, and 31 and 33 countries had programmes without and with
structural conditions, respectively. See the fourth section for the list of countries.
4
For example, we classified the ‘introduction of ad valorem excise duties’ as a revenue-
increasing condition; a ‘reduction in civil service positions’ as an expenditure-lowering condition;
and the ‘adoption of accounting system of the Treasury’ as a neutral condition.
A Bulı
´
r
ˇ
&SMoon
Fiscal Adjustment and the IMF
377
Comparative Economic Studies

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Is fiscal adjustment more durable when the imf is involved?" ?

This paper investigates fiscal developments in 112 countries during the 1990s. 

Q2. What future works have the authors mentioned in the paper "Is fiscal adjustment more durable when the imf is involved?" ?

The findings in this paper are not definitive and the possibilities for further research are extensive. Second, the policy reaction function can be specified differently, reflecting, for example, policies that would stabilise the debt-to-GDP ratio or that would be based on ‘ fiscal rules ’. 

Q3. What were the main factors that weakened the implementation of the programme?

Regarding the former, strong special interests, political instability, inefficient bureaucracies, lack of political cohesion, and ethno-linguistic divisions weakened programme implementation. 

Q4. How did the adjustment affect revenue performance after the end of the programme?

in IMF-supported programmes that included structural conditions, the adjustment was effected primarily through sharp expenditure compression in order to offset revenue declines. 

Q5. o rmal ity test (f) 0.05 1.?

Fp rog ram me d u mm ya0 .01 3 8(0 .88 )0 .01 0 7(0 .67 )0 .01 8 0(0 .85 )Co n diti ona li tyva ri able sSt ruct u ral con d itio n alit y(d u mm y)b0 .04 0 7(3 .10 )0 .03 8 9(3 .19 )0 .03 6 8(3 .20 )0 .03 2 4(4 .01 )0 .06 2 0(4 .49 )0 .04 9 7(4 .12 )R 20 .45 40 .44 90 .50 50 .47 00 .31 90 .32 20 .37 10 .33 70 .44 80 .45 20 .53 40 .50 3Lo g -lik elih o o d1 7 6 .81 7 6 .31 8 2 .31 7 8 .41 6 6 .71 6 6 .91 7 1 .11 6 8 .21 4 4 .11 4 4 .61 5 2 .51 4 9 .3N u mb ero fo b serv atio n s1 1 21 1 21 1 21 1 21 0 91 0 91 0 91 0 99 79 79 79 7N o rmal ity test [w2 (2,2 )]1 6 .41 2 4 .12 9 .26 2 2 .82 2 6 .83 2 5 .54 2 3 .63 2 3 .22 2 1 .23 1 6 .34 1 8 .94 2 6 .62H eter o sced asti city test (F) 1 .36 1 .05 1 .02 1 .55 0 .52 0 .77 0 .64 0 .96 0 .72 1 .48 0 .92 0 .39 

Q6. What was the effect of the structural conditionality variables on expenditure development?

The structural conditionality variables were negative and significant, suggesting relative expenditure compression in countries with a structural conditionality of 2 percentage points of GDP or more. 

Q7. How much of the fiscal balance was improved in non-programme countries?

The fiscal balance improved in two-thirds of all countries by an average of 2 percentage points of GDP between the pre-programme and post-programme periods or between 1993 and 1999 for the nonprogramme countries (Figure 1 and Table 2). 

Q8. What is the effect of structural conditionality on post-programme fiscal performance?

post–programme fiscal performance in those countries was driven by accelerating expenditure compression, which may not be a bad thing, provided, for example, the pre–programme level of spending was wasteful or that a statist budget was replaced with a less intrusive one. 

Q9. What is the appropriate technique for evaluating IMF-supported programmes?

An appropriate technique is the general evaluation estimator (GEE), due to Goldstein and Montiel (1986), which constructs counterfactual economic policies first and then tests the importance of IMF-supported programmes. 

Q10. How high was the probability of a reversal in fiscal adjustment?

15 Gupta et al. (2002) reported that the probability of a reversal in fiscal adjustment was as high as 70 percent at the end of the second post-programme year for low-income countries. 

Q11. What is the likelihood of waivers being positively related to the political clout of individual?

Providing the macroeconomic programme remained on track, the missed condition would likely be waived, the likelihood of waivers being positively related to the political clout of individual countries (Bird, 2002). 

Q12. How many countries improved their fiscal balances after the end of the programme?

The magnitude of the post–programme fiscal improvement was not uniform, however, and nonprogramme countries improved their fiscal balances by more than programme countries: 3 and 12 of a percentage points of GDP, respectively. 

Q13. What was the median end-period observation for non-structural countries?

the nature of the initial disequilibrium differed across countries: in nonstructural programme countries, GDP declined more sharply prior to the programme and their rates of inflation and GDP per capita were higher (Table 3).