Chapter

Part II Objectives and Outcomes

Author(s):
Charalambos Christofides, Atish Ghosh, Uma Ramakrishnan, Alun Thomas, Laura Papi, Juan Zalduendo, and Jun Kim
Published Date:
September 2005
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Contents of Part II

Appendix I IMF-Supported Programs, 1995–2000
IMF-Supported Programs: General Resources Account, 1995–2000
CountryArrangement TypeApproval DateEnd Date
GRA-Supported Nontransition Countries
AlgeriaEFFMay 1995May 1998
ArgentinaSBAApr. 1996Jan. 1998
ArgentinaEFFFeb. 1998Feb. 2001
ArgentinaSBAMar. 2000Mar. 2003
BrazilSBADec. 1998Dec. 2001
Cape VerdeSBAFeb. 1998Apr. 1999
ColombiaEFFDec. 1999Dec. 2002
Costa RicaSBANov. 1995Feb. 1997
EcuadorSBAApr. 2000Apr. 2001
EgyptSBAOct. 1996Sep. 1998
El SalvadorSBAJuly 1995Sep. 1996
El SalvadorSBAFeb. 1997Apr. 1998
El SalvadorSBASep. 1998Feb. 2000
GabonEFFNov. 1995Nov. 1998
GabonSBAOct. 2000Apr. 2002
IndonesiaSBANov. 1997Nov. 2000
IndonesiaEFFAug. 1998Nov. 2000
IndonesiaEFFFeb. 2000Dec. 2002
JordanEFFFeb. 1996Feb. 1999
JordanEFFApr. 1999Apr. 2002
KoreaSBADec. 1997Dec. 2000
LesothoSBAJuly 1995June 1996
LesothoSBASep. 1996Sep. 1997
MexicoSBAFeb. 1995Aug. 1996
MexicoSBAJuly 1999Nov. 2000
NigeriaSBAAug. 2000Aug. 2001
PanamaSBANov. 1995Mar. 1997
PanamaEFFDec. 1997Dec. 2000
PanamaSBAJune 2000Feb. 2002
Papua New GuineaSBAJuly 1995Jan. 1997
Papua New GuineaSBAMar. 2000May 2001
PeruEFFJuly 1996Mar. 1999
PeruEFFJune 1999May 2002
PhilippinesSBAApr. 1998Mar. 2000
ThailandSBAAug. 1997June 2000
TurkeySBADec. 1999Dec. 2002
UruguaySBAMar. 1996Apr. 1997
UruguaySBAJune 1997Mar. 1999
UruguaySBAMar. 1999Mar. 2000
UruguaySBAMay 2000Mar. 2002
VenezuelaSBAJuly 1996July 1997
ZimbabweSBAJune 1998June 1999
ZimbabweSBAAug. 1999Oct. 2000
GRA-Supported Capital Account Crises Countries
ArgentinaSBAApr. 1996Jan. 1998
ArgentinaSBAMar. 2000Mar. 2003
BrazilSBADec. 1998Dec. 2001
IndonesiaEFFAug. 1998Nov. 2000
KoreaSBADec. 1997Dec. 2000
MexicoSBAFeb. 1995Aug. 1996
ThailandSBAAug. 1997Jun. 2000
TurkeySBADec. 1999Dec. 2002
GRA-Supported Transition Countries
BelarusSBASep. 1995Sep. 1996
BulgariaSBAJuly 1996Mar. 1998
BulgariaSBAApr. 1997June 1998
BulgariaEFFSep. 1998Sep. 2001
CroatiaEFFMar. 1997Mar. 2000
EstoniaSBAApr. 1995July 1996
EstoniaSBAJuly 1996Aug. 1997
EstoniaSBADec. 1997Mar. 1999
EstoniaSBAMar. 2000Aug. 2001
HungarySBAMar. 1996Feb. 1998
KazakhstanSBAJune 1995June 1996
KazakhstanEFFJuly 1996July 1999
KazakhstanEFFDec. 1999Dec. 2002
LatviaSBAApr. 1995May 1996
LatviaSBAMay 1996Aug. 1997
LatviaSBAOct. 1997Apr. 1999
LatviaSBADec. 1999Apr. 2001
LithuaniaSBAMar. 2000June 2001
Macedonia, FYRSBAMay 1995June 1996
Macedonia, FYREFFNov. 2000Nov. 2003
RomaniaSBAApr. 1997May 1998
RomaniaSBAAug. 1999Mar. 2000
RussiaSBAApr. 1995Mar. 1996
RussiaEFFMar. 1996Mar. 1999
RussiaSBAJuly 1999Dec. 2000
UkraineSBAApr. 1995Apr. 1996
UkraineSBAMay 1996Feb. 1997
UkraineSBAAug. 1997Aug. 1998
UkraineEFFSep. 1998Sep. 2001
UzbekistanSBADec. 1995Mar. 1997
IMF-Supported Programs: Poverty Reduction and Growth Facility, 1995–2000
CountryArrangement TypeApproval DateEnd Date
PRGF-Supported Nontransition Countries
BeninESAFAug. 1996Aug. 1999
BeninPRGFJuly 2000July 2003
BoliviaESAFSep. 1998Sep. 2001
Burkina FasoESAFJune 1996June 1999
Burkina FasoESAFSep. 1999Sep. 2002
CambodiaESAFOct. 1999Oct. 2002
CameroonESAFAug. 1997Aug. 2000
CameroonPRGFDec. 2000Dec. 2003
Central African Rep.ESAFJuly 1998July 2001
ChadESAFSep. 1995Aug. 1998
ChadPRGFJan. 2000Jan. 2003
Congo, Rep. ofESAFJune 1996June 1997
Côte d’IvoireESAFMar. 1998Mar. 2001
DjiboutiPRGFOct. 1999Oct. 2002
EthiopiaESAFOct. 1996Oct. 1999
Gambia, TheESAFJune 1998June 2001
GhanaESAFJune 1995June 1998
GhanaESAFMay 1999May 2002
GuineaESAFJan. 1997Jan. 2000
Guinea-BissauESAFJan. 1995Jan. 1998
Guinea-BissauPRGFDec. 2000Dec. 2003
GuyanaESAFJuly 1998July 2001
HaitiESAFOct. 1996Oct. 1999
HondurasESAFMar. 1999Mar. 2002
KenyaESAFApr. 1996Apr. 1999
KenyaPRGFAug. 2000Aug. 2003
MadagascarESAFNov. 1996Nov. 1999
MalawiESAFOct. 1995Oct. 1998
MalawiPRGFDec. 2000Dec. 2003
MaliESAFApr. 1996Apr. 1999
MaliESAFAug. 1999Aug. 2002
MauritaniaESAFJan. 1995Jan. 1998
MauritaniaESAFJuly 1999July 2002
MozambiqueESAFJune 1996June 1998
MozambiqueESAFJune 1999June 2002
NicaraguaESAFMar. 1998Mar. 2001
NigerESAFJune 1996June 1999
NigerPRGFDec. 2000Dec. 2003
PakistanESAFOct. 1997Oct. 2000
RwandaESAFJune 1998June 2001
São Tomé and PríncipePRGFApr. 2000Apr. 2003
SenegalESAFApr. 1998Apr. 2001
TanzaniaESAFNov. 1996Nov. 1999
TanzaniaPRGFMar. 2000Mar. 2003
UgandaESAFNov. 1997Nov. 2000
Yemen, Rep. ofESAFOct. 1997Oct. 2000
ZambiaESAFDec. 1995Dec. 1998
ZambiaESAFMar. 1999Mar. 2002
PRGF-Supported Transition Countries
AzerbaijanESAFDec. 1996Dec. 1999
GeorgiaESAFFeb. 1996Feb. 1999
Kyrgyz RepublicESAFJune 1998June 2001
MoldovaPRGFDec. 2000Dec. 2003
MongoliaESAFJuly 1997July 2000
TajikistanESAFJune 1998June 2001
Appendix II Robustness of the Analysis of the Debt-Stabilizing Current Account

Figures 2.8 and 2.12 of the text compare actual and debt-stabilizing current account balances for GRA- and PRGF-supported countries. This appendix elaborates on those results. The appendix first discusses the robustness of the results under alternative assumptions underlying the calculation of the debt-stabilizing balance as well as excluding transition economies.

Robustness of Calculation of the Debt-Stabilizing Balance

In the calculations underlying the debt-stabilizing current account, long-run growth is estimated as the historical average of growth in U.S. dollars for the five years prior to the commencement of the IMF-supported program. To ascertain whether this result is robust to changes in assumptions, alternative debt-stabilizing current account estimates are derived based on four specifications:

  • Using a 10-year average for growth centered on the first year of the program;
  • Using a 10-year historical average for growth;
  • Limiting the sample to nontransition countries; and
  • Using a 3-year average for the actual current account in percent of GDP.

As shown in Figure 2.A1, the proportion of observations in each of the six categories (classified according to the initial level of debt and whether the current account balance exceeds the debt-stabilizing balance) is very similar to the proportions reported in Figure 2.8 of the text. As such, the broad conclusions about adjustment reported in the text appear robust to alternative assumptions for the underlying calculations.

Figure 2.A1.Sensitivity Analysis on Debt-Stabilizing Current Account Balances in GRA-Supported Programs1

(In percent of GDP)
(In percent of GDP)

Sources: IMF, MONA and WEO databases; and IMF staff estimates.

Note. See Appendix I for a list of countries.

1*significant at 10 percent level and ***significant at 1 percent levels.

For the PRGF countries, an alternative debt-stabilizing current account estimate is derived based on a 10-year average for growth centered on the first year of the program. As for the GRA programs, the results of the baseline scenario are robust to changes in the assumptions since the negative relationship between the current account overadjustment and the external debt ratio remains (Figure 2.A2).

Figure 2.A2.Sensitivity Analysis on Debt-Stabilizing Current Account Balances in PRGF-Supported Programs1

(In percent of GDP)

Sources: IMF, MONA and WEO databases; and IMF staff estimates.

Note: See Appendix I for a list of countries.

1Non-HIPC countries are depicted by triangles; ** significant at 5 percent, *** significant at 1 percent levels.

Appendix III Face-Value-Stabilizing and NPV-Stabilizing Current Account Balances

In the text, it is claimed that the face-value-stabilizing and NPV-stabilizing current account balances are the same under the assumption that the grant element on the outstanding stock of debt is approximately constant between two periods.

Face-Value-Stabilizing Balance

Debt dynamics are given by:

where D is the face value of debt and CA is the current account balance. As a ratio to GDP:

The face-value-stabilizing current account balance, ca*, has the property dt+1 = dt:

NPV-Stabilizing Balance

Starting from the face value dynamics:

which can be written in NPV terms as:

where GE is the grant element. Then, as a ratio to GDP:

Now assume that GEt+1GEt:

The NPV-stabilizing current account balance, ca**, has the property that npvt+1 = npvt:

which is the same as the debt-stabilizing current account balance since dt+1 = npvt+1/(1 – GE):

Appendix IV Confronting the Counterfactual: Estimating the Effects of IMF-Supported Programs

Various approaches have been used to estimate a country’s expected gain from participation in an IMF-supported program. Each approach tries to measure the impact of IMF-supported programs by comparing the actual result with a counterfactual using either country data or information from a sample of countries (Table 2.A1); the key difficulty that all studies face lies in constructing a convincing counterfactual.

Table 2.A1.Summary of Empirical Evaluations of the Effect of IMF-Supported Programs
Effects on
Time PeriodNumber of ProgramsNumber of CountriesBalance of paymentsCurrent accountInflationGrowth
Before-after
Reichman and Stillson (1978)1963–727900+
Connors (1979)1973–7731230000
Killick (1984)1974–79382400–*0
Zulu and Nsouli (1985)1980–813522000
Goldstein and Montiel (1986)1974–816858
Pastor (1987)1965–8118+*000
Khan (1990)1973–8825969++*
Killick, Malik, and Manuel (1992)1979–8516+*+*–*+*
Schadler and others (1993)1983–935519++
Simulation/estimation
Khan and Knight (1981)1968–7529++
Khan and Knight (1985)1968–7529++
Control group
Donovan (1981)1970–761212+
Donovan (1982)1971–807844++
Goldstein and Montiel (1986)1974–816858++
Gylfason (1987)1977–793214+*00
Loxley (1984)1971–82383800–*0
Khan (1990)1973–8825969+*+*+
Przeworski and Vreeland (2000)1951–902260–*
Generalized evaluation
Goldstein and Montiel (1986)1974–816858+
Khan (1990)1973–8825969+*+*–*
Conway (1994)1976–8621773+*–, +*
Bagci and Perraudin (1997)1973–9268+*+*+*
Dicks-Mireaux and others (2000)1986–918874+*
Sources: Conway (1998) and IMF staff updates.Note. * indicates statistically significant results.; 0 indicates that the results of the various studies were inconclusive; + indicates a positive effect on the variable indicated; and – indicates a negative effect on the variable indicated.
Sources: Conway (1998) and IMF staff updates.Note. * indicates statistically significant results.; 0 indicates that the results of the various studies were inconclusive; + indicates a positive effect on the variable indicated; and – indicates a negative effect on the variable indicated.

Before-after calculations compare the performance of the program country in the program period with its own performance in the period before participation. This method suffers from biases associated with a change in the economic structure of the country or shocks between both periods that are unrelated to the decision to participate in a program. Estimation and simulation can be used to address the bias in the first method either by: (1) estimating the economic model and policy reaction function of the participating country before and during the IMF-supported program; or (2) pairing the program country with one or more nonprogram countries and attributing differences in performance to program participation. This modification (control group comparison) may not lead to an improvement because of cross-country differences in exogenous shocks, in economic structures, and in the participation decision. For example, the choice of participating in an IMF-supported program can lead to its own biases because of the unique features of this choice and requires its own controls. These concerns may be reduced, however, by assembling data for a large group of countries, dividing the countries into participants and nonparticipants, controlling for the choice of an IMF-supported program, and testing for statistical significance of differences in average macro-economic performance and policy. The generalized evaluation estimator removes external influences by estimating the channels through which IMF-supported programs and external shocks affect macroeconomic outcomes in the participating and nonparticipating country.

Academic studies on the effects of IMF-supported programs have used all these methods and have tended to concentrate on broad outcomes during the program period such as improvements in the current account and overall balance of payments, inflation, and economic growth. Studies have generally found that the balance of payments has improved, but while inflation has fallen, the decline is generally not significant, partly because most of these studies were conducted before the sharp decline in inflation in the 1990s. Findings on the effects of IMF-supported programs on growth are mixed. Some studies find a significant positive relationship with respect to growth in the short term (Killick (1995), Bagci and Perraudin (1997), and Dicks-Mireaux and others (2000)) and up to three years after the program (Conway (1994)), whereas other studies, in particular, Khan (1990) and Przeworski and Vreeland (2000) find significant negative growth effects in the short and long term. Conway (2000) shows that the macroeconomic performance of countries under IMF-supported programs declines with the length of time a country spends under such a program. Perhaps surprisingly, in light of the IMF’s responsibility for external sustainability, no academic study has considered the effects of an IMF-supported program on the evolution of debt.

Traditionally, studies have not distinguished between Stand-By, EFF, and PRGF programs although the few studies that have made this separation find sizable differences. Kochhar and Coorey (1999) find that whereas in the early 1980s, ESAF countries grew at about 1 percentage point a year less than non-ESAF poor countries, by the early 1990s, this negative differential had vanished. Barro and Lee’s (2002) analysis of SBAs and EFFs showed no growth improvement following IMF-supported programs over the 1970–2000 period.

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1

To include both program and postprogram experience, the sample covers programs approved over the period 1995–2000; see Appendix I. During this period, the IMF’s engagement with low-income countries underwent important changes with the shift from the ESAF to the PRGF. The findings for low-income countries in this paper pertain primarily to ESAF-supported programs.

2

See Schadler and others (1995), which covered a sample of Stand-By and Extended Arrangements approved between 1988 and 1991.

3

As discussed below, among GRA-supported programs there is a subset where the primary focus is on the endorsement of a policy package, since IMF financing is not envisaged. In some of these cases, the thrust of the program is to reduce domestic interest rates and retain access to external markets rather than external adjustment.

4

As discussed below, this is less true of more recent programs.

5

As discussed below, the pattern for capital account crises is also similar in some respects, though it differs markedly for the behavior of fiscal policy.

6

For Figures 2.1 through 2.5, only the most recent program is taken in cases of multiple arrangements. To minimize the effect of outliers, all variables are mapped to lie in the interval (–100,100) percent by the transformation 100(z/100+z,) if z>0 and 100(z/100–z) if z<0, where z is the annual growth rate or percentage of GDP, as applicable.

7

The average duration of Stand-By Arrangements, which constitute 75 percent of the sample of Stand-By and EFF programs, is 15 months.

8

The Independent Evaluation Office (IEO) study of “Fiscal Adjustment in IMF-Supported Programs” (IEO, 2003b) finds that most of the fiscal adjustment takes place in the first year of the program.

9

Movements in the real exchange rate are too small to have contributed significantly to the external adjustment; while depreciating by about 5 percent in the program period, it reappreciated by about 5 percent over the subsequent two years.

10

A precautionary arrangement is one under which the authorities indicate that they do not intend to make a purchase. It is not legally different from a nonprecautionary arrangement, since the member retains the right to draw (provided that it has met the relevant conditionality).

11

There is no definitive sample of “capital account crises”; Ghosh and others (2002) list Mexico (1995), Argentina (1995), Thailand (1997), Korea (1997), Indonesia (1997), and Brazil (1998). To this list may be added the 2000 augmentation of the 1999 Stand-By Arrangement for Turkey, and also the Stand-By Arrangements for Argentina (2000) and Brazil (2001 and 2002). In Figure 2.3, to illustrate the crisis dynamics more clearly, year “t” is aligned as follows: Argentina (1995), Brazil (1999), Indonesia (1998), Mexico (1995), Korea (1998), Thailand (1998), and Turkey (2001).

12

In a few cases, for example, Turkey, the member had an IMF arrangement in place when the crisis broke.

13

As noted above, the sample period covers primarily ESAF arrangements and preliminary experience with PRGF arrangements.

14

More than half of ESAF/PRGF-supported programs over the period 1995–2000 introduced trade liberalization measures.

15

For a fuller discussion see Daseking and others (2004) and IEO (2004).

16

For instance, during the last quarter of 1997, the real exchange rate depreciated by 35 percent, private capital outflows amounted to almost 25 percent of GDP, and the current account balance improved by some 12 percent of GDP; as a result of the severe economic disruption, output growth fell by 12 percentage points.

17

IMF financing cannot resolve a “solvency” problem (whereby the country is unable to generate the required surpluses to satisfy the intertemporal budget constraint), since it effectively replaces one source of financing (the private sector) with another (the official sector). There are two possible exceptions. First, to the extent that IMF resources are made available at a cost below the marginal cost of market borrowing, the present value of the debt is correspondingly lower; for plausible amounts of IMF financing, however, this effect is likely to be negligible. Second, the IMF’s support of a member’s adjustment program could, via confidence effects, lower the market cost of its borrowing and help spur growth, making an otherwise unmanageable level of debt more sustainable.

18

See “Debt Sustainability in Low-Income Countries” (IMF, 2004) and Bulíř and Hamann (2003) and Bulíř and Lane (2002).

19

A useful summary of the issues and work in this area may be found in “Private Sector Involvement in the Prevention and Resolution of Financial Crises—Report of the Managing Director to the International Monetary and Financial Committee” (IMF, 2001).

20

These floors are intended as safeguards or “tripwires” that indicate a possible need to reconsider program policies: they are not intended to delineate the baseline adjustment path.

21

Of course, IMF disbursements add to the country’s foreign exchange liabilities and therefore require it to adjust eventually. These disbursements, however, help the country to avoid abrupt adjustment that would be disruptive to economic activity.

22

While IMF disbursements raise GIR, there is no change in NIR since assets and liabilities increase by the same amount. For the median program country, the IMF disburses about 1 percent of GDP (20 percent of the current account balance for the previous year) during the first year of a program, varying narrowly between 1 percent of GDP for “traditional” SBAs and EFFs (40 percent of the current account for the previous year) and 1.2 percent of GDP (47 percent of the current account for the previous year) for capital account crisis countries.

23

This may explain why, in Figure 2.2, the current account adjustment is so similar in precautionary and nonprecautionary arrangements.

24

In some cases the IMF has helped a country avoid a potentially costly default (Mexico, 1995).

25

See Cottarelli and Curzio (2002) for a discussion. Killick, Malik, and Manuel (1992) and Bird and Rowlands (1997) find no empirical evidence for a catalytic effect of IMF support. In contrast, Marchesi (2003) shows that such support helps a country to reschedule its private debt obligations, while Mody and Saravia (2003) note that it raises the likelihood that a debtor country may issue a bond and reduce its spreads at the time of issuance. Bordo, Mody, and Oomes (2004) show that IMF-supported programs are effective in reducing bond spreads when the debt-to-GDP ratios are between 30 percent and 70 percent. They also highlight that, while precautionary programs have no independent effect on the probability of bond issuance, they are associated with significantly reduced spreads. Further, they stress that IMF-supported programs raise capital flows after one year in countries with poor initial conditions.

26

While macroeconomic policies were arguably insufficiently strong, thereby failing to engender a return of confidence, the issue of policy appropriateness remains an open question. Benelli (2003) has found that the disparity between projections and realizations of capital flows is positively associated with the size of financial assistance and negatively associated with policy adjustment, but this finding only suggests that the amount of financing and the type of policy choices were associated with differences in projection errors and were not necessarily related to actual movements in capital flows.

27

Stabilizing the external debt ratio implies intertemporal solvency; though solvency does not require a stable debt ratio—see IMF (2002).

28

The debt-stabilizing current account balance (in percent of GDP) is given by ca* = –gd, where g is the medium-term growth rate of the U.S. dollar value of GDP (calculated as the five-year average of the growth of U.S. dollar value of GDP), and d is external debt (in percent of GDP) averaged over end-period t and end-period t+1. Although FDI does not incur additional debt, it is a liability for the recipient country that will eventually need to be serviced in the form of repatriated profits.

29

For convenience, the range from 40 percent to 60 percent of GDP is shaded in the figure. For a discussion of external debt thresholds see IMF (2002 and 2003a), and Reinhart, Rogoff, and Savastano (2003). On thresholds for public debt, see IMF (2003a and 2003b).

30

In a few of these cases in Section I, however, the current account balance reflected positive terms of trade shocks rather than import compression. Specifically, about a quarter of these cases are associated with positive terms of trade shocks, positive real GDP growth, and constant or rising imports.

31

For example, Korea underwent a sharp adjustment of its current account balance in late 1997 and early 1998 in the face of capital outflows, accumulating more foreign exchange reserves than programmed in the latter half of 1998 as capital inflows resumed.

32

That is, countries better able to adjust externally through the choice of appropriate policies may be more likely to seek IMF support.

33

There were six PRGF-supported programs with non-HIPCs, of which, three had current account balances similar to the HIPCs.

34

Of the 1.7 percent of GDP larger than projected current account deficits, 1 percent of GDP is financed by greater borrowing and 0.7 percent of GDP by lower accumulation of reserves than programmed.

35

If this grant shortfall is viewed as temporary—for instance, a delay in disbursement because of administrative reasons—then a correspondingly larger current account deficit would be warranted as the country borrows against this temporary negative shock. In fact, countries ran a current account deficit that was larger than the shortfall in grant disbursements.

36

Figure 2.12 is based on the current account balance that stabilizes the face value, rather than the net present value (NPV) of debt. It can be shown, however, that under the assumption that the grant element on the existing stock of debt is approximately constant between two periods, the face-value-stabilizing balance will equal the NPV-stabilizing balance (see Appendix III).

37

Empirical studies have found that, on average, low-income countries face an increased risk of debt distress at an NPV debt to GDP ratio of 45 percent (IMF, 2004). Assuming an average grant element of 40 percent, this roughly corresponds to a nominal debt ratio of about 80 percent of GDP. This is shown as a vertical line in the figure, though—as with market borrowers—a range of debt levels, rather than a specific level, might be more appropriate given the difficulties of establishing precise thresholds at which debt distress is likely to occur.

38

The HIPC Initiative was launched in September 1996. As of end-December 2004, 15 countries had reached completion point under the enhanced HIPC Initiative.

39

For this purpose, the actual debt ratio is replaced by debt ratio after relief in calculating the debt-stabilizing balance, CA*=g*npv¯, where g* is the historical growth rate of the U.S. dollar value of GDP, and where npv¯ is the debt ratio that will prevail following debt relief.

40

Indeed, even this counterfactual calculation underestimates the buildup of debt that would have occurred in the absence of debt relief because it is based on actual current account balances rather than the balances that would have prevailed had interest payments been made as scheduled.

41

Likewise, the difference between the implied and actual debt stock for GRA countries is only 6 percent of GDP, and has remained fairly constant since 1993.

42

For the purposes of this section a GRA-supported program applies to countries that were not PRGF eligible as of mid-2003 (and vice versa for PRGF-supported programs). The distinction between “GRA-supported” and “non-PRGF eligible” arises because, particularly in the early 1990s, some low-income countries had either stand-alone Stand-By Arrangements or simultaneous Stand-By and ESAF/PRGF programs. The discussion in this section and the results presented in Table 2.3 classifies these countries as PRGF-supported programs—the assumption is made that the objectives pursued are closer to those of other low-income countries despite their support from GRA resources.

43

Empirical studies face a number of other problems; Appendix IV surveys the literature.

44

This finding is consistent with the Schadler and others (1995).

45

For instance, Deininger and Squire (1996) and Dollar and Kraay (2001) argue that the poor benefit more from increasing aggregate output than by reducing inequality through redistribution. Moreover, Ravaillon and Chen (1997) have found that changes in inequality are uncorrelated with changes in average living standards. Quah (2001) argues, based on an analysis of India and China, that improvement in living standards due to aggregate economic growth overwhelms any deterioration due to increases in inequality. To evaluate the association between real GDP and poverty, the poverty indicator based on the fraction of the population living on less than $2 a day was correlated with the level of real GDP per capita in 1995. When purchasing power parity deflators are used for the real GDP calculation, the correlation coefficient is –0.7, whereas when the current exchange rate is used, the correlation coefficient is –0.6. Either measure of real output therefore appears to be (inversely) related to poverty.

46

This inverse relationship between inflation and income inequality is documented in Bulíř and Gulde (2000) and Bulíř (2001).

47

A similar equation for upper- and lower-middle-income countries (non-PRGF countries) with IMF-supported programs yields slightly larger coefficients for growth of G-7 countries and for macroeconomic indicators. The coefficients on the effects of internal and external shocks are similar to those of PRGF-eligible countries, but they appear to play a less important role in explaining changes in growth. This may reflect a more diversified structure of the economy.

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