Abstract
Do highly indebted countries suffer from a debt overhang? Can debt relief foster their growth rates? To answer these important questions, this article looks at how the debt-growth relation varies with indebtedness levels, as well as with the quality of policies and institutions, in a panel of developing countries. The main findings are that, in countries with good policies and institutions, there is evidence of debt overhang when the net present value of debt rises above 20–25 percent of GDP; however, debt becomes irrelevant above 70–80 percent. In countries with bad policies and institutions, thresholds appear to be lower, but the evidence of debt overhang is weaker and we cannot rule out that debt is always irrelevant. Indeed, in such countries, as well as in countries with high indebtedness levels, investment does not depend on debt levels. The analysis suggests that not all countries are likely to profit from debt relief, and thus that a one-size-fits-all debt relief approach might not be the most appropriate one.
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Notes
The HIPC initiative and Multilateral Debt Relief Initiative (MDRI) offer a comprehensive approach to debt reduction for heavily indebted poor countries pursuing IMF- and World Bank-supported adjustment and reform programs. As of September 2008, assistance in the amount of $117 billion (in nominal terms) had been committed to the 33 post-decision point HIPCs, mostly under the HIPC initiative and through the MDRI. This represents on average about 50 percent of these countries’ 2007 GDP. After the full delivery of debt relief, their debt burden is expected to be reduced by about 90 percent. See www.imf.org/external/pp/longres.aspx?id=4278.
Husain (1997) maintains that the disincentive effects associated with debt overhang have to be implausibly high for a country to be on the negative side of the debt Laffer curve.
See also Cordella, Ricci, and Ruiz-Arranz (2005).
The few other previous studies that relied on net present value calculations of debt were employing Easterly's data set, which ends in late 1990s (http://www.nyu.edu/fas/institute/dri/index.html).
As data for secondary education for the first part of the sample are available only every five years and our regression observations are based on three-year averages, we interpolated the missing observations.
DRS is maintained by the financial data team of the Development Data Group. Aggregate statistics from DRS are published in Global Development Finance. We thank the team leader Ibrahim Levent for providing us with the series (please note that the World Bank does not guarantee the accuracy of the data and accepts no responsibility for any consequence of their use).
We used the “xtabond2” Stata routine developed by David Roodman.
We find some evidence that the use of filtered data helps alleviate the endogeneity problem. For instance, the aid estimates appear negative and significant in the nonfiltered regressions, but they turn insignificant in the filtered regressions.
Results are robust to the exclusion of investment (available from the authors upon request).
We cannot a priori rule out the possibility that the patterns of aid and debt service may be different between countries with different indebtedness levels. We thus allow for different slopes for these variables as well.
The approximation of the interval is due to the fact that calculations are performed on a logarithmic basis. Results based on equally spaced intervals calculated on the level of debt delivered qualitatively similar results. The range of 10–80 percent of GDP covers about 70–80 percent of the debt ratio distributions.
As very few observations lie beyond the irrelevance threshold, and this threshold is identified at the top of the range, the positive coefficient at high levels of debt, β2+β3+β4, is not particularly meaningful. Similarly, the effect of debt is somewhat positive below the overhang threshold, but not significant, which is not surprising as there are few observations in that range as well.
Threshold estimation has been applied for nonparametric function estimation, as well as for empirical sample splitting of a continuously distributed variable. Applying such a methodology, we can endogenously determine the threshold levels of debt (and their confidence intervals) at which the relationship between debt and growth changes. We adapted to our analysis the Gauss programs kindly made available by Hansen at http://www.ssc.wisc.edu/~bhansen.
The threshold variable could be the dependent variable, a regressor or a third variable, not included in the regression, and it is assumed to have a continuous distribution.
The test of the null hypothesis of no threshold against the alternative of threshold is performed using a Wald test under the assumption of homoskedastic errors. Using 1,000 bootstrap replications, the p-value for the threshold model was 0. This suggests that there is evidence of a regime change at the specified levels of debt.
The 95 percent confidence intervals are (5, 37) and (34, 39) , for the debt overhang and debt irrelevance thresholds, respectively.
Although observations tend to be concentrated in particular indebtedness ranges, all intervals are reasonably populated. Indeed, Table 6 indicates that 19, 65, and 16 percent of all good policy observations fall within the low-, medium-, and high-debt regions, respectively. Table 7 shows that the distribution of bad policy observations is 18, 27, and 54 percent for low-, medium-, and high-debt regions, respectively.
One supportive piece of evidence is the increase in litigation by commercial creditors in HIPCs. It suggests that creditors are recognizing that conditions have improved, and expect that there may now be some possibility of repayment.
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Additional information
*Tito Cordella is a lead economist with the Brazil Office of the World Bank. Luca Antonio Ricci is a deputy division chief with the IMF Research Department. Marta Ruiz-Arranz is an economist with the IMF Asia and Pacific Department. The authors thank Andy Berg, Steve Bond, Julian di Giovanni, Gian Maria Milesi-Ferretti, Bruce Hansen, Russell Kinkaid, Aart Kraay, Enrique Mendoza, Prachi Mishra, Alessandro Missale, Jonathan Ostry, Sam Ouliaris, Ugo Panizza, Catherine Pattillo, Alessandro Prati, Raghuram Rajan, David Roodman, and Arvind Subramanian for helpful comments; and Ibrahim Levent for kindly sharing his data set. Naomi Griffin and Utsav Kumar provided excellent research assistance; Katia Berruetta, Nong Jotikasthira, Laura Leon, and Maria Orihuela-Quintanilla provided excellent editorial assistance.