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Total Public Debt and Growth in Developing Countries

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Abstract

The global crisis and the expansionary government reaction in many countries have revamped the attention of policymakers and academics on the growth effects of large public debts. Recent empirical studies investigate the impact of public debt on growth in advanced and emerging countries. This article aims at complementing the existing evidence focusing on developing countries, where the increase in domestic borrowing, already started before the crisis, requires a more comprehensive analysis, based not only on external debt, but also on total public debt. Results on a panel of low- and middle-income countries over the period 1990–2007 show that public debt has a negative impact on output growth until it reaches 90 per cent of GDP. Beyond this threshold, the debt effect on growth becomes irrelevant. This nonlinear effect can be explained by country-specific factors, as debt overhang is a growth constraint only in countries with sound macroeconomic policies and stable institutions.

La crise mondiale et les conséquent politiques expansive des gouvernements de plusieurs pays ont amené les décideurs politiques à s′intéresser à nouveau aux effets d′une forte dette publique sur la croissance. Etudes empiriques récents examinent l′impact de la dette publique sur la croissance dans les pays développés aussi bien que dans le pays émergentes. Cet article cherche à apporter des éléments d′information supplémentaires en portant une attention particulière aux pays en développement où la montée de la dette intérieure, datant d′avant la récession, requiert une analyse plus complète qui prenne en compte non seulement la dette extérieure, mais l′ensemble de la dette publique. Les résultats obtenus à partir d′un panel de pays à revenus faibles ou intermédiaires pour la période allant de 1990 à 2007 montrent que la dette publique a un impact négatif sur la croissance au seuil de 90 per cent du PIB, au delà duquel l′effet n′est plus significatif. Cet effet non linéaire s’explique par des facteurs spécifiques à chaque pays puisque le sur-endettement ne constitue une contrainte de croissance que dans les pays pourvus de politiques macroéconomiques saines et d′institutions stables.

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Notes

  1. Abbas and Christensen (2010) complement the vast literature on external debt and growth finding that domestic debt has a hump-shaped effect on GDP growth.

  2. Checherita and Rother (2010) and Cecchetti et al (2011) complement this strand of literature, but focus exclusively on European and OECD countries, respectively.

  3. Regarding the role of institutions, for instance, Eicher and Leukert (2009) suggest that different set of institutions might matter in advanced and developing countries and show that the impact of institutions varies substantially across subsamples: they are about three times more important in developing countries than in OECD countries.

  4. Throughout the article, we refer to good/bad and strong/weak policies and institutions in a relative sense, considering that the institutional setting and the macroeconomic framework of the average country in the sample is far from ideal.

  5. The complete list of countries includes: Albania, Algeria, Argentina, Armenia, Belarus, Belize, Bolivia, Bhutan, Botswana, Brazil, Bulgaria, Cambodia, Cameroon, Cape Verde, Chad, Chile, China, Cote d’Ivoire, Congo DR, Colombia, Costa Rica, Djibouti, Dominican Republic, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Fiji, Gabon, Georgia, Ghana, Guinea, Gambia, Grenada, Guatemala, Guyana, Honduras, Indonesia, India, Jordan, Kazakhstan, Kenya, Kyrgyz Republic, Lao PDR, Lebanon, Lesotho, Lithuania, Latvia, Morocco, Moldova, Mexico, Mongolia, Mozambique, Mauritania, Mauritius, Malawi, Malaysia, Namibia, Nicaragua, Nepal, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Romania, Russian Federation, Rwanda, Senegal, Sierra Leone, South Africa, Sri Lanka, Sudan, Swaziland, St. Lucia, St. Vincent and the Grenadines, Tajikistan, Thailand, Tonga, Tunisia, Turkey, Uganda, Ukraine, Uruguay, Uzbekistan, Venezuela, Vanuatu, Zambia, Zimbabwe.

  6. These data, such as others used to construct the final data set, are publicly available at the Website www.graduateinstitute.ch/md4stata (Catini et al, 2010).

  7. Even if it received several criticisms, the HP filter withstood the test of time and is a standard method for removing trend (Ravn and Uhlig, 2002). Given the annual frequency of GDP data, the smooth parameter is set equal to 6.25, accordingly to what suggested by Ravn and Uhlig (2002).

  8. According to the basic and augmented Solow model (Mankiw et al, 1992) and the empirical findings by Levine and Renelt (1992), the growth rate of population should also be included and secondary education should be taken as a measure of investment in human capital instead of primary education. Instead, we choose this specification as population growth is always not significant and primary education is likely to be more informative in low- and middle-income countries (Kalaitzidakis et al, 2001). However, the main findings do not change relaxing these assumptions; see section ‘Robustness’.

  9. The CPIA score is a composite index measuring the extent to which country policies and institutions create a good environment for growth and poverty reduction. The CPIA indicators are developed by the World Bank and reflect its staff professional judgment, based on country knowledge, policy dialogue and relevant publicly available indicators. To overcome criticisms related to lack of transparency and objectivity, in 2004 the CPIA process and methodology were extensively reviewed by an external independent panel and, starting from 2005, these data are fully disclosed and published in WDI. The broad coverage (136 countries) and the long time horizon (data go back to 1977) make this indicator very useful for empirical analysis based on panel data (International Development Association, 2007).

  10. For an extensive review of the empirics of economic growth using panel data, see Durlauf et al (2005).

  11. For robustness, we also show the estimates obtained collapsing the instruments set; see section ‘Robustness’.

  12. We choose not to estimate the endogenous threshold according to the methodology proposed by (Hansen, 2000) and implemented also by Cordella et al (2010), as this procedure does not consent to take into account the endogeneity issue. We believe that the latter is the most important problem in this kind of exercise, and in the trade-off between the two competing aims we choose to deal with endogeneity. However, we can limit the arbitrariness implied by the spline approach, at least partially circumventing the impossibility to endogenously estimate the debt thresholds, running several spline specifications and choosing the ones the fit best the data.

  13. Lind and Mehlum (2010) develop a test to avoid the misleading interpretation of a concave but monotone curve with an inverse U-shaped one, frequent when the turning point is too close to (or beyond) the end point of the data range. The procedure jointly tests whether the relationship between growth and debt is increasing at low values and decreasing at high values of PUBLIC DEBT within the sample, and it is implemented in Stata by the command UTEST.

  14. We prefer to leave the 90 per cent threshold also for reason of comparability with the evidence documented by Reinhart and Rogoff (2010b) and by Kumar and Woo (2010). Estimating a spline specification with one discontinuity point in occurrence with a level of public debt equal to 10 per cent of GDP uncovers a positive (negative) correlation before (after) the threshold. These results are not shown (but are available upon request from the author) for reasons of space and because they are less informative than the reported model with two breaks.

  15. Summary statistics point out that countries with sound policies and institutions grow twice faster than the ones with a weak institutional setting.

  16. Specifically, total public debt is equal to 49 (66) per cent of GDP in the average country with good (bad) institutions and policies and the difference is statistically significant.

  17. We show the results obtained using the dummy variable proposed by Cheibub et al (2010), but the results do not change when the continuous polity score calculated by the Polity IV project is adopted (Marshall et al, 2010). Similarly, we controlled the robustness of our conclusions including a number of the other variables used in the growth literature, without finding significant changes in the debt effect on growth. Given the lack of informative power of this exercise, we choose to show only the results relative to the most widely used variables.

  18. Results not shown for reasons of space; they are available in the working paper version.

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Acknowledgements

I wish to thank Tito Cordella, Markus Eberhardt, Michele Fratianni, Bernhard Gunter, Douglas Hostland, Uma Kambhampati (the editor), Camelia Minoiu, Ugo Panizza, Luca Papi, three anonymous referees and participants at the 2011 CSAE Conference (Oxford, 2011) and a seminar at the University of Milan for insightful suggestions.

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  1. Università Politecnica delle Marche, MoFiR, Ancona, Italy

    Andrea F Presbitero

  2. Centre for Macroeconomic and Finance Research (CeMaFiR), Milan, Italy

    Andrea F Presbitero

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Presbitero, A. Total Public Debt and Growth in Developing Countries. Eur J Dev Res 24, 606–626 (2012). https://doi.org/10.1057/ejdr.2011.62

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