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Nexus between total natural resource rents and public debt in resource-rich countries:A panel data analysis

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  • Ampofo, Gideon Minua Kwaku
  • Jinhua, Cheng
  • Bosah, Philip Chukwunonso
  • Ayimadu, Edwin Twum
  • Senadzo, Patrick

Abstract

The study investigates the long-run and causal correlation between total natural resource rents and economic development in a public debt function. We integrate trade openness, inflation, population growth, and unemployment in the model as additional regressors. Empirical evidence is premised on an annual balanced panel data between 1991 and 2017 for 17 selected resource-rich countries. Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) econometric method is employed as the most suitable estimation model that deals with various econometric issues, including heterogeneity between the selected countries. The Johansen Fisher Panel Cointegration Test and Kao Test reveal a cointegration between the variables. The PMG-ARDL results suggest a significant positive relationship between countries’ resource earnings and public debt in the long-run and a negative link in the short-run. Implying that overdependence on total natural resource rents affects public debt sustainability of the panel countries if effective fiscal and economic management policies are disregarded. The panel Vector Error Correction Model (VECM) result shows a causal relationship between resource abundance and government debt. Finally, bidirectional causal relationships are found to exist between natural resource rents and public debt accumulation. To avoid debt-overhang incidence, governments of resource-abundant countries should engage in responsible borrowing, invest in sectors that will stimulate development, and implement anti-corruption policies to seal revenue leakages.

Suggested Citation

  • Ampofo, Gideon Minua Kwaku & Jinhua, Cheng & Bosah, Philip Chukwunonso & Ayimadu, Edwin Twum & Senadzo, Patrick, 2021. "Nexus between total natural resource rents and public debt in resource-rich countries:A panel data analysis," Resources Policy, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721002877
    DOI: 10.1016/j.resourpol.2021.102276
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