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The purpose of this study is to examine the corruption-tax evasion nexus and to establish the strength of relationships among corrupting activities.

The research applied structural equation modelling on selected data from the World Economic Forum Executive Opinion Survey on corruption activities and data on tax evasion triggering factors from the World Development Indicators and the Bank of Ghana to test two hypotheses.

The test of the first hypothesis suggests that corrupting activities significantly cause tax-evading activities in Ghana; hence, there is at least one corrupting activity triggering tax evasion. Testing the second hypothesis revealed that corruption in Ghana exhibits all of the five dimensions of corruption that were examined. Hence, there is correlation among the corrupting activities.

The research is limited by the availability of data; hence, only data for selected variables for the period were examined.

The results are indicative that most emerging economies tend to have more than one type of dominating corruption dimension, which are tax-evading triggers.

The study extends the literature by examining the various dimensions of corruption, analysing the strength of their relationships and how they impact tax evasion in an emerging economy. By identifying and employing specific corrupting activities, there is a better understanding and appreciation of the corruption-tax evasion nexus in the revenue generation process. This may aid emerging economies in the drafting of tax evasion and corruption reduction policies/programmes to ensure the achievement of sustainable development goals.

Debt sustainability and the growing level of external debt in sub-Saharan African (SSA) continue to be significant research priorities. This study aims to examine the corruption-external debt nexus in SSA economies and whether different levels of corruption better explain this relationship.

The panel quantile regression approach was applied to account for the heterogeneous effect of the exogenous variables on external debts. The research covers 30 years of panel data from 30 selected SSA economies for the period spanning from 2000 to 2021.

The empirical findings of the regression analysis demonstrate the heterogeneous influences of the exogenous variables on external debt. While there was a positive impact of foreign direct investment (FDI) inflows on external debts, corruption established a negative relationship with external debt from the 10th to the 80th quantile. The findings showed a positive link between trade openness and external debt, while they also showed a negative relationship between gross fixed capital formation and external debt.

It is implied that corruption “sands the wheels” of external debts in the selected SSA countries. Therefore, the amount of external debt that flows into SSA is inversely correlated with corruption activity.

To the best of the authors’ knowledge, this study is one of the first to use panel quantile regression to analyze how corruption affects debt dynamics across different levels of debt, allowing for a more nuanced understanding of how corruption affects debt dynamics. Based on the findings of this study, SSA countries should create enabling environments to attract FDI inflows and to continue to drive domestic revenue mobilization and capital so as to be less dependent on external debts.