Governance and the capital flight trap in Africa

Abstract

The study examines the use of governance tools to fight capital flight by reducing the capital flight trap. Two overarching policy syndromes are addressed in the study. It first assesses whether governance is an effective deterrent to the capital flight trap in Africa, before examining what thresholds of government quality are required to fight the capital flight trap in the continent. The following findings are established. Evidence of a capital flight trap is apparent because past values of capital flight have a positive effect on future values of capital flight. The net effects from interactions of the capital flight trap with political stability, regulation quality, economic governance and corruption-control on capital flight are positive. The critical masses at which ‘voice and accountability’ and regulation quality can complement the capital flight trap to reduce capital flight are respectively, 0.120 and 0.680, which correspond to the best performing countries. Policy implications are discussed.

Keywords:

• Governance
• capital flight
• capital flight trap
• Africa

JEL CLASSIFICATION CODES:

• C50
• E62
• F34
• O55
• P37

Notes

Disclosure statement

The authors are self-funded and have received no funding for this manuscript. The authors also have no conflict of interest.

This article does not contain any studies with human participants or animals performed by the authors.

Notes

1 The capital flight trap can be defined as persistence in capital flight whereby past capital flight positively affects future capital flight. The conception and definition of the capital flight trap is consistent with contemporary literature on persistence in macroeconomic phenomena in which hysteresis in macroeconomic phenomena is apparent when past values of macroeconomic phenomena have a positive incidence on future values of the corresponding macroeconomic phenomena, notably: persistence in terrorism (Asongu, 2019) and inequality (Tchamyou, 2020a). In the attendant persistence literature, one lag is enough to capture past information. The one lag rule of thumb is consistent with the data of capital flight in this study because, the correlation between level and first lag series’ of capital fight is high (i.e. exceeds the rule of thumb threshold of 0.800) while the correlation between the level and second lag series’ is not high.

2 “First, the null hypothesis of the second-order Arellano and Bond autocorrelation test (AR(2)) in difference for the absence of autocorrelation in the residuals should not be rejected. Second the Sargan and Hansen overidentification restrictions (OIR) tests should not be significant because their null hypotheses are the positions that instruments are valid or not correlated with the error terms. In essence, while the Sargan OIR test is not robust but not weakened by instruments, the Hansen OIR is robust but weakened by instruments. In order to restrict identification or limit the proliferation of instruments, we have ensured that instruments are lower than the number of cross-sections in most specifications. Third, the Difference in Hansen Test (DHT) for exogeneity of instruments is also employed to assess the validity of results from the Hansen OIR test. Fourth, a Fisher test for the joint validity of estimated coefficients is also provided” (Asongu & De Moor, 2017, p.200).

3 0.172 is the mean value of Economic Governance.

Additional information

Notes on contributors

Simplice A. Asongu

Simplice A. Asongu is the Lead Economist and Director of the African Governance and Development Institute.

Joseph Nnanna

Joseph Nnanna is the Chief Economist of the Development Bank of Nigeria.