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 & 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.

Fighting capital flight in Nigeria: have we considered global uncertainties and exchange rate volatilities? Fresh insights via quantile ARDL model

“…The effects of socio-political and institutional factors, such as military expenditure, terrorism, political instability, corruption control on capital flight were considered in the studies of Efobi and Asongu (2016), Asongu and Amankwah-Amoah (2018), Asongu et al (2019), Osei-Assibey et al ( 2017), and Asongu and Nnanna (2020), respectively. Generally, they provided evidence of the effects of these non-economic factors on capital flight in Sub-Saharan African countries at one time or the other.…”

“…We added RCF t−1 , an autoregressive function showing the effects of past values of capital flight on its current value. This is so expressed, following Asongu and Nnanna (2020) who document that the current value of capital flight is a positive function of its past value (hysteresis). More so, the μ is the stochastic term representing those factors outside the model that might influence its outcome.…”

“…In the same vein, Igwemma et al (2018) document that a survey of six Sub-Saharan African countries (Nigeria inclusive) indicates that between 1989 and 2016, Nigeria alone lost about $21 billion, representing about 60% of capital flight from the six African countries. More worrisome is the fact that the country is bedeviled with a large scale of unemployment, poverty, increasing crime rate, the rising scale of insecurity, and several socio-economic vices, much so that scholars are linking these socio-economic quagmires to capital flight (Ndikumana and Boyce 2018;Effiom and Edet 2019;Effiom et al 2020;Asongu and Nnanna 2020). More so, Pastor (1990) describes it as the major cause of macroeconomic, social, and political disruptions.…”

Doing Business and capital flight: role of financial development

“…This study also showed that lagged capital flight, external debt, foreign direct investment and macroeconomic uncertainty induce capital flight in SSA nations. Also, Asongu and Nnanna (2020) looked at how governance measures may be used to combat capital flight by minimizing the capital flight trap. This study found that previous capital flight values positively influence future capital flight values, indicating evidence of a capital flight trap.…”

Asymmetric effects of capital flight on domestic investment in Nigeria: evidence from non-linear autoregressive distributed lag model

“…These avenues through which capital exits a country's economy, combined with unhealthy domestic macroeconomic and political conditions, result in massive and widespread distortions and loss of confidence by private capital holders. On the macro front, high and persistent inflation, cost of capital differentials, differentials in the rate of return on investment, huge budget deficits, exchange rate devaluation, poor governance, as well as domestic tax cum trade policies may significantly inspire the flight of capital from the domestic economy (Asongu and Nnanna 2020;Asongu and Odhiambo 2019;Gankou et al 2016;Ndikumana 2016;Okoli and Akujuobi 2009;Hermes and Lensink 2000;Cuddington 1987;Lessard and Williamson 1987;Olopoenia 2000).…”