How Terrorism Explains Capital Flight from Africa

We assess the effects of terrorism on capital flight in a panel of 29 African countries for which data is available for the period 1987-2008. The terrorism dynamics entail domestic, transnational, unclear and total terrorisms. The empirical evidence is based on Generalised Method of Moments (GMM) with forward orthogonal deviations and Quantile regressions (QR). The following findings are established. First, for GMM, domestic, unclear and total terrorisms consistently increase capital flight, with the magnitude relative higher from unclear terrorism. Second, for QR: (i) the effect of transnational terrorism is now positively significant in the top quantiles (0.75th and 0.90th) of the capital flight distribution, (ii) domestic and total terrorisms are also significant in the top quantiles and (iii) unclear terrorism is significant in the 0.10th and 0.75th quantiles. Policy implications are discussed

Foreign aid, instability and governance in Africa

This study contributes to the attendant literature by bundling governance dynamics and focusing on foreign aid instability instead of foreign aid. We assess the role of foreign aid instability on governance dynamics in fifty three African countries for the period 1996-2010. An autoregressive endogeneity-robust Generalized Method of Moments is employed. Instabilities are measured in terms of variance of the errors and standard deviations. Three main aid indicators are used, namely: total aid, aid from multilateral donors and bilateral aid. Principal Component Analysis is used to bundle governance indicators, namely: political governance (voice & accountability and political stability/no violence), economic governance (regulation quality and government effectiveness), institutional governance (rule of law and corruption-control) and general governance (political, economic and institutional governance). Our findings show that foreign aid instability increases governance standards, especially political and general governance. Policy implications are discussed

On the Empirics of Institutions and Quality of Growth: Evidence for Developing Countries

We explore a newly available dataset on quality of growth to investigate the effect of institutions on growth quality in 93 developing countries for the period 1990 to 2011. Quality of institutions is measured in term of political risk. The empirical evidence is based on: (i) Ordinary Least Squares (OLS) and Two Stage Least Squares (2SLS) and (ii) cross-sectional and panel data structures. In order to avail room for more policy implications, the dataset is further disaggregated into income levels, namely: Lower middle income (LMIC), low income (LI) and upper middle income (UMIC). Three main findings are established. First, institutions are positively related to the quality of growth. Second, institutions have significantly contributed to growth quality in increasing order during the following time intervals: 2005-2011, 1995-1999 and 2000-2004. Third, the positive nexus between institutions and growth quality is fundamentally driven by LMIC. Policy implications are discussed