PurposeThe purpose of this paper is to examine the relationship between the quality of different dimensions of institutional and economic growth in a panel of 15 member ECOWAS.Design/methodology/approachThe study adopts Driscoll and Kraay′s nonparametric covariance matrix estimator, and the spatial error model to account for cross-section dependency, cross-country heterogeneity and spatial dependence inherent in empirical modelling, which has largely been ignored in previous studies. This is because, the likelihood that corruption and human capital cluster in space is very high because factors that affect these phenomena disperse across borders. Similarly, to test the threshold effect, the study adopts the more refined and more appropriate dynamic panel data which models a nonlinear asymmetric dynamics and cross-sectional heterogeneity, simultaneously, in a dynamic threshold panel data framework.FindingsThe empirical evidence supports findings by previous researchers that better-quality political and economic institutions can have positive effects on economic growth. Similarly, our results support a nonlinear relationship between political institutions and economic institution, confirming the “hierarchy of institution hypothesis” in ECOWAS. Specifically, the findings show that economic institutions will only have the desired economic outcome in ECOWAS, only when political institution is above a certain threshold.Originality/valueUnlike previous studies which assume cross-sectional and spatial independence, the authors account for cross-section dependency and cross-country heterogeneity inherent in empirical modelling.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2019-0630
Drawing from the experience of the global financial crisis that sprang forth from the US stock market, an empirical assessment of the dynamic correlation analysis of financial contagion with evidence from (5) African countries (South African, Nigeria, Egypt, Kenya, Tunisia) is presented. Monthly stock prices indices from 2004 to 2018 was analyzed using the dynamic conditional correlation multivariate GARCH model to ascertain the contagious effect of the US to the selected African markets. By analyzing the correlation coefficient series, three phases of the crisis periods were identified {pre-crisis (2004–2007); crisis (2007–2009) and post-crisis (2009–2018), respectively}. The study revealed that a significant relationship exists between the returns of the US market and the African markets. The inspection of the pre-crisis, crisis, post-crisis mean and variance estimation shows that the crisis period is characterized by substantial increases in volatility, establishing that the shock experienced in the US posed a threat to the African markets being examined. Further, evidence revealed that in the crisis period, an increase in correlation (contagion) existed, while a continued correlation (herding) existed in the post-crisis period.
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