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This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

The growth of both the informal sector and illicit financial outflows necessitated this study, in order to investigate how countries in Africa respond to these realities in terms of mobilization of domestic resources. These are the main motivation for the current study to the extant literature in conjunction with the adoption of employing second-generation econometric techniques which take into account cross-sectional dependence and country-specific heterogeneity.

This study therefore examined the capacity of Africa to mobilize domestic resources amidst rising illicit financial outflows and informal sector size in selected African countries between 2000 and 2018. Second-generation econometric techniques such as cross-sectional dependence tests, slope homogeneity tests, Westerlund (2007) long-run co-integration tests, Eberhardt and Teal (2010) augmented mean group estimations and Kónya (2006) panel causality testing were employed.

Findings revealed the existence of cross-sectional dependence and slope homogeneity in the data series. Findings also supported the existence of depressing long-run impacts of IFOs and ISS on domestic savings. Causality test results were not uniform across variables among countries. Policy recommendations favour formalizing the largely informal African economies through budgetary policy adjustments and commitment to building stronger institutions.

The fragility of the African countries economy and its macroeconomic indicators is suggestive for more policy construction.

This economic reality about the nature of the informal sector is one that has negated the traditional view which holds that economic reforms would make the informal sector shrink as it transits to formal sector. Experiences from Latin America and Africa in fact indicate that the informal sector is actually on an expansionary path in the wake of adjustment and policy reforms. It is often called the unobserved, unorganized or unprotected economy. With this sector growing in size, the possibility of a reverse may not be in sight, owing to the increasing poverty levels and unemployment prevalent in most African countries. Uncertain foreign investment and aid inflows coupled with lower export revenues and high levels of indebtedness have created new impetus to examine the capacity of Africa's fiscal policy regime to mobilise domestic resources for the development of the region. Surprisingly, the last decade witnessed continued rise in Africa's illicit financial outflows amidst large informal sector size (ISS).