This paper presents the first-ever analysis of South African and Eurozone road fuel markets for the possibility that firms may be manipulating the tax system to conceal rent-seeking behavior using the nonlinear ARDL model recently advanced by Shin et al. (2013). The paper also examines these markets for asymmetric price adjustment following changes in crude oil costs in the aftermath of the 2007-2008 Global Financial Crisis. Monthly data for gasoline, automotive diesel and costs of imported crude oil from November 2004 to August 2016 were used. The results indicate that while the Eurozone road fuel markets are fraught with the problems of long-run rent-seeking, rockets and feathers effect, and the possibility that firms may be exploiting the tax system to conceal rent-seeking behaviors, the South African markets are free from these problems. Even though South Africa and the Eurozone countries have high oil import dependency ratios, this paper shows that government regulatory activities somewhat account for the difference in market outcomes.

We examine the dynamics of output connectedness of Asian Pacific Economic Cooperation (APEC) economies using time‐varying, region‐specific, generalised connectedness measures. We find that the connectedness of APEC economies with the rest of the world is quite substantial, with the 2008–09 Global Financial Crisis increasing the connectedness measures above their precrisis levels. The USA, China, and Korea are shown to be systemically important and to dominate APEC’s real activities, while outside the APEC region the roles of India and the UK are also non‐negligible. These results suggest that the majority of APEC economies are considerably open to output shocks from the dominant economies such that policymakers in APEC must be continuously conscious of headwinds originating from these sources.

This paper presents the first value‐added model of private school effects in Peru, using the unique Young Lives longitudinal data. Raw differences in test scores show that children in private schools have higher test scores in both maths and Peabody Picture Vocabulary Test for the most part. Estimates from ordinary least squares regression also indicate the existence of private school premium in maths. However, when we controlled for prior achievement, we find no private school effects in learning. These results hold true for both low‐ability and high‐ability children and are robust to sorting on unobserved ability, grouping on lag structures and transfer between private and public schools. © 2019 John Wiley & Sons, Ltd.

Although years of schooling and enrolment rates can be used as measures of educational progress, they are inadequate in explaining children's learning process. This is because the benefits of education are ultimately determined by the skills acquired in school, and not just the number of years spent in education. This paper investigates the determinants of learning among primary school children in Ethiopia using Round 2 and 3 of the unique Young Lives survey data. Using the framework of the education production function, the inherent endogeneity problem is discussed and addressed as much as data permits. Empirical evidence suggests that children in private schools do not learn better than their counterparts in public schools. In addition, household income has little effect on children's learning. This suggests that government‐backed income transfer programmes to low‐income households may not achieve substantial improvement in learning outcomes. Rather, the number of hours spent studying at school may be more relevant in improving children's learning outcomes. Thus, full‐day teaching as against the erstwhile shift teaching system in Ethiopia should be fully implemented and sustained across regions and districts.

This paper examines the hedging effectiveness of US stocks against uncertainties due to equity market (financial risk) and pandemics (health risk), including COVID-19 pandemic.Consequently, we consider two categories of US stocksdefensive and non-defensive stocks drawn from ten different sectors and distinctly analysed over two data samplespre-and post-COVID periods. We construct a predictive panel data model that simultaneously accounts for both heterogeneity and common correlated effects and also complementarily determine the predictive power of accounting for uncertainties in the valuation of US stocks. We find that hedging effectiveness is driven by the types of stocks and measures of uncertainty. Defensive stocks provide a good hedge for pandemic-induced uncertainty, and the hedging effectiveness is higher during calm market conditions as compared to turbulent conditions, while both categories lack hedging capability in the face of equity-induced uncertainty. Finally, we find that the inclusion of uncertainty in the predictive model of US stock returns improves its forecasts and this conclusion is robust to alternative measures of uncertainty and multiple forecast horizons.