African Development ReviewVolume 30, Issue 3 p. 327-327 Issue InformationFree Access AIMS, SCOPE AND AUTHOR GUIDELINES First published: 09 September 2018 https://doi.org/10.1111/1467-8268.12293AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume30, Issue3September 2018Pages 327-327 RelatedInformation

Abstract The linkages between international trade and economic performance has received significant attention from policymakers and researchers. There is consensus in the literature that improved trade openness corresponds to improved economic growth. In this study, we argue that trade openness has a significant impact on population health outcomes and financing. The study employed a balanced panel data for 42 sub‐Saharan African (SSA) countries over the period 1995–2013. Population health status was measured by total life expectancy at birth, infant mortality rate and under‐five mortality rate. Three main estimation models were used: (1) fixed effect (FE); (2) random effect (RE); and (3) the generalized method of moments (GMM) in estimating the relationships. The results showed that trade openness has a positive and significant effect on life expectancy, a negative and significant effect on the infant mortality rate and a negative impact of trade openness on the under‐five mortality rate. A positive effect of trade openness on health financing was also realized. The findings of the study support international trade integration and emphasize the need for countries to be conscious of gains from trade within sub‐sectors of the economy.

Abstract Despite technological progress and society's changing lifestyles, preferences and attitudes towards public healthcare, little is known about the impact of these non‐economic factors (NEFs) on public health expenditure because existing studies have focused mainly on macroeconomic factors. This paper employs a structural time series model (STSM) to re‐examine and quantify the contributions of the key underlying drivers of public health expenditure while accounting for technological progress and other NEFs that have hitherto been ignored. The STSM captures the impact of NEFs via a stochastic trend component. The results of our application for Nigeria using data (1971–2013) sourced from the World Bank and Central Bank of Nigeria are robust to a battery of unit‐root and cointegration tests. We found that the key macroeconomic factors — economic output, current account and fiscal balance, official development assistance, oil revenue as well as urbanization and crude birth rate — are important drivers of public health expenditure. Technological progress and other NEFs have a non‐linear significant impact that varies with time and remains the largest contributor to annual change in public health expenditure. Policy implications from our findings are noted. Specifically, understanding and stabilizing both the macroeconomic and non‐economic factors are crucial to improve public health expenditure.

RésuméCe papier a pour objectif d'examiner les effets de la croissance économique sur les émissions de dioxyde de carbone (CO2) et sur l’évolution de la température au Cameroun sur la période 1972–2010. Le test de cointégration par les retards échelonnés ou Auto Regressive Distributed Lags (ARDL) indique l'existence d'une relation de long terme sous forme de « N inversé » entre la croissance économique et les indicateurs de dégradation environnementale (émissions de CO2 et évolution de la température) retenus dans cette étude. Ensuite, on constate que la consommation d’énergie et les activités industrielles accroissent les émissions de CO2 mais pas l’évolution des températures au Cameroun. Par contre, l'ouverture commerciale entraine une baisse du niveau de CO2 mais pas de la température. Ce résultat laisse entrevoir que le Cameroun exporte ou transmet sa pollution vers l'extérieur ou vers d'autres pays.

Abstract The study assesses the degree and patterns of horizontal inequity in maternal and child health care utilization in Nigeria. Horizontal inequity was estimated using concentration curves and a standardized concentration index, which was decomposed into need and non‐need variables to capture the major drivers of inequity in utilization. Maternal and child health care utilization was measured by antenatal visits, skilled delivery and immunization utilization. Four rounds of Nigerian Demographic and Health Survey (DHS) data (1999, 2003, 2008, 2013) were used. The results show a positive horizontal inequity index from 1999 to 2013; which indicates that there is pro‐rich inequity in utilization of antenatal, skilled delivery and immunization, respectively. The study concludes that there is higher and increasing inequity in maternal health care while inequity in utilization of child health care decreased over time with wealth status and education as the major non‐need drivers of inequity in utilization. Interventions to enhance women's wealth status and education could significantly improve equity in skilled delivery and antenatal care utilization. Hence wealth creation, women empowerment and education should be given more attention to improve the deteriorating equity in maternal health care utilization.

African Development ReviewVolume 29, Issue 3 p. 539-540 Book Review Book Review Mawuko Kokou Kponnou, Mawuko Kokou KponnouMacroeconomic Policy, Forecasting and Research Department, African Development Bank, Abidjan, Côte d'Ivoire; e-mail: k.kponnou@afdb.orgSearch for more papers by this author Mawuko Kokou Kponnou, Mawuko Kokou KponnouMacroeconomic Policy, Forecasting and Research Department, African Development Bank, Abidjan, Côte d'Ivoire; e-mail: k.kponnou@afdb.orgSearch for more papers by this author First published: 18 September 2017 https://doi.org/10.1111/1467-8268.12289 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume29, Issue3September 2017Pages 539-540 RelatedInformation

Foreign aid plays an important role in promoting economic development in Africa. Recently, several countries, most notably China, have emerged as alternative sources of foreign aid. However, their motives for providing foreign aid have been questioned. The present study examines and compares determinants of China's and Japan's foreign aid allocations in Africa. It assumes that the distribution of foreign aid was determined by the aid donors’ self-interest and also by the aid recipients’ needs. Three panel model methods, namely, the pooled OLS method, the one-way fixed effects method and the two-way fixed effects methods, were employed to examine and compare the patterns of China's and Japan's foreign aid allocation in Africa. The main finding was that the provision of foreign aid by China and Japan was primarily driven by the aid donors’ self-interest. Additionally, the size of population in a recipient country was an important element to determine China's and Japan's aid allocations. The findings also suggest that Japan tended to pay more attention to the aid recipient countries’ needs as well as to the quality of governance and institutions in these countries. Overall, the findings indicate that there was no considerable difference in the motives for the provision of aid between the two aid donor countries.

Abstract Sub‐Saharan Africa (SSA) has been receiving foreign aid for many decades; nonetheless, it ranked among the poorest regions in the world. This study revisits the aid effectiveness debate quantitatively by investigating the relationship among foreign aid, governance and economic growth in SSA using more recent data from 1996 to 2012 and testing for heterogeneity in aid recipient countries. Fundamental questions raised in this study are: does aid work the same way in all regions and group of countries in SSA? Do governance and size of aid matter? Employing the system generalized methods of moments (system GMM) technique, results show that foreign aid has an insignificant negative relationship with economic growth in aggregate SSA. However, one cap does not fit all in SSA as heterogeneity across aid recipients has implications for aid effectiveness. Moreover, governance and size of aid complement each other to improve growth in SSA. This study has been able to show quantitatively that a general policy for countries in SSA is not good enough for aid effectiveness; donors should increase the size of aid, and governance in recipient countries must improve. In conclusion, heterogeneity, governance and size of aid matter for aid effectiveness in SSA.

Abstract This paper investigates the determinants of educational achievements using household data collected in 2009 and 2010 from six sub‐Saharan African countries. The econometric strategy combines estimation of random effect Probit models and variance decompositions to assess the relative contributions of between‐family and within‐family inequalities in schooling. Whilst the selected countries are rather heterogeneous in terms of economic development and public education expenditures, very similar results are found in five out of the six sub‐Saharan countries. More than two‐thirds of differences in schooling are explained by educational differences between families and within‐household inequalities are very difficult to explain by observed family characteristics.