SUMMARYAccurate crop varietal identification is the backbone of any high-quality assessment of outcomes and impacts. Sweetpotato (Ipomoea batatas) varieties have important nutritional differences, and there is a strong interest to identify nutritionally superior varieties for dissemination. In agricultural household surveys, such information is often collected based on the farmer's self-report. In this article, we present the results of a data capture experiment on sweet potato varietal identification in southern Ethiopia. Three householdbased methods of identifying varietal adoption are tested against the benchmark of DNA fingerprinting: (A) Elicitation from farmers with basic questions for the most widely planted variety; (B) Farmer elicitation on five sweet potato phenotypic attributes by showing a visual-aid protocol; and (C) Enumerator recording observations on five sweet potato phenotypic attributes using a visual-aid protocol and visiting the field. In total, 20% of farmers identified a variety as improved when in fact it was local and 19% identified a variety as local when it was in fact improved. The variety names given by farmers delivered inconsistent and inaccurate varietal identities. Visual-aid protocols employed in methods B and C were better than those in method A, but greatly underestimated the adoption estimates given by the DNA fingerprinting method. Our results suggest that estimating the adoption of improved varieties with methods based on farmer self-reports is questionable and point towards a wider use of DNA fingerprinting in adoption and impact assessments.

BackgroundEthiopia has made considerable progress in maternal, newborn, and child health in terms of health outcomes and health services coverage. This study examined how different groups have fared in the process. It also looked at possible factors behind the inequalities.MethodsThe study examined 11 maternal and child health outcomes and services: stunting, underweight, wasting, neonatal mortality, infant mortality, under-5 mortality, measles vaccination, full immunization, modern contraceptive use by currently married women, antenatal care visits, and skilled birth attendance. It explored trends in inequalities by household wealth status based on Demographic and Health Surveys conducted in 2000, 2005, 2011, and 2014. The study also investigated the dynamics of inequality, using concentration curves for different years. Decomposition analysis was used to identify the role of proximate determinants.ResultsThe study found substantial improvements in health outcomes and health services: Although there is still a considerable gap between the rich and the poor, inequalities in health services have been reduced. However, child nutrition outcomes have mainly improved for the rich. The changes observed in wealth-related inequality tend to reflect the changing direct effect of household wealth on child health and health service use.ConclusionsThe country’s efforts to improve access to health services have shown some positive results, but attention should now turn to service quality and to identifying multisectoral interventions that can change outcomes for the poorest.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-017-0648-1) contains supplementary material, which is available to authorized users.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

The COVID-19 pandemic and its economic and social effects on households have created an urgent need for timely data to help monitor and mitigate the social and economic impacts of the crisis and protect the welfare of the least well-off in Ethiopian society. To monitor how the COVID-19 pandemic is affecting Ethiopia's economy and people and to inform interventions and policy responses, the World Bank designed and conducted its High-Frequency Phone Survey of Households (HFPS-HH). The HFPS-HH builds on the national longitudinal Ethiopia Socioeconomic Survey (ESS) that the Central Statistical Agency (CSA) carried out in 2019 in collaboration with the World Bank. The HFPS-HH drew a subsample of the ESS sample that was representative of households with access to a working phone. The same households will be tracked over six months, with selected respondents (typically the household head) completing phone-based interviews every three to four weeks. This high-frequency follow-up allows for better understanding the effects of and household responses to the COVID-19 pandemic in near real time to support new, evidence-based responses. This survey brief summarizes the results of the first round of the HFPS-HH, implemented between April 22 and May 13, 2020. 1 The brief is based on a sample of 3,249 households in both urban and rural areas in all regions of Ethiopia. The 15-minute questionnaire covers such topics as knowledge of COVID and mitigation measures, access to educational activities during school closures, employment dynamics, household income and livelihood, income loss and coping strategies, and assistance received. To prevent the spread of COVID-19 and to ensure that measures to slow it, such as mobility restrictions and market closures, are effective, it is essential that people be aware of the need to change their behaviors. Virtually every household (99.7 percent) had heard about the coronavirus or COVID-19. The respondents reported being wellinformed about actions to reduce the spread. Almost everyone knew about handwashing, and 89 percent knew 1 The data collection was undertaken by Laterite (Ethiopia) Ltd. Households seem well aware of COVID-19, and the vast majority have knowledge of behaviors necessary to minimize the risk of contracting or spreading the virus. Schools have been closed for two months but in only 12 percent of rural households are children engaged in any form of distance learning. The percentage in urban areas is more than three times higher. The COVID-19 pandemic has hit total household incomes hard: 55 percent of respondents report that household incomes were either reduced or had totally disappeared. 13 percent of respondents lost their job since the outbreak of COVID-19 in Ethiopia-18 percent in urban areas and 10 percent in rural areas. Hospitality, construction, and wholesale and retail were the most affected in terms of job losses. Since the outbreak began 8 percent of households-10 percent of rural and 3 percent of urban-have received assistance from government, NGOs, or religious in...

Reducing child undernutrition is a key social policy objective of the Ethiopian government. Despite substantial reduction over the last decade and a half, child undernutrition is still high; with 48 percent of children either stunted, underweight or wasted, undernutrition remains an important child health challenge. The existing literature highlights that targeting of efforts to reduce undernutrition in Ethiopia is inefficient, in part due to lack of data and updated information. This paper remedies some of this shortfall by estimating levels of stunting and underweight in each woreda for 2014. The estimates are small area estimations based on the 2014 Demographic and Health Survey and the latest population census. It is shown that small area estimations are powerful predictors of undernutrition, even compared to household characteristics, such as wealth and education, and hence a valuable targeting metric. The results show large variations in share of children undernourished within each region, more than between regions. The results also show that the locations with larger challenges depend on the chosen undernutrition statistic, as the share, number and concentration of undernourished children point to vastly different locations. There is also limited correlation between share of children underweight and stunted across woredas, indicating that different locations face different challenges.