The poverty headcount in Ethiopia is falling. The share of the population below the national poverty line decreased from 30 percent in 2011 to 24 percent in 2016. This decrease was achieved in spite of the fact that the 2015-16 survey was conducted during the severe El-Nino drought. The observed reduction in poverty is robust to the use of alternative deflators. The fall in the poverty headcount was driven mainly by Ethiopia’s strong economic growth over that period. This poverty assessment focuses on the evolution of poverty and other social indicators in Ethiopia between 2011 and 2016. It uses data from a variety of sources, mainly the Household Consumption and Expenditure Survey (HCES), the Welfare Monitoring Surveys (WMS), the Ethiopia Socioeconomic Survey (ESS) and the Demographic and Health Surveys (DHS), to observe trends in monetary and non-monetary dimensions of living standards and to examine the drivers of these trends, with a special focus on government programs. The aim of the poverty assessment is to provide policymakers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.

Ethiopia has seen many changes since 2016, which until now, has been the reference year for data about the level and pattern of poverty in the country. The narrative around poverty was that years of high growth resulted in a significant reduction in poverty, but by less than expected because growth was uneven between rural and urban areas which received most of the gains from growth and there was a slow shift of labor from agriculture into the fast-growing segments of the economy. Since 2016, GDP per capita growth has decelerated - to 4.6 percent during 2016-2022 compared to nearly 7.4 percent during 2010-2016 - not least because of multiple crises, including a global pandemic, droughts, locust infestation, conflict, and market shocks. This Poverty and Equity Assessment (PEA) updates the understanding of poverty and inequality in the country, using new data collected from 2021. This data was collected amidst security concerns, which posed challenges during the data collection process. Despite these challenges, data quality checks have verified that the collected information is reliable and representative of the country, excluding areas that were inaccessible, such as Tigray. The PEA updates statistics on poverty rates, inequality, the poverty profile, and identifies the drivers of these trends (Part 1). It provides an in-depth understanding of the key drivers of poverty in the country (Part 2) and charts the course for reducing poverty in the years to come (Part 3). Below are some high-level messages drawn from the analysis presented in the seven chapters of the report. Additional details are accessible in background papers accompanying the report.

Community characteristics of women dropped out from maternal service care, Ethiopia Demographic and Health Survey, 2016.

Maternal characteristics result of respondents in 2016 EDHS, Ethiopia.

Underweight among lactating mothers by background individual and community-level characteristics in Ethiopia, 2016 (n = 3,848).

Individual-level characteristics of included children age 6–59 months selected from the 2016 EDHS.

Individual and community-level factors associated with anemia among children age 6–59 months selected from the 2016 EDHS.

Community-level variance and model comparison of multilevel logistic regression model predicting under-weight among lactating mothers, Ethiopia 2016.

Multilevel logistic regression analysis of individual and community factors on dropout from maternal continuum of care among women with a live birth in five years preceding 2016 EDHS, Ethiopia.

Determinants of Underweight among lactating mother in Ethiopia, 2016; results for multilevel logistic models.

Socio-demographic and economic characteristics of respondents in 2016 EDHS, Ethiopia (weighted N = 4690).

Multi-variable multilevel binary logistic regression analysis result of both community and individual level factors associated with utilization of deworming medication in pregnant mothers in Ethiopia, EDHS 2016.

Welfare dynamics studies are useful in understanding how individuals, families, society, and a country are organised. For the last two decades, Ethiopia’s economic reports on income disparity, poverty, and other welfare metrics have been hopeful and controversial. It is crucial to understand how rural households of various income levels perform over time and income mobility. Income mobility can be observed as a change in position over time between two income vectors, with some climbing and others sliding down and changing places at various rates. This study, therefore, explored the rural households’ income mobility in Ethiopia using three waves of the Living Standards Measurement Study-Integrated Survey on Agriculture (LSMS-ISA) collected from 2011 to 2016. The Shorrocks rigidity index, transition probability matrix, Fields, and Ok methods were employed to analyse the relative and absolute income mobility. The logit model with conditional fixed effect was used to assess the drivers of individual households’ income mobility and the multinomial logit model with conditional fixed effect as an alternative model. Based on the finding of this study, it is suggested to implement different policies targeting income growth to shorten mobility gaps and address factors contributing to downward income mobility in rural households in Ethiopia are necessary.