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The empirical analysis of poverty over time is still severely constrained by the available survey data in developing countries. In the past, this has led to a neglect of certain aspects of poverty dynamics or even biased assessments of poverty dynamics. This book explicitly takes into account the present data limitations, proposing alternative methods for the empirical analysis of poverty dynamics. The work addresses both the problems related to limited data in the analysis of macro-level (or national) as well as micro-level (or household) poverty dynamics. The proposed methods are applied to survey data from various sub-Saharan African countries. As these countries do not only have the most limited economic survey data but also show the highest poverty rates in the world an accurate understanding of the underlying poverty dynamics seems to be most important for these countries.

The empirical analysis of poverty over time is still severely constrained by the available survey data in developing countries. In the past, this has led to a neglect of certain aspects of poverty dynamics or even biased assessments of poverty dynamics. This book explicitly takes into account the present data limitations, proposing alternative methods for the empirical analysis of poverty dynamics. The work addresses both the problems related to limited data in the analysis of macro-level (or national) as well as micro-level (or household) poverty dynamics. The proposed methods are applied to survey data from various sub-Saharan African countries. As these countries do not only have the most limited economic survey data but also show the highest poverty rates in the world an accurate understanding of the underlying poverty dynamics seems to be most important for these countries.

Poverty Dynamics - Poverty - Pro-Poor Growth - Vulnerability - Analysis of Household Survey Data - Informal Labor Markets - Competitive and Segmented Labor Markets - Inflation Inequality - Idiosyncratic and Covariate Shocks - Multi-Level Modelling - Finite Mixture Models - Sub-Saharan Africa.

The empirical analysis of poverty over time is still severely constrained by the available survey data in developing countries. In the past, this has led to a neglect of certain aspects of poverty dynamics or even biased assessments of poverty dynamics. This book explicitly takes into account the present data limitations, proposing alternative methods for the empirical analysis of poverty dynamics. The work addresses both the problems related to limited data in the analysis of macro-level (or national) as well as micro-level (or household) poverty dynamics. The proposed methods are applied to survey data from various sub-Saharan African countries. As these countries do not only have the most limited economic survey data but also show the highest poverty rates in the world an accurate understanding of the underlying poverty dynamics seems to be most important for these countries.

The first sustainable development goal (SDG 1) is "to end poverty in all its forms everywhere and for all", which seems to be non-negotiable for the "world we want", which would provide minimum living standards for all global citizens. However, the question remains: is this goal feasible, especially given the set-backs in the fight against poverty and the unequal access to health resources that we have observed in 2020 and 2021? If yes, how do governments and civil society need to engage and what resources are needed? In this book, we bring together a diverse set of perspectives on SDG 1 from leading scholars around the world. When we first invited scholars in 2019 to reflect on ending poverty by 2030, the world looked very different; or rather, the necessity of global social protection, decent and not only sufficient livings standards and strong international cooperation to fight global poverty became even more apparent—and the pandemic put a spotlight on the lack of these three components. The COVID-19 pandemic and the resultant lockdowns across the world have not only led to millions of lost lives across the world, but have also led to large numbers of people falling once again into extreme poverty. ; ISSN:2624-9324 ; ISSN:2624-9332

A considerable and increasing share of foreign aid stems from private donations. Hence, individual donors can increase social welfare in developing countries by directing their funds to the most effective NGOs. Surprisingly few studies have analyzed whether private donors care about aid effectiveness when they donate to an international charity. In a laboratory experiment, we investigate if private donors seek information about the exact impact of their donation to an international NGO before they donate. Furthermore, we investigate how relevant private donors find information about aid impact compared to information about administrative costs, and the recipient type who benefits from a donation. First, we find that a relatively small share of individuals makes a well-informed donation decision. Second, the demand for information about aid impact is lowest, and it is highest for information about the recipient type. Third, exact information about aid impact did not lead to a significant change in average donation levels, while information about the exact recipient type and administrative costs led to a significant change in donation levels. In the recipient type group, informed participants donated significantly more than uninformed participants because they "rewarded" the preferred recipient with higher-thanaverage transfers. In the administration costs group, informed participants donated significantly less than uninformed participants because they used the information to "punish" NGOs with high administration costs.

We investigate whether sub‐Saharan African countries are affected by an "urban mortality penalty" repeating the history of industrialized countries during the nineteenth century. We analyze Demographic and Health Surveys from several sub‐Saharan African countries for differences in child and adult mortality between rural and urban areas. For the first decade of the 2000s, our findings indicate that child mortality is higher in rural than in urban areas for all countries. On average, child mortality rates are 13.6 percent in rural areas and 10.8 percent in urban areas. In contrast, average urban adult mortality rates (14.1 percent) have exceeded rural adult mortality rates (12.4 percent). Child mortality rates are on average 65 percent higher in urban slums than in formal settlements. Child mortality rates in slum areas are, however, still lower than or equal to those in rural areas for most countries in our sample.