Other Poverty Study
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Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda: Results from the High-Frequency Phone - Third Round
2021-05-18, World Bank
The High-Frequency Phone Survey for refugees in Uganda (URHFPS) tracked the socioeconomic impacts of the COVID-19 (coronavirus) crisis on refugees throughout three rounds. The World Bank (WB) in collaboration with the Uganda Bureau of Statistics (UBOS) and the United Nations High Commissioner for Refugees (UNHCR) launched and conducted the URHFPS. The URHFPS tracked the impacts of the pandemic between October 2020 and March 2021. Data collection for the first round of the URHFPS took place between October 22 – November 25, 2020, the second round took place between December 5-24, 2020, and the final and third round was conducted between February 8-March 14, 2021. This brief discusses the results from the third round. Where possible and appropriate, the results are compared across the three rounds and also benchmarked against Ugandans by using the national High-Frequency Phone Survey on COVID-19 (UHFPS). Detailed results for the first round are available in Atamanov et al. (2021a) and for the second round in Atamanov et al. (2021b)
The Geography of Welfare in Benin, Burkina Faso, Côte d'Ivoire, and Togo
2017-08, Nguyen, Nga Thi Viet, Dizon, Felipe F.
This report aims to assess the spatial disparities in economic development along four important dimensions: (i) It provides stylized facts of the underlying forces behind within-country inequality, namely natural endowment, agglomeration economies, and market access. These are the three building blocks of the economic geography literature; (ii) It examines spatial disparities in welfare and poverty. As the agricultural sector is a cornerstone of the economy in this sub-region, the report explores geographical differences in agricultural activity; (iii) It quantifies the roles of natural endowment, agglomeration economies, and market access in determining the spatial distribution of welfare and agricultural productivity; (iv) It suggests a number of policy guidelines that may help improve shared prosperity across space.
COVID-19 Impact Monitoring: Uganda, Round 4-5
2021-02, World Bank
In June 2020, the Uganda Bureau of Statistics, with the support from the World Bank, has launched the High-Frequency Phone Survey on COVID-19 (coronavirus) to track the impacts of the pandemic on a monthly basis for a period of 12 months. The survey aimed to recontact the entire sample of households that had been interviewed during the Uganda National Panel Survey 2019/20 round and that had phone numbers for at least one household member or a reference individual. This report presents the findings from the fourth and fifth rounds of the survey that were conducted respectively between October 27th and November 17th, 2020 and February 2nd and February 21st, 2021.
Geography of Poverty in Mali
2015-04-23, World Bank
This study discusses the impact of economic geography and (low) population density on development outcomes in Mali and explores how policies to reduce poverty can be made more effective by taking these two factors into account. The crisis in north Mali which started in 2012 and continues to date has brought questions of economic geography to the center of attention. To help answer such questions, and to analyze how to reduce poverty in Mali as a whole, this study uses different sources of information to analyze the diversity of livelihood patterns, in access to services and in living standards. The study uses quantitative information from household surveys, population and firm censuses, administrative and geographic data, and qualitative information about livelihoods. This study argues that the authorities will need to employ all three policy instruments, while emphasizing that if the objective is poverty reduction, most attention should be focused on spatially blind approaches. The study is organized as follows: chapter one gives introduction. Chapter two emphasizes differences in population density which allows distinguishing between types of agglomeration from villages, to rural town, to large cities. Chapter three categorizes the country into various livelihood zones and considers how the agro-physical environment affects the way people live. In chapter four authors turn to household welfare. Chapter five considers access to services. Chapter six is forward looking.
Fiscal Incidence Analysis for Kenya: Using the Kenya Integrated Household Budget Survey 2015-16
2018-06-29, World Bank
Kenya has made satisfactory progress in reducing poverty and inequality in recent years. Economic growth in Kenya between 2005-06 and 2015-16 averaged around 5.3 percent, exceeding the average growth of 4.9 percent observed for Sub-Saharan Africa. This robust economic growth resulted in a reduction in poverty, whether measured by the national or international poverty line. The proportion of the population living beneath the national poverty line fell from 46.8 percent in 2005-06 to 36.1 percent in 2015-16, showing a modest improvement in the living standards of the Kenyan population. Similarly, poverty under the international poverty line of US$ 1.90 a day declined from 43.6 percent in 2005-06 to 35.6 percent in 2015-16. At this level, poverty in Kenya is below the average in sub-Saharan Africa and is amongst the lowest in the East African Community (World Bank, 2018b). However, the proportion of the population living in poverty remains comparatively high in Kenya and the rate at which growth translated into poverty reduction was lower than elsewhere. At twice the average, Kenya’s poverty rate is still high for a lower-middle income country, a group that Kenya joined only in 2015. In addition, the Kenya’s growth elasticity of poverty reduction, the percentage reduction in the poverty rate associated with a one-percent increase in mean per capita income is only 0.57, lower than in Tanzania, Ghana, or Uganda (World Bank, 2018b). This leads to the obvious question of what can be done to make economic growth more pro-poor in Kenya. This study assesses the distributional consequences of Kenya’s system of taxes and transfers, covering 60 percent of revenue and between 25 and 30 percent of government spending. The analysis of fiscal incidence and distributional consequences of Kenya’s tax and transfer system is an important input for designing pro-poor policies and potentially for influencing the rate at which economic growth translates into poverty reduction. In this study, direct taxes and transfers, indirect taxes (VAT and excise duties), as well as public health and education spending are assessed in terms of their distributional impacts. Overall, these taxes and transfers account for about 60 percent of revenue and between 25 and 30 percent of government spending.