Types of Research
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Labor & Time Use filter Labor & Time Use
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
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- (-) Remove Aid & Other Development Finance filter Aid & Other Development Finance
This report draws on past and present peer-reviewed articles and published reports by institutions including the World Health Organization (WHO), the UK Department for International Development (DFID), and others to provide a scoping summary of the household-level spillovers and broader impacts of a select group of health initiatives. Rather than focusing on estimates of the direct health impacts of investments (e.g., reductions in mortality from vaccine delivery), we focus on estimates of the less-often reported spillover effects of specific health investments on household welfare or the broader economy. The brief is designed to give a concise overview of major theories linking health improvements to broader social and economic outcomes, followed by more in-depth summaries of available local- and country-level estimates of broader impacts, defined as project spillovers offering local, regional and national social and economic benefits not typically reported in project evaluations.
This report summarizes current trends in the application of Development Finance Institution (DFI)-based returnable capital finance in developing countries, with an emphasis on “pro-poor” development initiatives. We begin by reviewing the financial instruments used by DFIs. We then review the major DFI providers of returnable-capital based finance, drawing on past and present peer-reviewed articles and published reports exploring trends in the uses of different returnable capital instruments over time. Finally, we conclude by further examining recent efforts to use returnable capital to finance development initiatives explicitly targeting the poor.
This brief draws on recent reports by the OECD, the World Bank, the Overseas Development Institute (ODI), the Climate Policy Initiative (CPI) and others to provide an overview of climate finance in developing countries. The brief is divided into three sections: (i) sources of global climate finance; (ii) country-level flows of climate finance; and (iii) applications of climate finance in developing countries. The brief is designed to give a concise overview of financial flows directed at climate change mitigation and adaptation globally and in developing countries, with an introduction to climate finance accounting such that climate financial flow volumes can be compared to aid volumes in other sectors. Total global climate finance flows were approximately USD $364 billion in 2011 (Buchner et al., 2012) and $359 billion in 2012. However the vast majority of these flows - 76%, or $275 billion - was finance generated and spent within a country’s own borders (domestic finance) (Buchner et al., 2013). The “Fast-Start Finance” period from 2010-2012 saw $35 billion in new aid mobilized for climate finance in developing countries. Developed countries have recently committed to mobilize an additional $100 billion per year by 2020.
The commercial alcohol industry in Africa may provide opportunities to increase market access and incomes for smallholder farmers by increasing access to agriculture-alcohol value chains. Despite the benefits of increased market opportunities, the high costs to human health and social welfare from increased alcohol use and alcoholism could contribute to a net loss for society. To better understand the tradeoffs between increased market access for smallholders and societal costs associated with harmful alcohol consumption, this paper provides an inventory of the societal costs of alcohol in Sub-Saharan Africa (SSA). We examine direct costs associated with addressing harmful effects of alcohol and treating alcohol-related illnesses, as well as indirect costs associated with the goods and services that are not delivered as a consequence of drinking and its impact on personal productivity. We identified resources using Google Scholar and the University of Washington libraries, and utilized the Global Burden of Disease (GBD) database by the Institute for Health Metrics and Evaluation (IHME) and the World Health Organization’s Global Information System on Alcohol and Health (GISAH) database. We also utilized FAOSTAT to retrieve raw data on national-level alcohol production and export statistics. We find that hazardous alcohol use contributes to early mortality and morbidity, loss of productivity, property damage, and other social costs and harms for drinkers and those around them. Drinking also affects vulnerable segments of the population disproportionately. Policymakers, local authorities, and donor agencies can use the information presented in this paper to plan and prepare for the higher consumption levels and subsequent social costs that may follow through agricultural development and economic growth in the region.
The purpose of this analysis is to provide a measure of marketable surplus of maize in Tanzania. We proxy marketable surplus with national-level estimates of total maize sold, presumably the surplus for maize producing and consuming households. We also provide national level estimates of total maize produced and estimate “average prices” for Tanzania which allows this quantity to be expressed as an estimate of the value of marketable surplus. The analysis uses the Tanzanian National Panel Survey (TNPS) LSMS – ISA which is a nationally representative panel survey, for the years 2008/2009 and 2010/2011. A spreadsheet provides our estimates for different subsets of the sample and using different approaches to data cleaning and weighting. The total number of households for Tanzania was estimated with linear extrapolation based on the Tanzanian National Bureau of Statistics for the years 2002 and 2012. The weighted proportions of maize-producing and maize-selling households were multiplied to the national estimate of total households. This estimate of total Tanzanian maize-selling and maize-producing households was then multiplied by the average amount sold and by the average amount produced respectively to obtain national level estimates of total maize sold and total maize produced in 2009 and 2011.