Presents and compares a large selection of poverty and food-security mapping methodologies in use. The choice of a poverty-mapping methodology depends on a number of logical and legitimate considerations, such as the objectives of the poverty mapping exercise, philosophical views on poverty, limits on data and analytical capacity, and cost.

The allocation of resources and the design of policies tailored to local-level conditions require highly disaggregated information. Data on poverty at the local level is typically not available because most household surveys are not representative past the regional level. This volume aims to promote the effective use of Small Area Estimation poverty maps in policy making. It presents the range of policies and interventions which have been informed by poverty maps, focusing on the political economy of poverty maps and the key elements to their effective use by policy makers. The volume also looks at the future of poverty maps in terms of new techniques and new areas of application.

.."in many developing countries, there are large differences in economic conditions and the standard of living between regions, and even between communities within the same region. In many countries, poverty has a clear geographic dimension, since the poor are often concentrated in pockets of poverty. Therefore, the design of poverty alleviation policies must also have a signficant spatial component." Although development projects are carefully designed and meticulously evaluated for cost effectiveness and benefits, too many of them are not sufficiently targeted geographically. The growing availability and use of spatial data, organized in a computer system such as a geographical information system (GIS), makes it more feasible to analyze the impact of projects in specific locales and to achieve more effective targeting. 'Geographical Targeting for Poverty Alleviation' introduces the basic concepts of a GIS. It also demonstrates how to organize geographic and nongeographic data. In addition, it presents different methods for using the data of the Household Income and Expenditure Survey, together with other surveys and the population census, to provide estimates for the standard of living and the incidence of poverty incidence in different geographical areas of a country. Ultimately, these estimates should be used to establish guidelines for targeting poverty alleviation projects. This publication illustrates different GIS applications for identifying the project's target population, determining the project's spatial 'sphere of influence' or deciding where to locate public facilities. This publication is of interest to task managers, economists, development researchers, and geographers.

This report presents the results of subnational poverty estimation using aggregate poverty statistics and how they can help policy interventions. In particular, they estimate the poverty map across the DS division level in Sri Lanka. The poverty map depicts the proportion of households below the poverty line, which is based on household expenditure for food for obtaining the minimum calorie requirement.

A comprehensive guide to implementing SAE methods for poverty studies and poverty mapping There is an increasingly urgent demand for poverty and living conditions data, in relation to local areas and/or subpopulations. Policy makers and stakeholders need indicators and maps of poverty and living conditions in order to formulate and implement policies, (re)distribute resources, and measure the effect of local policy actions. Small Area Estimation (SAE) plays a crucial role in producing statistically sound estimates for poverty mapping. This book offers a comprehensive source of information regarding the use of SAE methods adapted to these distinctive features of poverty data derived from surveys and administrative archives. The book covers the definition of poverty indicators, data collection and integration methods, the impact of sampling design, weighting and variance estimation, the issue of SAE modelling and robustness, the spatio-temporal modelling of poverty, and the SAE of the distribution function of income and inequalities. Examples of data analyses and applications are provided, and the book is supported by a website describing scripts written in SAS or R software, which accompany the majority of the presented methods. Key features: Presents a comprehensive review of SAE methods for poverty mapping Demonstrates the applications of SAE methods using real-life case studies Offers guidance on the use of routines and choice of websites from which to download them Analysis of Poverty Data by Small Area Estimation offers an introduction to advanced techniques from both a practical and a methodological perspective, and will prove an invaluable resource for researchers actively engaged in organizing, managing and conducting studies on poverty.

Publ. in association with UNEP/GRID-Arendal, Norway.