Poverty and food security are highly heterogeneous phenomena in most countries; it is thus common to find wide spatial variability. Types and depth of poverty, measured in a range of different ways, vary between and within countries, regions and other geographic and administrative units. Spatial heterogeneity can develop for a variety of reasons such as differences in geography, history and ethnicity, access to markets, public services and infrastructure, and other aspects of public policy (see de Janvry and Sadoulet, 1997; Bloom and Sachs, 1998; Jalan and Ravallion, 2002). Heterogeneity in poverty and food security is, however, often hard to measure correctly with conventional analytical tools. The fundamental problem is obtaining data that permit measurement of poverty and food security at a level of disaggregation sufficient to capture the heterogeneity brought about by spatial variability.
The concept of mapping involves measuring the incidence of poverty and food security in some predetermined area. While the term &#laquo;poverty&#raquo; mapping has become ubiquitous in research and policy circles, an almost unlimited variety of poverty and food-security indicators can be mapped with the methods described in this paper. Although poverty and food security are not necessarily the same concept, the terms are used interchangeably in this paper, because the focus is on methods, not specific indicators.
Poverty and food-security mapping can take place at global, continental and regional levels, and includes subnational analysis and areas within countries. Global or regional mapping typically uses country-level or broad geographical variables. At subnational level, poverty mapping in its various forms involves techniques that permit sufficient disaggregation of a poverty measure to local administrative levels or small geographical units. It is based on a wide variety of possible criteria such as agro-ecological, land-use, livelihood and production-system parameters, in order to gauge spatial heterogeneity accurately by specific criteria. All poverty maps that aspire to national coverage require a census on which microanalysis can be based, either directly or by extrapolation. All poverty-mapping techniques imply alternative schemes for weighting a particular poverty index, and may imply alternative rankings by poverty of the chosen unit. Statistical error and possible bias are thus fundamental issues in poverty mapping, though most practitioners to date have remained unaware of these complications.
The purpose of this paper is to discuss poverty and food-security mapping in terms of relevance and available options for analysis, policy design and implementation in the rural sectors of developing countries. It will present and compare a large selection of poverty and food-security mapping methodologies in use, in order to provide some guidance as to their potential and appropriateness for different policy applications. The aim is to send some warning signals regarding the deceptive ease with which it is possible to construct colourful and informative poverty maps, when different methods or different data could lead to very different results. This is done by studying in detail a number of applications of poverty mapping to policy questions. The paper concludes by indicating areas where more research is necessary. The focus is primarily on the subnational level, where there has been a considerable amount of analytical activity over the last few years.
