1Measuring poverty is of crucial importance for a society. At the macroeconomic level it is a means of assessing one aspect of the population’s economic wellbeing by focusing on its poorest segment; also of comparing findings across countries or periods. At the microeconomic level, the objective is to identify who is poor, which then helps policymakers target the most needy.
2Multidimensional methods for measuring poverty are designed to apprehend its many facets and so to offer a new perspective on the phenomenon. The authors of this work present those methods from a technical perspective that is both normative and empirical. The book is structured in two parts: Chapters 2 to 4 present the analytic framework and a wide range of multidimensional methods for measuring poverty; Chapters 5 to 10 focus in on the Alkire Foster or AF method and how to apply it.
3The introduction explains why it is important to measure poverty multidimensionally. The standard approach, in use since the 1920s, is to measure poverty in terms of household income. This means measuring “equivalent income,” i.e., monetary resources per consumption unit, in order to define a poverty line (e.g., the equivalent of a dollar in purchasing power parity or 60% of median equivalent income), with the understanding that any person whose equivalent income falls below that line is poor. This approach is attractive because it is easy to apply. Unfortunately, it does not effectively identify who is poor. Poverty affects several different dimensions of individuals’ lives – education, health, housing conditions and others – causing deprivation in all of them. A measuring methodology that takes into account only one dimension, income, cannot apprehend the phenomenon as a whole. For example, empirical studies show that some households counted as poor in monetary terms are not experiencing malnutrition, a severe type of deprivation, whereas other households may suffer from malnutrition without being counted as poor.
4Chapter 2 presents the notation and basic concepts needed to understand the rest of the book. The authors emphasize the particular precautions that should be taken, especially when it comes to ensuring measurement comparability across individuals and dimensions. It also presents the properties or principles that multidimensional poverty measurement should satisfy. Some are the same as those that should be satisfied in the unidimensional framework. For example, data must be anonymous (anonymity property); measures should not be affected by changes in scale (scale invariance property); they should be sensitive to changes in poor persons’ living conditions but not to changes in the living conditions of non-poor persons (poverty focus principle), etc.
5Chapter 3 presents multidimensional approaches that have been widely used since the 1970s and describes their advantages and shortcomings. One set of approaches describes several poverty dimensions but cannot apprehend their interrelatedness; they cannot tell us whether a few people are undergoing all the types of deprivation described or many people are undergoing one type of deprivation. These measurements are easy to construct because aggregate data from different sources may be used. The second set of approaches captures the interrelatedness of different types of deprivation and requires specific individual databases. However, while they describe the phenomenon of poverty in precise detail for a given population, most fail to provide a simple image comparable across time and place, and, once again, they do not effectively identify who is poor.
6Chapter 4 presents counting approaches. This type of approach does effectively identify who is poor, by taking into account the interrelatedness of certain dimensions. Here poverty is measured directly, using the following simple method. First, the unit of analysis (individual, adult or child, household) is specified; then researchers define the relevant dimensions for the population under study and the poverty cutoff for each dimension; for example, access to drinking water, being able to attend school or to have a varied diet. The dimensions in which a given individual suffers deprivation are then counted to determine a deprivation score (this may involve weighting some dimensions); the person is considered poor if his/her score exceeds a certain number. This method, which has been developed in many directions, is at the core of European Union poverty measurement policy. However, it does not inform us on poverty intensity as it takes into account only whether or not the number of deprivations exceeds a pre-established threshold.
7Alkire and Foster’s method (AF), presented in Chapter 5, also draws on counting approaches. It differs from them, however, when it comes to aggregating to determine a poverty index, the point being to integrate all the properties presented in Chapter 2. The method first proceeds in the same way as counting methods by identifying which individuals or households are poor. It then identifies deprivation intensity by calculating the average deprivation score; that is, the average number of (non-weighted) dimensions in which a poor person is suffering deprivation. The AF poverty index is the multiplication of the proportion of persons identified as poor and the average deprivation score for poor people. This index thus combines the size of the poor population and poverty intensity and enables us to determine which of the two characterizes poverty in the given population. The AF poverty index may also be broken down by population subgroup and deprivation dimension in order to identify the poorest groups and determine which deprivation dimension is most often found in them.
8Chapters 6 to 8 are a guide to implementing AF poverty measurement. The authors begin by presenting a list of variables for researchers to choose from: unit of analysis, deprivation dimensions, deprivation cut-offs, dimension weights, and poverty line. They review the problems that may arise and explain how to deal with them. Chapter 7 then describes the type of data required and the various data sources available. It also explains the difficulties inherent in this type of data when it comes to establishing or implementing the poverty indicator, and possible solutions. Chapter 8 presents methods for testing AF measurement robustness, particularly in connection with the initial choices discussed in Chapter 6. It also addresses the technical issue of statistical inference, presenting methods for constructing standard deviations for AF poverty measures.
9Chapter 9 takes up questions of poverty dynamics, specifically how to interpret changes in the poverty index. An increase in poverty may be explained by an increase in the number of poor persons (new entries into poverty) or by deteriorating living conditions among people who are already poor. The authors present decomposition methods that will enable researchers to distinguish between effects due to the size of the poor population and effects due to poverty intensity. The question of how to measure chronic poverty, i.e., the fact that some people experience longer periods of poverty than others, is also addressed.
10Chapter 10 explains the theoretical framework and the relevant econometric methods for analysing multidimensional poverty determinants. At the micro level, the aim is to explain the poverty status of a given unit of analysis by way of independent variables, particularly individual characteristics or specific public policies. At the macro level, the point is to relate the AF poverty measure found for a given population to such variables as expenditure on education, the growth rate, the demographic structure of the given population, etc.
11This book is a thoroughgoing theoretical and practical overview and guide to multidimensional poverty measures and is therefore of vital importance to anyone wishing to perform this kind of measurement.