Academic journal article Population

Multidimensional Poverty Measurement and Analysis

Academic journal article Population

Multidimensional Poverty Measurement and Analysis

Article excerpt

Sabina AlKire, James foster, Suman seth, Maria Emma sAntos, José Manuel r°Che and Paola Ballon, Multidimensional Poverty Measurement and Analysis, Oxford University Press, 2015, XI-356 p.

Measuring 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.

Multidimensional 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.

The 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.

Chapter 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.

Chapter 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.

Chapter 4 presents counting approaches. This type of approach does effectively identify who is poor, by taking into account the interrelatedness of certain dimensions. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.