Poverty and Social Exclusion

Gianni Betti,Achille Lemmi

• Éditeur: Routledge
• Année: 2013
• ISBN:
  9781136196294
• Édition: 1
• Sujet: Business
• Sous-sujet: Business General

Poverty and inequality remain at the top of the global economic agenda, and the methodology of measuring poverty continues to be a key area of research. This new book, from a leading international group of scholars, offers an up to date and innovative survey of new methods for estimating poverty at the local level, as well as the most recent multidimensional methods of the dynamics of poverty.

It is argued here that measures of poverty and inequality are most useful to policy-makers and researchers when they are finely disaggregated into small geographic units. Poverty and Social Exclusion: New Methods of Analysis is the first attempt to compile the most recent research results on local estimates of multidimensional deprivation. The methods offered here take both traditional and multidimensional approaches, with a focus on using the methodology for the construction of time-related measures of deprivation at the individual and aggregated levels. In analysis of persistence over time, the book also explores whether the level of deprivation is defined in terms of relative inequality in society, or in relation to some supposedly absolute standard.

This book is of particular importance as the continuing international economic and financial crisis has led to the impoverishment of segments of population as a result of unemployment, bankruptcy, and difficulties in obtaining credit. The volume will therefore be of interest to all those working on economic, econometric and statistical methods and empirical analyses in the areas of poverty, social exclusion and income inequality.

1 Introduction

Gianni Betti and Achille Lemmi

Over the last five years the University of Siena’s Research Centre on Income Distribution “C. Dagum” and its research group have been awarded several research grants funded by international bodies such as the European Union, the World Bank and Eurostat. In particular, the SAMPLE project, funded by the EU under the seventh FP, is the main source of theory and results for this book (www.sample-project.eu/). The reason that prompted us to put together this collective volume is that measures of poverty and inequality are most useful to policymakers and researchers when they are finely disaggregated, i.e. when they are estimated for small geographic units, such as cities, municipalities, districts or other “local” administrative partitions of a country. This book is the first attempt to bring together the most recent research results on local estimates of multidimensional poverty (deprivation).

Moreover, one of the book’s significant innovations lies in its analysis of poverty dynamics using both traditional and multidimensional approaches. The focus will be on using this methodology for the construction of time-related measures of deprivation at individual and aggregated levels. Regarding the analysis of persistence over time, a related issue dealt with concerns whether the level of deprivation is defined purely in terms of the relative disparity in society, or in relation to some supposedly absolute standard. The book explores the implications of this choice on the analysis of the persistence of deprivation in society.

These research themes constitute a consistent and relevant part of the recent economic, econometric and statistical methods and empirical analyses in the international scientific literature. They also play a seminal role in policymaking, given the importance of inequality and poverty reduction, and of improving living conditions within a framework of sustainable economic development.

Moreover, the present dramatic international economic and financial crisis emphasizes the role of social equity in policymaking, in order to effectively combat the increasing impoverishment of relevant segments of population, due to unemployment, bankruptcy and difficulties related to bank credit.

The book we propose contains a selection of the most original research from the abovementioned projects, complemented by chapters proposed by outstanding researchers in the field of poverty. The chapters have been chosen taking into account three criteria: (i) scientific quality; (ii) capacity to represent the key issues in current scientific research; (iii) existence of a sort of scientific “fil rouge” among the contributions, with the aim of proposing a homogeneous, useful and up-to-date book.

In particular, the main themes are related to: (i) innovation in the theory and methods regarding poverty and social exclusion; (ii) poverty mapping and its policy implications; (iii) worldwide empirical applications in applied economic analysis.

The book boasts a good balance between theoretical/methodological and empirical chapters. The group of authors constitutes a mixture of very renowned researchers in the fields of economic and statistical approaches to poverty measurement, and a group of young and very promising scholars. The case studies are always applications of the economic theories proposed and appeal to an international audience; they cover the Americas, Asia, Africa and Europe.

The book is made up of 16 chapters. After this Introduction, the others are divided into three Parts, respectively devoted to: Part I, Multidimensional poverty; Part II, Longitudinal and chronic poverty; Part III, Small area estimation methods. Each Part begins with an Overview chapter written by leading researchers on that topic.

Chapter 2 by Jacques Silber and Gaston Yalonetzky on “Measuring multidimensional deprivation with dichotomized and ordinal variables” is more than an overview of Part I on Multidimensional poverty and deprivation. The purpose of this chapter is to provide an introduction to the measurement of multidimensional poverty when dealing with counting and ordinal variables. The authors first present a general framework for measuring multidimensional poverty with ordinal variables. A distinction is made between individual and social poverty functions. At the individual level they stress the difference between the identification function and the “breadth of poverty” function and review the properties of such an individual poverty function, combining “identification” and “breadth of poverty” elements. When aggregating these individual deprivation functions they then make a distinction between the case in which the social poverty function is an average of the individual poverty functions and that of alternative aggregation methods. This chapter also discusses the issue of inequality in the distribution of deprivation among the poor, looks at alternative identification functions and discusses the issues of weights, robustness and partial ordering. Finally, a simple empirical illustration of the different approaches is presented.

Chapter 3 by Walter Sosa-Escudero, German Caruso and Marcela Svarc on “Poverty and the dimensionality of welfare” reviews recent methods for quantifying the dimensionality of welfare and its relationship with deprivation. The authors discuss two alternative strategies based on factor analytic methods and on variable selection after cluster analysis. Unlike latent variable methods, variable selection strategies are immediate to interpret and resample, since they choose variables originally in the data set. The advantages and disadvantages of both strategies are discussed, as well as some recent empirical applications of these methods. The methods are shown to be capable of summarizing an initially large list of variables into a few new variables (as in factor analytic methods) or a subset of the original ones (as in feature selection/cluster methods), which can serve the purpose of characterizing the poor. These methods can contribute to the conceptual search for relevant dimensions of welfare, or provide confirmatory analysis of alternative, probably multidisciplinary, studies aimed at isolating relevant factors for poverty analysis.

Chapter 4 by Naama Haron on “Income, material deprivation and social exclusion in Israel” aims at illustrating the state of economic poverty, material deprivation and social exclusion in Israel. The author examines the correlation between these phenomena and attempts to identify and characterize the afflicted population. The research presented herein is based on Israeli societal survey data of 2007. The Central Bureau of Statistics has carried out this survey since 2002, permitting the development of an index uniquely adapted to these needs. In order to maintain clarity and create as clear a distinction as possible between economic poverty, material deprivation and social exclusion, the definition of the paradigm of social quality is followed (Berman and Phillips, 2000). This paradigm serves as a superstructure for understanding and organizing the various levels of an individual’s life in the society in which he/she resides, including the absence of economic security and social exclusion.

Chapter 5 by Gianni Betti, Francesca Gagliardi and Vincenzo Salvucci deals with “Multidimensional and fuzzy measures of poverty and inequality at national and regional level in Mozambique”. This chapter provides a step-by-step account of how fuzzy measures of non-monetary deprivation and also monetary poverty can be calculated in Mozambique. For non-monetary deprivation, meaning dimensions or groupings of initial items of deprivation are identified using explanatory and confirmatory factor analyses, and a weighting system is applied for the aggregation of individual items into the dimension they represent. An application is conducted on Mozambique using 2008–2009 data: estimates are provided at national level and also disaggregated at provincial level. Standard errors are provided using a recent methodology based on Jack-knife Repeated Replication (Verma and Betti, 2011).

Chapter 6 by Vijay Verma and Francesca Gagliardi “On assessing the time-dimension of poverty” constitutes an overview of Part II on Longitudinal and chronic poverty. In the chapter, various issues are addressed concerning the time-dimension of poverty, in particular measures of poverty trend over time at the aggregate level and measures of persistence or otherwise of poverty at the micro level. The main measurement problem in the assessment of poverty trends is the definition of the poverty threshold and its consistency over time. The main measurement problem in the assessment of persistence of poverty concerns the effect of random measurement errors on the consistency of the individuals’ observed poverty situation at different times.

Chapter 7 by Walter Bossert, Lidia Ceriani, Satya R. Chakravarty and Conchita D’Ambrosio looks at “Intertemporal material deprivation”. The purpose of this chapter is to add intertemporal considerations to the analysis of material deprivation. The authors employ the EU-SILC panel data set, which includes information on different aspects of wellbeing over time. EU countries are compared based on measures that take this additional intertemporal information into consideration. Following the path of material deprivation experienced by each individual over time, a picture that differs from the annual results is obtained. Since the measurement of material deprivation is used by the EU member states and the European Commission to monitor national and EU progress in the fight against poverty and social exclusion, the results suggest that time cannot be neglected. Countries should not only be compared based on their year by year results, but additional information needs to be gained by following individuals over time and producing an aggregate measure once time is taken into account.

Chapter 8 by James E. Foster and Maria Emma Santos on “Measuring chronic poverty” proposes a new class of chronic poverty measures, which does not require resources in different periods to be perfect substitutes when identifying the chronically poor. The authors use a general mean to combine the resources of a person into a permanent income standard, which is then compared to a poverty line to determine when a person is chronically poor. The parameter of the general mean allows for varying degrees of substitutability over time, from perfect substitutes to perfect complements. The decomposable CHU poverty measure with the same parameter is applied to the distribution of permanent income standards to measure overall chronic poverty. Each measure has a convenient expression in terms of a censored matrix and satisfies a host of properties, including decomposability. This chapter provides an interesting empirical application of the new measures using panel data from urban areas in Argentina.

Chapter 9 by Catherine Porter and Natalie Naïri Quinn on “Measuring inter-temporal poverty: policy options for the poverty analyst” presents an analytical review of the recent technical literature on intertemporal poverty measurement (also known as chronic poverty measurement or lifetime poverty measurement). Individual measures of wellbeing (or the lack of ) are aggregated both over time and across people, to compare wellbeing over more than one time period. The chapter has a practical emphasis. The main aims are to make the intertemporal poverty measures which have been introduced in the technical literature accessible to applied practitioners conducting poverty analysis and to offer advice on which may be appropriate in alternative circumstances. Different measures have different properties which reflect alternative normative principles or judgements. First, the authors present intuitive motivations for and explanations of these properties; then they relate these properties to practical considerations, such as measurement error in data, as well as normative principles. The chapter then gives a comprehensive review of the properties satisfied by several of the recently suggested measures, in order to understand when they might be appropriate.

Chapter 10 by Stephan Klasen on “measuring levels and trends in absolute poverty in the world: open questions and possible alternatives” critically analyses changes in the Global Poverty numbers generated by the World Bank in 2008. While they have little impact on observed poverty trends and while there are good reasons to believe that the previous numbers were based on weak foundations, the new numbers on levels of poverty in the developing world create new uncertainties and questions. In particular, there are conceptual and empirical issues involved in using one (updated) ICP round to update all poverty numbers, as well as questions regarding the adjustment of the international poverty line. This chapter reviews these issues and finds that we cannot be very certain about levels of absolute poverty in the world and that the current method for generating absolute poverty numbers is problematic and should possibly be abandoned. At the same time, poverty trends are much less affected by these methodological issues. This chapter also discusses potential alternatives to the current methods and highlights their strengths and weaknesses. Unfortunately, there is no readily available alternative to the current method, although such an alternative could be developed, with some difficulty.

Chapter 11 by Ray Chambers and Monica Pratesi on “Small area methodology in poverty mapping: an introductory overview” proposes the use of small area estimation methods for estimating poverty at local level; these methods constitute a set of advanced statistical inference techniques that can be used for the measurement of poverty and living conditions by survey practitioners, researchers in private and public organizations, official statistical agencies and local governmental agencies. In particular, the estimates produced using small area estimation methods are well suited to mapping geographical variations in these conditions. The aim of the chapter – and the entire Part III of the book – is to provide the reader with an overview of small area estimation methods that focus on poverty measurement.

Chapter 12 by Stephen Haslett concerns “Small area estimation of poverty using the ELL/PovMap method, and its alternatives”. Small area estimation of poverty-related variables, such as poverty incidence, gap and severity is an important analytical tool used to target the delivery of food and other aid in developing countries at a finer level. Although there is a wide variety of small area estimation methods, the principal method used for poverty estimation (and hence poverty mapping) at small area level is that of Elbers, Lanjouw and Lanjouw (2003), commonly referred to as ELL. The ELL method differs from many other small area methods in that it uses both survey and census data at household level, and a model based on the survey data to make household level predictions for all census observations, which are then aggregated. When the model is correct, using the ELL method can give considerable improvements in terms of accuracy over small area estimation methods based on surveys alone. However, when it is incorrect the estimated standard errors can be severe underestimations. This chapter explores the ELL method and its underlying assumptions, considers model diagnostics and the utility of the World Bank’s PovMap software that implements ELL, and outlines both variations of and alternatives to ELL.

Chapter 13 by Isabel Molina and Jon N.K. Rao on the “Estimation of poverty measures in small areas” describes methods for the estimation of poverty indicators at local level. The methodology described here is generally applicable to practically any poverty indicator, but for the sake of illustration they focus on the class called FGT poverty measures. This class includes poverty incidence, or the proportion of individuals living in poverty in a small area, poverty gap, which measures the area mean of the relative distance from the poverty line of each individual, and poverty severity, which measures the area mean of the squared relative distance: large values of this measure point to areas with severe levels of poverty. A comparison of the different estimation procedures through model-based and design-based simulation studies is provided.

Chapter 14 by Nicola Salvati, Caterina Giusti and Monica Pratesi on “The use of spatial information for the estimation of poverty indicators at the small area level” considers a model-based perspective and presents different models that use geographical information. The authors apply these spatial models to data from the EU-SILC 2008 survey to estimate various indicators of poverty and living conditions for each Local Labour System in three Italian regions: Lombardy in the North, Tuscany in Central Italy and Campania in Southern Italy. The choice of these three regions, out of the 20 existing in Italy, is motivated by the geographical differences that characterize the country. In particular, since each of the three regions can be considered as representative of the corresponding geographical area of Italy (Northern, Central and Southern/Insular Italy), this allows us to investigate the so-called “north–south” divide.

Chapter 15 by Nikos Tzavidis, Stefano Marchetti and Steve Donbavand on “Outlier robust semi-parametric small area methods for poverty estimation” reviews small area estimation methodologies for poverty indicators, with specific emphasis on outlier robust estimation. The World Bank and Empirical Best Prediction approaches are presented alongside an outlier robust, semi-parametric approach based on the M-quantile model. The World Bank and M-quantile approaches are empirically compared using Monte-Carlo simulation. Using data from the EU survey of income and living conditions (EU-SILC) and Census micro-data from Italy the authors apply the M-quantile app...

Table des matières

• Cover Page
• Half Title page
• Series Page
• Title Page
• Copyright Page
• Contents
• Illustrations
• Contributors
• 1 Introduction
• Part I Multidimensional poverty
• Part II Longitudinal and chronic poverty
• Part III Small area estimation methods
• Index