SSRN Author: James E. FosterJames E. Foster SSRN Content
http://www.ssrn.com/author=1537907
http://www.ssrn.com/rss/en-usSun, 29 Nov 2015 02:00:50 GMTeditor@ssrn.com (Editor)Sun, 29 Nov 2015 02:00:50 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Multidimensional Poverty Measurement and Analysis: Chapter 5 – the Alkire-Foster Counting MethodologyThis chapter provides a systematic overview of the Alkire-Foster multidimensional measurement methodology with an emphasis on the Adjusted Headcount Ratio. The chapter is divided into seven sections. The first shows how this measure combines the practical appeal of the counting tradition with the rigor of the axiomatic one. The second sets out the identification of who is poor using the dual-cutoff approach, and the third outlines the aggregation method used to construct the Adjusted Headcount Ratio. In the fourth, we take stock and present the main distinctive characteristics of the Adjusted Headcount Ratio, whereas the fifth section presents its useful, consistent partial indices or components. To illustrate, we present a case study using the global Multidimensional Poverty Index (MPI) in the sixth section. The final section presents the members of the AF class of measures that can be constructed in less common situations where data are cardinal.
http://www.ssrn.com/abstract=2564787
http://www.ssrn.com/1448391.htmlSat, 28 Nov 2015 13:25:07 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 10 – Some Regression Models for Af MeasuresThis Chapter provides the reader with a general modelling framework for analysing the determinants of the Alkire and Foster (2011) poverty measures for both micro and macro levels of analyses. At the micro level, we present a model where the focal variable is a person’s poverty status. At the macro level we present a model where the focal variable is an overall poverty measure like the poverty headcount ratio or the adjusted headcount ratio. The chapter presents these regression models within the structure of Generalized Linear Models (GLM’s), which allow accounting for bounded and discrete variables. GLMs encompass linear regression models, logit and probit models, and models for fractional data. Thus, they offer a general framework for our analysis of functional relationships with Alkire and Foster poverty measures.
http://www.ssrn.com/abstract=2575966
http://www.ssrn.com/1380291.htmlThu, 12 Mar 2015 06:19:34 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 9 – Distribution and DynamicsFor meaningful policy analysis, it is important not only to look at overall poverty, and compare countries or regions at a single point in time, but also to understand the distribution among the poor, the disparity across subgroups, and the dynamics of poverty. This extends the methodological toolkit presented in Chapter 5. First we present a new measure of inequality among the poor and its axiomatic justification. The same measure, a form of variance, can be extended to analyse horizontal inequalities, which are disparities across different population subgroups. The next two sections provide methodological extensions that are required for inter-temporal analysis of poverty using repeated cross-sectional data, and for the analysis of dynamic subgroups. The last section elaborates a measure chronic multidimensional poverty, which uses a counting approach both across dimensions and across periods, and provide its consistent partial indices, including a new statistic on the duration of ...
http://www.ssrn.com/abstract=2575975
http://www.ssrn.com/1380312.htmlThu, 12 Mar 2015 06:17:24 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 8 – Robustness Analysis and Statistical InferenceThe design of a poverty measure involves the selection of a set of parameters and poverty figures. In most cases the measures are estimated from sample surveys. This raises the question of how conclusive particular poverty comparisons are subject to both the set of selected parameters (or variations within a plausible range) and the sample datasets. This chapter shows how to apply dominance and rank robustness tests to assess comparisons as poverty cutoffs and other parameters changes. It presents ingredients of statistical inference, including standard errors, confidence intervals, and hypothesis tests. And it discusses how robustness and statistical inference tools can be used together to assert concrete policy conclusions. An appendix presents methods for computing standard errors, including the bootstrapped standard errors.
http://www.ssrn.com/abstract=2575964
http://www.ssrn.com/1380310.htmlThu, 12 Mar 2015 06:13:05 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 8 – Robustness Analysis and Statistical InferenceThe design of a poverty measure involves the selection of a set of parameters and poverty figures. In most cases the measures are estimated from sample surveys. This raises the question of how conclusive particular poverty comparisons are subject to both the set of selected parameters (or variations within a plausible range) and the sample datasets. This chapter shows how to apply dominance and rank robustness tests to assess comparisons as poverty cutoffs and other parameters changes. It presents ingredients of statistical inference, including standard errors, confidence intervals, and hypothesis tests. And it discusses how robustness and statistical inference tools can be used together to assert concrete policy conclusions. An appendix presents methods for computing standard errors, including the bootstrapped standard errors.
http://www.ssrn.com/abstract=2575964
http://www.ssrn.com/1380309.htmlThu, 12 Mar 2015 06:10:28 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 8 – Robustness Analysis and Statistical InferenceThe design of a poverty measure involves the selection of a set of parameters and poverty figures. In most cases the measures are estimated from sample surveys. This raises the question of how conclusive particular poverty comparisons are subject to both the set of selected parameters (or variations within a plausible range) and the sample datasets. This chapter shows how to apply dominance and rank robustness tests to assess comparisons as poverty cutoffs and other parameters changes. It presents ingredients of statistical inference, including standard errors, confidence intervals, and hypothesis tests. And it discusses how robustness and statistical inference tools can be used together to assert concrete policy conclusions. An appendix presents methods for computing standard errors, including the bootstrapped standard errors.
http://www.ssrn.com/abstract=2575964
http://www.ssrn.com/1380308.htmlThu, 12 Mar 2015 06:10:05 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 7 – Data and AnalysisThis chapter introduces empirical issues that are distinctive to counting-based multidimensional poverty methodologies. It is crucial that indicators accurately reflect deprivations at the individual level and that all indicators be transformed to reflect deprivations in the chosen unit of analysis. This chapter is divided into four sections. The first section very briefly the different types of data sources used for multidimensional measures: censuses, administrative records, and household surveys – as well as outstanding data needs. The second discusses distinctive issues to be considered when constructing the indicators to include in a multidimensional poverty measure. The third section presents some basic descriptive analytical tools that can prove helpful in exploring the relationships between different indicators, detecting redundancy, and informing measure design and analysis.
http://www.ssrn.com/abstract=2564810
http://www.ssrn.com/1374034.htmlMon, 16 Feb 2015 06:36:49 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 6 – Normative Choices in Measurement DesignAfter a measurement methodology has been chosen, the design of poverty measures — whether unidimensional or multidimensional — require a series of normative choices. These choices relate to the space of the measure, its purpose, unit of identification and analysis, dimensions, indicators, deprivation cutoffs, weights, and poverty line. The normative contribution is not simply philosophical; it has a practical aim: to motivate action. This entails reasoned assessment of multiple considerations including feasibility, technical and statistical strength, ease of communication, and legitimacy. This chapter describes each of these normative choices in the context of multidimensional poverty measurement design. It clarifies the implications of each choice, illustrates interconnections between them, and outlines alternative ways that these choices might be understood, made, and justified.
http://www.ssrn.com/abstract=2564809
http://www.ssrn.com/1374010.htmlMon, 16 Feb 2015 06:35:07 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 6 – Normative Choices in Measurement DesignAfter a measurement methodology has been chosen, the design of poverty measures—whether unidimensional or multidimensional — require a series of normative choices. These choices relate to the space of the measure, its purpose, unit of identification and analysis, dimensions, indicators, deprivation cutoffs, weights, and poverty line. The normative contribution is not simply philosophical; it has a practical aim: to motivate action. This entails reasoned assessment of multiple considerations including feasibility, technical and statistical strength, ease of communication, and legitimacy. This chapter describes each of these normative choices in the context of multidimensional poverty measurement design. It clarifies the implications of each choice, illustrates interconnections between them, and outlines alternative ways that these choices might be understood, made, and justified.
http://www.ssrn.com/abstract=2564809
http://www.ssrn.com/1374033.htmlMon, 16 Feb 2015 06:34:42 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 4 – Counting Approaches: Definitions, Origins, and ImplementationsThe measurement of poverty involves identification: the fundamental step of deciding who is to be considered poor. A ‘counting approach’ is one way to identify the poor in multidimensional poverty measurement, which entails the intuitive procedure of counting the number of dimensions in which people suffer deprivation. Atkinson (2003) advised an engagement between multidimensional measures from social welfare and the counting approaches due to the widespread policy use of the latter. This chapter reviews applications of the counting methods in the history of poverty measurement. We focus on empirical studies since the late ‘70s which developed relatively independently of each other in two regions. In Latin America, applications of the Unsatisfied Basic Needs Approach were widespread, often using census and survey data. European work drew on concepts of social exclusion and inclusion, and now include national and European initiatives.
http://www.ssrn.com/abstract=2564785
http://www.ssrn.com/1374032.htmlMon, 16 Feb 2015 06:33:19 GMTREVISION: Multidimensional Poverty Measurement and Analysis: Chapter 5 – the Alkire-Foster Counting MethodologyThis chapter provides a systematic overview of the Alkire-Foster multidimensional measurement methodology with an emphasis on the Adjusted Headcount Ratio. The chapter is divided into seven sections. The first shows how this measure combines the practical appeal of the counting tradition with the rigor of the axiomatic one. The second sets out the identification of who is poor using the dual-cutoff approach, and the third outlines the aggregation method used to construct the Adjusted Headcount Ratio. In the fourth, we take stock and present the main distinctive characteristics of the Adjusted Headcount Ratio, whereas the fifth section presents its useful, consistent partial indices or components. To illustrate, we present a case study using the global Multidimensional Poverty Index (MPI) in the sixth section. The final section presents the members of the AF class of measures that can be constructed in less common situations where data are cardinal.
http://www.ssrn.com/abstract=2564787
http://www.ssrn.com/1374009.htmlMon, 16 Feb 2015 06:31:23 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 3 – Overview of Methods for Multidimensional Poverty AssessmentThis chapter presents a constructive survey of the major existing methods for measuring multidimensional poverty. Many measures were motivated by the basic needs approach, the capability approach, and the social inclusion approach among others. This chapter reviews Dashboards, the composite indices approach, Venn diagrams, the dominance approach, statistical approaches, fuzzy sets, and the axiomatic approach. The first two methods (dashboard and composite indices) are implemented using aggregate data from different sources ignoring the joint distribution of deprivations The other methods reflect the joint distribution and are implemented using data in which information on each dimension is available for each unit of analysis. After outlining each method, we provide a critical evaluation by discussing its advantages and disadvantages.
http://www.ssrn.com/abstract=2564782
http://www.ssrn.com/1374008.htmlMon, 16 Feb 2015 06:29:14 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 2 – The FrameworkThis working paper introduces the notation and basic concepts that are used throughout the OPHI Working Papers 82-91. The Paper has five sections. First we review unidimensional poverty measurement with particular attention to the well-known Foster-Greer-Thorbecke measures of income poverty as many methods presented in OPHI Working Paper 84 (Chapter 3 – Overview of Methods for Multidimensional Poverty Assessment) as well as the measure presented in OPHI Working Papers 86-90 (Chapters 5-9) are based on these measures. The second section introduces the notation and basic concepts for multidimensional poverty measurement that are used in subsequent chapters. Third we define indicators’ scales of measurement, and fourth, addressissues of comparability across people and dimensions. The fifth section systematically explains different properties that have been proposed in axiomatic approaches to multidimensional poverty measurement, which enable the analyst to understand the ethical ...
http://www.ssrn.com/abstract=2564766
http://www.ssrn.com/1374031.htmlMon, 16 Feb 2015 06:27:31 GMTNew: Multidimensional Poverty Measurement and Analysis: Chapter 1 – IntroductionThis working paper presents the normative, empirical, and policy motivations for focusing on multidimensional poverty measurement and analysis in general, and one measurement approach in particular. The fundamental normative motivation is to create effective measures that better reflect poor people’s experience, so that policies using such measures reduce poverty. Such measures are needed because, empirically, income-poor households are (surprisingly) not well-matched to households carrying other basic deprivations like malnutrition; also the trends of income and non-income deprivations are not matched, and nor does growth ensure the reduction of social deprivations. And, a dashboard overlooks the interconnection between deprivations, which people experience and policies seek to address. Turning to policy, we close by discussing how the Alkire-Foster methodology we present in Working Paper 86 (“Multidimensional Poverty Measurement and Analysis: Chapter 5 – The Alkire-Foster Counting ...
http://www.ssrn.com/abstract=2564702
http://www.ssrn.com/1374030.htmlMon, 16 Feb 2015 06:16:20 GMT