The Experts below are selected from a list of 12978 Experts worldwide ranked by ideXlab platform
James E. Foster - One of the best experts on this subject based on the ideXlab platform.
-
multidimensional Poverty Measurement and analysis chapter 3 overview of methods for multidimensional Poverty assessment
2015Co-Authors: Sabina Alkire, Suman Seth, Maria Emma Santos, Jose Manuel Roche, James E. Foster, Paola BallonAbstract:This 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.
-
Multidimensional Poverty Measurement and Analysis
Research Papers in Economics, 2015Co-Authors: Sabina Alkire, Suman Seth, Maria Emma Santos, Jose Manuel Roche, James E. Foster, Paola BallonAbstract:Multidimensional Poverty Measurement and analysis is evolving rapidly. Notably, it has informed the publication of the Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national Poverty measures in Mexico, Colombia, Bhutan, the Philippines and Chile. The academic response has been similarly swift, with related articles published in both theoretical and applied journals. The high and insistent demand for in-depth and precise accounts of multidimensional Poverty Measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of Poverty Measurement, and technical staff in governments and international agencies who create multidimensional Poverty measures. The book is organized into four elements. The first introduces the framework for multidimensional Measurement and provides a lucid overview of a range of multidimensional techniques and the problems each can address. The second part gives a synthetic introduction of 'counting' approaches to multidimensional Poverty Measurement and provides an in-depth account of the counting multidimensional Poverty Measurement methodology developed by Alkire and Foster, which is a straightforward extension of the well-known Foster-Greer-Thorbecke Poverty measures that had a significant and lasting impact on income Poverty Measurement. The final two parts deal with the pre-estimation issues such as normative choices and distinctive empirical techniques used in measure design, and the post-estimation issues such as robustness tests, statistical inferences, comparisons over time, and assessments of inequality among the poor.
-
counting and multidimensional Poverty Measurement
Journal of Public Economics, 2011Co-Authors: Sabina Alkire, James E. FosterAbstract:This paper proposes a new methodology for multidimensional Poverty Measurement consisting of an identification method ρk that extends the traditional intersection and union approaches, and a class of Poverty measures Mα. Our identification step employs two forms of cutoff: one within each dimension to determine whether a person is deprived in that dimension, and a second across dimensions that identifies the poor by ‘counting’ the dimensions in which a person is deprived. The aggregation step employs the FGT measures, appropriately adjusted to account for multidimensionality. The axioms are presented as joint restrictions on identification and the measures, and the methodology satisfies a range of desirable properties including decomposability. The identification method is particularly well suited for use with ordinal data, as is the first of our measures, the adjusted headcount ratio M0. We present some dominance results and an interpretation of the adjusted headcount ratio as a measure of unfreedom. Examples from the US and Indonesia illustrate our methodology.
-
understandings and misunderstandings of multidimensional Poverty Measurement
Journal of Economic Inequality, 2011Co-Authors: Sabina Alkire, James E. FosterAbstract:Multidimensional measures provide an alternative lens through which Poverty may be viewed and understood. In recent work we have attempted to offer a practical approach to identifying the poor and measuring aggregate Poverty (Alkire and Foster, J Public Econ, 2011). As this is quite a departure from traditional unidimensional and multidimensional Poverty Measurement—particularly with respect to the identification step—further elaboration may be warranted. In this paper we elucidate the strengths, limitations, and misunderstandings of multidimensional Poverty Measurement in order to clarify the debate and catalyse further research. We begin with general definitions of unidimensional and multidimensional methodologies for measuring Poverty. We provide an intuitive description of our Measurement approach, including a ‘dual cutoff’ identification step that views Poverty as the state of being multiply deprived, and an aggregation step based on the traditional FGT measures. We briefly discuss five characteristics of our methodology that are easily overlooked or mistaken and conclude with some brief remarks on the way forward.
-
counting and multidimensional Poverty Measurement
Research Papers in Economics, 2009Co-Authors: Sabina Alkire, James E. FosterAbstract:This paper proposes a new methodology for multidimensional Poverty Measurement consisting of an identification method ρκ ('rho-kapa') that extends traditional approaches, and a class of Poverty measures Μα ('Mu-alpha') that satisfies several desirable properties including decomposability. Our identification step employs two forms of cutoff: one within each dimension and a second across dimensions that identifies the poor by counting their deprivations. We aggregate using Foster-Greer-Thorbecke measures adjusted for multidimensionality. Our adjusted headcount ratio is well suited for use with ordinal data. Examples from Indonesia and the US illustrate our methodology.
Sabina Alkire - One of the best experts on this subject based on the ideXlab platform.
-
multidimensional Poverty Measurement and analysis chapter 3 overview of methods for multidimensional Poverty assessment
2015Co-Authors: Sabina Alkire, Suman Seth, Maria Emma Santos, Jose Manuel Roche, James E. Foster, Paola BallonAbstract:This 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.
-
Multidimensional Poverty Measurement and Analysis
Research Papers in Economics, 2015Co-Authors: Sabina Alkire, Suman Seth, Maria Emma Santos, Jose Manuel Roche, James E. Foster, Paola BallonAbstract:Multidimensional Poverty Measurement and analysis is evolving rapidly. Notably, it has informed the publication of the Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national Poverty measures in Mexico, Colombia, Bhutan, the Philippines and Chile. The academic response has been similarly swift, with related articles published in both theoretical and applied journals. The high and insistent demand for in-depth and precise accounts of multidimensional Poverty Measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of Poverty Measurement, and technical staff in governments and international agencies who create multidimensional Poverty measures. The book is organized into four elements. The first introduces the framework for multidimensional Measurement and provides a lucid overview of a range of multidimensional techniques and the problems each can address. The second part gives a synthetic introduction of 'counting' approaches to multidimensional Poverty Measurement and provides an in-depth account of the counting multidimensional Poverty Measurement methodology developed by Alkire and Foster, which is a straightforward extension of the well-known Foster-Greer-Thorbecke Poverty measures that had a significant and lasting impact on income Poverty Measurement. The final two parts deal with the pre-estimation issues such as normative choices and distinctive empirical techniques used in measure design, and the post-estimation issues such as robustness tests, statistical inferences, comparisons over time, and assessments of inequality among the poor.
-
a multidimensional approach Poverty Measurement beyond
Social Indicators Research, 2013Co-Authors: Sabina Alkire, Maria Emma SantosAbstract:This special issue comprises a set of nine papers that utilise the AF methodology. Their preliminary versions were presented at an OPHI workshop in June 2009 on ‘‘Multidimensional Measures in Six Contexts’’. In this Introduction we set out the AF methodology used throughout this issue, define terms that are common across papers, and highlight the advantages and limitations of this method. We also present other multidimensional Poverty measures to which the AF measures are compared in some papers, namely, the Unsatisfied Basic Needs (UBN) Index and the family of Bourguignon and Chakravarty (2003) measures. We close with a succinct overview of each paper in this issue.
-
counting and multidimensional Poverty Measurement
Journal of Public Economics, 2011Co-Authors: Sabina Alkire, James E. FosterAbstract:This paper proposes a new methodology for multidimensional Poverty Measurement consisting of an identification method ρk that extends the traditional intersection and union approaches, and a class of Poverty measures Mα. Our identification step employs two forms of cutoff: one within each dimension to determine whether a person is deprived in that dimension, and a second across dimensions that identifies the poor by ‘counting’ the dimensions in which a person is deprived. The aggregation step employs the FGT measures, appropriately adjusted to account for multidimensionality. The axioms are presented as joint restrictions on identification and the measures, and the methodology satisfies a range of desirable properties including decomposability. The identification method is particularly well suited for use with ordinal data, as is the first of our measures, the adjusted headcount ratio M0. We present some dominance results and an interpretation of the adjusted headcount ratio as a measure of unfreedom. Examples from the US and Indonesia illustrate our methodology.
-
beyond headcount measures that reflect the breadth and components of child Poverty
Social Science Research Network, 2011Co-Authors: Sabina Alkire, Jose Manuel RocheAbstract:This paper presents a new approach to child Poverty Measurement that reflects the breadth and components of child Poverty. The Alkire and Foster method presented in this paper seeks to answer the question ‘who is poor’ by considering the intensity of each child’s Poverty. Once children are identified as poor, the measures aggregate information on poor children’s deprivations in a way that can be broken down to see where and how children are poor. The resulting measures go beyond the headcount by taking into account the breadth, depth or severity of dimensions of child Poverty. The paper illustrates one way to apply this method to child Poverty Measurement, using Bangladeshi data from four rounds of the Demographic Health Survey covering the period 1997–2007. Results for Bangladesh show that the AF adjusted headcount ratio adds value because it produces a different ranking than the simple headcount, because it also reflects the simultaneous deprivations children experience (intensity). Given this, we argue that child Poverty should not be assessed only according to the incidence of Poverty but also by the intensity of deprivations that batter poor children’s lives at the same time. The Bangladesh example is used to illustrate how to compute and interpret the child Poverty figures, how the final measure can be broken down by groups and by dimensions in order to analyse child Poverty, how to interpret changes over time, and how to undertake robustness checks concerning the Poverty cut-off.
Peter Heindl - One of the best experts on this subject based on the ideXlab platform.
-
A Service of zbw Measuring fuel Poverty: General considerations and application to German household data SOEPpapers on Multidisciplinary Panel Data Research, No. 632 SOEPpapers on Multidisciplinary Panel Data Research Measuring Fuel Poverty: General Consi
2020Co-Authors: Gert G Wagner, Peter HeindlAbstract:Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly. Terms of use: Documents in Any opinions expressed in this series are those of the author(s) and not those of DIW Berlin. Research disseminated by DIW Berlin may include views on public policy issues, but the institute itself takes no institutional policy positions. Abstract Fuel Poverty Measurement consists of two independent parts: firstly, the definition of an adequate fuel Poverty line, and secondly, techniques to measure fuel Poverty. This paper reviews options for the definition of fuel Poverty lines and techniques for fuel Poverty Measurement. Based on household data from Germany, figures that would result from different fuel Poverty lines are derived. Different fuel Poverty lines yield highly different results with respect to which households are identified as fuel poor. Thus, the choice of the fuel Poverty line matters decisively for the resulting assessment. Options for fuel Poverty Measurement and subgroup comparison are discussed. Das Wichtigste in Kürz
-
Dynamic Properties of Energy Affordability Measures Dynamic Properties of Energy Affordability Measures Dynamic Properties of Energy Affordability Measures
2020Co-Authors: Peter Heindl, Rudolf SchüsslerAbstract:Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar. Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. Dynamic Properties of Energy Affordability Measures Peter Heindl* Department of Environmental and Resource Economics Centre for European Economic Research, Mannheim (Germany) and Rudolf Schüssler** Department of Philosophy University of Bayreuth (Germany) -Abstract - Measures of affordability are applied in practice, e.g., to assess the affordability of energy services, water or housing. They can be interpreted as measures of deprivation in a specific domain of consumption. The large body of literature on affordability measure has little overlap with the existing literature on Poverty Measurement. A comprehensive assessment of the response of affordability measures as a result of changes in the distribution of income or expenditure is missing. This paper aims to fill this gap by providing a conceptual discussion on the 'dynamics' of energy affordability measures. Several types of measures are examined in a microsimulation framework to assess their dynamic properties. Our results indicate that some measures exhibit odd dynamic behavior. This includes measures used in practice, such as the low income/high cost measure and the double median of expenditure share indicator. Odd dynamic behavior is attributed to definitions made with respect to higher moments of the expenditure distribution. Definitions that rely on a percentage share of expenditure relative to income or an absolute or relative income Poverty line fare well from a dynamic perspective
-
measuring fuel Poverty general considerations and application to german household data
SOEPpapers on Multidisciplinary Panel Data Research, 2014Co-Authors: Peter HeindlAbstract:Fuel Poverty Measurement consists of two independent parts: firstly, the definition of an adequate fuel Poverty line, and secondly, techniques to measure fuel Poverty. This paper reviews options for the definition of fuel Poverty lines and techniques for fuel Poverty Measurement. Based on household data from Germany, figures that would result from different fuel Poverty lines are derived. Different fuel Poverty lines yield highly different results with respect to which households are identified as fuel poor. Thus, the choice of the fuel Poverty line matters decisively for the resulting assessment. Options for fuel Poverty Measurement and subgroup comparison are discussed.
-
measuring fuel Poverty general considerations and application to german household data
FinanzArchiv: Public Finance Analysis, 2013Co-Authors: Peter HeindlAbstract:Fuel Poverty may become an increasingly severe problem in developed countries in cases when real prices for fossil fuels increase at high rates or when real energy prices increase due to policies for greenhouse gas abatement. Fuel Poverty Measurement consists of two largely independent parts, firstly, the definition of an adequate fuel Poverty line, and secondly, the application of techniques to measure fuel Poverty given some Poverty line. This paper reviews options for the definition of fuel Poverty lines as well as techniques for fuel Poverty Measurement. Based on household data from Germany, figures that would result from different fuel Poverty lines are derived. Different fuel Poverty lines partly yield highly different results with respect to which households are identified as fuel poor. Thus, the choice of the fuel Poverty line matters decisively for the resulting fuel Poverty assessment. Options for fuel Poverty Measurement and subgroup comparison in order to identify most vulnerable types of households are discussed in the light of the literature and based on applications to German household data.
Dahlia K Remler - One of the best experts on this subject based on the ideXlab platform.
-
including health insurance in Poverty Measurement the impact of massachusetts health reform on Poverty
Journal of Health Economics, 2016Co-Authors: Sanders Korenman, Dahlia K RemlerAbstract:We develop and implement what we believe is the first conceptually valid health-inclusive Poverty measure (HIPM) – a measure that includes health care or insurance in the Poverty needs threshold and health insurance benefits in family resources – and we discuss its limitations. Building on the Census Bureau's Supplemental Poverty Measure, we construct a pilot HIPM for the under-65 population under ACA-like health reform in Massachusetts. This pilot demonstrates the practicality, face validity and value of a HIPM. Results suggest that public health insurance benefits and premium subsidies accounted for a substantial, one-third reduction in the health inclusive Poverty rate.
-
including health insurance in Poverty Measurement the impact of massachusetts health reform on Poverty
National Bureau of Economic Research, 2016Co-Authors: Sanders Korenman, Dahlia K RemlerAbstract:We develop and implement what we believe is the first conceptually valid health-inclusive Poverty measure (HIPM)—a measure that includes health care or insurance in the Poverty needs threshold and health insurance benefits in family resources—and we discuss its limitations. Building on the Census Bureau’s Supplemental Poverty Measure, we construct a pilot HIPM for the under-65 population under ACA-like health reform in Massachusetts. This pilot is intended to demonstrate the practicality, face validity and value of a HIPM. Results suggest that public health insurance benefits and premium subsidies accounted for a substantial, one-third reduction in the Poverty rate. Among low-income families who purchased individual insurance, premium subsidies reduced Poverty by 9.4 percentage points.
Yanhua Liu - One of the best experts on this subject based on the ideXlab platform.
-
a geographic identification of multidimensional Poverty in rural china under the framework of sustainable livelihoods analysis
Applied Geography, 2016Co-Authors: Yanhua LiuAbstract:Abstract Developing methods of measuring multidimensional Poverty and improving the accuracy of Poverty identification have been hot topics in international Poverty research for decades. They are also key issues for improving the quality and effectiveness of rural Poverty reduction programs in China. So far, selection and integration of Poverty indicators remains the main difficult for Measurement of multidimensional Poverty. Guided by the sustainable livelihoods framework developed in the UK by the Department for International Development (DFID), an index system and an integration method for geographical identification of multidimensional Poverty were established, and they were further used to carry out a county-level identification of Poverty in rural China. Additionally, comparisons were made of the identification results with counties having single-dimension income Poverty in rural areas and poor counties designated by the Chinese central government. The results showed that a total of 655 counties, with 141 million rural residents, were identified as multidimensionally poor. They are concentrated and conjointly distributed geographically, and evil natural conditions are their common features. In comparison to the income poor and the designated poor counties, the multidimensionally poor counties were not only worse in single-dimensional and composite scores, but also having multiple disadvantages and deprivations. By identifying the disadvantage and deprived dimensions, the Measurement of multidimensional Poverty should be very helpful for each county to work out and implement antiPoverty programs accordingly, and it would make contribution to improve the sustainability of Poverty reduction. Hopefully, this research may also shed light on multidimensional Poverty Measurement for other developing countries.