Setting weights for aggregate indices: An application to the commitment to development index and human development index

Chowdhury, Shyamal; Squire, Lyn

doi:10.1080/00220380600741904

Cited by 144 publications

(81 citation statements)

References 14 publications

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“…Normative approaches, on the other hand, only depend on the value judgements to set the weights. Despite its popularity, the arbitrariness of equal weighting is far from uncontroversial (Chowdhury & Squire, 2006;Ravallion, 2011). The fundamental problem is: whose value judgements on welfare are used?…”

Section: Constructing the Sampi-oimentioning

confidence: 99%

The threshold effects of household indebtedness on multidimensional poverty

Ntsalaze

Ikhide

2017

IJSE

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DeclarationBy submitting this dissertation electronically, I declare that the entirety of the work contained therein is my own, original work, that I am the sole author thereof (save to the extent explicitly otherwise stated), that reproduction and publication thereof by Stellenbosch University will not infringe any third party rights and that I have not previously in its entirety or in part submitted it for obtaining any qualification.This dissertation includes two published and one accepted but not yet published original papers in peer-reviewed international journals. The fourth paper representing chapter eight is ready for submission for peer review. The development and writing of the papers (published and unpublished) were the principal responsibility of myself and, for each of the cases where this is not the case, a declaration is included in the dissertation indicating the nature and extent of the contributions of co-authors. AbstractGlobal household indebtedness has reached unprecedented levels over the past few decades.The household sector has had to cope with significant losses in income and wealth as well as the burden of debt service since the beginning of the financial crisis. Research focus on this phenomenon, together with its social implications, has grown. This study uses the National Income Dynamics Study (NIDS) data to empirically investigate the effects of household debt on multidimensional poverty. This was achieved through four independent research papers meant to address different angles of the subject. Chapter 5 provides a snapshot of the prevalence of over-indebtedness, using various international indicators and the National Credit Regulator (NCR) indicator, and describes which households are over-indebted. A total of eight percent of South African households are overindebted, and 61.4 percent of those households are found in the lowest income category (R0 -R2 000), spending more than 45 percent of their household income on debt repayments, which is beyond levels that are considered sustainable. The alarming revelation is that, according to the unsecured debt indicator, 15.2 percent of households are over-indebted, while 11 percent of households are driven below the relative income poverty line after making debt repayments. Stellenbosch University https://scholar.sun.ac.za 3The racial distribution indicates that households headed by Africans are overrepresented (79%).Most over-indebted households are found amongst those who own their places of residence (78.6%), do not receive government grants (71.7%), are male (53.8%), and have an unemployed household head (53.5%).Chapter 6 examines the presence of thresholds in the debt-poverty nexus at micro level, i.e. the tipping point above which debt is associated with more multidimensional poverty. By applying the Generalised Additive Model (GAM) using regression splines, the study finds the existence of critical tipping points between household debt service-to-income ratio and multidimensional poverty along with other explanatory variables (age...

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Section: Constructing the Sampi-oimentioning

confidence: 99%

The threshold effects of household indebtedness on multidimensional poverty

Ntsalaze

Ikhide

2017

IJSE

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“…The HDI was initially developed to underline that people and their capabilities should be the ultimate criteria for evaluating the development level of a country along with economic growth (UNDP, 2013a). Despite a number of authors discuss some drawbacks of the HDI (Trabold-Nübler, 1991;Hicks, 1997;Ivanova, Arcelus, & Srinivasan, 1999;Chowdhury & Squire, 2006;Klugman, Rodríguez, & Choi, 2011), and even propose some modified indices (Paul, 1996;Sharma, 1997;Noorbakhsh, 1998;Chakravarty, 2003;Mazumdar, 2003;Grimm, et al, 2008;Harttgen & Klasen, 2012;Herrero, Martínez, & Villar, 2012;Bilbao-Ubillos, 2013;Blancard & Hoarau, 2013); one of the most significant superiorities of the HDI is regarded as its usefulness that is able to represent both social and economic development through a single value between 0 and 1 (UNDP, 2013b).…”

Section: Human Development and The Hdimentioning

confidence: 99%

Determinants of the Levels of Development Based on the Human Development Index: A Comparison of Regression Models for Limited Dependent Variables

Eren

Çelik

Kubat³

2014

RES

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This paper aims to examine the factors affecting the level of development of countries using various regression models for limited dependent variables including binary logit, probit and Tobit analyses. In this manner, the paper may suggest a road map for high developed countries to achieve very high developed levels. For this purpose, Human Development Indices of 84 countries were involved in the analysis with respect to nine independent variables. The results of the all regression models indicate that determinants including life expectancy at birth, expected years of schooling, labour force participation rate (female-male ratio), and GDP per capita have statistically significant effects on the level of development.

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“…Each of the metrics and indicators was scored from 0 to 100, with higher values desirable. Various systems have been proposed for weighting indicators [15][16][17]. However, based on stakeholder feedback, we have chosen to apply equal weighting to indicators, as indicated in Table 1.…”

Section: Metrics Definitionsmentioning

confidence: 99%

Seven Food System Metrics of Sustainable Nutrition Security

et al. 2016

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Sustainability considerations have been absent from most food security assessments conducted to date, despite the tremendous economic, environmental, and social implications of meeting accelerating food demand in the face of water shortages and climate change. In addition, previous food security work has generally focused only on achieving adequate calories, rather than addressing dietary diversity and micronutrient adequacy, both of which are critical to maintaining a healthy overall nutritional status. In response to the limitations of previous assessments, a new methodology is proposed here based on the concept of "sustainable nutrition security" (SNS). This novel assessment methodology is intended to remedy both kinds of deficiencies in the previous work by defining seven metrics, each based on a combination of multiple indicators, for use in characterizing sustainable nutrition outcomes of food systems: (1) food nutrient adequacy; (2) ecosystem stability; (3) food affordability and availability; (4) sociocultural wellbeing; (5) food safety; (6) resilience; and (7) waste and loss reduction. Each of the metrics comprises multiple indicators that are combined to derive an overall score (0-100). A novel SNS assessment methodology based on these metrics can be deployed by decision-makers and investors to set meaningful goals, track progress, and evaluate the potential impact of food system interventions intended to improve sustainability and human nutrition outcomes.

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Setting weights for aggregate indices: An application to the commitment to development index and human development index

Cited by 144 publications

References 14 publications

The threshold effects of household indebtedness on multidimensional poverty

The threshold effects of household indebtedness on multidimensional poverty

Determinants of the Levels of Development Based on the Human Development Index: A Comparison of Regression Models for Limited Dependent Variables

Seven Food System Metrics of Sustainable Nutrition Security

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