Evaluating the welfare of nations is high on the research agenda of the economists, practitioners and policy-makers. The literature contributions of the last decades triggered a multivariate perception of the well-being, which is suggested to go beyond the GDP, and created a need for more complex approaches to evaluate the welfare as well as poverty. The first essay investigates the approaches to multivariate poverty measurement and focuses on the composite index approach and the steps involved in it. An important aspect of the multivariate perspective in well-being is the dependence among the underlying indicators. There is growing evidence in the literature that well-being dimensions are interrelated. This dependence among attributes matters for multidimensional poverty measurement, since income is no longer the only indicator to be considered. However, the reviewed approaches to multivariate poverty measurement do not commonly capture this interdependence. The second essay suggests a copula function as a flexible tool to estimate the dependence among welfare variables. Moreover, it proposes to incorporate the evaluated dependence in the composite indicator. The trade-off among attributes, which is established via the weighting of dimensions, is identified as a possible channel to include the interdependence in the composite indicator. The third essay of this dissertation defines bivariate and multivariate copula-based measures of dependence and applies them using the recent data from the EU-SILC. The results suggest that key dimensions of well-being, i.e. income, education and health, are positively interdependent. In addition, the strength of pairwise and multivariate dependence reinforced in the post-crisis period in some European countries. Finally, the last essay proposes a new class of the copula-based multidimensional poverty indices by innovating over the weighting approach. The weighting scheme proposed in this dissertation incorporates the estimated copula-based dependence and contains necessary normative controls to be chosen by the practitioner. The findings of the last essay suggest that the overall poverty is driven not only by the individual shortfalls, but also by the degree of interdependence among well-being indicators. Considering the proposed copula-based weighting scheme and the proposal of the new class of copula-based poverty indices, this dissertation contributes to the multivariate poverty measurement by suggesting the channel to enclose the dependence structure in the composite indicators. The proposed copula-based methodology will advance the multidimensional poverty analysis and the poverty-reducing policy, which can be designed to address the problem of interdependence of individual achievements.

(2019). Essays on multidimensional poverty measurement and the dependence among well-being dimensions. (Tesi di dottorato, Università degli studi dell'Insubria, 2019).

Essays on multidimensional poverty measurement and the dependence among well-being dimensions

TKACH, KATERYNA
2019-09-13

Abstract

Evaluating the welfare of nations is high on the research agenda of the economists, practitioners and policy-makers. The literature contributions of the last decades triggered a multivariate perception of the well-being, which is suggested to go beyond the GDP, and created a need for more complex approaches to evaluate the welfare as well as poverty. The first essay investigates the approaches to multivariate poverty measurement and focuses on the composite index approach and the steps involved in it. An important aspect of the multivariate perspective in well-being is the dependence among the underlying indicators. There is growing evidence in the literature that well-being dimensions are interrelated. This dependence among attributes matters for multidimensional poverty measurement, since income is no longer the only indicator to be considered. However, the reviewed approaches to multivariate poverty measurement do not commonly capture this interdependence. The second essay suggests a copula function as a flexible tool to estimate the dependence among welfare variables. Moreover, it proposes to incorporate the evaluated dependence in the composite indicator. The trade-off among attributes, which is established via the weighting of dimensions, is identified as a possible channel to include the interdependence in the composite indicator. The third essay of this dissertation defines bivariate and multivariate copula-based measures of dependence and applies them using the recent data from the EU-SILC. The results suggest that key dimensions of well-being, i.e. income, education and health, are positively interdependent. In addition, the strength of pairwise and multivariate dependence reinforced in the post-crisis period in some European countries. Finally, the last essay proposes a new class of the copula-based multidimensional poverty indices by innovating over the weighting approach. The weighting scheme proposed in this dissertation incorporates the estimated copula-based dependence and contains necessary normative controls to be chosen by the practitioner. The findings of the last essay suggest that the overall poverty is driven not only by the individual shortfalls, but also by the degree of interdependence among well-being indicators. Considering the proposed copula-based weighting scheme and the proposal of the new class of copula-based poverty indices, this dissertation contributes to the multivariate poverty measurement by suggesting the channel to enclose the dependence structure in the composite indicators. The proposed copula-based methodology will advance the multidimensional poverty analysis and the poverty-reducing policy, which can be designed to address the problem of interdependence of individual achievements.
Gigliarano, Chiara
Multidimensional poverty measurement; Composite indicators; Weighting; Copula function; Copula-based dependence
English
PhD Program in Methods and Models for Economic Decisions
31
2018/2019
Università degli studi dell'Insubria
(2019). Essays on multidimensional poverty measurement and the dependence among well-being dimensions. (Tesi di dottorato, Università degli studi dell'Insubria, 2019).
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/317984
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