Abstract
Poverty has been conceptualized and measured from a multidimensional perspective, generally by applying the classical composite index approach. However, this approach is far from capturing the diversity of individual’s poverty profiles and suffers from several shortcomings, notably regarding comparability, weighting, and aggregation issues. Such multidimensional indices are based on a dichotomized simplistic view of poverty in which binary category opposition prevails such as poor and non-poor, deprived and non-deprived. Furthermore, combining dichotomized threshold-based scores hides the complexity of ‘in-between poverty and prosperity’ profiles. In this chapter, we show that in comparison to the traditional composite index approach, the partial order theory allows to detect these ‘in-between’ profiles. In our study, monetary poverty, material deprivation, and well-being, measured with objective and subjective indicators, are used to analyse multidimensional poverty in Switzerland. The empirical analysis is based on the Swiss Household Panel data of 2013 and is realized by using partial order R package PARSEC.
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Notes
- 1.
Ordinal indicators (e.g. 0 = not at all satisfied, 1 = a very little satisfied, …, 10 = totally satisfied) can be seen as a (quantitative) scale but they cannot be numerically combined (e.g. by mathematical functions).
- 2.
In 2010, Alkire and Foster’s method is used for creating the United Nations Development Programme’s MPI (Multidimensional Poverty Index) which replaced the Human Poverty Index (HPI).
- 3.
The SHP is a longitudinal survey with yearly waves conducted since 1999.
- 4.
The relative monetary poverty variable is a dichotomous (0 = having an income less than 60% of annual median equivalized net household income (OECD criterion); 1 = otherwise), i.e. having an income less than 60 % of the median is considered poor.
- 5.
Generally, profiles can be written in a form such as 3,1,4 instead of 3/1/4. However, as the outputs obtained from the R package PARSEC yield profiles information in a form with ‘/’, so we kept the format with ‘/’ to avoiding confusion.
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Acknowledgment
This contribution is based on the project ‘Multidimensional well-being: conceptual, methodological, analytical perspectives’, financed by the Indo-Swiss Joint Research Programme in the Social Sciences (seed money grants).
This study has been realized using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social sciences FORS in Lausanne. The SHP data are collected within the framework of the research program ‘Living in Switzerland’, financed by the Swiss National Science Foundation.
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Beycan, T., Suter, C. (2017). Application of Partial Order Theory to Multidimensional Poverty Analysis in Switzerland. In: Fattore, M., Bruggemann, R. (eds) Partial Order Concepts in Applied Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-45421-4_9
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