Binary data, hierarchy of attributes, and multidimensional deprivation
Shatakshee Dhongde (),
Yi Li (),
Prasanta K. Pattanaik () and
Yongsheng Xu ()
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Yi Li: Slippery Rock University
Prasanta K. Pattanaik: University of California, Riverside
Yongsheng Xu: Georgia State University
The Journal of Economic Inequality, 2016, vol. 14, issue 4, No 2, 363-378
Abstract Empirical estimation of multidimensional deprivation measures has gained momentum in the last few years. Several existing measures assume that deprivation dimensions are cardinally measurable, when, in many instances, such data is not always available. In this paper, we propose a class of deprivation measures when the only information available is whether an individual is deprived in an attribute or not. The framework is then extended to a setting in which the multiple dimensions are grouped as basic attributes that are of fundamental importance for an individual’s quality of life and non-basic attributes which are at a much lower level of importance. Empirical illustrations of the proposed measures are provided based on the estimation of multidimensional deprivation among children in Ethiopia, India, Peru and Vietnam.
Keywords: Binary data; Children; Deprivation; Hierarchy; Multiple dimensions; Poverty (search for similar items in EconPapers)
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