Poverty measurement and the analysis of the progress (or otherwise) of the poor, whether it is societies, families or individuals, is beset with difficulties and controversies surrounding the definition of a poverty line or frontier. Here, borrowing ideas from the mixture model literature, a new approach to assigning poverty-non poverty status is proposed which avoids specifying a frontier, the price is that an agent's poverty status is only determined to the extent of its chance of being poor. Invoking variants of Gibrat's law to give structure to the distribution of outcomes for homogeneous subgroups of a population within the context of a finite mixture model of societal outcomes facilitates calculation of an agent's poverty status probability. From this it is straightforward to calculate all the usual poverty measures as well as other characteristics of the poor and non poor subgroups in a society. These ideas are exemplified in a study of 47 countries in Africa over the recent quarter century which reveals among other things a growing poverty rate and a growing disparity between poor and non poor groups not identified by conventional methods. © 2013 Springer Science+Business Media New York.
Poverty status probability: a new approach to measuring poverty and the progress of the poor / Gordon, Anderson; Pittau, Maria Grazia; Zelli, Roberto. - In: THE JOURNAL OF ECONOMIC INEQUALITY. - ISSN 1569-1721. - STAMPA. - 12:4(2014), pp. 469-488. [10.1007/s10888-013-9264-5]
Poverty status probability: a new approach to measuring poverty and the progress of the poor
PITTAU, Maria Grazia;ZELLI, Roberto
2014
Abstract
Poverty measurement and the analysis of the progress (or otherwise) of the poor, whether it is societies, families or individuals, is beset with difficulties and controversies surrounding the definition of a poverty line or frontier. Here, borrowing ideas from the mixture model literature, a new approach to assigning poverty-non poverty status is proposed which avoids specifying a frontier, the price is that an agent's poverty status is only determined to the extent of its chance of being poor. Invoking variants of Gibrat's law to give structure to the distribution of outcomes for homogeneous subgroups of a population within the context of a finite mixture model of societal outcomes facilitates calculation of an agent's poverty status probability. From this it is straightforward to calculate all the usual poverty measures as well as other characteristics of the poor and non poor subgroups in a society. These ideas are exemplified in a study of 47 countries in Africa over the recent quarter century which reveals among other things a growing poverty rate and a growing disparity between poor and non poor groups not identified by conventional methods. © 2013 Springer Science+Business Media New York.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.