Dublin Core
Title
Comparison Study of Approaches to Measuring Poverty Implementing Fuzzy Set and Classic Set Using The Household Data of Turkey
Abstract
Poverty is one of the issues several industrialized and developing countries encounter in the world. No country is exempt from this problem and its consequences. The top list item of the agendas of both countries and international agencies is related to diminishing poverty. Before taking action against it, countries and agencies need to measure poverty based on collected data. It is a sophisticated issue having several dimensions. So far measuring it with available data has resulted with indicators which show some deficiencies. When poverty is considered, it is a linguistic term and has a vague concept as mentioned in the theory of fuzzy set. Therefore, a new approach is proposed in the literature to examine it in order to overcome those deficiencies mentioned when classic tools are employed. On the other hand, fuzzy set theory is a mathematical tool used for linguistic calculations. For example, when said that income level is low. Actually everybody knows what it means. But what it means changes depending upon the perception of the person. Therefore, measuring low income is a problematic area. Fuzzy set theory enables practitioners to calculate those linguistic terms. In this study, the household data of Turkey of the year 2003 collected annually based on almost 25000 is used to calculate both classic poverty indicator(s) and fuzzy poverty indicator in order to compare those measures. In the end we will show that fuzzy poverty indicator can be comprehensive in some comparisons. Also, it provides more information in terms of understanding the concept of poverty Keywords: Poverty, fuzzy set, fuzzy index, Sustainable development
Keywords
Conference or Workshop Item
PeerReviewed
PeerReviewed
Date
2012-05-31
Extent
1160