Using Data Envelopment Analysis to Construct Human Development Index

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Author(s): Paulo Nocera Alves Junior (University of São Paulo (USP), Brazil), Enzo Barberio Mariano (São Paulo State University (UNESP), Brazil)and Daisy Aparecida do Nascimento Rebelatto (University of São Paulo (USP), Brazil)
Copyright: 2017
Pages: 26
Source title: Emerging Trends in the Development and Application of Composite Indicators
Source Author(s)/Editor(s): Veljko Jeremic (University of Belgrade, Serbia), Zoran Radojicic (University of Belgrade, Serbia)and Marina Dobrota (University of Belgrade, Serbia)
DOI: 10.4018/978-1-5225-0714-7.ch013

Keywords: Data Analysis & Statistics / Data Analysis and Statistics / Information Science Reference / Library & Information Science

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Abstract

This chapter addresses problems related to methodological issues, such as data normalization, weighting schemes, and aggregation methods, encountered in the construction of composite indicators to measure socio-economic development and quality of life. It also addresses the use of several Data Envelopment Analysis (DEA) models to solve these problems. The models are discussed and applied in constructing a Human Development Index (HDI), derived from the most recent raw and normalized data, using arithmetic and geometric means to aggregate the indices. Issues related to data normalization and weighting schemes are emphasized. Kendall Correlation was applied to analyze the relationship between ranks obtained by DEA models and HDI. Recommendations regarding the advantages and disadvantages of using DEA models to construct HDI are offered.

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