Human Development Index: Are Developing Countries Misclassified? (former title: "Consequences of Data Error in Aggregate Indicators: Evidence from the Human Development Index)
AbstractThis paper examines the consequences of data error in data series used to construct aggregate indicators. Using the most popular indicator of country level economic development, the Human Development Index (HDI), we identify three separate sources of data error. We propose a simple statistical framework to investigate how data error may bias rank assignments and identify two striking consequences for the HDI. First, using the cutoff values used by the United Nations to assign a country as ‘low’, ‘medium’, or ‘high’ developed, we find that currently up to 45% of developing countries are misclassified. Moreover, by replicating prior development/macroeconomic studies, we find that key estimated parameters such as Gini coefficients and speed of convergence measures vary by up to 100% due to data error.
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Bibliographic InfoPaper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49763.
Date of creation: 2009
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More information through EDIRC
Measurement Error; International Comparative Statistics; International Development; O10; C82;
Find related papers by JEL classification:
- O10 - Economic Development, Technological Change, and Growth - - Economic Development - - - General
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-16 (All new papers)
- NEP-DEV-2009-05-16 (Development)
- NEP-HAP-2009-05-16 (Economics of Happiness)
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