Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/35185 
Year of Publication: 
2008
Series/Report no.: 
IZA Discussion Papers No. 3346
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
This 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.
Subjects: 
Measurement error
international comparative statistics
JEL: 
O10
Document Type: 
Working Paper

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