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Consequences of Data Error in Aggregate Indicators: Evidence from the Human Development Index

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  • Wolff, Hendrik

    (Simon Fraser University)

  • Chong, Howard

    (University of California, Berkeley)

  • Auffhammer, Maximilian

    (University of California, Berkeley)

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.

Suggested Citation

  • Wolff, Hendrik & Chong, Howard & Auffhammer, Maximilian, 2008. "Consequences of Data Error in Aggregate Indicators: Evidence from the Human Development Index," IZA Discussion Papers 3346, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp3346
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    Cited by:

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    2. Andrea Brandolini & Giovanni Vecchi, 2011. "The Well-Being of Italians: A Comparative Historical Approach," Quaderni di storia economica (Economic History Working Papers) 19, Bank of Italy, Economic Research and International Relations Area.

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    More about this item

    Keywords

    international comparative statistics; measurement error;

    JEL classification:

    • O10 - Economic Development, Innovation, 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

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