Classification, Detection and Consequences of Data Error: Evidence from the Human Development Index

Working Paper No. 16572 We measure and examine data error in health, education and income statistics used to construct the Human Development Index. We identify three sources of data error which are due to (i) data updating, (ii) formula revisions and (iii) thresholds to classify a country's dev...

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Bibliographic Details
Published in:NBER Working Paper Series 2010-12, p.16572
Main Authors: Wolff, Hendrik, Chong, Howard, Auffhammer, Maximilian
Format: Article
Language:English
Subjects:
Classification
Cooperation
Economic growth
Economic indicators
Economic statistics
Economic theory
Education
GDP
Gross Domestic Product
Human Development Index
International relations
Revisions
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Summary:Working Paper No. 16572 We measure and examine data error in health, education and income statistics used to construct the Human Development Index. We identify three sources of data error which are due to (i) data updating, (ii) formula revisions and (iii) thresholds to classify a country's development status. We propose a simple statistical framework to calculate country specific measures of data uncertainty and investigate how data error biases rank assignments. We find that up to 34% of countries are misclassified and, by replicating prior studies, we show that key estimated parameters vary by up to 100% due to data error.
ISSN:0898-2937
DOI:10.3386/w16572