Classification, Detection and Consequences of Data Error: Evidence from the Human Development Index
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.
|Date of creation:||Jan 2011|
|Publication status:||Published in Economic Journal, Volume|
|Contact details of provider:|| Postal: Box 353330, Seattle, WA 98193-3330|
Web page: http://www.econ.washington.edu/
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- Juan D Moreno-Ternero & John E Roemer, 2006.
"Impartiality, Priority, and Solidarity in the Theory of Justice,"
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- MORENO-TERNERO, Juan D. & ROEMER, John E., 2005. "Impartiality, priority, and solidarity in the theory of justice," CORE Discussion Papers 2005077, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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- de la Fuente, Angel & Doménech, Rafael, 2000. "Human Capital In Growth Regressions: How Much Difference Does Data Quality Make?," CEPR Discussion Papers 2466, C.E.P.R. Discussion Papers.
- Angel de la Fuente & Rafael Donénech, 2000. "Human Capital in Growth Regressions: How much Difference Does Data Quality Make?," OECD Economics Department Working Papers 262, OECD Publishing.
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