The Data Quality Concept of Accuracy in the Context of Public Use Data Sets
Carsten Kuchler and
No 586, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research
Like other data quality dimensions, the concept of accuracy is often adopted to characterise a particular data set. However, its common specification basically refers to statistical properties of estimators, which can hardly be proved by means of a single survey at hand. This ambiguity can be resolved by assigning 'accuracy' to survey processes that are known to affect these properties. In this contribution, we consider the sub-process of imputation as one important step in setting up a data set and argue that the so called 'hit-rate' criterion, that is intended to measure the accuracy of a data set by some distance function of 'true' but unobserved and imputed values, is neither required nor desirable. In contrast, the so-called 'inference' criterion allows for valid inferences based on a suitably completed data set under rather general conditions. The underlying theoretical concepts are illustrated by means of a simulation study. It is emphasised that the same principal arguments apply to other survey processes that introduce uncertainty into an edited data set.
Keywords: Survey Quality; Survey Processes; Accuracy; Assessment of Imputation Methods; Multiple Imputation (search for similar items in EconPapers)
JEL-codes: C11 C13 C15 C81 C83 (search for similar items in EconPapers)
Pages: 22 p.
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Persistent link: https://EconPapers.repec.org/RePEc:diw:diwwpp:dp586
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