Premium
Means, Motive, and Opportunity – Local Government Data Distortion in a High‐Stakes Environment
Author(s) -
Drew Joseph,
Grant Bligh
Publication year - 2017
Publication title -
australian journal of public administration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.524
H-Index - 41
eISSN - 1467-8500
pISSN - 0313-6647
DOI - 10.1111/1467-8500.12225
Subject(s) - salient , distortion (music) , depiction , government (linguistics) , empirical evidence , public policy , conceptual framework , economics , business , public economics , computer science , sociology , artificial intelligence , computer network , amplifier , linguistics , philosophy , social science , bandwidth (computing) , epistemology , economic growth
Regulatory authorities are increasingly relying upon performance data for developing public policy. However, this reliance necessarily assumes that the data are free from material distortion. This paper provides a conceptual framework for understanding the ‘means’, ‘motive’, and ‘opportunity’ for distorting data employed in high‐stakes performance‐management programmes. We present empirical evidence which suggests that the use of data drawn entirely from financial statements by no means guarantees a distortion‐free depiction of performance. In addition, we provide econometric evidence of some important determinants of performance data distortion. Taken as a whole, the following analysis provides a comprehensive picture of the salient matters which must be addressed to ensure accurate data for public policy‐making purposes.