INTRODUCTION
11.1 Among national statistical agencies, quality is generally accepted as 'fit for purpose'. Fit for purpose implies an assessment of an output, with specific reference to its intended objectives or aims. Quality is therefore a multidimensional concept which does not only include the accuracy of statistics, but also includes other aspects such as relevance and interpretability.
11.2 Over the last decade, considerable work has been undertaken in statistical and economic agencies to define and measure quality. The ABS Data Quality Framework uses seven dimensions of quality, reflecting a broad and inclusive approach to quality definition and assessment. The seven dimensions of quality are institutional environment, relevance, timeliness, accuracy, coherence, interpretability and accessibility.
11.3 There are often trade-offs between the different dimensions of quality. In order to make economic statistics timely enough to be relevant indicators for the analysis of current and recent economic conditions this is likely to be at the expense of some degree of accuracy. The ABS, in consultation with data users, aims to optimise the different dimensions of quality.
11.4 This chapter will assess the quality of international merchandise trade statistics using the seven dimensions of quality. When assessing the quality of statistics the ABS and international organisations recommend that all seven dimensions should be considered together but some statistical users may place more weight on particular dimensions.
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