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In the European Union, tens of billions of euros are spent on regional policy every year. A major part of this amount is allocated on the basis of regional gross domestic product per capita. Because of the administrative use of this statistical estimate, the requirements for the quality of these figures are very strict. This quality is, however, not easy to specify by means of a confidence interval. What can be done to monitor the quality as a basis for improvement? In this paper an inventory is drawn up of recent work on the quality of regional accounts estimates. Special attention is paid to the instrument of process tables. In the last five years process tables have been developed for the national accounts (GNI Committee) as well as the regional accounts. The focus of the regional accounts process tables is on the treatment of multi-regional companies and the sources for top-down methods. The regional accounts should be compiled in close cooperation with the national accounts. The quality of the national accounts estimates and – indirectly – the regional accounts estimates, could be improved by the findings of the regional accounts compilation process. [ABSTRACT FROM AUTHOR]

Abstract. The Office for National Statistics Longitudinal Study (LS) contains anonymised linked census and life event data for one per cent of the population of England and Wales. This dataset has been prepared, maintained and developed for the last thirty years to a high standard of quality. Data quality is maintained through an optimal balance between user needs and processing constraints, including costs. The current linkage of 2001 Census data is described with reference to the quality dimensions of relevance, accuracy, timeliness, accessibility and clarity, comparability, coherence and completeness. Some of the processes described are context-specific, like the availability of expert tracing staff at the National Health Service Central Register and the use of ONS administrative data. Others are good practices that can be shared by other Statistical Agencies, including effective communications, comprehensive metadata, a safe setting environment for authorised user s to access the data, user support and training. Quality management in the LS involves the monitoring of processes and products in a cycle of continuous improvement. This process of proactive, continuous change is demanding and relies crucially upon the contribution of a dedicated and expert staff. [ABSTRACT FROM AUTHOR]