Fiscal data as a tool for improving information quality in the trade satelliteaccount

This paper focuses on the use of administrative data (in the specific case, fiscal data)for improving statistical information quality, mainly relevance and accuracy.To be precise: a) the use of fiscal data has demonstrated that it is possible to improvethe information on the structural characteristics of the internal trade sector, especiallyregarding the gain in more detailed information; b) the accuracy which may be obtainedby working on fiscal data is discussed.In this study information coming from two different types of taxes is compared. The firsttax is VAT (value added tax), which is applied in a standardized way at European level.The second tax is the Regional Tax on Production (in Italian IRAP), which is a tax appliedin Italy. Each source of data is constructed with reference to the motives for which thetax is applied, therefore each gives a partial description of internal trade. In order to usethe above-mentioned sources for economic analysis, statistical work is required.Firstly, this paper deals with the problem of transforming administrative data intostatistical economic information. With this aim, a conceptual framework which linksIRAP and VAT databases is proposed. The framework formalizes the logical linkbetween fiscal definitions and the definitions of the satellite account for trade (or moregenerally national accounting definitions). The conceptual framework proposed allowsanalyses on administrative data to be carried out which are similar to that usuallycarried out on macroeconomic aggregates.Secondly, the authors give a critical evaluation of administrative data quality anddiscuss how an appropriate application of fiscal data requires that the limitations thatthese intrinsically have be taken into consideration, i.e. mainly under-declaredrevenues or over-declared costs. Moreover, the quality of information is discussed,taking into account the fact that fiscal data is a powerful tool for statistical analysis.Given the censorial nature of the data used, structural analyses can be performedwhich are highly detailed both from the sectorial point of view as well as from theterritorial point of view.In conclusion, the authors, using the detailed information outlined above, apply dataanalysis techniques to VAT and IRAP information, aimed at identifying clusters ofenterprises which are not classified a priori. Clusters are based on the homogeneousstructural characteristics of the enterprises themselves. Special attention is paid to thelevel of efficiency in delivering a service as well as on the role of commerce in consumerprice formation. Relevance of the obtained information is underlined.