FAQs
The statistics record the level and daily evolution of sales (domestic and export) made by companies included in the Immediate Information Supply (SII) system. The daily sales series comes from the VAT management system based on the SII, implemented since July 2017 (RD 596/2016, of December 2). This system allows the exchange of tax information practically in real time between the Tax Agency and taxpayers obliged to the SII by sending the details of the billing records within a period of four days through the electronic headquarters of the Tax Agency.
The daily data in this publication can be considered a leading indicator of the sales published in the monthly report on Sales, Employment and Salaries of Large Companies and in the quarterly report on Sales, Employment and Salaries in Large Companies and SMEs. Both offer information from VAT declarations and withholdings for work income; The first includes exclusively taxpayers considered as Large Companies for tax purposes, while the second adds information on SMEs in the form of public limited companies and limited liability companies. In addition to complementing these two publications, the rapid availability and broad coverage of the information provide added value in the short-term forecasting and monitoring of both tax collection and macroeconomic variables.
Those obliged to comply with their tax obligations through the SII are Large Companies (those with a volume of operations in the previous year greater than 6 million euros), VAT groups and companies covered by the Monthly Refund Registry (REDEME). . Given the size and profile of these taxpayers, the daily sales available represent around 70% of the total domestic sales of all VAT taxpayers (the percentage is higher if the total declared volume of operations is considered), with a great diversity of coverage by activities (the SII companies are very representative of some sectors, while in others their number and weight are reduced, as is the case in part of the construction, in the hotel and catering industry or in some modalities Of transport).
The geographical scope is the so-called Common Tax Regime Territory; That is, companies that operate exclusively in the territories managed by the estates of the Basque Country and Navarra, and companies that do so in the territories that are outside the scope of application of VAT (Canary Islands, Ceuta and Melilla) are excluded.
Taxpayers are territorially assigned to the place where they have their tax domicile. The information on the tax domicile of the seller and buyer can be obtained from the SII system, but the place where the sales were made cannot be determined unequivocally.
Companies included in the Immediate Information Supply (SII) system are classified according to the activity declared by the companies themselves. Activities are classified according to the headings of the Economic Activities Tax (IAE). Its regulation is found in Royal Legislative Decree 1175/1990, which approves the rates and instructions of the Tax on Economic Activities, and its successive updates. For the purposes of publishing the report, companies are classified using four digits of the CNAE-2009 and are grouped accordingly.
The total sales variable presented in this report is obtained from the aggregation of two variables:
1.- Domestic sales: They are obtained from the aggregation of the non-exempt tax bases available in the register of issued invoices. This tax base includes both the part corresponding to the sale of goods and the provision of services and is similar to the concept of domestic sales (excluding exempt sales) available in the Sales, Employment and Salaries statistics in tax returns.
2.- Exports: They include both the sales of goods or services leaving the territory of the Peninsula and the Balearic Islands to third countries outside the EU, as well as the deliveries of goods or services produced to another Member State of the EU, obtained from the record book of invoices issued. .
Daily economic series pose a number of problems that are not observed to such an extent in lower frequency series (monthly or quarterly). These problems arise, above all, from the complex and unstable structure of the calendar (different lengths and compositions of months, mobile seasonal elements such as Easter, leap years and a mobile work calendar that also interacts with the weekly composition of the months) and from the existence of seasonal elements that overlap cycles of different frequencies.
Added to this is the intensity that its irregular component usually presents (smoothed when dealing with monthly data) and the impact of exogenous elements that distort the usual behavior of the systematic components of these series (in the case of the SII these elements can be, for example, different billing dates in different companies, which cause abnormally high values to appear that interact with other components of the series).
For all these reasons, the estimation of a robust economic signal is especially difficult and requires a treatment based on econometric models that represent the aforementioned phenomena in a joint and statistically satisfactory manner. To do this, a structural time series model is used that flexibly captures all of these elements and includes, in order to preliminarily correct part of these effects, a treatment through exogenous variables of a deterministic nature. These last variables are designed to control for the presence of anomalous observations and calendar-specific effects that, due to their aperiodic or moving periodicity nature, do not fit into the structural representation considered.
Estimating a robust economic signal in daily series is particularly difficult and an approximation based on structural econometric models of time series is used for this purpose. In this case, the TBATS modeling approach is applied to the corrected series of deterministic effects.1.2, which is based on the representation of unobserved components (trend, seasonality, irregularity) through explicit dynamic models. This approach is very flexible as it allows the simultaneous consideration of several seasonal components (weekly, monthly and annual) and, thanks to its trigonometric representation, allows the treatment of fractional periodicities (for example, those induced by leap years), offering a very compact representation of these components. From this model, it is possible to obtain the trend series and the series corrected for seasonal and calendar variations (CVEC), as well as the corresponding seasonal factors at their different frequencies (weekly, monthly and annual). The average of these factors is zero at each of these frequencies.
1 TBATS: Trigonometric seasonality, Box-Cox transformation, ARMA innovations, Trend and Seasonality (De Livera et al., 2011).
2 A concrete application of these series can be found in Cuevas, Ledo and Quilis, SERIEs, 2021, 10.1007/s13209-021-00251-7. https://link.springer.com/content/pdf/10.1007/s13209-021-00251-7.pdf