The Quarterly National Accounts of Spain: Main aggregates (QSNA) is a short-term shyntesis statistics whose main objective is to provide a coherent quantitative description of the behavior of the Spanish economy as a whole in the short term. It provides estimates of the main aggregates of the national economy: Gross Domestic Product (GDP) and its components, from the perspective of supply, demand and income, employment and national income. Such estimates are offered at current prices and in terms of volume (in the case of estimates of national income only at current prices), both in unadjusted terms and adjusted for seasonal and calendar effects. In addition, indicators of productivity and labor costs are added, derived from the aforementioned results.
The QSNA is developed within the framework of the national accounts system, being integrated, both methodologically and quantitatively, with the set of operations that make up the National Accounts of Spain:
- From a conceptual point of view, it adopts the methodology established in Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May concerning the European System of National and Regional Accounts of the European Union (ESA 2010). In this sense, the concepts, valuation principles and structures are the same as those used in the Annual National Accounts of Spain, with some peculiarities due to the period of time covered by the results.
- From the quantitative point of view, the aggregation of the quarterly estimates, for the quarters corresponding to any year, coincides with the estimate of the Annual National Accounts of Spain for such year. Likewise, the QSNA is fully consistent with the other operations of the system, such as the Quarterly Non-Financial Accounts of the Institutional Sectors and the General Government Statistics developed by the Audit Office, and consistent with the statistics of Balance of Payments, compiled by the Bank of Spain.
The branches of activity are grouped and codified in reference to the National Classification of Economic Activities of 2009 (CNAE-2009). Specifically, the breakdown of Gross Value Added, compensation of employees and their components and estimates of employment is offered with the following disaggregation by branch of activity (sections of the CNAE-2009 to which correspond in parentheses):
- Agriculture, livestock, forestry and fishing (A)
- Industry (B, C, D and E)
- Construction (F)
- Trade, transport and accomodation and restaurants (G, H and I).
- Information and communications (J).
- Financial and insurance activities (K).
- Real estate activities (L).
- Professional, scientific and technical activities and others (M and N).
- Public administration, education and health activities (O, P and Q).
- Arts, entertainment and other services (R and S).
The non-financial assets produced are grouped into:
- Material fixed assets:
Housing and other buildings and constructions.
Machinery, equipment goods and weapons systems.
Cultivated biological resources.
- Products of intellectual property.
National economy and branches of activity in which it is divided.
The units that are used are defined according to the type of economic analysis that is intended to be carried out. For the analysis of economic behavior, institutional units are used. An institutional unit is an economic entity characterised by decision-making autonomy in the exercise of its principal function. The institutional units that have a similar type of economic behavior are combined into groups called institutional sectors. To describe process of production and carry out the input-output analysis, the units used are the local kind-of-activity units (local KAU). The ESA groups the local kind-of-activity units by branch of activity. An activity is characterised by an inputs of products, a production process and an output of products. An institutional unit includes one or several local KAU; a local KAU belongs to a single institutional unit.
The population under study is the set of resident units in the national economy. An institutional unit is resident in a country when it has its centre of predominant economic interest in the economic territory of the country, irrespective of nationality, legal form or presence on the economic territory at the time they carry out a transaction . Having a centre of predominant economic interest indicates that a location exists within the economic territory of a country where a unit engages in economic activities and transactions on a significant scale, either indefinitely or over a finite but long period of time (a year or more). The ownership of land and buildings within the economic territory is deemed to be sufficient for the owner to have a centre of predominant economic interest there. By national economic territory it is understood: a. The area (geographic territory) under the effective administration and economic control of a single government. b. Any free zones, including bonded warehouses and factories under customs control. c. The national air-space, the territorial waters and the continental shelf lying in international waters over which the country enjoys exclusive rights. d. Territorial enclaves, which are geographic territories situated in the rest of the world and used, under international treaties or agreements between states, by the general government agencies of the country (such as embassies, consulates, military bases, etc.) e. Deposits (oil, gas, etc.) in international waters outside the continental shelf of the country, worked by units resident in the territory according to the previous points.
It is constituted by the national economic territory:
a. The area (geographic territory) under the effective administration and economic control of a single government. b. Any free zones, including bonded warehouses and factories under customs control. c. The national air-space, the territorial waters and the continental shelf lying in international waters over which the country enjoys exclusive rights. d. Territorial enclaves, which are geographic territories situated in the rest of the world and used, under international treaties or agreements between states, by the general government agencies of the country (such as embassies, consulates, military bases, etc.) e. Deposits (oil, gas, etc.) in international waters outside the continental shelf of the country, worked by units resident in the territory according to the previous points.
In the current accounting series (Benchmarck Revision 2019) there is information available since the first quarter of 1995 (since 1999 in the case of national income aggregates). However, there are results available since the first quarter of 1970 in previous accounting series:
• Base 2010, there is information available from the first quarter of the year 1995 to the second quarter of 2019. • Base 2008, there is information available from the first quarter of the year 1995 to the second quarter of 2014. • Base 2000, there is information available from the first quarter of 1995 to the second quarter of 2011. • Base 1995, there is information from the first quarter of 1980 to the fourth quarter of 2004, except for the series of the quarterly non-financial accounts of the total economy and the rest of the world beginning in the first quarter of 1995. • Base 1986, there is information from the first quarter of 1970 to the fourth quarter of 1998.
The evolution of the quarterly aggregates measured at current prices can be separated into two components, one that reflects the evolution of prices and the other the movements in volume. The main purpose of the volume estimates is to offer measures of economic activity in which the effect of the variation in prices is eliminated. When making estimates in volume, the main choice is the base year in which these estimates are going to be expressed: fixed base or mobile base. Until the base change that gave rise to base 2000 in May 2005, the National Accounts have used a fixed base year for calculating their estimates in volume. This base year was updated every so often, and all available time series must be expressed at current prices and prices of the new base year. However, changes in the structure of base year exchanges that occur over time as a result of changes in relative prices, technology, products exchanged, preferences, etc., imply the loss of significance and statistical relevance of the valuations on a fixed basis. A solution to the problem of loss of relevance is to review the basis with the same frequency with which the estimate is made. In this way, speaking in annual terms, estimates are obtained at prices of the previous year. These estimates constitute the so-called links. In this way, there would not be a single base year but it would change as the estimates progress over time. This way of acting provides relevant estimates at constant prices, however, the direct comparison can only be made between two consecutive years. The formation of a homogeneous series that represents the complete sequence of years requires the chaining of all the links (which are elaborated using the Laspeyres formula in the case of volume variations). The reference year (2015, in the current series) is the one that defines the scale of the linked index (becoming 100), while the temporary base is mobile, with as many bases as pairs of consecutive years, so the linked valuation lacks of fixed base (mobile base).
Million euros for aggregates valued at current prices and number (in thousands) for employment variables, such as number of full-time equivalent jobs, number of hours worked, number of employees, etc.
The natural or calendar quarter.
Data referred to the period: Trimestral A: 2019 TRI: II
The compilation and dissemination of the data are governed by the Statistical Law No. 12/1989 "Public Statistical Function" of May 9, 1989, and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2017-2020, approved by Royal Decree 410/2016, of 31 October, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2017-2020. (Statistics of the State Administration).
The Regulation (EU) no. nº 549/2013 of the Council, 21 May 2013, regarding the European System of National and Regional Accounts, contains the reference framework of common accounting concepts, definitions, classifications and norms intended for the development of national accounts in the EU.
Besides, QSNA is a statistical action included in the National Statistical Plan, which is therefore subject to the Law on the Public Statistical Function, 9 May 1989. As a result, its data is protected by Statistical Secrecy in all the stages of its development.
An advance of results is disseminated around 30 days after the end of the reference quarter (t + 30), with the information available up to that moment. This advance is updated around t + 90 days, also incorporating the results on national income for the quarter.
INEbase is the system the INE uses to store statistical information on the Internet. It contains all the information the INE produces in electronic formats. The primary organisation of the information follows the theme-based classification of the Inventory of Statistical Operations of the State General Administration . The basic unit of INEbase is the statistical operation, defined as the set of activities that lead to obtaining statistical results on a determined sector or subject based on the individually collected data. Also included in the scope of this definition are synthesis preparation.
Information about QSNA base 2010 can be obtained in the following link.
Because of the nature of the national, no microdata is available.
This action is carried out in accordance with the accounting principles established in ESA-2010. A detailed methodology of the QNA can be found at: https://www.ine.es/daco/daco43/metodologia_cntr.pdf In addition, you can also consult the Handbook on quarterly national accounts (2013 edition):
Technical project of Benchmarck Revision 2019 of the Spanish National Accounts::
The quality criteria that must be applied to the data of the QSNA are those established in Article 12, paragraph 1, of Regulation (EC) No 223/2009 of the European Parliament and of the Council of March 11, 2009 relative to European statistics. In the methodological manual of the QSNA published in the following link:
A chapter dedicated to the analysis of revisions is included.
This methodological report also contains, in fields 10.6 to 17, the elements that are considered the "User-oriented quality report" for this operation.
Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 16 principles, gathered in three areas: Institutional Environment, Processes and Products. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, Self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation.
The main objective of the QSNA is to offer a comprehensive and complete description of the behavior of a short-term economy. In this sense, there are numerous macroeconomic relations among all the aggregates that make up the QSNA, which are studied and contrasted each quarter by means of analysis and numerous controls. On the other hand, as part of the system of national accounts of Spain, the QSNA complies with the principles of coherence and consistency with the other parts of the same, which gives it an additional level of solidity. This consistency is reached in a double sense: methodological and numerical: - Methodological coherence: the principles, definitions, classifications and structure of the quarterly accounts must be the same as those adopted by the rest of the system, in particular by the annual and regional accounts. - Numerical coherence with aggregates, both quarterly and annual from other parts of the system. In the last phase of development of the QSNA, a global assessment of all the information is carried out, carrying out numerous coherence and feasibility checks, among which the following stand out: - Consistency between raw data and adjusted seasonal and calendar effects. - Comparison of the resulting quarterly aggregates with the current base information available. - Study of deflators and seasonal factors. - Analysis of the coherence and interpretation of certain ratios (productivities, average remunerations, unit labor costs (ULC), etc.) - Study of the revisions. - Etc. Finally, Eurostat has a complete validation system for all the data that are sent quarterly with regulatory character.
Eurostat submits to exhaustive analysis of the quality of the data transmitted by Spain on its national accounts within the framework of the provisions of the National Accounts Data Transmission Program to Eurostat set by Regulation (EU) 549/2013 on the European System of National and Regional Accounts.
Some of the important points of this statistic are:
Firstly, the dissemination of an advance estimate of quarterly GDP (Gross Domestic Product) with great immediacy (around 30 days later) since the fourth quarter of 2011. In addition, as from the publication of July of 2018, this advance estimate offers not only an advance estimate of the growth of GDP generated in the economy during the reference quarter in terms of volume and adjusted for seasonality and calendar effects, also an estimation of that aggregate at current prices and in terms of volume, and in adjusted and unadjusted terms of seasonality and calendar effets, and of each of its components. These results are offered from its three approaches: supply, demand and income (only at current prices in the case of the income approach), as well as a measure of the evolution of employment in the economy in terms of employed persons, jobs, equivalent full-time jobs and hours worked.
Secondly, the update of this advance estimate is carried out, since the second quarter of 2018, around 90 days after the end of the reference quarter, with all the information available of the reference quarter, particularly considering quarterly results of the Balance of Payments, published by the Bank of Spain days before, and integrating the results of Quarterly Non-Financial Accounts of Public Administrations, disseminated around the same date by Audit Office. This guarantees the consistency of the set of macroeconomic statistics in the measurement of the short term situation of national economy at each moment of time.
The QSNA can be used to analyze and evaluate the recent evolution of the Spanish economy as a whole and of each activity sector, comparable to other economies. The results of the same have a fundamental importance for the Government of Spain and for the EU and its Member States when formulating and supervising its economic and social policy. With this, among the main users of the results of this operation we can highlight the Government of Spain, the European Commission, the European Central Bank, OECD, the IMF and all types of economic studies and analysts services.
The INE has carried out general user satisfaction surveys in 2007, 2010, 2013 and 2016 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...
On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date.(Click next link)
100% of the information required by Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European System of National and Regional Accounts of the EU to the Member States is provided.
R1= 100%, R1 is the rate of completeness of the data
The QSNA is a shyntesis statistics, so its acuracy depends, to a large extent, on the sources of information used in its preparation. Nonetheless, the identities established by the system and the general equilibrium process of the national accounts make it possible to verify and improve the coherence and completeness of the estimates, avoiding possible gaps and inconsistencies in the basic data sources.
The QSNA is a shyntesis statistics, so the concept of sampling errors is not applicable. However, it is affected indirectly by such errors, due to the fact that surveys are among its sources of information. However, the identities established by the system allow the consistency and completeness of the estimates to be checked and improved.
The QSNA is a synthetic statistics, so it is affected indirectly by all the errors that exist in its information sources. However, the identities established by the national accounts system allow to verify and improve the coherence and completeness of the estimates, reducing the impact of this type of errors.
The advance of QSNA results is published around 30 days after the end of the reference quarter t (t + 30 days), with the information available up to that moment. These results are updated in t + 90 days, once all the information available for the quarter has been incorporated, especially the quarterly results of the Balance of Payments, disseminated by the Bank of Spain.
The results of the QSNA are published on time, in agreement with the the INE short-term statistical publication calendar.
One of the objectives of the ESA 2010 is the harmonization of the methodology and the precision and rigor of the concepts, the definitions, the classifications and the accounting rules that must be applied in order to obtain a comparable description of the economies of the countries of the European Union. Therefore, the results of the CNTR are comparable with those of the Member States of the EU. They are also compatible on an international scale since the concepts of the ESA are fully coherent with those contained in the existing global guidelines on national accounting, which are included in the System of National Accounts (drawn up under the joint responsibility of the United Nations, the International Monetary Fund, Eurostat, the OECD and the World Bank).
In the current accounting series, homogeneous series are available from the first quarter of the year 1995 (of 1999, in the case of the results related to national income). Thus, for example, until the fourth quarter of 2018 the length of comparable time series is 98 quarters.
The QSNA integrates the results of the quarterly results of the Goverment Finance Statistics, prepared by the Audit Office, being, therefore, fully consistent with them. In addition, the ESA 2010 is broadly consistent with the principles established in the Balance of Payments and International Investment Position Manual (6th edition), so that the results of the QSNA are consistent with that of the Balance of Payments, which disseminates the Bank of Spain. In addition, because it is a synthetic statistic, the results of this operation are generally consistent with those of the statistical and administrative sources used in its preparation.
The accounting methodology established in the ESA 2010 guarantees the compliance in the National Accounts of Spain of all the identities that are established there in, this is the coherence of all the measures established to describe the different parts of the economic process. This allows the joint and consistent analysis of the different aspects and phases of the same and the behavior of the different economic agents, including their relations with the rest of the world. On the other hand, at a quantitative level, the quarterly estimates of all the aggregates are temporarily consistent with the annual figures.
In the 2019 Annual Program, the estimate of the necessary budget credit to finance this statistical operation is 288.02 thousand euros.
The workload for informants is non-existent since QSNA is compiled using the information provided by other statistics.
The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (link).
This general policy sets the criteria that the different type of revisions should follow: routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.
The advance of QSNA results for quarter t is published around t + 30 days. These results are updated around t + 90 days. At the same time, updated results are disseminated from the previous quarters of the current year. In addition, in the case of the second quarter of each year, revised results are disseminated from the first quarter of year T-3, consistent with the policy of review of results of the Annual National Accounts of Spain.
The advance of QSNA results for quarter t is published around t + 30 days. These results are updated around t + 90 days. At the same time, updated results are disseminated from the previous quarters of the current year. In addition, in the case of the second quarter of each year, revised results are disseminated from the first quarter of year T-3, consistent with the policy of review of results of the Annual National Accounts of Spain. The values of the indicators MAR and RMAR for the annual quarterly GDP rate in terms of volume (corrected for seasonal and calendar effects) for the period between the first quarter of 2015 and the fourth quarter of 2018 are:
MAR is the absolute average size of revisions, where the revision is defined as the difference between the two estimates and the average extends to a number of revisions of the same data.
RMAR is the percentage of the average size of the revisions relative to the values of the revised estimates.
The QSNA integrate and combines a great number of short-term economic information sources. There are two types of quantitative short-term statistical information:
Among the indirect indicators used, the following shall be pointed out:
Monthly or quarterly.
The data used are statistics prepared by the INE or other organizations. The collection of data varies according to the type of source and the way of disseminating the information (database, electronic publication, etc.). In general, the necessary information is published on the web pages, directly accessing the publication or the corresponding database. Regarding unpublished information, it is sent directly to the Department of National Accounts from the responsible agencies.
Once the base indicators are selected, they are subjected to a series of treatments: identification of outliers, error filtering, prediction of missing data, adjustment to National Accounts terms...
The compilation process of QSNA may be structured in different stages:
1. Updating of indicators
The quality of the quarterly estimates obtained by indirect method depends greatly on the indicators. When selecting the basic indicators, the main criteria taken into account is: conceptual coherence with the annual aggregate to be indicated, correlation with that aggregate, quarterly frequency or higher, minimum time-lag, enough length, future availability, minimum prediction and statistical quality errors.
2. Univariate treatment of basic series
Once base indicators are updated, they are subjected to a series of treatments. The main treatments consist in: identification of outliers, error filtering, prediction of missing data and adjustment to National Accounts terms.
3. Building synthetic indicators
Based on the series of basic indicators, the information is synthesized, this way obtaining a synthetic indicator (of value or volume and prices) for each aggregate and at the necessary breakdown level. The objective is to obtain more unhurried models in terms of parameter estimate. In order to design synthetic indicators, different techniques are used such as Factorial Analysis, Weighted Average, Main Components or Canonical Correlation.
4. Application of temporary breakdown procedures
Once there is a synthetic indicator for each aggregate(for variation in current terms and for volume evolution) temporary breakdown procedures are applied to the series of annual aggregates (mainly the general Chow and Lin method, 1971) so as to obtain the series of quarterly aggregates. This way, a first version is obtained of the quarterly estimates in current terms, at average prices of the previous year and chained-linked volume indices that are temporarily consistent with the annual estimates.
5. Balance and conciliation process of gross estimates
In order to solve supply-demand inconsistency problems and keep the temporary consistency and therefore obtain the almost-definite gross quarterly aggregates, the balance and conciliation process shall be carried out. This process has two stages:
The series of quarterly aggregates in gross terms of supply, demand, income and employment, that are obtained at the end of this stage will be definitive after the final viability study. This study also includes the adjusted seasonal and calendar quarterly series.
6. Application of signal extraction procedures
Each aggregate series obtained in the previous section is applied signal extraction procedures in order to obtain the series of adjusted seasonal and calendar quarterly aggregates.
The procedure of seasonal adjustment applied in QSNA, uses the signal extraction methodology based on ARIMA models (MBSE) implemented in programs TRAMO and SEATS (Gomez and Maravall, 1997) which is one of the procedures recommended by Eurostat. The applied procedures follow the recommendations included in the standard of seasonal adjustment of INE, in the Handbook on Quarterly National Accounts (Eurostat, 2013) and in the final report of the work group about seasonal adjustment in Quarterly National Accounts (Eurostat and European Central Bank, 2008).
Adjustment is carried out on quarterly series in gross terms and not on the indicators. The model is chosen once a year.
7. Balance and conciliation process of adjusted data.
The objective of this stage is to obtain temporary consistency and accounting balance of the adjusted quarterly series. To do so, proceed similarly to section 5. Once quantitative and transverse coherence of the adjusted data is obtained, it is subjected to a process of residual seasonal control.
8. Overall valuation of gross/adjusted data.
Finally there is an overall valuation of all the information (adjusted and non-adjusted quarterly aggregate series of supply, demand, income and employment in current and volume terms), and numerous coherence and viability controls are carried out.
The elaboration of adjusted seasonality and calendar results covers both the signal extraction process, which includes the treatment of seasonal adjustment and calendar effects, as well as the procedures that guarantee the necessary annual consistency between the gross data and the seasonally adjusted data and among the aggregates of the account system. The procedures applied are in accordance with the recommendations published in the quarterly accounts manuals (Eurostat, 1999/2013 and International Monetary Fund 2001/2016) and seasonal adjustment (ESS guidelines on seasonal adjustment, 2015 and with the INE Standard for the correction of seasonal effects and calendar effects in the short term series, 2013). In this way, the seasonal adjustment procedures are developed according to a parametric approach, based on regression models with ARIMA errors, identifying and estimating a priori a model that adequately fits the observed series and deriving appropriate models from it for each of the components of the series (cycle-trend, seasonal and irregular). The latest version of the TRAMO-SEATS software is used (Gómez and Maravall, 1994). It must be borne in mind that the choice of the ARIMA model is made once a year at the time when the annual series are also reviewed. Such models remain fixed for the remaining quarters of the year. However, these are monitored in all quarters. In addition, the parameters of the ARIMA model are re-estimated each time a new observation is available. The annual consistency between the gross data and the seasonally adjusted data is also maintained, that is, the annual total of the seasonally adjusted series coincides with the annual total of the original series. This preference for consistency over optimality in the sense of seasonal adjustment must be understood in the context of the coherence that must exist in any system of national accounts, essential for the analysis of the evolution of the economy in both the short and the long term. To do this, we use model-based methods for the disaggregation of time series and adjustment of the quarterly data set to the annual data.
The method for obtaining an adjusted series of GDP in terms of volume is direct, that is, the aggregate signal is not obtained as a sum of the corresponding signals of its components, but the signal extraction procedures are applied directly to the aggregate in gross terms. Afterwards, and once each of the components has been adjusted to the seasonally adjusted calendar effects, balance and conciliation procedures are applied in order to obtain consistent adjusted series that are transversal and temporal. Finally, an exhaustive control is carried out to verify that there is no residual seasonality in the seasonally adjusted series, a control that is especially important for the balance and conciliation procedures applied to the seasonally adjusted series discussed. In addition, following the recommendations of Eurostat, no adjustment is made to the lack of additivity caused by the adoption of the chained-linked index methodology for the measurement of volume variations in supply and demand aggregates.Metadata for the seasonal adjustment in QSNA.xlsx
For further information see the "Handbook on quarterly national accounts- 2013 edition", in the link: