National accounts, non-financial sector accounts

Name: National accounts, non-financial sector accounts
Topic: National accounts and business cycles

Division for National Accounts.

National level.

Quarterly statistics. The first version for quarter k t is published after k+60 days, followed by revisions in the following quarterly publications. The final version is published together with the final annual accounts in August/September year t+2.

Eurostat (from 2006).

Not relevant.

The national accounts statistics are designed to provide a consistent and comprehensive survey of the national economy. The national accounts contain national aggregates and give detailed descriptions of transactions between different sectors of the domestic economy and between Norway and the rest of the world. The national accounts also provide information on different types of capital stock.

The first Norwegian national accounts based on modern principles were published by Statistics Norway in 1952. In the beginning only the parts of the national accounts, referred to as the real accounts (see section Production) were published. The non-financial sector accounts were published from 1978.

The annual final non-financial sector accounts data are based on all available economic statistics, and take some time to produce. The purpose of the quarterly sector accounts is to give timely updated information about the economic development.

The quarterly non-financial sector accounts were first published in June 2005, with time series from 2002 onwards. The accounts cover all sectors from publishing of figures for the 3rd quarter 2015, namely, the non-financial and financial corporation sectors, general government, households, non- profit institutions serving households (NPISHs) and the rest of the world. Before this the published accounts covered only the sectors households and NPISHs. Consistent time series for all sectors are available from the 1st quarter 2002 onwards.

National accounts are used as a tool to compare the economic situation in different countries, and therefore it is important that the national accounts in various countries are based on a common template. Staff involved in elaborating national accounts in Statistics Norway participated actively in developing international recommendations and concepts regarding national accounts. The first international standard for national accounts, 1953 System of National Accounts (1953 SNA), was published by UN in 1953. In the 1970s the Norwegian national accounts were considerably expanded and adapted to the most recent standard 1968 SNA at that time.

From time to time adaptations or changes are made to the common international recommendations for national accounts. This requires corresponding changes in the construction of the Norwegian national accounts. At different time intervals, new source statistics are produced and indicate that parts of the national accounts figures need to be revised. Since one objective of the national accounts is to provide a picture of the development over time as correctly as possible, it is not possible to introduce such changes from one year to another. With different time intervals, it will therefore be necessary to carry out major revisions of the national accounts figures, so-called main revisions, in order to introduce adaptations due to new international recommendations or to introduce new levels based on new statistical sources. As part of these main revisions the time series are also revised so that the revised national accounts can give a consistent picture of the economic development over time.

In recent decades, Statistics Norway has carried out main revisions published in 1995, 2002, 2006, 2011 and 2014. The main purpose of the main revisions published in November 2014 was to incorporate updated international recommendations in 2008 SNA and the European standard ESA 2010.

Changes due to this main revision are described, among others, in the article Main revision 2014. Planned changes in the national accounts statistics.

The publication History of national accounts in Norway. From free research to statistics regulated by law provides more information about the history of national accounts in Norway, including main revisions.

Since the quarterly figures are completely harmonised with the annual national accounts, it is also necessary to revise the quarterly figures once the annual national accounts figures have been revised.

The national accounts are an important tool for macroeconomic analysis, and Statistics Norway's macroeconomic models are based on the national accounts.

Major users of the national accounts are the Ministry of Finance and other ministries, Norges Bank (the Norwegian central bank), research institutes, financial sector analysts, international organisations, the media etc.

No external users have access to the statistics and analyses before they are published and accessible simultaneously for all users on ssb.no at 08.00 am. Prior to this, a minimum of three months' advance notice is given in the Statistics Release Calendar. This is one of Statistics Norway’s key principles for ensuring that all users are treated equally.

The annual and quarterly non-financial sector accounts are fully consistent with other parts of the national accounts statistics, including the annual and quarterly national accounts (the real accounts), and the annual financial sector accounts. The Norwegian Balance of Payments (BoP) is an integrated system in the Norwegian system of national accounts, and the BoP figures are fully consistent with other NA figures, including the annual and quarterly non-financial sector accounts. The regional accounts by county, as well as various satellite accounts (environment, tourism, health, non-profit institutions) are all based on the annual NA, so these accounts are therefore also consistent and compatible with the annual and quarterly non-financial sector accounts. Previous published figures from the regional accounts and various satellite accounts are, however, not revised as a part of main revision of the national accounts, so figures for previous years may not necessarily be compatible with updated national accounts time series.

As mentioned in the chapter "Production: Data sources and sampling", the national accounts are based on various statistical sources. The source statistics may not use the same definitions or groupings as the national accounts. As a result, figures in the source statistics may be adapted or corrected before use in the national accounts. Published figures in the source statistics of certain industries may therefore not correspond to published figures in the national accounts.

Not relevant.

Regulation (EU) No 549/2013 (ESA 2010). The European Parliament and of the council of 21 May 2013 on the European system of national and regional accounts in the European Union (text with EEA relevance).

The scope of the national accounts is defined in international guidelines in the 2008 System of National Accounts (2008 SNA), published by the UN, OECD, IMF, World Bank and the European Commission, and The European System of National and Regional Accounts 2010 (ESA 2010).

The total national economy, and the distinction between the national economy and foreign ones, is defined in terms of resident units. A unit is defined as a resident unit of the country when it has a centre of economic interest in the economic territory of the country - i.e. when it is involved in economic activities on this territory for an extended period of time (one year or more).

The national accounts contain two fundamental types of information: flows and stocks. Flows refer to actions and effects of events that take place within a given period of time, for example the output of an industry in one year. Stocks refer to positions at a certain point of time, for example the value of capital stock or the number of employed persons.

Institutional units are economic entities that are capable of owning goods and assets, of incurring liabilities and of engaging in economic activities and transactions with other units in their own right. An institutional unit contains one or more local kind-of-activity units (local KAUs).

The national accounts consist of two main sets of tables; supply and use tables (SUT), also described as the real accounts, and the institutional sector accounts. The two sets of accounts are based on two different statistical units: The real accounts are based on local kind-of-activity units (KAUs), while the institutional sector accounts are based on institutional units.

Institutional units are economic entities that are capable of owning goods and assets, of incurring liabilities and of engaging in economic activities and transactions with other units in their own right. Institutional units are capable of providing a full set of accounts. An institutional unit contains one or more local kind-of-activity units (local KAUs).

The local KAUs are classified by type of activity. An activity is characterised by input of products, a production process and output of products. All local KAUs engaged in the same or similar kind-of-activity constitute an industry.

In the institutional sector accounts, the institutional units are grouped in institutional sectors on the basis of their principal economic functions, behavior and objectives; see Section Definition, Classification. The institutional sector accounts consist of the non-financial sector accounts and the financial sector accounts. The non-financial sector accounts describe all economic transactions in the various sectors. The accounts also provide information on the stocks of financial and non-financial capital. The financial accounts provide a survey of institutional sectors assets, liabilities and financial transactions. The financial accounts also provide information on asset relationships between different sectors of the domestic economy and between Norway and the rest of the world.

The non-financial sector accounts are consistent with the real accounts. This description of the national accounts covers the annual and quarterly non-financial sector accounts.

The non-financial sector accounts are based on many different statistical sources, mainly statistics from other Divisions in Statistics Norway. Se more information in the section Collection of data, editing and estimations.

The national accounts are based on various statistical sources collected by other divisions in Statistics Norway. The source statistics may not use the same definitions or groupings as the national accounts. As a result, figures in the source statistics may be adapted or corrected before use in the national accounts. Published figures in the source statistics of certain sectors and variables may therefore not correspond to published figures in the national accounts.

Since the non-financial sector accounts are based on, and reconciliated with, figures from the annual and quarterly supply and use tables (the real accounts) all statistical sources used in the real accounts are used indirectly also in the non-financial sector accounts, including figures from the Balance of Payments statistics and the labour accounts.

The statistics general government revenue and expenditures, accounting statistics for financial and to non-financial enterprises, tax statistics, income and deduction statistics and balance of payments statistics are also used directly in the calculations.

Annual process

Figures from the annual national accounts, the Balance of Payments statistics, the labour accounts and the most important source statistics are transferred electronically to the calculation system for the non-financial sector accounts.

The sector accounts are first compiled separately for each sector of the economy. As a first process figures for each institutional sector is calculated, based on independent estimate for various transactions.

The process to establish figures for the household sector deviate from the process to establish figures for other institutional sectors, since there is no direct reporting of most household figures from the households to Statistics Norway. Instead information from other sectors about transactions with the household sector are combined with external sources. like assessment data. Independent estimates for household consumption expenditures, as well as estimates for gross fixed capital formations and export and import are also carried out.

The final step of the compilation process of the sector accounts consists of balancing across sectors and against the real accounts. The transactions are put together in a system where all incomes and expenditures are reconciliated by using supplementing information as well as assumptions about the quality of the various sources. Usually estimates based on statistical sources for the general government, the financial corporations and the sector rest of the world are rarely adjusted. Therefore many corrections will in general be on the non-financial corporation sector.

Figure 1 illustrates the calculation system for the annual non-financial sector accounts.

Figure 1. Calculation system of the annual non-financial sector accounts

Quarterly process

The calculation system for preliminary annual figures is basically the same as for final annual figures. The main difference is that the available data sources for preliminary figures may be more incomplete and uncertain. Preliminary figures for non-financial enterprises are, for example, based on information for other sectors and additional external sources.

Preliminary figures are revised until final annual national accounts figures are available.

Households and Non-Profit Institutions Serving Households (NPISHs)

Quarterly figures for households and NPISHs are to some extent based on information for other sectors (cross-sector information). For example figures for financial incomes and expenditures are based on information for the financial corporation sector. Quarterly figures for revenue and expenditures in the general government are used to calculate social benefits and other transfers from the general government to the household sector and NPISHs, as well as current transfers from the household sector and the NPISHs to the general government. Figures for output, consumption expenditures and gross fixed capital formation, are collected from the supply and use tables in the quarterly national accounts (qna). Other sources are also used.

Financial Corporations

Most financial corporations are obliged to report quarterly figures to Statistics Norway, the Central Bank and the Financial Supervisory Authority of Norway. The reports give detailed accounts information for banks and insurance companies that are used to calculate figures for the sector financial corporations.

Non-Financial Corporations

As for the household sector, there exists no single data source that covers quarterly information for the sector non-financial corporations specifically. Figures for production income, as well as consumption expenditures and gross fixed capital formation, are collected from the supply and use tables in the quarterly national accounts (qna). Figures for financial incomes and expenditures are based on information for the financial corporation sector and the rest-of-the-world (cross-sector information). To some extent the figures are also influenced by balancing the transfers of incomes and expenditures between all sectors.

General government

Quarterly figures for revenue and expenditures in the central government and in the local general government are used as data source to calculate figures for the general government in the quarterly sector accounts (qnri), as well as in the quarterly national accounts supply and use tables (qna). For common variables (output, intermediate consumption and gross fixed capital formation), the same computed figures are used in qnri and qna. The data sources also give financial information that are used in the qnri.

The Rest-of-the-World

Figures for the sector the rest-of-the-world are transferred from the quarterly Balance of Payments (BoP).

After establishing independent accounts of the different sectors based on data sources as described, the production process takes a step further by balancing the transfers of incomes and expenditures between all sectors.

After establishing independent accounts of the different sectors based on data sources as described, the production process takes a step further by balancing the transfers of incomes and expenditures between all sectors. The balancing of figures across sectors is mainly based on assumptions of the quality of the various source statistics.

More about methods and sources for calculation of the households net lending

Net lending in the household sector is net acquisition of financial requirements and liabilities in a period. In principle there are three ways to provide figures for net lending in the household sector:

One may observe directly all financial transactions the households’. In practice this may be an impossible task.

As one alternative net lending may be calculated indirectly as a balance in a macro economic statistical system, either by:

a. calculating all incomes and subtract all expenditures in the period (inclusive consumption expenditures and gross fixed capital formation), or

b. to calculate the difference between the households stock of financial capital by the beginning and end of the period, and in addition correct for price differences and other changes in the stock values not due to purchase and sale of the objects.

To calculate the non financial sector accoutns we use the first method. However, the financial sector accounts also publish figures net lending in the household sector, but these figures are calculated by using the last mentioned methods. In theory, these two methods should lead to the same figure. In practice, this demands that all the data used are consistent, correct, and in line with the national accounts principles and definitions.

As mentioned above, the calculations of figures for the households sector is based on various sources. Besides the households’ consumer surveys, the data are not calculated directly from the households. The Norwegian Registry of Securities gives valuable information about transactions in certifications, bonds, shares and primary capital certificates. However it is not possible to control or revise overall account figures for single units within the household sector, so we have to construct a consistent picture on a macro level.

The quarterly national accounts figures may be influenced by different weather conditions, holidays, etc. The effects of conditions that are repeated at the same time every year are referred to as seasonal effects, while effects that are directly connected to changes in the calendar from one year to another are referred to as calendar effects. The increase in household consumption of goods in December is an example of a seasonal effect, while the number of working days in each quarter is a calendar effect. Incidental happenings such as a strike or a production stoppage may also affect the figures. The seasonal adjustment program is supposed to recognise and adjust the figures to seasonal effects and calendar effects, but not incidental effects. In cases where Statistics Norway has information on strikes or other incidental happenings that are assumed to have effect on the figures, these incidents are mentioned when the figures are published.

See About seasonal adjustment for more information about methods and routines used to calculate seasonal adjusted figures.

§ 2-6 of the Statistics Act states that data under no circumstances shall be published in such a way that they may be traced back to the supplier.

§2-4 of the Statistics Act contains provisions regarding professional secrecy for the staff as well as other provisions regarding confidentiality and integrity.

Consistent time series are available from 1. Quarter 1999 onwards.

The system of national accounts is compiled using several different statistical sources. The statistical sources consist of collected data from firms and enterprises, households or different types of registers. The uncertainty in the national accounts figures is therefore related to the uncertainty in source data and the compilation methods. Uncertainty connected to the different statistical sources is usually described as part of the documentation of sources. Several of the statistical sources used in the compilation of the national accounts remain preliminary for longer periods, as they require extensive analysis and numerous revisions before the final figures are known. The preliminary national accounts figures are therefore more uncertain than the final figures.

Since the system of national accounts is an integrated system containing many routines for balancing and consistency checks of data, one could assume that the national accounts help reduce some of the uncertainty in the source data. On the other hand, the national accounts require compilation of figures in areas where source statistics are very limited or even lacking. In these cases figures are often compiled using a residual method. The uncertainty can be substantial in these areas.

The International Monetary Fund (IMF) completed an evaluation of central parts of Norwegian macroeconomic statistics in autumn 2002, including the Norwegian national accounts. In the report IMF (2003), the Norwegian macroeconomic statistics, including the national accounts, got positive reviews: "In summary, Norway's macroeconomic statistics are of generally high quality." About the national accounts, the IMF also expressed that: "The source data for both the annual and the quarterly national accounts are generally sound and timely, and sufficiently portray reality."

The EU Commission and Eurostat have effected quality evaluations (revisions) of the national accounts in all EEA countries, up to the calculations of the value of GNI. The conclusions have been that the Norwegian national accounts are of a high quality.

Preliminary quarterly and annual figures are revised until final annual figures are published (in August/September year t+2). See Administrative information, Frequency and timeliness.

In addition, periodical main revisions give revised series of figures. See Background and purpose.

What is seasonal adjustment?

Monthly and quarterly time series are often characterised by considerable seasonal variations that might complicate their inter-period comparability. Such time series are therefore subjected to a process of seasonal adjustment in order to remove the effects of these seasonal fluctuations. Once data have been adjusted for seasonal effects by X-13-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.

For more information on seasonal adjustment: http://www.ssb.no/english/metadata/methods/seasonal_adjustment.html

Why do we seasonally adjust QSA ?

The quarterly institutional sector accounts (QSA) consist of a set of incomes and expenditures from which the items net savings and net lending/net borrowing are derived.

The balancing items, savings and net lending/net borrowing are shown in the accounts for incomes and expenditures for one sector. The saving ratio (the ratio between saving and disposable income) indicates how the sector has been financed. If savings are denoted by a negative sign, it means that a sector has used more resources than it had and had to finance its expenses through borrowing.

Some of the most relevant series in the QSAs show clear evidence of seasonality, for example gross value added and for total consumption. Most of the other series show seasonality in quite different ways. It seems to be that series for income and expenditure do not have identical seasonality.

Therefore, in order to evaluate the current saving rate in an appropriate way, the seasonality must be removed from its components. Series for the QSAs are now extensive enough to identify their seasonality.

Series are long enough to run X-12-ARIMA but remain quite short and therefore some problems of instability can arise. For different reasons as mentioned above, some of the aggregate series show non-identical seasonal patterns before and after 2006.

Seasonally adjusted series

All series included in the QSA have been seasonally adjusted. The indirect approach has been used for the main aggregates. This means that consistency is maintained for aggregation and definitions in the released tables for the seasonally-adjusted figures. We get better results for the main components when adjusting in this way (indirectly) in place to adjust directly. To arrive to such conclusion we use the results as well as other analysis using figures and output from X-12-ARIMA..
It seems to be that the indirect adjustment of the main components leads to more stable series (lower irregular components) and therefore less revisions in the future. This is particularly relevant for the saving ratio and net lending/borrowing.
The main elements for the seasonal adjustment of the QSA’s serer are given by:
• We use X12-ARIMA without stipulate that annual figures for unadjusted and seasonally adjusted are identical.

• We are using X-12_ARIMA for adjust each individual time series.. Seasonally adjusted aggregates emerge as a result by aggregating the seasonally adjusted components.

• The series that do not have season (there are many in QSA) are not adjusted. Mao: adjusted and unadjusted are identical
• In a few cases, we use trend in place for seasonally adjusted in order to avoid negative numbers.

• Some series are not long enough but they clearly shows seasonal pattern. In that case series are extrapolated to estimate seasonal factors
• Series corresponding with QNA was adjusted by identical factors than the QNA

• Only the last three years are reviewed when figures for new quarter are included.

Relationship and consistency demands careful checking via established graphs when new figures for seasonal adjustment are treated.

The following table shows the method used to adjust the individual time series:

Description of the table: J: Direct seasonal adjustment, A: Additive adjustment due to negative values, N: No clear seasonal pattern, M: Manual adjustment due to short time series, S: Sum of components, T: Using trend series, QNA: Series which are based on pre-existing databases are denoted as QNA, from Quarterly national accounts.

Setting up a full set of QSA data set implies that certain accounting relations between institutional sectors are still preserved after the seasonal adjustment. For each transaction total uses must equal total resources and thereby preserving the same horizontal consistency as QSA. This is achieved for every transaction by residualizing a carefully selected series. The choice of residual sector cannot be a series from an already existing data set like QNA. The data series must be rather large so that any erratic pattern is diluted in the time series. And the QSA raw data series cannot be estimated with a linear trend, for example where we have annual series divided by 4 quarters.

Seasonally adjusted series for the balancing items such as gross operating surplus, gross disposable income, saving etc. are derived by indirect calculation. The balancing items are thus calculated taking into account all the upstream transactions (vertical consistency).

For more information on the properties of the series please refer to "Analyzing the series of Quarterly Sector Accounts.doc“

http://www.ssb.no/english/subjects/09/90/doc_200907_en/doc_200907_en.pdf

Pre-treatment routines/schemes

Pre-treatment is an adjustment for variations caused by calendar effects and outliers

•Running an automatic pre-treatment of the raw data based on standard options in the seasonal adjustment tools. The method used to calculate the raw data for some of the series allows to remove both seasonal and outlier effects. This is especially true for the compensation of employees and for taxes and subsidies on production.

Calendar adjustment

Calendar adjustment involves adjusting for the effects of working days/trading days and for moving holidays. Working days/trading days are adjustment for both the number of working days/trading days and for that the composition of days can vary from one month to anoth

•The series tested on the number of working days in a quarter can affect the results. For quarterly series, these effects are rarely identified. This is the case for the Norwegian QSAs. None of the series have been pre-treated for trading-day effects.

•More relevant is the Easter effect. Four series have been corrected for Easter effects: production, compensation of employees, benefits from pension funds and consumption.

Methods for trading/working day adjustment

•RegARIMA correction – in this case, the effect of trading days is estimated in a RegArima framework. The effect of trading days can be estimated by using a correction for the length of the month or leap year, regressing the series on the number of working days, etc. In this case, the residuals will have an ARIMA structure.

Correction for moving holidays

•Use of standard options X-12-ARIMA, RegARIMA modeling, to identify and remove Easter effects.

•Consumption: Correction based on an estimation of the duration of the moving holidays effects, specifically adjusted to Norwegian circumstances.

National and EU/euro area calendars

•Use of default calendars. The default in X-12-ARIMA is the US calendar.

Comments : Final consumption expenditure for households uses the Norwegian calendar.

Treatment of outliers

Outliers or extreme value, are abnormal values of the series

•Outliers are detected automatically by the seasonal adjustment tool. The outliers are removed before seasonal adjustment is carried out, and then reintroduced into the seasonally adjusted data.

Model selection

Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.

•X-12-ARIMA automatically identifies one model if the average of the forecast errors is less than a previously established value. If all the models are refused one of them is manually selected (i.e. a default option). Under these premises the automatic selection must be synonymous with better quality of the results.

•The model (0, 1, 1) (0, 1, 1), often referred to as the airline model, is generally the best one. This model has only 2 parameters and is easy to interpret.

Decomposition scheme

The decomposition scheme specifies how the various components – basically trend-cycle, seasonal and irregular – combine to form the original series. Most frequently used decomposition schemes are the multiplicative, additive or log additive.

•It has been taken manual selection after graphical inspection of time series.

•For stationary series (constant mean and variance) additive decomposition has been used.

Choice of seasonal adjustment approach

•X-12-ARIMA

Consistency between raw and seasonally adjusted data

•The seasonal adjusted quarterly data will not sum up to the annual unadjusted data. This is in line with international recommendations. For the annual figures the seasonally adjusted and the raw series will be alike. This means that the sum of the seasonally adjusted figures for the 4 quarters in a year do not normally add up to the seasonally adjusted annual numbers.

Consistency between aggregate/definition of seasonally adjusted data

•The chosen method imposes the equality between aggregated series and the component series.

•Definitions and relationships also apply for seasonally adjusted figures.This is the main reason for choosing the indirect method for component series.

Direct versus indirect approach

Direct seasonal adjustment is performed if all time series, including aggregates, are seasonally adjusted on an individual basis. Indirect seasonal adjustment is performed if the seasonally adjusted estimate for a time series is derived by combining the estimates for two or more directly adjusted series.

•Indirect approach has been used. The seasonal adjustment of components occurs using the same approach and software, and then totals are derived by aggregation of the seasonally adjusted components.

Horizon for estimating the model and the correction factors

When performing seasonal adjustment of a time series, it is possible to choose the period to be used in estimating the model and the correction factors. Correction factors are the factors used in the pre-treatment and seasonal adjustment of the series.

•The whole time series is used to estimate the model and the correction factors.

Seasonally adjusted data may change due to a revision of the unadjusted (raw) data or the addition of new data. Such changes are called revisions, and there are several ways to deal with the problem of revisions when publishing the seasonally adjusted statistics.

•Both raw and seasonally adjusted data are revised between two consecutive official releases of the release calendar

General revision policy

Seasonally adjusted data are revised in accordance with a well-defined and publicly available revision policy and release calendar.

Concurrent versus current adjustment

•Partial concurrent adjustment: the model is identified and estimated yearly, while filters, outliers and regression parameters are re-identified and estimated continuously as new or revised data become available.

Horizon for published revisions

•The revision period for the seasonally adjusted results is limited to 3-4 years (preferably 4) prior to the revision period of the unadjusted data, while older data are frozen.

Evaluation of seasonally adjustment data

Continuous/periodical evaluation using standard measures proposed by different seasonal adjustment tools.

Quality measures for seasonal adjustment

•For most of the series, a selected set of diagnostics and graphical facilities for bulk treatment of data is used.

X-12-ARIMA chooses automatically the most appropriate model for the individual series.

ANOVA shows that the rates of change for the original series are primarily due to seasonal effects.

Seasonal adjustment of short time series

•All series are sufficiently long to perform an optimal seasonal adjustment.

Treatment of problematic series

•Problematic series are treated in a special way only when they are relevant. The remaining series are treated according to normal procedures.

Data availability

Options:

•Raw and seasonally adjusted data are available.

•All metadata information associated with an individual time series is available.

•Historical data are available to enable revision analysis.

Press releases

•In addition to raw data, at least one of the following series is released: pre-treated, seasonally adjusted, seasonally plus working day adjusted, trend-cycle series.

•Only levels or different forms of growth rates are presented.

•For each series, some quality measures of the seasonal adjustment are presented.

Analysing the series for Quarterly Sector Accounts (QSA): Income, expenditure and savings for households and the NPISH sector

The Committee for Monetary, Financial and Balance of Payments statistics: ESS-Guidelines on seasonal adjustment - ESS Guidelines on Seasonal Adjustment

EUROSTAT: Seasonal Adjustment. Methods and Practices

Hungarian Central Statistical Office (2007): Seasonal adjustment methods and practices (European Commission Grant 10300.2005.021- 2005.709)

U.S. Census Bureau (2002). X-12-ARIMA Reference Manual