households savings ratio
|2015||2016||1st quarter 2017||2nd quarter 2017||3rd quarter 2017|
|Disposable income||1 352 043||1 371 655||350 208||352 857||357 382|
|Saving||154 242||104 885||25 466||23 942||25 985|
|Savings ratio (per cent)||10.7||7.2||6.9||6.4||6.9|
|Real disposable income, growth||5.3||-1.8||-1.6||1.1||2.4|
|National income||3 247 407||3 266 913||857 547||854 684||853 004|
|Disposable income||2 636 246||2 638 615||702 192||694 769||695 648|
|Disposable income in 2005 prices, growth||-3.2||-2.4||1.5||-2.2||2.0|
See more tables on this subject
|2015||2016||1st quarter 2017||2nd quarter 2017||3rd quarter 2017|
|GROSS DOMESTIC PRODUCT, market values||3 118 116||3 117 032||818 786||815 991||814 766|
|+ Primary income from the rest of the world||337 660||353 049||93 073||93 716||94 472|
|- Primary income to the rest of the world||208 369||203 168||54 312||55 022||56 234|
|= GROSS NATIONAL INCOME||3 247 407||3 266 913||857 547||854 684||853 004|
|- Consumption of fixed capital||555 288||572 064||142 666||144 928||145 071|
|= NATIONAL INCOME, NET||2 692 119||2 694 849||714 880||709 756||707 934|
|+ Current transfers from the rest of the world||33 933||35 753||9 493||9 565||8 202|
|- Current transfers to the rest of the world||89 806||91 987||22 573||24 116||21 000|
|= DISPOSABLE INCOME||2 636 246||2 638 615||702 192||694 769||695 648|
|= Final consumption expenditure||2 082 990||2 176 271||557 551||563 454||569 077|
|- Adjustment, household pension funds. Net||-2 348||-2 223||-616||-626||-621|
|= SAVING||550 908||460 121||144 025||130 689||125 950|
|+ Capital transfers, net||-870||-822||16||-388||-271|
|- Net acquisiton of other non-financial assets||304 476||341 910||94 097||92 852||77 450|
|= NET LENDING (+) / NET BORROWING (-)||245 562||117 389||49 553||37 885||47 717|
|MEMO: Disposable income in 2005-prices||1 937 135||1 891 475||494 573||483 613||493 174|
Special tables for experienced users:
About the statistics
The sector accounts show economic flows such as interests, dividends, taxes and pensions within and between the sectors of the economy. The main areas are gross national income, disposable income, savings and net lending/net borrowing.
See Concepts and definitions in national accounts for definitions of variables and other concepts used in the national accounts.
The accounting system of the Norwegian national accounts is based on the international standards for national accounts, i.e. 2008 SNA and ESA 2010. The accounting system outlines the framework and contents for the production of national accounts statistics. In addition to accounting structure, the accounting system contains a number of groupings or classifications used in the national accounts, of which the most important for the non-financial sector accounts are
The institutional units (see section Production) are grouped in institutional sectors on the basis of their principal economic functions, behavior and objectives. The classification of institutional sectors in the non-financial sector accounts is based on the principles in 2008 SNA and ESA 2010, as well as Statistics Norway's standard Institutional Sector Classification 2012 (which also is based on 2008 SNA and ESA 2010). The main sectors in the economy are the non-financial corporations, financial corporations, general government, households, non-profit institutions serving households and rest of the world. See Concepts and definitions in national accounts for an explanation of the main sectors The main sectors are classified into more detailed sectors and sub-sectors. Figures from the non-financial sector accounts are published separately for the different main sectors in the economy, and final annual figures are also published in some more detail, see Sectors in the Norwegian Non-financial Sector Accounts.
Name: National accounts, non-financial sector accounts
Topic: National accounts and business cycles
Division for National Accounts
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).
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 annual final non-financial sector accounts data are based on all avvailable economic statistics, and take some time to produce. The purpose of the quarterly sector accounts is to give 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, that is the non-financial and financial corporation sectors, general government, households, non- profit institutions serving households (NPISH) and the-rest-of-the world. Before this the published accounts did only cover the sectors households and NPISH. Consistent time series for all sectors are available from the 1st quarter 2002 onwards.
The Norwegian National Accounts, including the quarterly non-financial sector accounts, are based on the international recommendations in the System of National Accounts (SNA), published by UN, OECD, IMF, EU and the World Bank and The European System of national and regional Accounts (ESA). From time to time some 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. Since one objective of the national accounts is to provide a picture of the development over time which is as correct 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 introduce new levels based on new statistical sources. As a part of these main revisions the time series are revised so that the revised national accounts can give a consistent picture of the economic development over time.
Statistics Norway has recently carried out a new main revision published in November 2014, to incorporate updated international recommendations in 2008 SNA and ESA 2010. Changes due to this main revision are described, among else, in the article Main revision 2014. Planned changes in the national accounts statistics.
From the Norwegian national accounts were established and until today, Statistics Norway has carried out 6 main revisions. The previous main revision, published in 2011 is described in the article Revised national accounts figures 1970-2010.
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.
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 non-financial sector accounts are fully consistent with other parts of the national accounts statistics, that is the annual national accounts (the real accounts), the quarterly national accounts, and the annual non-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.
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 SNA (published by the UN, OECD, IMF, World Bank and the European Commission) and the European System of Accounts ESA 2010.
The national accounts contain two fundamental types of information: flows and stocks. Flows refer to changes that take place during a certain period of time, for example the production in an industry during a year. Stocks refer to the situation at a certain point in time, e.g. the value of the stock of non-financial capital or the number of employed persons.The delineation of the economy towards the rest of the world is based on the concept of resident units. A unit is a resident unit when it has a centre of economic interest in the economic territory in question, i.e. when it is engaged in economic activity in a territory for a long period of time (at least one year).
The national accounts comprise two fundamental statistical units: institutional units and local kind-of-activity units (establishments). 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 local KAUs are classified by type of activity. An activity is characterised by an input of products, a production process and an output of products. All local KAUs engaged in the same, or similar kind-of-activity constitute an industry.
The national accounts consist of two main sets of tables; the supply and use tables (SUT), also described as the real accounts, and the institutional sector accounts. The real accounts (the annual real accounts are referred to as the annual national accounts when publishing the data) are based on local kind-of-activity units (KAU).
The non-financial sector accounts are based on institutional units. Institutional units are capable of providing a full set of accounts. The non-financial sector accounts therefore describe all economic transactions in the various sectors. The accounts also provide information on the stocks financial and non-financial capital. Financial sector accounts are also based on institutional units. The institutional units are grouped in institutional sectors on the basis of their principal economic functions, behavior and objectives; see Section Definition, Classification.
The non-financial sector accounts are consistent with the real accounts. This description of the national accounts covers the quarterly non-financial sector accounts.
Households and Non-Profit Institutions Serving Households (NPISH)
Quarterly figures for households and NPISH’s are to some extent based on information for other sectors (cross-sector information). For example are figures for financial incomes and expenditures 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 NPISH, as well as current transfers from the household sector and the NPISH 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.
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.
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.
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.
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.
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.
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.
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 2002 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.
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.
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 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-13-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-13-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 X13-ARIMA without stipulate that annual figures for unadjusted and seasonally adjusted are identical.
• We are using X-13_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:
Income Resident sectors, total Non-financial corporations Financial corporations General government Households NPISH Rest of the world Imports of goods QNA Imports of services QNA Value added, gross QNA Residual QNA QNA J QNA S Compensation of employees Sum J J Operating surplus Sum S S S S S S Subsidies Sum Residual J N A N Property income Sum J T T J J T
Financial Intermediation Services Indirectly Measured
Sum A A N A A T Balance of primary income Sum S S S S S S Contributions to social security Sum J Current taxes on income and wealth Sum J M Pensions and social benefits from public administr. Sum Residual J Unfunded and privately funded social benefits Sum N Residual N J A A Other current transfers Sum J J J J J J Disposable income Sum S S S S S S Adjustment, household pension funds Sum J Saving Sum S S S S S S Capital transfers Sum Residual N A N A Net lending Sum S S S S S S Expenditures Resident sectors, total Non-financial Corporations Financial corporations General government Households NPISH Rest of the world Exports of goods QNA Exports of services QNA Consumption of fixed capital Sum Residual N J N Compensation of employees Sum Residual J N J N J Taxes on production and imports Sum Residual J N A N Property expenses Sum Residual T J J J T Financial Intermediation Services Indirectly Measured Sum J Residual N J N T
Contributions to social security
Sum J Current taxes on income and wealth Sum Residual J M J T Pensions and social benefits from public administration Sum J A Unfunded and privately funded social benefits Sum N Residual N J A A Other current transfers Sum Residual J J J J A Consumption QNA QNA QNA QNA Adjustment, household pension funds Sum J Capital transfers Sum N N J N N Gross fixed capital formation QNA Residual QNA QNA J QNA Changes in stocks and statistical discrepancies QNA Residual Net aqcuisition of non-produced non-financial assets Sum Residual N N
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“
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 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.
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.
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
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-13-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.
•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.
•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.
•Hungarian Central Statistical Office (2007): Seasonal adjustment methods and practices (European Commission Grant 10300.2005.021- 2005.709)