Banking and financial markets
pengemengde, Monetary aggregates, money, notes and coins, assetsFinancial indicators, Banking and financial markets

Monetary aggregates


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Key figures

4.3 %

twelve-month growth in total money supply M3 November 2019

Monetary aggregate M3. Twelve-month growth. Per cent
August 2019September 2019October 2019November 2019
Money holding sector5.
Households etc.
Non-financial corporations8.
Municipal government2.
Other financial corporations-1.9-7.0-5.7-4.4

See selected tables from this statistics

Table 1 
Monetary aggregate M3, by money holding sectors. NOK million

Monetary aggregate M3, by money holding sectors. NOK million
August 2019September 2019October 2019November 2019
Money holding sector2 379 1932 358 1812 362 1892 373 377
Households etc.1 366 7471 355 3511 348 2341 349 735
Non-financial corporations785 997768 255773 522778 701
Municipal government95 647108 510105 074113 684
Other financial corporations130 803126 065135 359131 257

Table 2 
Monetary aggregate M3, by financial instrument. NOK million

Monetary aggregate M3, by financial instrument. NOK million
August 2019September 2019October 2019November 2019
Notes and coins37 76337 50136 16836 450
Transaction deposits2 156 7092 135 2262 139 2082 148 545
M1 Total2 194 4732 172 7272 175 3762 184 994
Other deposits179 561179 758182 571184 296
M2 Total2 374 0342 352 4852 357 9472 369 290
Certificates and bonds4 8644 8363 8483 743
Repurchase agreements295860394344
M3 Total2 379 1932 358 1812 362 1892 373 377
-M3: In foreign exchange125 607140 505125 904132 449

About the statistics

The main focus of the monetary aggregate statistics is the twelve-month growth of the money-holding sectors’ stock of money and other highly liquid financial assets. Calculations of transactions and growth are adjusted for changes caused by exchange rate fluctuations and non-transactional breaks.


Definitions of the main concepts and variables

The money-issuing sector consists of Norges Bank (The central bank of Norway), banks and mortgage companies (MFIs). In the monetary base M0 the money-issuing sector consists of Norges Bank.

The money-neutral sector consists of the central government, state lending institutions etc. and foreign sectors.

The money-holding sector consists of all sectors not included in the money-issuing or money-neutral sector, i.e. the general public (municipalities, non-financial corporations, nonprofit organisations and households) and financial corporations that are not MFIs. 

The monetary base M0 is defined as the sum of Norwegian notes and coins in circulation and the MFIs’ and the money-holding sector's deposits in Norges Bank. 

Narrow money M1 is defined as the money-holding sector's stock of Norwegian banknotes and coins (currency in circulation) and their transaction deposits in Norwegian kroner and foreign currency. Transaction deposits compromise deposits from which, regardless of purpose, payments and withdrawals may be made directly, without additional costs beyond regular transaction fees (overnight deposits).

Intermediate money M2 is defined as the sum of M1 and the money-holding sector's deposits in Norwegian kroner and foreign currency with period of notice up to three months or agreed maturity of up to two years.

Broad money M3 is defined as the sum of M2 and marketable instruments issued by the MFI sector. This includes repurchase agreements and debt securities/bonds with an original maturity of up to two years.

Standard classifications

The classification of most financial instruments and sectoral structure used in the monetary aggregates follows the principles of the Monetary and Financial Statistics Manual (MFSM) and the Manual on MFI Balance Sheet Statistics (see coherence with other statistics section).

The monetary aggregates have two different breakdowns; holding sector and money supply object. Holding sector is a breakdown of the money-holding sector, by other financial corporations, non-financial corporations, municipalities and households. Money supply objects are currency in circulation, transaction deposits, other deposits, debt securities and repurchase agreements.

Administrative information

Name and topic

Name: Monetary aggregates
Topic: Banking and financial markets

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Responsible division

Division for Financial Markets Statistics

Regional level

National level.

Frequency and timeliness

Monthly. Monetary aggregates are published within one month after the reference period.

International reporting

Reporting to the International Monetary Fund (IMF) via the Special Data Dissemination Standard (SDDS) and the Bank for International Settlements (BIS).


Collected microdata and published data are stored in databases at Statistics Norway.


Background and purpose

Monetary aggregates are used as a basis for monetary policy. The statistics were established by Norges Bank in 1971 and adjusted for IMF standards in the publication of figures for November 2000. Following a review of content and international standards in 2014, the monetary aggregates now include the broad monetary aggregate M3.

Norway takes part in the Special Data Dissemination Standard (SDDS) of the International Monetary Fund (IMF). This standard requires Norway to publish a detailed breakdown of the monetary aggregates.

As of 1 January 2007, most of the work related to collection and release of financial markets statistics were transferred to Statistics Norway from Norges Bank. This included the monetary aggregates statistics.

Users and applications

The main users are monetary policy authorities, i.e. Norges Bank, the Financial Supervisory Authority and the Ministry of Finance. Other users are financial market operators and research institutions as well as students.

Equal treatment of users

No external users have access to the statistics and analyses before they are published and accessible simultaneously for all users on ssb.no at 8 am. Prior to this, a minimum of three months' advance notice is given in the Statistics Release Calendar. For more information, see Principles for equal treatment of users in releasing statistics and analyses.


Coherence with other statistics

The statistics are based on the guidelines of the standards System of National Accounts 2008 (SNA 2008) and European System of National Accounts 2010 (ESA 2010), as well as guidelines for money supply statistics in IMF's Monetary and Financial Statistics Manual and Compilation Guide (2016) and the European Central Bank’s Manual on MFI Balance Sheet Statistics (2019).

The data sources of the monetary aggregates are the same as for the Financial corporations, balance sheet statistics. Data on debt securities are collected from the Norwegian Central Securities Depository (VPS); the same source used in the Securities statistics.

Legal authority

Not relevant.

EEA reference

 Derived statistics, without direct Council Directives or Council Regulations from the EU.






The statistics consist of the monetary aggregates M1, M2 and M3. See the section on definitions for further information. The money-issuing sector consists of Norges Bank, banks and mortgage companies (MFIs). In the monetary base M0, the money-issuing sector consists of Norges Bank.

Data sources and sampling

Data for the money-issuing sector are derived from the accounting statistics of ORBOF (Reporting of banks, mortgage companies, state lending institutions and finance companies’ accounts to the public authorities). Data for issued debt securities are derived from statistics for securities registered with the Norwegian Central Securities Depository (VPS). Exchange rate adjustments are calculated using the official exchange rates from Norges Bank and information on the currency composition of the money-holding sector’s deposits in banks from the BIS survey (report 13). Shares of deposits in foreign currency to calculate valuation changes are updated quarterly.

The statistics have a full census.

Collection of data, editing and estimations

From 2007, collecting accounting data for banks and financial corporations has been the responsibility of Statistics Norway. Editing of data are undertaken by Statistics Norway and the Financial Supervisory Authority. The editing policy is to publish corrections of the previous month’s data together with the current month’s data. With every release, the latest 25 periods of stock data and 13 periods of transaction and growth data are updated. Statistics Norway is fully prepared to edit in a timely manner, with appropriate notification to users and the media, should it be deemed necessary by the magnitude of a past error, or, owing to other exceptional circumstances. Some of the reported data may contain preliminary data that are subsequently corrected. Statistics Norway monitors and analyses the data, and editing are conducted regularly.

The main focus in the statistics is transaction-based changes. In growth calculations that include deposits in foreign currency, the transaction and growth rates are adjusted for changes in exchange rates. Growth calculations are also adjusted for structural breaks. These adjustments will lead to discrepancies between growth calculations based on stocks and growth calculations based on transactions. Revisions in accounting standards and changes in accounting legislation may also lead to breaks in the time series.

Seasonal adjustment

The seasonal adjustment of monetary aggregate stocks is carried out using the X12 Arima method. Seasonal components are recalculated with each publication and seasonally adjusted stocks, as well as monthly transactions and growth rates are updated.  Only the broad money supply (M3) is seasonally adjusted. For this aggregate, seasonally adjusted series are released by money-holding sector, households, non-financial corporations, municipalities and other financial corporations.


Not relevant

Comparability over time and space

Revisions in international standards and major changes in fiscal legislation can lead to breaks in the time series. The same consequences can result from sectoral shifts. Transactions and growth estimates are adjusted for breaks in time series (see the section on data collection, revision and estimations).

Change in the statistics on banks and mortgage companies in 2018

The adjustment of ORBOF to IFRS has led to a change in the statistics on banks and mortgage companies from January 2018. An important implication for the money supply is that accrued interests and changes in value are included with the underlying financial object. As of January 2018, the stock time series are not comparable with previous periods. Transaction and growth series are corrected for this break.

Change in the monetary aggregate statistics in 2015

The stock series, transactions and growth rates in the money supply changed as a result of the change in the monetary aggregate statistics in 2015. In the new money supply statistics framework, M3 is included as the main aggregate in the money supply. M1 and M2 are continued as subsets.

As of April 2015, new deposit specifications were introduced in the balance sheet reporting. This lead to a break in the stock time series involving deposits. The monetary aggregate statistics time series from the periods prior to April 2015 are therefore not comparable with later periods. Transaction and growth series are corrected for this break. Growth series are thus comparable back to January 2009.

New institutional sector classification in 2012

As from January 2012, the Norwegian institutional sector classification has been revised in line with the international classification. This change implies a break in stock time series between February and March 2012.


Accuracy and reliability

Sources of error and uncertainty

The statistics are mainly derived from the financial markets statistics. Errors and inconsistencies in these statistics will also affect the monetary aggregates. In this context, we refer to the sections on sources of error and uncertainty in these statistics.

For the monetary aggregates, the response rate is 100 per cent, and variance and bias are not relevant.


The statistics show preliminary figures. Data may be revised in future publications. At each publication, stock time series are updated with the latest 25 periods. Transactions and growth are updated for 13 periods.

About seasonal adjustment

General information on seasonal adjustment

Monthly and quarterly time series are often characterised by considerable seasonal variations, which might complicate their interpretation. 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-12-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.

For more information on seasonal adjustment: metadata on methods: seasonal adjustment

Why seasonally adjust these statistics?

On the basis of public holidays and holiday period in July and December the intensity of the supply and demand of money fluctuates through the year. This complicates a direct comparison of money supply figures from one month to the next. To adjust for these relations the money supply seasonally adjusts the actual level for the monetary aggregate M3, so that one can analyse the underlying money supply development.

Seasonally adjusted series

EUROSTAT: Seasonal Adjustment. Methods and Practices

US census: X-12-ARIMA-manual

Money supply statistics publishes five seasonally adjusted series; M3, M3-households, M3-non financial corporations, M3-municipal government and M3-other financial corporations. The seasonally adjusted figures for M3-other financial corporations is not a result of own seasonal adjustment, but a residual from the difference of seasonally adjusted M3 and the sum of the other sectors’ seasonally adjusted figures.


Pre-treatment routines/schemes

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

  • No pre-treatment.

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 another.

  • No calendar adjustment of any kind is performed.

Methods for trading/working day adjustment

  • No correction.

Correction for moving holidays

  • No correction.

National and EU/euro area calendars

  • Definition of series not requiring calendar adjustment.

Treatment of outliers

Outliers, or extreme values, 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.

  • Automatic model selection by established routines in the seasonal adjustment tool.

Decomposition scheme

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

  • Manual decomposition scheme selection after graphical inspection of the series.
  • We have chosen compulsory multiplicative decompositions. The program chose automatically this option until 2008, and it is now incorporated as a claim.

Seasonal adjustment

Choice of seasonal adjustment approach:

  • X-12-ARIMA

Consistency between raw and seasonally adjusted data

In some series, consistency between raw and seasonally adjusted series is imposed.

  • Do not apply any constraint.

Consistency between aggregate/definition of seasonally adjusted data

In some series, consistency between seasonally adjusted totals and the aggregate is imposed .For some series there is also a special relationship between the different series, e.g. GDP which equals production minus intermediate consumption.

  • Do not apply any constraint.

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.

  • Mixed indirect approach where the seasonal adjustment of components possibly occurs using different approaches and software.

Comments: The total is computed independently of the components. The last component is computed as a residual of the difference between the total and the other 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.

  • Only part of the time series is used to estimate the correction factors and the model.

Comments: The data used for th3 M3 series are data from Januay 2008 to the last observed December figure. 

Audit procedures

General revision policy

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.

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

Comments: The program for seasonal adjustment with new seasonal components is made once in a year, but seasonally adjusted figures are audited in accordance with audited raw data.

Concurrent versus current adjustment

  • Controlled current adjustment: Forecasted calendar factors derived from a current adjustment are used to seasonally adjust the new or revised raw data. The numbers are revised when new, fixed factors are estimated once a year.

Horizon for published revisions

  • The entire time series is revised in the event of a re-estimation of the seasonal factors.

Comments: The whole series which enters into seasonal adjustment is audited once a year. Apart from this, the elderly seasonal adjustment figures are only audited when unadjusted figures are been audited.

Quality of seasonal adjustment

Evaluation of seasonally adjustment data

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

Quality measures for seasonal adjustment

  • No quality measures for seasonal adjustment assessment are used.

Special cases

Seasonal adjustment of short time series

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

Treatment of problematic series

  • Νο series are treated in a special way, irrespective of their characteristics.

Posting procedures

Data availability

  • Raw and seasonally adjusted data are available.

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.

Relevant documentation