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

Monetary aggregates


Next update

Key figures

5.6 %

twelve-month growth in total money supply M3 August 2019

Monetary aggregate M3. Twelve-month growth. Per cent
May 2019June 2019July 2019August 2019
Money holding sector4.
Households etc.
Non-financial corporations3.
Municipal government2.33.3-0.42.5
Other financial corporations0.7-1.83.0-1.7

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
May 2019June 2019July 2019August 2019
Money holding sector2 304 3082 364 7592 383 6802 379 193
Households etc.1 309 9861 377 4261 360 3521 366 747
Non-financial corporations744 545738 991775 973785 997
Municipal government114 497117 539113 72295 647
Other financial corporations135 280130 803133 634130 803

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

Monetary aggregate M3, by financial instrument. NOK million
May 2019June 2019July 2019August 2019
Notes and coins38 15438 65538 08737 763
Transaction deposits2 085 2062 145 1562 162 3602 156 709
M1 Total2 123 3592 183 8112 200 4462 194 473
Other deposits175 090175 679178 045179 561
M2 Total2 298 4492 359 4912 378 4912 374 034
Certificates and bonds5 5474 9804 9154 864
Repurchase agreements312288274295
M3 Total2 304 3082 364 7592 383 6802 379 193
-M3: In foreign exchange126 145125 762144 922125 607

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

The money-neutral sector consist 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 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 other deposits in Norwegian kroner and foreign currency with original maturities of up to two years and deposits redeemable at up to three months' notice.

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/bonds and repurchase agreements.

Administrative information

Name and topic

Name: Monetary aggregates
Topic: Banking and financial markets

Next release

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).


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.

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 (2000) and the European Central Bank’s Manual on MFI Balance Sheet Statistics (2012).

The data sources of the monetary aggregates are the same as for the Financial corporations, balance sheet statistics. Data on securities are collected from the Norwegian Central Securities Depository (VPS); the same source used in the Mutual funds 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). Valuation changes 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 34).

The statistics have a full census. Shares of deposits in foreign currency to calculate valuation changes are updated quarterly.

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. 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 valuation changes. 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 program. Seasonal components are calculated for one year ahead, when publishing data for January. Revisions of the components for previous periods are also carried out when publishing the January figures. Seasonally-adjusted volume figures for previous periods and growth rates based on such figures are thus affected.


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)

New institutional sector classification
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 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 from 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.

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