Accommodation

Name: Accommodation
Topic: Transport and tourism

Division for Business Cycle Statistics

County, region, tourism region and municipality. Commercial guest nights are published for counties, municipalities and tourism regions. Guest nights in private cabins and holiday houses arranged through Norwegian-registered intermediaries are published for regions.

Monthly. Published 3-4 weeks after the end of the month.

Statistics Norway reports the statistic to the following international organisations:

• Statistical Office of the European Communities (Eurostat)
• The Organisation for Economic Co-operation and Development (OECD)
• The United Nations (UN), i.e. World Tourism Organization (UNWTO)

Collected and revised data are stored securely by Statistics Norway in compliance with applicable legislation on data processing.

Statistics Norway can grant access to the source data (de-identified or anonymised microdata) on which the statistics are based, for researchers and public authorities for the purposes of preparing statistical results and analyses. Access can be granted upon application and subject to conditions. Refer to the details about this at Access to data from Statistics Norway.

The purpose of the statistics is to measure the level and development in the guest nights at Norwegian collective accommodation establishments, which are an important part of the Norwegian tourism industry.

The accommodation statistics for hotels and similar establishments were established in 1950.
The accommodation statistics for camping sites were established in 1968.
The accommodation statistics for holiday dwellings were established in 1998.

Statistics for intermediaries of holiday homes were established in 1999. They were initially published annually as intermediaries of cabins.

Figures for Hostelling International Norway were published for the first time in Statistics Norway's annual publication in 1965 and included in Statistics Norway's monthly figures from July 2002. Holiday dwellings and youth hostels were combined in 2020 to enable publishing at county level.

Considerably more respondents were included to the statistics for intermediaries of holiday homes from January 2020 and the survey covers a wider range of holiday homes, not just cabins. Respondents were further added in January 2025. This means that data is not directly comparable with previous years. From January 2021, these statistics are published under accommodation statistics, and changed from an annual to a monthly publication.

Users include public authorities, organizations, consulting firms, research institutions, as well as international organizations like Eurostat.
Knowledge of the tourist traffic to Norway is important for research and for measuring the results of Norwegian marketing efforts abroad and form a basis for the Government's backing of tourism as a growth area.

The Division for National Accounts in Statistics Norway is also an important user.

No external users have access to statistics before they are released at 8 a.m. on ssb.no after at least three months’ advance notice in the release calendar. This is one of the most important principles in Statistics Norway for ensuring the equal treatment of users.

The Division for National Accounts uses the hotel data in their quarterly publishing.

The accommodation statistics are used to check the quality of the Travel- and Holiday Survey and the Structural Business Statistics for Hotels and Restaurants.

The accommodation statistics are also used for estimates in the quarterly turnover index for transport and tourism.

The statistics are developed, produced and disseminated pursuant to Act no. 32 of 21 June 2019 relating to official statistics and Statistics Norway (the Statistics Act).

Council Regulation (EC) no. 1165/98 of 19 May 1998 concerning short-term statistics.
Regulation (EC) no. 692/2011.

The statistics cover all hotels and similar establishments (SIC 55.1), camping sites with a capacity of at least 20 units in total capacity (SIC 55.3), holiday dwellings with a capacity of at least 10 beds, and all youth hostels (SIC 55.2), as well as all Norwegian-registered intermediaries of private homes. The capacity for camping sites includes places for campers, tents and bed places in camping huts.

Hotels: The statistics is based on monthly reporting of data on the number of guest nights by nationality and purpose of the stay. Hotels also report revenue, rooms sold and nationality of the arrivals.

For camping sites, holiday dwellings and youth hostels, the statistics is based on monthly reporting on either the number of unit nights or guest nights, by nationality. Figures are published only on guest nights, using factors reported by the establishments.

Intermediaries of private homes report guest nights monthly. The guest nights are categorized by nationality and by the county the guest nights were in. They also report arrivals. Arrivals here are used only for controlling for logical and mathematical errors.

The nationalities published are in line with the EU regulations, combined with selected countries based on needs by users.

Data reported directly from the establishments’ booking systems or internet questionnaires.

Total count all hotels, youth hostels and intermediaries of holiday homes. All camping sites with more than 20 units, and holiday dwellings with more than 10 beds are included in the survey.

The questionnaires are sent out at the end of the month. The response deadline is 10 days after the questionnaire is sent. All questionnaires and all data reported electronically are subject to logic and mathematical checks.

Editing is defined here as checking, examining and amending data.

About 2 per cent of the establishments do not respond. For these establishments, the number of guest nights and sales are calculated based on the establishments that responded.

Seasonally adjusted figures for accommodation statistics were first introduced with the publication of the January 2022 statistics. Monthly time series are often characterized by considerable seasonal variations, which might complicate their interpretation. Such time series are therefore subjected to a process of seasonal adjustment to remove these fluctuations. A clearer picture of the time series emerges once the data have been adjusted for seasonal effects.

The accommodation statistics are seasonally adjusted using the X-12 ARIMA method. The series are controlled for seasonality, moving holidays such as Easter and extreme values. For more information on seasonal adjustment: metadata on methods: seasonal adjustment.

Employees of Statistics Norway have a duty of confidentiality.

Statistics Norway does not publish figures if there is a risk of the respondent’s contribution being identified. This means that, as a general rule, figures are not published if fewer than three units form the basis of a cell in a table or if the contribution of one or two respondents constitutes a very large part of the cell total.

Statistics Norway can make exceptions to the general rule if deemed necessary to meet the requirements of the EEA agreement, if the respondent is a public authority, if the respondent has consented to this, or when the information disclosed is openly accessible to the public.

More information can be found on Statistics Norway’s website under Methods in official statistics, in the ‘Confidentiality’ section.

To ensure confidentiality, the ‘suppression’ method is used in these statistics.

The hotel statistics were established in 1950. Due to several changes in the scope of the statistics, these are not comparable for the whole period. With the revision of the Hotel Act in 1984, the approval system was removed, and this increased the number of establishments. There have been several other changes, the latest one in 2020. Hotel statistics are however comparable from 1985 to today.

The camping statistics were established in 1968 and the scope has been revised several times. In 1988, a register with information on opening hours and capacity was established, enabling estimates for non-respondents. In 1998, the cover was extended to include overnight stays in caravans on seasonal contracts. The camping statistics were also extended to include the winter and autumn season and to include consecutive monthly publication. The camping statistics are therefore comparable from 1998.

The holiday dwelling statistics were established in 1998 and are comparable from 1998.

Statistics for intermediaries of holiday homes was established in 1999 as intermediaries of holiday cabins. In the period 1999-2005 the statistics covered both Norwegian and foreign intermediaries, but only intermediaries with activity in Norway since 2006. From 2020, the statistics cover more Norwegian intermediaries. More intermediaries were further added in 2025 and statistics before and after January 2025 are not directly comparable. These changes compromise comparability over time over the whole period.

Figures for Svalbard were included in 2013.

In January 2013 the production of the statistics changed considerably, with new cut-offs based on international regulations. Establishments were now defined by the Business Register. This led to significantly more establishments in the population.

From January 2017, reporting of accommodation statistics switched to the digital ALTINN platform. This transition came with changes to the questionnaire. The list of countries was expanded and the category ‘The rest of Europe’ removed. More countries have subsequently been added, affecting the category ‘The rest of Asia’. Reporting directly from establishments’ booking systems was also made possible.

Statistics Norway continually works to improve reporting of data, and the quality of statistics will gradually improve along with this.

Incorrect responding can occur due to incorrect data entry, interpretational errors, and other reasons. As a result, figures will occasionally be edited.

Measurement errors are caused by the questionnaire design or the respondent’s internal systems for obtaining the data. One source of measurement errors may be ambiguous guidelines. The introduction of electronic data collection has reduced the scope of measurement errors.

Processing errors may occur when Statistics Norway processes the data. Typical examples are misinterpretations, or when correct answers are assumed to be false and corrected. Electronic data collection through Altinn reduces these kinds of errors.

Errors of non-response refer to errors that either occur due to missing questionnaires or blank boxes in the questionnaire. In this situation, respondents are re-contacted.

Sampling errors refer to the uncertainty that occurs in sample surveys as opposed to a full count. These errors are not relevant for intermediaries of holiday homes since all active units are included in the survey.

Coverage errors refer to errors in the registers that define the population. Units may be incorrectly included in or excluded from the population, usually because of delayed register updates. Calculations on the size and significance of such errors have not yet been carried out. However, such errors are not considered to be greater than for other quantitative short-term statistics.

Modeling errors are related primarily to problems with seasonal adjustment of time series.

Not relevant.

Monthly time series are often characterized by considerable seasonal variations, which might complicate their interpretation. Such time series are therefore subjected to a process of seasonal adjustment 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 and the changes in the time series emerges.

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

The number of guest nights and revenue in accommodation statistics will normally vary from month to month due to factors such as the length of the month, number of working days and moving holidays such as Easter. The purpose of the seasonally-adjusted figures is to show the real trends by eliminating interference caused by seasonal variations.

A total of 130 seasonal adjusted series are published for the accommodation statistics. They include hotel guest nights by county, guest nights at camping sites and holiday dwellings by county and hotel revenue at county level. Seasonally adjusted values for the whole country are also published for these series.

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

Before the seasonal adjustment can be made the series are pre-corrected for, among other things, extreme values. We follow the European Statistical (ESS) guidelines as far as possible. Identified extremes are explained/modelled using all available information.

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.

Calendar adjustments are done on all series showing significant and plausible calendar effects within a statistically robust approach, such as regression or RegARIMA (a regression model with an ARIMA structure for the residuals). The regression variables for the calendar adjustment are adapted to reflect the working days and public holidays specific to Norway.

Methods for trading/working day adjustment

RegARIMA correction is used – 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

Correction is based on an estimation of the duration of the moving holidays effects, specifically adjusted to Norwegian conditions.

National and EU/euro area calendars

Use of the Norwegian calendar, which considers Norwegian working days and public holidays.

Treatment of outliers

Outliers, or extreme values, are abnormal values of the series.

Series are inspected to identify outliers. Identified outliers are then modelled using available information. The outlier is included as a regressor where it’s interpretation is clear (such as a new large popular hotel).

Model selection

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

Model selection is automatic, with established routines in the seasonal adjustment tools.

Decomposition routine

The decomposition routine specifies how the trend, seasonal and irregular components are decomposed. The most common decompositions are the multiplicative, additive or log additive.

Multiplicative decomposition is used in this model.

Choice of seasonal adjustment approach: X-12-ARIMA.

Consistency between raw and seasonally adjusted data

In some series it is preferred that, for example, the sum of monthly seasonally adjusted figures for a year should be identical to the sum of monthly figures in the original raw series.

For the accommodation statistics, no consistency conditions are applied.

Consistency between aggregate/definition of seasonally adjusted data

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

No consistency conditions are applied.

Direct versus indirect approach

Direct seasonal adjustment is performed if every 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.

Direct approach is used here. The raw data are aggregated, and the aggregates and components are then directly seasonally adjusted using the same approach and software. Any discrepancies across the aggregation structure are not removed.

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 for hotel guest nights and revenue. The time period for camping sites and holiday dwellings begins at January 2013. Series for Svalbard start from January 2010.

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.

In accordance with recommendations from the ESS, the models behind the seasonally adjusted figures will be subject to a thorough review once a year.

Concurrent versus current adjustment

The model, filters, outliers and regression parameters are re-identified and re-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

A set of available diagnostics within the seasonal adjusted tools and graphical capabilities are used.

A table containing selected quality indicators for the seasonal adjustments is available. The table covers the published industry aggregates for the volume of production. The table is available here: indicators of quality in seasonal adjusted figures.

For more information on the quality indicator in the table see: metadata on methods: seasonal adjustment.

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

Unadjusted figures (original series or raw data), seasonally adjusted and smoothed seasonally adjusted figures are available.

Seasonal adjustment: general information.

ESS guidelines on seasonal adjustment.