The production index for construction will change from being published on a quarterly basis to a monthly basis. The last quarterly statistics published was the 4th quarter of 2021. The monthly production index for January 2022 will be published on the 11th of March.
Production index for construction
Updated: 30 November 2022
Next update: 6 January 2023
About the statistics
The production index measures the development of activity in the construction industry. The statistics is a monthly volume index and is based on hours worked in the industry.
Hours worked: Productive hours worked by employees employed in the construction industry. Paid unproductive hours such as holidays, sickness, leave, courses, etc. is not included.
Establishment is defined as a locally limited functional unit that mainly conducts business within a specific industry group (Standard for industry groupings).
Name: Production index for construction
Topic: Construction, housing and property
Division for Business Cycle Statistics
Index at national level.
Monthly frequency. Published within 45 days after the end of the relevant month.
Non-edited and edited micro data are stored in accordance with Statistics Norway's guidelines for storing computer files.
The overall purpose of the production index is to measure the development in added value (production minus intermediate consumption) in the construction industry on a monthly basis. However, this is quite difficult, so the index maps out the development of production in the construction industry by using an estimation of hours worked. The statistics thus assume that there is a stable relationship between production and intermediate consumption (over a year). The statistics is financed exclusively by government appropriations.
In line with new requirements from Eurostat, the production index for construction was changed from being published on a quarterly basis to a monthly basis as of January 2022. Time series back to January 2016 have been calculated for aggregates on industrial level according to NACE. For the total index, the time series dates to January 2005. This series is based on the old quarterly statistics and is calculated by breaking down the time series from quarterly to monthly.
Statistics Norway's national accounts division uses the production index for construction as a control mechanism in the national accounts. Other key users of the statistics are the Ministry of Finance, Norges Bank, international users, as well as authorities and organizations in the construction industry.
The production index is used internally in Statistics Norway as a control in the national accounts as an indicator of the development in the construction industry's gross production.
The development in the production index is also seen in connection with the development in turnover and the processing value for the construction industry in the statistics Structural business statistics.
Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics (EBS).
The population covers all activity in the construction industry section F Standard Industrial Classification (SIC2007) . The statistics are limited to activities within market-oriented sectors, i.e. pure municipal and state enterprises are excluded.
The observation unit and the analysis unit in the survey are establishments. The number of establishments included in the calculation of the production index is approximately 25.000.
The data source used as a basis for the calculations of hours worked is the A-ordningen and include all establishments. Establishments are obtained from the A-ordningen as classified in the construction industry registered as active in Statistics Norway's own Business Register.
The weights are calculated on the basis of the processing value at the factor price for construction activities from the statistics Structural business statistics.
The production index is published as a volume index with the year 2015 as reference period. The index is calculated based on hours worked. Hours worked is a recommended (Eurostat) indicator for the development of value added in the construction industry where the work processes are very long, and where it is difficult to measure production using output data. No adjustments are made for changes in labour productivity and hired labour is not included.
Data for the hours worked is based on employments and are collected from the A-ordningen. A first version of A-ordningen is used to calculate the latest monthly production index, while an updated delivery from A-ordningen is used to revise the previous month with updated values. This means that the last published monthly values must be regarded as preliminary figures, while the previous month present final figures.
The number of employees and estimated hours are compared against corresponding values in previous months. Establishments going in or out of the population are examined and industry changes are controlled.
Estimations of hours worked
Calculation of hours worked is estimated according to a formula from Statistics Norway’s Labour Accounts. The formula is used to calculate quantities for hours worked in the national accounts. The hours are calculated for each active employment. The hours are then aggregated on establishments and then on industry subclasses where the lowest level is 4-digit NACE.
Short time indices
Monthly calculated hours worked in year t are compared with calculated hours in year t-1. This provides a basis for calculating the short-term index for the industry. An unadjusted short-term index of 105 then shows an increase of 5 percent compared to an average of last year's calculated hours.
In order for the aggregate indices to be able to absorb changes in the relative relationship between the industries, aggregated indices are calculated by weighing the short-term indices at the lowest level (4-digit NACE) together. Value added at factor prices from the statistics Structural business statistics for year t-3, is used as weights. The weights are updated annually.
Chaining to long-term indices:
The short-term index is chained to the average long-term index from the previous year. This must be done to be able to compare the indices over time.
Chained indices are calculated with reference year 2015 for industry section F, at industry divsion (2-digit NACE), and at industry group (3-digit NACE).
Due to moving holidays and holidays in July and December, the intensity of construction activites varies throughout the year. This complicates a direct comparison from one month to the next. There are considerable seasonal variations in the production index for the construction industry. By removing seasonal variation, the underlying economic development becomes clearer.
Calendar adjusted, seasonally adjusted and smoothed seasonally adjusted (trend) indices are published. The calendar adjusted indices take into account moving holidays and weekday effects. When comparing calendar adjusted figures, it is most appropriate to look at changes in the last 12 months and not changes from month to month. The seasonally adjusted indices are used to compare changes from month to month.
The production index for the construction industry is seasonally adjusted using the X13-ARIMA method.
For more details on seasonal adjustment of the Production Index, see below, under "About seasonal adjustment".
It is not possible to identify sensitive information from the statistics. Individual units cannot be identified in the publication of the statistics.
The use of data collected from respondents takes place in accordance with the provisions of the Statistics Act.
The production index for construction changes frequency from quarterly to monthly publications from the statistical month January 2022 and onwards. Additional changes are introduced at the publication levels. This means that one shifts from publishing by type of building and construction activity (CC code) to industry section F using the Standard industrial classification (SIC2007). Publication will be detailed at the level industry group (3-digit NACE). The change is a result of the introduction of a new European regulation for business statistics called European Business Statistics (EBS). Simultaneously both the data source and the calculation method will change. The new production index is based on estimated hours worked from A-ordningen in combination with weights from the statistics Structural business statistics.
Quarterly sample survey including the 4th quarter of 2021 (closed time series)
Before the second quarter of 2004, hired labour was not included. From the second quarter of 2004 labour hired from employment agencies was included. This was reversed in 2011 as it occurred that the companies omit to include hired labour in their reports. Therefore, Statistics Norway will use other sources to estimate hours worked in construction industry by labour hired from employment agencies.
In 2003, Mesta AS was separated as a private company from the Norwegian Public Roads Administration and is included in the calculation basis.
The calculation method was changed in 2000. From the 1st quarter of 2000, the calculation of the production index is based on measuring the number of hours worked. Earlier, the calculation is based on employment figures. The quarterly figures calculated after 1999 are therefore not directly comparable with the figures calculated before the 1st quarter of 2000.
In 1999 the figures from the Matrikkel was not included because of increasing reporting delay in the register.
From 1995 to 1998 the index for new buildings were calculated from a model based on new buildings started from the building register from the Matrikkel and the rest was based on employment-figures.
Closed Statbank series can be found here:
Measurement errors in reporting to the A-ordningen are caused by the respondent’s internal system for obtaining the data. Examples are misunderstandings in the completion of the A-ordningen or errors in the data of the respondent. To avoid this, great emphasis has been placed on clarity in the guidance to the A-ordningen and controls in the reporting solution.
Processing errors may occur when Statistics Norway processes the data. This may be due to technical errors in the programs used to produce the statistics or in the connection of various data sources. We have a comprehensive control system to avoid processing errors.
Errors of non-response refer to error that is either due to unit dropout, i.e. that the unit has failed to answer, or partial dropout, i.e. that the unit has failed to answer at least one of the questions in the survey. In the production of the index it can occur that some companies do not meet deadlines for reporting to the A-ordningen. To reduce the effect of this, the previous month will be revised with a newer version of the reporting which also includes any missing units in the first version. To correct this the first version of A-ordningen is adjusted by factors calculated between the first and second versions of data from the same month the year before on the 4-digit NACE.
Coverage errors refer to errors in registers that define the population, in this case the Central Register of Establishments and Enterprises. As a result of such errors, units may be incorrectly included in or excluded from the population. Other problems are related to delays in the update of the registers and units that are incorrectly classified. From experience, a limited share of the population units is incorrectly classified. This is usually due to misleading or insufficient information at a certain time. No calculations on the size and significance of such errors have been carried out. However, such errors are not considered to be greater than for other quantitative short-term statistics.
Modelling errors are mainly related to problems with the seasonal adjustment of time series. Such problems are caused by deviation from the conditions that form the basis for the model used. Typical problems are related to movable public holidays such as Easter and Pentecost. X13-ARIMA generates a number of indicators that are used to evaluate the quality of the seasonal adjustment. These indicators have identified a stable seasonal pattern.
When publishing a new monthly figures, the previous month is revised with updated data from the A-ordningen. This means that the last published monthly values must be regarded as preliminary figures, while the previous month present final figures.
What is 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-13-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.
For more information on seasonal adjustment: Seasonal adjustment: general information
Seasonally adjusted series
For the production index for construction, seasonally series are published on the industry level 2 and 3 together with the total series.
The production index is adjusted for seasonal variations since analysis show a stable seasonally pattern. By removing the seasonal effects, the underlying economic development becomes more evident.
A detailed pre-treatment is done. This means that the tools are based on special adjusted models and not based on standard options in the seasonal adjustment tools.
Calendar adjustments are performed 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).
Methods for trading/working day adjustment
The series are corrected using RegARIMA modeling: The effect of working days is estimated by correcting for then length of each month when one also takes into account the occurrence of leap years. The regressor used is given by the number of working days. Within RegARIMA modeling, the effect of the working days is estimated, and an ARIMA structure is obtained for the residuals.
Correction for moving holidays
Correction for moving holidays is done by counting these days as Sundays.
National and EU/euro area calendars
In the seasonal adjustment of the production index for construction, a calendar based on Norwegian public holidays is used.
Treatment of outliers
Outliers are detected automatically by the seasonal adjustment tool and are removed before the seasonal adjustment is carried out. The extreme values are subsequently included in the seasonally adjusted figures.
Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.
Model selection is primarily automatic, but in some cases models are selected manually. A log transformation of unadjusted (raw) data is performed for pre-treatment of the series in the production index.
After the automatic model selection, the model parameters are held constant throughout the year.
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.
For decomposition of the index a multiplicative decomposition is in use.
Choice of seasonal adjustment approach
Consistency between raw and seasonally adjusted data
In some series, consistency between raw and seasonally adjusted series is imposed.
For the production index of construction, no constraints 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.
For the production index of construction there is no consistency imposed.
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.
Direct approach where 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.
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 between two consecutive official releases of the release calendar.
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 approximately 3 years prior to the revision period of the unadjusted data, while older data are frozen.
When changing the method, the entire time series can be recalculated and updated.
Evaluation of seasonally adjustment data
Continuous/periodical evaluation using standard measures proposed by different seasonal adjustment tools.
Quality measures for seasonal adjustment
To analyse the time series, a limited range of diagnostics and graphics are used by the seasonal adjustment tool.
A monthly graphical and detailed empirical analysis is available.
Seasonal adjustment of short time series
All series are sufficiently long to perform an optimal seasonal adjustment.
Treatment of problematic series
None of the published series are viewed as problematic.
Unadjusted figures (orignial series or raw data), calendar adjusted, seasonally adjusted and smoothed seasonally adjusted figures are available.
In addition to unadjusted figures (raw data), the following series are released: calendar adjusted, seasonally adjusted and smoothed seasonally adjusted figures.
Both levels/indices and different forms of growth rates are presented.