The statistics has been discontinued.
Updated
Key figures
6 %
growth in new orders received from Q4 2016 to Q4 2017
| Per cent | Index | ||
|---|---|---|---|
| 3rd quarter 2017 - 4th quarter 2017 | 4th quarter 2016 - 4th quarter 2017 | 4th quarter 2017 | |
| New orders received | |||
| Total | 8 | 6 | 170 |
| Buildings | 22 | 12 | 164 |
| Civil engineering works | -17 | -3 | 176 |
| Stock of orders | |||
| Total | 0 | 15 | 207 |
| Buildings | 3 | 18 | 202 |
| Civil engineering works | -4 | 9 | 218 |
About the statistics
The order statistics are a leading indicator for the value of projects in building and construction industry. The survey measures the value of new orders received during the period concerned and the stock of orders at the end of the period in current prices.
Definitions
-
Order refers to a client’s request to the construction producer for future production and deliveries.
New orders is the value of all new orders the enterprises has received in the course of the quarter, including orders completed in the course of the same quarter.
Order reserves is the value of all orders in the stock that the enterprises has left to fill by the end of the quarter.
The value of an order is the sales value, excluding VAT, but including any productions and sales taxes and subcontracts of the project (contract) covered by the order. The order amount associated with rigs and modules is not counted.
-
Standard Industrial Classification (SN2007)
The indices are published by project groups as follows:
Residential buildings also includes combined buildings where at least 50 per cent of the utility floor space is for housing purposes. This group also includes garages, outbuildings and other small houses in connection with dwellings.
Other buildings also includes holiday homes and old people's homes/nursing homes.
Rehabilitation of buildings includes repair, improvement and maintenance. If the rehabilitation project also includes additions, the order is regarded as a new building if the addition makes up more than 50 per cent of the value of the order.
Civil engineering works also includes common systems (road, water and sewer, cables etc.) in connection with the development of large housing estates or industrial areas.
The stock of orders is broken down geographically in relation to an aggregation of counties in 8 regional districts:
- Oslo, Akershus and Østfold
- Hedmark and Oppland
- Telemark, Vestfold and Buskerud
- Aust- and Vest-Agder
- Rogaland
- Hordaland, Sogn og Fjordane
- Møre og Romsdal, Sør- and Nord-Trøndelag
- Nordland, Troms, Finnmark and Svalbard
Administrative information
-
Name: Construction, new orders (discontinued)
Topic: Construction, housing and property
-
Division for Business Cycle Statistics
-
Indices of new orders are only calculated on a national level. Indices for unfilled orders are broken down into 8 districts.
-
Quarterly. The statistics are published about 8 weeks after the end of the quarter.
-
Not relevant.
-
Data at the enterprise level are stored as text files on LINUX.
Background
-
The order statistics are a leading indicator for the future production. The survey measures the value of new orders received during the period concerned and the stock of orders at the end of the period in current prices. The statistics started in 1977 and a major revision was conducted in 1992. The projects residential buildings and non-residential buildings were divided in new buildings and renovations. At the same time the sample was expanded from all the establishments employing 29 persons or more to all establishments employing 20 persons or more.
-
The construction industry and the financial and economic sector analyses environment.
-
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 inthe Statistics Release Calendar. This is one of Statistics Norway’s key principles for ensuring that all users are treated equally.
-
The order statistics are a leading indicator on future production and turnover in the construction industry and is utilized for controlling purposes with corresponding information on production and turnover .
-
The Statistics Act, Sections 2-1, 2-2 and 2-3.
-
Not relevant.
Production
-
The population is all enterprises in the construction sector according to Standard Industrial Classification (SN2007):Section F: Construction except group 41.1, Development of building projects. The observation unit is enterprises, but before 2016 local Kind of Activity Unit (local KAU) data was collected.
-
Information from enterprises through a quarterly survey and data on employment from the Central Register of Establishments and Enterprises.
The sample includes all the enterprises employing 20 persons or more, about 2 200 units. These enterprises cover about 30 percent of the employment in the construction industry.
-
The data is collected by electronic survey at the end of the quarter, and the questionnaire can be filled out by Statistics Norway on Internet at Altinn, Altinn.no.
Mathematical and logical controls are incorporated in the registration procedure to verify the consistency in the values stated on the form and the correspondence with reserve values given the previous quarter. If a discrepancy is discovered, the respondent is contacted by phone or e-mail.
Indices are calculated by comparing new orders and stock of orders for enterprises included in the sample both in the basis quarter and in the statistical quarter in question. The data from the sample enterprises are not grossed up to the population. It is assumed that the development in the sample is representative to the development in the whole population.
The index is published as a value index with the year 2010 as reference period.
The calculations can be described by the following equation:
where
U t = all enterprises in the sample giving data in quarter t .
O t = the value of new orders or the value of stock of orders in quarter t.
O o = the value of new orders or the value of stock of orders in quarter o .
The sample is updated every first quarter of a year. The index figures are chained with the first quarter as new basis.
-
Seasonally adjusted series are available for stock of orders for civil engineering, construction total and residential buildings. The numbers are adjusted for seasonal variations applying the X12ARIMA method with non-fixed seasonal effects and multiplicative model. No pre-correction of trading-day or Easter effects. Trend data are computed for all series.
Read more: Seasonally adjustment
-
Not relevant.
-
The indices have been published since 1977. In its present form the indices go back to 1992. In 1992 there was a major revision of the index.
Accuracy and reliability
-
The respondent can misunderstand the questions on the form and processing errors can occur in our internal coding procedure.
The response rate at the time of publishing is normally about 97 per cent. In the case of partial non-response the missing information is obtained by phone. There is no imputation.
As a consequence of the fact that the calculation do not include a grossing up of the sample data, sampling errors may occur, if it is a correlation between what we are measuring and the sample. Enterprises with less than 20 employees could have a stronger growth in new order than the sample average. And probably it is a relation between the size of the enterprises and the type of work they carry out.
-
Not relevant.
About 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
Seasonally adjusted series
Seasonally adjusted series are available for stock of orders for civil engineering, construction total and residential buildings.
-
Data are adjusted for seasonal effects in order to be able to analyse the underlying development in data.
-
Pre-treatment routines/schemes
Running an automatic pre-treatment of the raw data based on standard options in the seasonal adjustment tools.
Calendar adjustment
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 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.
Model selection is primarily automatic, but in some cases models are selected manually.
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.
-
Choice of seasonal adjustment approach
X-12-ARIMA
Consistency between raw and seasonally adjusted data
Do not apply any constraint.
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.
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.
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.
Only part of the time series is used to estimate the correction factors and the model.
-
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.
Both raw and seasonally adjusted data are revised between two consecutive official releases of the release calendar.
Comments: Raw data are not revised.
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 entire time series is revised in the event of a re-estimation of the seasonal factors.
-
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.
-
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.
-
Data availability
Raw and seasonally adjusted data are available.
All metadata information associated with an individual time series is 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.
Both levels/indices and different forms of growth rates are presented.
For each series, some quality measures of the seasonal adjustment are presented.
-
- Dokumentasjon av sesongjustering i SSB
- The Committee for Monetary, Financial and Balance of Payments statistics: ESS-Guidelines on seasonal adjustment
- EUROSTAT: Seasonal Adjustment. Methods and Practices
- US census: X-12-ARIMA-manual
- Notat 2008/58 Nye US Census-baserte metoder for ukedageffekter for norske data
- Notat 2007/43 Ny metode for påskekorrigering for norske data
- Notat 2001/54 Sesongjustering av tidsserier, Spektralanalyse og filtrering
- Notat 2001/02 Innføring i tidsserier, Sesongjustering og X-12-ARIMA
Contact
-
Statistics Norway's Information Centre