8002_om_not-searchable
/en/energi-og-industri/statistikker/osi/kvartal
8002_om
statistikk
2018-02-09T08:00:00.000Z
Energy and manufacturing;National accounts and business cycles
en
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Index of orders in manufacturing (discontinued)Q4 2017

Statistics Norway has decided to stop the publication of the Index of orders in manufacturing from the first quarter of 2018. One reason for this was that the statistic previously was a part of Eurostat's regulation for short-term statistics, but this requirement was removed from the regulation in 2012. However, indicators for new orders and stock of orders are available in Business tendency survey for manufacturing, mining and quarrying.

Content

About the statistics

Definitions

Name and topic

Name: Index of orders in manufacturing (discontinued)
Topic: Energy and manufacturing

Responsible division

Division for Business Cycle Statistics

Definitions of the main concepts and variables

Local unit (establishment) : An enterprise or part of an enterprise that is located in one particular place and can be identified geographically.

Enterprise : The smallest combination of legal units that is an organisational unit producing goods or services and that benefits from a certain degree of autonomy in decision making.

Altinn : The Reporting portal for delivery of figures electronically to Statistics Norway. 

NACE : Standard for industrial classification used by EUROSTAT. It is based on the UN's international standard for industrial classification, ISIC Rev. 3.

Standard Industrial Classification (SIC) The standard is primarily a statistical standard. It forms the basis for classifying units according to main activity in the Central Register of Establishments and Enterprises (CRE). The use of common standards is essential in enabling the comparison and analysis of statistical data at national/international level and over time. The standard is identical to NACE. However, a fifth figure (subclass) is added to the standard to create a national Norwegian level.

Imputation : An estimated value for a missing observation.

Processing level : The most detailed level of the statistics.

Seasonal adjusted figures : Time series for which calendar and seasonal effects have been removed. X12-ARIMA is used to calculate these figures.

Unadjusted figures : Raw data figures with primary information from the respondent.

Order : Order refers to a customer's request to the producer for future deliveries.

Elementary index : A formula where the estimated value of a variable is divided by the average annual value for the same variable for a previous (base) year - e.g. 2005..

Domestic : This refers to all orders from customers in Norway. The export market includes all other customers.

New orders received : The value of new orders received during the period excluding taxes. Orders from group enterprises in the same industry are not included. Packaging and transportation costs are included if they are included on the invoice.

Executed orders : The value of orders and sales of goods and services during the period - either by production or by sale from stock.

Stock of orders : The value of all orders in stock not delivered at the end of the period. The stock of orders is divided into the domestic market and the export market.

Standard classifications

The survey is classified according to the Standard Industrial Classification 2007 (SIC2007). This is a Norwegian adaptation of NACE Rev. 2. SIC2007 forms the basis for coding units according to principal activity in the Central Register of Establishments and Enterprises. The use of common standards is essential in enabling comparison and analysis of statistical data at national/international level and over time.

Administrative information

Regional level

National level only.

Frequency and timeliness

Quarterly.

International reporting

Not relevant

Microdata

Non-revised and revised micro data are stored in accordance with Statistics Norway's guidelines for storing of computer files.

Background

Background and purpose

Statistics on new orders play an important role in the system for short-term statistics that monitor the economy. The Statistics on new orders are a leading indicator for the changes in production in the short and medium term.

The survey measures in current prices the value of new orders received during the period and the stock of orders at the end of the period.

The statistics were first published in 1975. In 1996, a major revision was conducted in which the number of units was increased from around 380 to around 750 units.

As from Q1 2009, all results will refer to SIC2007 (See explanation under Definitions). The historical series have been recalculated according to this version of SIC, and results dating back to 1995 are available in the Statbank database. Historical series based on SIC2002 are still available, but they will not be updated. The survey is wholly financed by government appropriations.

Users and applications

The results are used in internal controls in other economic trend surveys. Other users include financial and analytical institutions and, to some extent, public institutions (the Ministry of Finance and Norges Bank among others).

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 08 am. Prior to this, a minimum of three months' advance notice is given inthe Statistics Release Calendar.

Coherence with other statistics

The order statistics are a leading indicator of future production and turnover in the manufacturing industry and one of several indicators that monitor the performance of the economy. The correlation with the Index of production and Statistics on turnover is utilised for control purposes.

Legal authority

The Statistics Act of 16 June 1989, §§2-1, 2-2 and 2-3.

EEA reference

Not relevant

Production

Population

The population covers all establishments except sole proprietors in the industries textiles and wearing apparel (13-14), paper and paper products (17), chemical and pharmaceutical products (20-21), basic metals (24), fabricated metal products (25), computer and electrical equipment (26-27), machinery and equipment (28), ships boats and oil platforms (301), transport equipment n.e.c (29,30(-301), repair, installation of machinery (33), see Standard Industrial Classification 2007 (SIC2007). The population is defined by the Central Register of Establishments and Enterprises, and establishment is the observation unit in the survey. (See Definitions for a complete definition of establishment and enterprise.)

Data sources and sampling

The survey uses investment data collected by questionnaires from the units included in the sample, in addition to information from the Central Register of Establishments and Enterprises.

The sample includes about 750 establishments. The sample includes all establishments with 100 employees or more, or establishments with a turnover of at least 10 per cent of the publishing level. The remaining units are drawn based on stratification and optimal allocation proportional to the size of the unit measured by the number of employees. The sample does not include establishments with ten employees or fewer.

Collection of data, editing and estimations

The survey is based on data collected by questionnaire in Altinn. More than 99 per cent of the respondents prefer to use the Internet. Contact are informed that a new period of the survey is avaliable in Altinn through a text Message.

The establishment's local office normally fills in the questionnaire, but in some cases the head office reports data for several units. Establishments that fail to report in time receive a reminder approximately 5 days after the deadline. A new deadline of seven to nine days is given, depending of which quarter, and a compulsory fine if they do not return the questionnaire within fourteen days after the new deadline.

The data are automatically checked for duplicates and errors in totals. The figures are edited on the basis of a revision programme (for example errors regarding reporting in NOK million or large deviations from previous reported figures). Where there are considerable deviations, the establishment is contacted. In case of extreme deviations, further revisions are carried out.

The sample data are inflated to population level using a ratio estimator. The ratio estimator uses turnover figures from the Manufacturing statistics, structural data as auxiliary variables.

Time series sometimes contain significant seasonal variation that makes it difficult to interpret the results from one period to another. In the survey, seasonally adjusted figures and trend figures are calculated with X12-ARIMA for the manufacturing industry.

Seasonal adjustment

For seasonal adjustment, more details are available in About seasonal adjustment

Confidentiality

Confidential micro data : According to § 2-4 of the Statistics Act , collected data are subject to secrecy and are to be kept or destroyed in a secure manner. Any use of the data must be in accordance with the rules set out by the Data Inspectorate.

Time series that are not to be published : The publication of data is subject to the provisions of § 2-6 of the Statistics Act . The main rule is that data should not be published if they can be traced back to the respondent, i.e. figures for which less than three respondents make up the foundation for a cell in the table, figures where one respondent represents more than 90 per cent of the total value or figures where two respondents represent at least 95 per cent of the total value.

Unpublished data : Revised data that are not published are subject to secrecy. This implies that they are unavailable to users without distinct approval. Such agreements only apply to internal users.

Comparability over time and space

As from January 2009, SIC2002 is replaced by SIC 2007. Users must ensure that they use results based on the same version of SIC when making comparisons over time.Historical series based on SIC2002 remain available in the Statbank database for the period 1988 to 2008. To get an overview of possible changes in industrial groupings, see the Correspondence Table SN2007, SN2002 .

Accuracy and reliability

Sources of error and uncertainty

Measurement errors are caused by the questionnaire or the respondents internal system for obtaining the data. Examples are ambiguous questions, misunderstood questions or erroneous data from the respondents. In the Statistics on new orders, errors in reported figures may originate from misunderstandings of the concept of orders or the definition of the main variables used in the survey. Unambiguous guidelines and definitions are therefore emphasised. The use of incorrect units of measurement may occur since the figures should be reported in NOK million. This type of error will become evident during the revision of the data. The introduction of Altinn has contributed to reduce such errors, as data from electronic questionnaires are loaded directly into the system.

Errors of non-response refer to errors that either occur due to missing questionnaires or blank boxes in the questionnaire.

The response rate after the deadline has expired is around 95 per cent. Critical units, i.e. units that have a considerable impact on the results on a detailed level aggregation (2-digit NACE), are contacted by mail and telephone. Calculations of the effect of missing units have been carried out, but no skewness has been encountered. Missing questionnaires are mainly imputed automatically, based on previous reported figures (cold-deck method). Large units are imputed automatically using rates of change at processing level and the reported figures from the enterprise in the previous quarter (type of hot-deck). An imputed value is not imputed in the following quarter.

Boxes that are left blank (partial non-response) are imputed manually.

Sampling errors refer to uncertainty that occur in sample surveys as opposed to full counts. The sample variance equals the expected deviation between a sample survey and a full count. In the Statistics on new orders the sample represents 15 per cent of the population that covers about 80 per cent of the turnover in the population. In order to ensure a high degree of relevance at the lowest cost possible, great effort is put into including all large units in the population in the sample.

Calculations of the sampling errors for the survey have been conducted. This is limited to an interest variable: "total new orders received". In the survey the variation coefficient according to SIC2007 is calculated to be:

  • 3rd quarter of 2014: 0,9 per cent

The given percentages represent the total.

Establishments that close down may be a source of skewness if the proportion of closing downs in the sample deviates from the population. The Statistics on new orders are mainly based on a fixed sample (panel). Periodic updates of the sample ensure that the sample is in accordance with the population.

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 are incorrectly classified. This is usually due to misleading or insufficient information at a certain time. Calculations of the size and significance of such errors have not 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 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 Christmas and Easter. However, such problems are considered greater for surveys published on a monthly basis. X12-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.

Revision

Data is revised two quarters back in time as a routine. This is due to changes in previous data and late deliveries.