Basic data of the statistics
The statistics on new orders in manufacturing describe development in new orders of enterprises for those commodities and services that are produced by establishments located in Finland. The task of the index of new orders in manufacturing is to provide rapid and reliable information about the development of new orders. In addition, the compiled statistics indicate how production and turnover are likely to change in future.
The statistics on new orders in manufacturing are based on a judicious sample. The population comprises industrial establishments and enterprises engaged in manufacturing activities in Finland belonging to the industries included in the statistics.
The statistical unit of the statistics on new orders in manufacturing is an enterprise or a kind-of-activity unit.
Unit of measure
The data on the statistics on new orders in manufacturing are published as index point figures. Change percentages are also calculated based on the indices.
The base year of the time series is 2015 (2015=100).
The reference period for the index of new orders in manufacturing is month. The statistics are published at a lag of 40 days from the end of the statistical reference month.
The index of new orders in manufacturing is published on the level of the whole country. Only such items whose production has been planned to take place in Finland are recorded in new orders in manufacturing.
In the statistics on new orders in manufacturing, manufacturing covers 2-digit industries belonging to section C Manufacturing in the Standard Industrial Classification TOL 2008: 17, 20, 21, 24, 25, 26, 27, 28, 29, 30. The data of the index of new orders in manufacturing are published as industry-specific index series. In addition to the aggregate level Manufacturing (new orders), the published index series are the manufacture of pulp, paper and paper products (17), the chemical industry (20-21) and the metal industry (24-30).
Monthly data on the statistics on new orders in manufacturing are available on the web pages starting from January 2005.
Frequency of dissemination
The data of the statistics are published monthly on Statistics Finland's website.
Seasonal adjustment means the estimation of seasonal variation and the elimination of its impact from a time series. The obtained result is a seasonally adjusted time series. The trend of a time series is obtained when both seasonal variation and irregular random variation are eliminated from a time series. Trading or working day adjusted series are in turn obtained when the factors caused by the variation in the number of trading days or weekdays is eliminated from the observation of the original time series. The Tramo/Seats method is used for the seasonal adjustment of time series at Statistics Finland. In the Tramo/Seats method, preadjustment is based on a regression model (which allows for outlying observations, public holidays and the weekday structure) and the seasonal adjustment proper on an ARIMA model constructed for the time series.
Annual change is the relative change of the index in comparison with the corresponding time period one year ago (e.g. annual change of total index of consumer prices, i.e. inflation).
Base year refers to the base point in time of a time series. Normally, years divisible evenly by five are used as base years. In releases base year is noted, for example, as 2010 = 100 or 2015 = 100. The mean of the index point figures of a base year is 100. For example, in monthly indices the the index point figures of the months of the base year disclose the distribution of an examined variable between different months.
An order is cancelled, when the producer of a commodity or service considers that a previously made agreement is no longer in force. Cancelled orders are not taken into account ex post in the calculation of the index of new orders.
The value of commodities and services delivered during one month.
An index is a ratio describing the relative change in a variable (e.g. price, volume or value) compared to a certain base period (e.g. one year). The index point figure for each point in time tells what percentage the given examined variable is of its respective value or volume at the base point in time. The mean of the index point figures for the base period is 100.
A value index for the commodities and services that are meant to be produced by establishments located in Finland and are either delivered to Finland or exported.
New domestic orders in manufacturing describe the value of new domestic orders manufacturing enterprises have received during a reference month. Received new orders are regarded as indicative of future output and domestic turnover.
New export orders describe the value of new orders received by manufacturing enterprises from export countries during the month. Received new orders are regarded as indicative of future production, turnover and exports.
New orders in manufacturing describe the value of new orders manufacturing enterprises have receive during a month. Received new orders are regarded as indicators of future production and turnover.
An agreement by which the producer commits to delivering in the future to the customer the agreed commodities or services for the price specified in the agreement.
An order stock is the value of undelivered orders of enterprises at the end of the month.
An index series from which the effects of factors not related to production have not been removed. Non-productional factors include variations in the number of working days per month and fluctuations in production caused by seasonal variation.
Panel calculation refers to a calculation method that is used to produce certain statistics on economic trends. If there is not enough source data for the latest examined time periods, as a rule the statistical units with comparative data for both the examined month and the corresponding month of the previous year are taken into account in the calculation. Data on this population, or panel, are used to calculate the change with which an index can be calculated for the examined point in time from the index of the corresponding point in time in the year before.
Revision means added accuracy of data. The accuracy of data can increase due to changes in the data that are used in calculations or to the availability of new data.
Seasonal variation is variation in a time series within one year that is repeated more or less regularly. Seasonal variation may be caused by the temperature, rainfall, public holidays, cycles of seasons or holidays.
Trend describes the long-term development in a time series. A trend series has been adjusted for seasonal and random variations, so that the effects of e.g. weather conditions or short-term labour disputes do not show in it. By contrast, permanent changes, such as growth in demand due to changed taxation, will show in a trend. The direction indicated by the end of a trend should be interpreted with caution. The latter part of a trend indicator may change once it has been updated with data for subsequent months.
A value index is a measure (ratio) that describes change in a nominal value relative to its value in the base year. The index point figure for each point in time tells what percentage a given value is at that point in time of its respective value at the base point in time. Thus, in monthly statistics the value index point figure for an examined month describes the percentage share of the value of that month of the average monthly value for the base year.
Accuracy, reliability and timeliness
The data on the statistics on new orders in manufacturing become revised in later releases. The main reasons for data revisions are supplementations or corrections to the data retrospectively and updating of the weight structure. In addition, seasonally adjusted series and trend series may change even if no changes took place in the original series. The models used in seasonal adjustment are updated once a year, when revisions can be larger than usual.
The data on the statistics on new orders in manufacturing are published at a lag of 40 days.
The data are published on the days indicated in the release calendar.
Comparability - over time
The statistics on new orders in manufacturing have been produced monthly since 2005. Efforts have been made to make the data as temporally comparable as possible. However, changes have taken place over time in the calculation method of the statistics and the source data used, so the data cannot be considered fully comparable over time.
Coherence - cross domain
Business statistics produced by Statistics Finland can be divided into structural statistics and business trend statistics. The differences in the statistics are caused by their length of the description period, publication delay and the extent of the data content so that the description period and release delay of business trend statistics are shorter and their data content more limited than in the structural statistics. Structural business statistics include structural business and financial statement statistics that describe the structure and activities of enterprises on the annual level. Business trend statistics include monthly trend indicators. Annual statistics are cross-sectional data on business activities in the year in question. By contrast, business trend data have been made temporally comparable as concerns enterprise reorganisations and industry transfers so that the indicators describe changes in each industry.
Coherence - sub-annual and annual statistics
Only monthly data are published on the index of new orders in manufacturing.
Coherence - internal
The statistics on new orders in manufacturing belong to statistics on economic trends that describe short-term development in various factors and areas of the economy. The data of the statistics cannot be fully compared with other indicators of output in manufacturing because the industry coverage is different.
There are also differences in the calculation methods of the indices. The over-the-year method is used in the calculation of the index of new orders in manufacturing, where each month is compared with the corresponding month of the previous year. The annual overlap method is used in the calculation of the volume index of industrial output, where each month is compared to the previous year's average.
Source data and data collections
The enterprises included in the sample are asked monthly about the value of new orders in Statistics Finland's own data collection.
Data for Statistics Finland's own data collection are gathered with a web questionnaire. The web questionnaire of the index of new orders in manufacturing has been tested in connection with its introduction and when changes have been made to it. In addition, the non-response rate of the inquiry is monitored monthly.
Frequency of data collection
The data of the index of new orders in manufacturing are collected monthly.
The calculation is based on estimation of change. Sums by industry are calculated at the 2-digit level with data on the enterprises for which comparable data are available for both the examined month and the corresponding month of the previous year. The obtained sums are used to calculate annual changes by industry. These annual changes are used to raise the index of new orders for the corresponding month of the year before. The calculation of annual changes also allows for enterprise reorganisations and for changes of industries. Indices for aggregated levels of the classification are obtained by weighting the indices at the 2-digit level of the industrial classification. Estimates of the values of the entire population’s new orders at the 2-digit level are used as weights.
The data are checked at the enterprise level by examining the values of new orders for all enterprises included in the sample for the month to be calculated. The value of the enterprise's calculated month is compared with the previous values of the time series. In addition, all enterprise reorganisations and enterprise closures are examined. The data are also compared with the data of other statistics in the statistical description area, such as the index of turnover in industry and the volume index of industrial output. Erroneous data detected in the data are corrected or their impact is eliminated.
Seasonal adjustment is a statistical method used to process time series. The method is used to remove variation occurring fairly regularly within a year from the data. The Tramo/Seats method and JDemetra+ software are used in the statistics. In addition, seasonal adjustment is based on the ESS Guidelines on Seasonal Adjustment.
Further information: Seasonal adjustment
on Statistics Finland's home page.
Principles and outlines
Contact organisation unit
Legal acts and other agreements
The compilation of statistics is guided by the Statistics Act. The Statistics Act contains provisions on collection of data, processing of data and the obligation to provide data. Besides the Statistics Act, the Data Protection Act and the Act on the Openness of Government Activities are applied to processing of data when producing statistics.
Statistics Finland compiles statistics in line with the EU’s regulations applicable to statistics, which steer the statistical agencies of all EU Member States.
Further information: Statistical legislation
The statistics on new orders in manufacturing are one of the so-called sensitive statistics whose data can be treated before publication only by persons separately named by virtue of the Act on the Openness of Government Activities (Section 24, Paragraph 1, Sub-paragraph 13). The results are not released to users before the official date of publication of the statistics.
Confidentiality - policy
The data protection of data collected for statistical purposes is guaranteed in accordance with the requirements of the Statistics Act (280/2004), the Act on the Openness of Government Activities (621/1999), the EU's General Data Protection Regulation (EU) 2016/679 and the Data Protection Act (1050/2018). The data materials are protected at all stages of processing with the necessary physical and technical solutions. Statistics Finland has compiled detailed directions and instructions for confidential processing of the data. Employees have access only to the data essential for their duties. The premises where unit-level data are processed are not accessible to outsiders. Members of the personnel have signed a pledge of secrecy upon entering the service. Violation of data protection is punishable.
Further information: Data protection | Statistics Finland (stat.fi)
Confidentiality - data treatment
The publication of the statistics on new orders in manufacturing does not include unit-level data. Industries 20, 21, 24, 25, 26, 27, 28, 29 and 30 are not published separately because they contain dominant enterprises. They are published as combined industries and they are included in the figures for the aggregate level 17, 20-21, 24-30 Manufacturing (new orders).
Statistics Finland publishes new statistical data at 8 am on weekdays in its web service. The release times of statistics are given in advance in the release calendar available in the web service. The data are public after they have been updated in the web service.
Further information: Publication principles for statistics at Statistics Finland
Accessibility and clarity
Statistical data are published as database tables in the StatFin database. The database is the primary publishing site of data, and new data are updated first there. When releasing statistical data, existing database tables can be updated with new data or completely new database tables can be published.
In addition to statistical data published in the StatFin database, a release on the key data is usually published in the web service. If the release contains data concerning several reference periods (e.g. monthly and annual data), a review bringing together these data is published in the web service. Database tables updated at the time of publication are listed both in the release and in the review. In some cases, statistical data can also be published as mere database releases in the StatFin database. No release or review is published in connection with these database releases.
Releases and database tables are published in three languages, in Finnish, Swedish and English. The language versions of releases may have more limited content than in Finnish.
Information about changes in the publication schedules of releases and database tables and about corrections are given as change releases in the web service.
Unit-level data of the statistics are used only for producing the statistics and others than producers of statistics do not have access to them.
Data revision - policy
Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions.
The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before.
Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data.
Seasonally adjusted data in statistics on economic trends become revised because of the calculation method used. Additional information on a new time series observation is exploited in model-based calculation methods and this is reflected as changes in previous releases. Revisions of the latest figures to be seasonally adjusted are elaborated on in the releases and quality reports of statistics.
A summary table of the revisions that have taken place is also published in connection with key statistics on economic trends and some annual statistics. The table shows how the data for the statistical reference periods have changed between the first and the most recent statistical release.
The data of the statistics are used to monitor and analyse the development of business services. Public administrations, business and research institutes use the data to assess the development of markets and competitors.
The quality of the statistics on new orders in manufacturing is evaluated in several different stages of the statistical process. Revisions to the unit-level data of the statistics are examined monthly and coherence analyses are made with other statistics on economic trends.
Quality management requires comprehensive guidance of activities. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The frameworks complement each other. The quality criteria of Official Statistics of Finland are also compatible with the European Statistics Code of Practice.
Further information: Quality management | Statistics Finland (stat.fi)
Data are released to all users at the same time. Statistical data may only be handled at Statistics Finland and information on them may be given before release only by persons involved in the production of the statistics concerned or who need the data of the statistics concerned in their own work before the data are published.
Further information: Publication principles for statistics