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 2000 = 100 or 2005 = 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.
Domestic turnover refers to the volume of domestic taxable sales in the payment control data of the Tax Administration. In addition to domestic sales, the volume of taxable sales includes own use of (construction)services.
Growth reviews are analyses that provide information in the form of figures, tables and written descriptions about the breakdown of growth in, say, turnover, sum of wages and salaries or number of employees between enterprises. Growth reviews can be used to ascertain how much small enterprises or local enterprises only operating in their own area influence growth in their respective industry or whether the growth originates from just a few strongly expanding enterprises. The share of growing enterprises of all enterprises in the industry can be examined with growth reviews.
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.
The index of turnover of construction companies describes development in the turnover of enterprises liable to value added tax in the construction industry. Sub-indices of turnover are calculated for building construction and civil engineering within the index. The examined variable is domestic turnover.
The breakdown into building construction and civil engineering is based on the handbook Standard Industrial Classification 1995 (Handbooks 4, Statistics Finland). The base year of the index is 1995 (1995 = 100).
The index is calculated using data from the Tax Administration which are supplemented at Statistics Finland. The data used in calculating the index of turnover of construction companies are exclusive of value added tax.
The index point figure is produced with the panel method. The panel includes all enterprises for which comparable data are available for the examined month and for the corresponding month of the previous year. A change percentage is calculated for the industry from the data on these enterprises. The index series is continued with this figure. Enterprises whose development deviates significantly from the industry's general development are left out of the calculation.
The index series starts from January 1995. Apart from the original index series, a seasonally adjusted series and a trend series are also calculated. The brevity of the time series makes calculation of the trend series difficult. For this reason an examination of the trend series should be accompanied by studying the behaviour of the original series.
Monthly business indicators are index-format indicators describing turnover, exports, sum of wages and salaries and number of employees that are produced monthly and by industry, and are intended to help in the monitoring of business trends. Production of the indicators was started based on the EU regulation concerning short-term business statistics. Monthly Business Indicators is also the name of the unit responsible for producing them at Statistics Finland's Business Structures department.
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.
The Tax Administration's periodic tax return data contain monthly and quarterly information concerning the payment of employer contributions and in respect of the payment of value added tax also yearly data. The observation unit is an enterprise. The periodic tax return data cover all enterprises and employers paying wages which the tax account reform concerns, in other words, almost the entire entrepreneurial activity in Finland. Starting from 2010, the periodic tax return data containing information about payments of value added tax and employer contributions are used in the calculation of the index.
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.
The sales inquiry covers around 2,000 most important enterprises in their respective industries from which data on turnover are collected monthly. In addition, data on the sum of wages and salaries are inquired from around 30 enterprises divided into kind-of-activity units, because these are not available from other sources.
The inquiry does not extend to enterprises operating in financing, the public sector, education or health and social care, because turnover data are not produced for them. The inclusion criterion is the size of the enterprise's turnover relative to the turnover of the respective industry.
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.
A seasonally adjusted series is obtained when the effect of seasonal variation is eliminated from the original time series. The figures of a seasonally adjusted series are mutually comparable and thus it is meaningful to compare two successive observations. A seasonally adjusted series can be used for detecting short-term developments and significant turns of economic cycles.
Tailored trend indicators is a charged information service providing fast data by area on e.g. turnover, exports, wages and salaries or numbers of employees. Additional growth reviews can be produced to elaborate on the factors behind development trends. The data on development in business trends can be supplied to the customers monthly, quarterly or annually as agreed.
Adjustments for trading days take into account different distributions of weekdays and public holidays in the compared months. Trading days could put the sales of an industry above normal in a certain month if the month concerned contains a higher than usual number of Fridays. In other words, the aim in making adjustments for trading days is to remove calendar effects in order to make the index figures for the corresponding months of different years as comparable as possible. However, adjustments for trading days do not remove the effects of monthly seasonal variation.
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.
Turnover refers to the information concerning sales obtained from the Tax Administration's periodic tax return data (total data) and from Statistics Finland's sales inquiry conducted among the 2,000 largest enterprises within their respective industries. In the periodic tax return data, turnover may also include profit and loss statement items external to turnover, such as sales of fixed assets, other income, extraordinary items, purchases inversely liable to tax, own use of products and agency sales. The largest items deviating in profit and loss account from turnover are adjusted in the calculation. The concept of turnover in Statistics Finland's sales inquiry is fairly close to the concept of turnover in the profit and loss statement. Turnover comprises both domestic and export turnover. Turnover is exclusive of value-added tax.
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.
A volume index describes volume change. It is obtained when price change is removed from a value index by means of a price index (deflation), in other words a value index is divided by price index and the obtained quotient is multiplied by one hundred. A volume index can also be produced direct from volume data without deflation with a price index.