Metadata File Name | SILC_ESQRS_A_FI_2012_0000 - Version 2 |
TimeDimension | 2012-A0 |
DataProvider | FI1 |
DataFlow | SILC_ESQRS_A |
3 Quality management - assessment | - |
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4 Relevance | - |
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4 . 1 Relevance - User Needs | - |
4 . 2 Relevance - User Satisfaction | - |
4 . 3 Completeness | - |
4 . 3 . 1 Data completeness - rate | - |
6 Timeliness and punctuality | - |
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6 . 1 Timeliness | - |
6 . 1 . 1 Time lag - first result | - |
6 . 1 . 2 Time lag - final result | - |
6 . 2 Punctuality | - |
6 . 2 . 1 Punctuality - delivery and publication | - |
7 Accessibility and clarity | - |
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7 . 1 Dissemination format - News release | - |
7 . 2 Dissemination format - Publications | - |
7 . 3 Dissemination format - online database | - |
7 . 3 . 1 Data tables - consultations | - |
7 . 4 Dissemination format - microdata access | - |
7 . 5 Documentation on methodology | - |
7 . 5 . 1 Metadata completeness - rate | - |
7 . 5 . 2 Metadata - consultations | - |
7 . 6 Quality management - documentation | - |
7 . 7 Dissemination format - other | - |
8 Comparability | According to the Regulation (EC) No 1177/2003 of the European Parliament and of the Council concerning EU-SILC: "Comparability of data between Member States shall be a fundamental objective and shall be pursued through the development of methodological studies from the outset of EU-SILC data collection, carried out in close collaboration between the Member States and Eurostat". Although the best way for keeping the comparability of data is to apply the same methods and definitions of variables, small departures of the definitions given by Eurostat are allowed in EU-SILC. In this way, the mentioned Regulation in its article 16th says: "Small departures from common definitions, such as those relating to private household definition and income reference period, shall be allowed, provided they affect comparability only marginally. The impact of comparability shall be reported in the quality reports." |
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8 . 1 Comparability - geographical | - |
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8 . 1 . 1 Asymmetry for mirror flow statistics - coefficient | - |
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8 . 1 . 2 Reference population |
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8 . 1 . 3 Reference Period |
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8 . 1 . 4 Statistical concepts and definitions | Cross and longitudinal data
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8 . 2 Comparability - over time | The income data are comparable over the survey years 2004—2012. |
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8 . 2 . 1 Length of comparable time series | - |
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8 . 3 Comparability - domain | - |
9 Coherence | The coherence of two or more statistical outputs refers to the degree to which the statistical processes, by which they were generated, used the same concepts and harmonised methods. A comparison with external sources for all income target variables and the number of persons who receive income from each ‘income component’ will be provided, where the Member States concerned consider such external data to be sufficiently reliable. |
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9 . 1 Coherence - cross domain | Information about coherence of the cross-sectional data with external data sources (incl. National Accounts) is provided in the Annex - Coherence. |
9 . 1 . 1 Coherence - sub annual and annual statistics | - |
9 . 1 . 2 Coherence - National Accounts | - |
9 . 2 Coherence - internal | - |
10 Cost and Burden | - |
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11 Confidentiality | - |
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11 . 1 Confidentiality - policy | - |
11 . 2 Confidentiality - data treatment | - |
12 Statistical processing | Detailed information concerning sampling frame, sampling design, sampling units, sampling size, weightings and mode of data collection can be found in this section. Such information is mainly used for the computation of the accuracy measures. |
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12 . 1 Source data | Description of the sampling frame
The Population Information System maintained by the Population Register Centre of Finland is the source data used for the sampling frame (see below). The Population Information System is a compilation of local registers kept up by population register districts. It covers basic data on all Finnish citizens and aliens permanently resident in Finland. Persons living in private households, institutions, persons living temporarily abroad and homeless persons are also included in the Population Information System. Because these persons do not belong to the target population, they are excluded from the sampling frame. Finland uses a unified identification code system across register sources, which means that every person residing in Finland has a unique identification code and each dwelling has a domicile code. Each person has been registered in the municipality where he/she has a permanent place of residence. The domicile code is the link between a person and his/her permanent dwelling. Persons without an address are registered in municipal registers as homeless persons. A person with a permanent address may also have a registered temporary address. A register data copy of the population information system is used as the sampling frame for the selection of the master sample, i.e. selected sample persons. Data refer to the end of the year preceding the survey year. Persons aged under 16 and persons placed in institutions and homeless people are excluded from the frame. The order of the frame is based on the domicile code indicating the location of a person's dwelling. The frame is also used for the construction of the household-dwelling units for the master sample, and for the sample stratification. After various checks and combinations (e.g. excluding collective households) household-dwelling units are compiled by adding all the persons sharing the same domicile code (occupying the same dwelling) with the selected person (target person) to the master sample. Before the interview fieldwork begins, the information for the second, third and fourth waves/replications of the EU-SILC and changes occurred for the first wave after the sample selection are updated on the basis of the register data. The master sample of household-dwelling units is used for different sampling purposes, one of them is the Finnish EU-SILC survey.
Information about the frame: reference period, updating actions, quality review actions
In general, the Population Information System of the Population Register Centre of Finland is exhaustive and up-to-date as regards persons. Information on population changes: births, deaths, migration, immigration and emigration, marriages, divorces, adoptions and changes of names are updated regularly. The Population Register Centre updates the official population figures on the 5th to 8th day of every month in all municipalities in Finland. The system is maintained by notifications of changes made by population districts authorities. The inhabitants themselves are responsible only for the notification of changes of residence. Those who move or immigrate are expected to report the new residence address to their local register office within one week of the move, specifying all the family or household members involved in the move. Those emigrating should supply a notice of the change of address in the country of entry. According to an agreement between the Nordic countries, the population register authorities of the country of entry inform the population register authorities about the country of exit. In the years when municipal elections are arranged (every 4th year), the population is corrected by around 1,000 persons, when emigrants whose emigration has been left unnoticed return notifications of voting. A reliability survey on the Population Information System is conducted yearly by means of a sample interview (CATI) survey of approximately 10,000 persons. From the EU-SILC point of view, reliability of its address information has special relevance. In the quality surveys, the final proportion of the correct addresses in the total sample has always been high, 98 to 99 per cent. The EU-SILC collects the variables PB130, PB140, PB150, PB190, PB210, PB220A and PB220B directly from the Population Information System. None of these, however, have been checked in the reliability survey. The Population Information System has no under-coverage in any population groups. Asylum seekers and refugees are not included in the resident population until their permit of residence has been processed. The small over-coverage exists as a consequence of the necessity to draw the sample in time before the reference time point of the sample households (31. Dec.). The sample data has further been updated by final register information (including tax information to be connected to the master sample in order to create the strata, for example) available after it’s selection. Various checks are conducted. At this point those who have died, moved permanently abroad or placed into an institution between the sample selection time point and the end of the year are excluded from the master sample. With this processing the frame imperfection (not describing the reference time point) is corrected in the sample. A household-dwelling unit may consist of several households, or all the dwelling occupants are not sharing in household expenses - a housekeeping unit is not a register concept – that is why the household composition is checked in the interview (referring to 31. Dec). The household members' presence vs. absence either temporarily or permanently is checked in the interview as well. Persons who recently changed a place of residence and/or household, new-borns, recently moved to institutions or died are the usual sources of non-correct register-based pre-entries in the EU-SILC questionnaire. |
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12 . 1 . 1 Sampling design and procedure |
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12 . 1 . 2 Sampling unit | The sampling unit is a person. Sample persons refer to persons selected in the household-dwelling units in the second phase of the two-phase stratified sampling (selected respondents). |
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12 . 1 . 3 Sampling rate and sampling size | Concerning the SILC instrument, three different sample size definitions can be applied: - the actual sample size which is the number of sampling units selected in the sample - the achieved sample size which is the number of observed sampling units (household or individual) with an accepted interview - the effective sample size which is defined as the achieved sample size divided by the design effect with regards to the at-risk-of poverty rate indicator
Cross-sectional data
The Finnish data provide a greater size of sample than the minimum sample required to be achieved in the EU-SILC. Because Finland uses a sample of persons, the minimum effective sample size is 5,063, and when taking account of the design effect term for the Finnish sample, deff2= 1.25 , the minimum sample to be achieved is 6,239 for the cross-sectional data. The minimum size of sample to be selected is 8,328, The figure includes non-response (overall response rate R is approximately 0.76 in the Finnish survey). In the survey year 2012, the size of the actual sample was 12,913 in the cross-sectional component. When excluding the presumed non-response (25% for the first panel, and 8.5% for the following panels), the number of respondents was expected to be 11,004. The realised number of accepted respondents was smaller, 10,307, due to higher non-response rate especially in the new rotational group. Also the non-response rate of the second rotational group (DB075=2) was relatively high in the survey year 2012. However, the minimum sample to be selected for cross-sectional data was clearly reached (6,239).
Achieved sample size according to the rotational groups (DB075) in the 2012 survey year
Information about the new sample (DB075=3) by primary strata (DB050) in the 2012 survey year
Information about the old rotationals groups' initial strata. Strata refer to the 2009-2011 survey years depending on the wave/replication.
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12 . 2 Frequency of data collection | Annually. |
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12 . 3 Data collection | Mode of data collection
A description of the mode of data collection used in your country. Please mention if you use mixed mode of data collection.
The mean interview duration
The mean interview duration per household is calculated as the sum of the duration of all household interviews plus the sum of the duration of all personal interviews, divided by the number of household questionnaires completed. Only households accepted for the database have to be considered. Average interview duration = 28.4 minutes. |
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12 . 4 Data validation | - |
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12 . 5 Data compilation | - |
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12 . 5 . 1 Weighting procedure |
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12 . 5 . 2 Estimation and imputation |
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12 . 6 Adjustment | - |
13 Comment | National questionnaire is available in Circa BC at: https://circabc.europa.eu/ Please select EU-SILC section and then select the folder called "06 National Questionnaire" in the library list.
Annexes: Coherence Data collection Estimation and imputation Item non-response rates National Questionnaire in Finnish Sampling errors Weighting procedure |
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Related metadata |
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Annexes | Description |
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Annex Sampling errors .xls | |
Annex - Item non-response rate.xls | |
Annex - Estimation and Imputation.pdf | |
Annex - Coherence.pdf | |
Annex - Data collection.pdf | |
Annex - Weighting procedure.pdf | |
Annex - National Questionnaire Finnish.pdf |
Metadata File Name | SILC_ESQRS_A_FI_2012_0000 - Version 2 |
TimeDimension | 2012-A0 |
DataProvider | FI1 |
DataFlow | SILC_ESQRS_A |
1 Contact | |
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1 . 1 Contact organisation | Statistics Finland. |
1 . 2 Contact organisation unit | Population and Social Statistics. |
1 . 3 Contact name | Marie Reijo. |
1 . 4 Contact person function | Data processing. |
1 . 5 Contact mail address | FI-00022 Statistics Finland Finland |
1 . 6 Contact email address | |
1 . 7 Contact phone number | +358-09-1734 2547 |
1 . 8 Contact fax number | - |
2 Introduction | The production of quality reports is part of the implementation of the EU-SILC instrument. In order to assess the quality of data at national level and to make a comparison among countries, the National Statistics Institutes are asked to report detailed information mainly on: the entire statistical process, sampling and non-sampling errors, and potential deviations from standard definition and concepts. This document follows the ESS standard for quality reports structure (ESQRS), which is the main report structure for reference metadata related to data quality in the European Statistical System. It is a metadata template, based on 13 main concepts, which can be used across several statistical domains with the purpose of a better harmonisation of the quality reporting requirements in the ESS. For that reason the template of this document differs from that one stated in the Commission Reg. 28/2004. Finally it is the combination of the previous intermediate and final quality reports therefore it is worth mentioning that it refers to both the cross sectional and the longitudinal data from 2013 onwards.
This document refers to Finland's cross-sectional data of the EU-SILC 2012 operation. |
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3 Quality management - assessment | - |
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4 Relevance | - |
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4 . 1 Relevance - User Needs | - |
4 . 2 Relevance - User Satisfaction | - |
4 . 3 Completeness | - |
4 . 3 . 1 Data completeness - rate | - |
5 Accuracy and reliability | The concept of accuracy refers to the precision of estimates computed from a sample rather than from the entire population. Accuracy depends on sample size, sampling design effects and structure of the population under study. In addition to that, sampling errors and non sampling errors need to be taken into account. Sampling error refers to the variability that occurs at random because of the use of a sample rather than a census and non-sampling errors are errors that occur in all phases of the data collection and production process.
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5 . 1 Accuracy - overall | In terms of precision requirements, the EU-SILC framework regulation as well the Commission Regulation on sampling and tracing rules refers respectively, to the effective sample size to be achieved and to representativeness of the sample. The effective sample size combines sample size and sampling design effect which depends on sampling design, population structure and non-response rate.
Considering the Finnish sample design described in Section 12 and data representativeness in general, it can be summarised that:
The precision requirements have been met by effective sampling design (Section 12.1.1), sampling rates and sizes (Section 12.1.3) and weighing methods of non-response corrections (Section 12.5.1). |
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5 . 2 Sampling error | EU-SILC is a complex survey involving different sampling design in different countries. In order to harmonize and make sampling errors comparable among countries, Eurostat (with the substantial methodological support of Net-SILC2) has chosen to apply the "linearization" technique coupled with the “ultimate cluster” approach for variance estimation. Linearization is a technique based on the use of linear approximation to reduce non-linear statistics to a linear form, justified by asymptotic properties of the estimator. This technique can encompass a wide variety of indicators, including EU-SILC indicators. The "ultimate cluster" approach is a simplification consisting in calculating the variance taking into account only variation among Primary Sampling Unit (PSU) totals. This method requires first stage sampling fractions to be small which is nearly always the case. This method allows a great flexibility and simplifies the calculations of variances. It can also be generalized to calculate variance of the differences of one year to another . The main hypothesis on which the calculations are based is that the "at risk of poverty" threshold is fixed. According to the characteristics and availability of data for different countries we have used different variables to specify strata and cluster information. In particular, countries have been split into four groups: 1)BE, BG, CZ, IE, EL, ES, FR, IT, LV, HU, NL, PL, PT, RO, SI, UK and HR whose sampling design could be assimilated to a two stage stratified type we used DB050 (primary strata) for strata specification and DB060 (Primary Sampling Unit) for cluster specification; 2) DE, EE, CY, LT, LU, AT, SK, FI, CH whose sampling design could be assimilated to a one stage stratified type we used DB050 for strata specification and DB030 (household ID) for cluster specification; 3) DK, MT, SE, IS, NO, whose sampling design could be assimilated to a simple random sampling, we used DB030 for cluster specification and no strata;
In case Eurostat methodology is not accepted by your country, please describe the methodology used at national level for computing the estimates.
The standard error and confidence limits estimates of the table below were computed by Eurostat's methododology (Taylor linearisation method). The Annex on sampling errors provides standard error estimates to mean income components based on analytical variance estimation methods. |
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5 . 2 . 1 Sampling error - indicators |
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5 . 3 Non-sampling error | Non-sampling errors are basically of 4 types:
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5 . 3 . 1 Coverage error | Coverage errors include over-coverage, under-coverage and misclassification:
Coverage errors of the Finnish SILC data are minor due to the exhaustive and up-to-date data source used for the sampling frame (section 12.1). |
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5 . 3 . 1 . 1 Over-coverage - rate |
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5 . 3 . 2 Measurement error |
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5 . 3 . 3 Non response error | Non-response errors are errors due to an unsuccessful attempt to obtain the desired information from an eligible unit. Two main types of non-response errors are considered: 1) Unit non-response which refers to the absence of information of the whole units (households and/or persons) selected into the sample. According the Commission Regulation 28/2004:
NRh=(1-(Ra * Rh)) * 100 Where Ra is the address contact rate defined as: Ra= Number of address successfully contacted/Number of valid addresses selected and Rh is the proportion of complete household interviews accepted for the database Rh=Number of household interviews completed and accepted for database/Number of eligible households at contacted addresses
NRp=(1-(Rp)) * 100 Where Rp is the proportion of complete personal interviews within the households accepted for the database Rp= Number of personal interview completed/Number of eligible
individuals in the households whose interviews were completed and
accepted for the database
*NRp=(1-(Ra * Rh * Rp)) * 100 For those Members States where a sample of persons rather than a sample of households (addresses) was selected, the individual non-response rates will be calculated for ‘the selected respondent’, for all individuals aged 16 years or older and for the non-selected respondent. 2) Item non-response which refers to the situation where a sample unit has been successfully enumerated, but not all the required information has been obtained. |
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5 . 3 . 3 . 1 Unit non-response - rate |
* All the formulas are defined in the Commission Regulation 28/2004, Annex II A* = Total sample; B = * New sub-sample .. = Not sample person. Finland's data. All sample persons are enumerated due to the register sampling frame (Section 12.1). Therefore, only the sample persons no longer in-scope in the survey year have been dropped from the non-response rate calculations: address contact rate = 100.0 %. |
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5 . 3 . 3 . 2 Item non-response - rate | The computation of item non-response is essential to fulfil the precision requirements concerning publication as stated in the Commission Regulation No 1982/2003. Item non-response rate is provided for the main income variables both at household and personal level.
Item non-response rates of the income components in the cross-sectional data are provided in the Annex - Item non-response rate.
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5 . 3 . 3 . 2 . 1 Item non-response rate by indicator |
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5 . 3 . 4 Processing error |
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5 . 3 . 4 . 1 Imputation - rate | - |
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5 . 3 . 4 . 2 Common units - proportion | - |
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5 . 3 . 5 Model assumption error | - |
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5 . 3 . 6 Data revision | - |
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5 . 3 . 6 . 1 Data revision - policy | - |
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5 . 3 . 6 . 2 Data revision - practice | - |
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5 . 3 . 6 . 3 Data revision - average size | - |
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5 . 3 . 7 Seasonal adjustment | - |
6 Timeliness and punctuality | - |
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6 . 1 Timeliness | - |
6 . 1 . 1 Time lag - first result | - |
6 . 1 . 2 Time lag - final result | - |
6 . 2 Punctuality | - |
6 . 2 . 1 Punctuality - delivery and publication | - |
7 Accessibility and clarity | - |
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7 . 1 Dissemination format - News release | - |
7 . 2 Dissemination format - Publications | - |
7 . 3 Dissemination format - online database | - |
7 . 3 . 1 Data tables - consultations | - |
7 . 4 Dissemination format - microdata access | - |
7 . 5 Documentation on methodology | - |
7 . 5 . 1 Metadata completeness - rate | - |
7 . 5 . 2 Metadata - consultations | - |
7 . 6 Quality management - documentation | - |
7 . 7 Dissemination format - other | - |
8 Comparability | According to the Regulation (EC) No 1177/2003 of the European Parliament and of the Council concerning EU-SILC: "Comparability of data between Member States shall be a fundamental objective and shall be pursued through the development of methodological studies from the outset of EU-SILC data collection, carried out in close collaboration between the Member States and Eurostat". Although the best way for keeping the comparability of data is to apply the same methods and definitions of variables, small departures of the definitions given by Eurostat are allowed in EU-SILC. In this way, the mentioned Regulation in its article 16th says: "Small departures from common definitions, such as those relating to private household definition and income reference period, shall be allowed, provided they affect comparability only marginally. The impact of comparability shall be reported in the quality reports." |
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8 . 1 Comparability - geographical | - |
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8 . 1 . 1 Asymmetry for mirror flow statistics - coefficient | - |
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8 . 1 . 2 Reference population |
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8 . 1 . 3 Reference Period |
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8 . 1 . 4 Statistical concepts and definitions | Cross and longitudinal data
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8 . 2 Comparability - over time | The income data are comparable over the survey years 2004—2012. |
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8 . 2 . 1 Length of comparable time series | - |
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8 . 3 Comparability - domain | - |
9 Coherence | The coherence of two or more statistical outputs refers to the degree to which the statistical processes, by which they were generated, used the same concepts and harmonised methods. A comparison with external sources for all income target variables and the number of persons who receive income from each ‘income component’ will be provided, where the Member States concerned consider such external data to be sufficiently reliable. |
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9 . 1 Coherence - cross domain | Information about coherence of the cross-sectional data with external data sources (incl. National Accounts) is provided in the Annex - Coherence. |
9 . 1 . 1 Coherence - sub annual and annual statistics | - |
9 . 1 . 2 Coherence - National Accounts | - |
9 . 2 Coherence - internal | - |
10 Cost and Burden | - |
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11 Confidentiality | - |
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11 . 1 Confidentiality - policy | - |
11 . 2 Confidentiality - data treatment | - |
12 Statistical processing | Detailed information concerning sampling frame, sampling design, sampling units, sampling size, weightings and mode of data collection can be found in this section. Such information is mainly used for the computation of the accuracy measures. |
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12 . 1 Source data | Description of the sampling frame
The Population Information System maintained by the Population Register Centre of Finland is the source data used for the sampling frame (see below). The Population Information System is a compilation of local registers kept up by population register districts. It covers basic data on all Finnish citizens and aliens permanently resident in Finland. Persons living in private households, institutions, persons living temporarily abroad and homeless persons are also included in the Population Information System. Because these persons do not belong to the target population, they are excluded from the sampling frame. Finland uses a unified identification code system across register sources, which means that every person residing in Finland has a unique identification code and each dwelling has a domicile code. Each person has been registered in the municipality where he/she has a permanent place of residence. The domicile code is the link between a person and his/her permanent dwelling. Persons without an address are registered in municipal registers as homeless persons. A person with a permanent address may also have a registered temporary address. A register data copy of the population information system is used as the sampling frame for the selection of the master sample, i.e. selected sample persons. Data refer to the end of the year preceding the survey year. Persons aged under 16 and persons placed in institutions and homeless people are excluded from the frame. The order of the frame is based on the domicile code indicating the location of a person's dwelling. The frame is also used for the construction of the household-dwelling units for the master sample, and for the sample stratification. After various checks and combinations (e.g. excluding collective households) household-dwelling units are compiled by adding all the persons sharing the same domicile code (occupying the same dwelling) with the selected person (target person) to the master sample. Before the interview fieldwork begins, the information for the second, third and fourth waves/replications of the EU-SILC and changes occurred for the first wave after the sample selection are updated on the basis of the register data. The master sample of household-dwelling units is used for different sampling purposes, one of them is the Finnish EU-SILC survey.
Information about the frame: reference period, updating actions, quality review actions
In general, the Population Information System of the Population Register Centre of Finland is exhaustive and up-to-date as regards persons. Information on population changes: births, deaths, migration, immigration and emigration, marriages, divorces, adoptions and changes of names are updated regularly. The Population Register Centre updates the official population figures on the 5th to 8th day of every month in all municipalities in Finland. The system is maintained by notifications of changes made by population districts authorities. The inhabitants themselves are responsible only for the notification of changes of residence. Those who move or immigrate are expected to report the new residence address to their local register office within one week of the move, specifying all the family or household members involved in the move. Those emigrating should supply a notice of the change of address in the country of entry. According to an agreement between the Nordic countries, the population register authorities of the country of entry inform the population register authorities about the country of exit. In the years when municipal elections are arranged (every 4th year), the population is corrected by around 1,000 persons, when emigrants whose emigration has been left unnoticed return notifications of voting. A reliability survey on the Population Information System is conducted yearly by means of a sample interview (CATI) survey of approximately 10,000 persons. From the EU-SILC point of view, reliability of its address information has special relevance. In the quality surveys, the final proportion of the correct addresses in the total sample has always been high, 98 to 99 per cent. The EU-SILC collects the variables PB130, PB140, PB150, PB190, PB210, PB220A and PB220B directly from the Population Information System. None of these, however, have been checked in the reliability survey. The Population Information System has no under-coverage in any population groups. Asylum seekers and refugees are not included in the resident population until their permit of residence has been processed. The small over-coverage exists as a consequence of the necessity to draw the sample in time before the reference time point of the sample households (31. Dec.). The sample data has further been updated by final register information (including tax information to be connected to the master sample in order to create the strata, for example) available after it’s selection. Various checks are conducted. At this point those who have died, moved permanently abroad or placed into an institution between the sample selection time point and the end of the year are excluded from the master sample. With this processing the frame imperfection (not describing the reference time point) is corrected in the sample. A household-dwelling unit may consist of several households, or all the dwelling occupants are not sharing in household expenses - a housekeeping unit is not a register concept – that is why the household composition is checked in the interview (referring to 31. Dec). The household members' presence vs. absence either temporarily or permanently is checked in the interview as well. Persons who recently changed a place of residence and/or household, new-borns, recently moved to institutions or died are the usual sources of non-correct register-based pre-entries in the EU-SILC questionnaire. |
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12 . 1 . 1 Sampling design and procedure |
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12 . 1 . 2 Sampling unit | The sampling unit is a person. Sample persons refer to persons selected in the household-dwelling units in the second phase of the two-phase stratified sampling (selected respondents). |
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12 . 1 . 3 Sampling rate and sampling size | Concerning the SILC instrument, three different sample size definitions can be applied: - the actual sample size which is the number of sampling units selected in the sample - the achieved sample size which is the number of observed sampling units (household or individual) with an accepted interview - the effective sample size which is defined as the achieved sample size divided by the design effect with regards to the at-risk-of poverty rate indicator
Cross-sectional data
The Finnish data provide a greater size of sample than the minimum sample required to be achieved in the EU-SILC. Because Finland uses a sample of persons, the minimum effective sample size is 5,063, and when taking account of the design effect term for the Finnish sample, deff2= 1.25 , the minimum sample to be achieved is 6,239 for the cross-sectional data. The minimum size of sample to be selected is 8,328, The figure includes non-response (overall response rate R is approximately 0.76 in the Finnish survey). In the survey year 2012, the size of the actual sample was 12,913 in the cross-sectional component. When excluding the presumed non-response (25% for the first panel, and 8.5% for the following panels), the number of respondents was expected to be 11,004. The realised number of accepted respondents was smaller, 10,307, due to higher non-response rate especially in the new rotational group. Also the non-response rate of the second rotational group (DB075=2) was relatively high in the survey year 2012. However, the minimum sample to be selected for cross-sectional data was clearly reached (6,239).
Achieved sample size according to the rotational groups (DB075) in the 2012 survey year
Information about the new sample (DB075=3) by primary strata (DB050) in the 2012 survey year
Information about the old rotationals groups' initial strata. Strata refer to the 2009-2011 survey years depending on the wave/replication.
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12 . 2 Frequency of data collection | Annually. |
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12 . 3 Data collection | Mode of data collection
A description of the mode of data collection used in your country. Please mention if you use mixed mode of data collection.
The mean interview duration
The mean interview duration per household is calculated as the sum of the duration of all household interviews plus the sum of the duration of all personal interviews, divided by the number of household questionnaires completed. Only households accepted for the database have to be considered. Average interview duration = 28.4 minutes. |
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12 . 4 Data validation | - |
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12 . 5 Data compilation | - |
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12 . 5 . 1 Weighting procedure |
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12 . 5 . 2 Estimation and imputation |
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12 . 6 Adjustment | - |
13 Comment | National questionnaire is available in Circa BC at: https://circabc.europa.eu/ Please select EU-SILC section and then select the folder called "06 National Questionnaire" in the library list.
Annexes: Coherence Data collection Estimation and imputation Item non-response rates National Questionnaire in Finnish Sampling errors Weighting procedure |
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Related metadata |
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Annexes | Description |
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Annex Sampling errors .xls | |
Annex - Item non-response rate.xls | |
Annex - Estimation and Imputation.pdf | |
Annex - Coherence.pdf | |
Annex - Data collection.pdf | |
Annex - Weighting procedure.pdf | |
Annex - National Questionnaire Finnish.pdf |