Study: MZ 2015
Additional Programs
- Health insurance (Sampling Fraction: 1% )
- Additional information on economic activity (II) (Sampling Fraction: 1% )
Ad-hoc-module EU Labour Force Survey
Changes In Questionnaire
- New variables of the supplementary health insurance program that were last collected in 2011 are: Health insurance (EF456, F166), Health insurance: Fund type (EF457, F167), Additional benefits: Dental treatment(EF458, F168), additional benefits: Loss of earnings (EF459, F168), additional benefits: 1/2-bed room, chief physician treatment (EF460, F168), additional benefits: Daily hospital allowance (EF461, F168), additional benefits: Travel abroad12(EF462, F168), additional benefits: Other benefits (EF463, F168), additional benefits: No(EF464, F168), Additional benefits: Not specified(EF465, F168), Optional tariff: Special forms of care(EF466, F169), Optional tariff: Deductible (EF467, F169), Optional tariff: Medicines for special therapeutic directions (EF468, F169), Optional tariff: Other optional tariffs(EF469, F169), Optional tariff: No (EF470, F169), Optional tariff: Not specified (EF471, F169), Health care: Other entitlement (EF472, F170), Health insurance cover (EF473)
- New variables of the Supplementary Programme Additional information on employment (II), last collected in 2011, are: Surv. activity performed (EF172, F30), enterprise: division into divisions (EF173, F41), workplace division (EF174, F42), position in enterprise (EF175, F27), Surv. activity performed: computer use (EF176, F31)
- In variable EF172, the response category 9 (research, design, construction, design of products, plans, programs) was divided into the two response categories 9 (construction, design of products, plans, programs and processes) and 21 (research and development) in comparison to 2011.
- To record the position in the company (EF175), the answer categories of the question about the position in the occupation are asked more differentiated than in the survey years without supplementary programme.
Methodological Notes
- For easier evaluations in the longitudinal section, the following linkages of identifiers (in brackets) are included in 2015: idpers (longitudinal personal identifier (EF1, EF3, EF4, EF63)), idpersx (cross-section personal identifier (EF1, EF3, EF4, EF5b, EF12, EF63)), idhh (longitudinal household identifier (EF1, EF3, EF4)), idhhx (cross-section household identifier (EF1, EF3, EF4, EF5b, EF12)))
Changes In Typification
- A number of typifications are no longer included to simplify data preparation in 2015. The report "Einführung in die eigenständige Erstellung von Typisierungen am Beispiel des Mikrozensus Scientific Use Files 2014" (Börlin 2020) shows how these typings can be created using the data available in the data, using the example of the MZ SUF 2014.
Anonymisation
- The regional details federal state (Bundesland) and a rough classification of the community size classes (Gemeindegrößenklassen) – the latter is not shown for the small federal states Bremen and Saarland – are included in the Scientific Use File (SUF). With the help of a special code of the variable community size class, it is possible to distinguish between West and East Berlin (EF563 = 9 Berlin-East).
- The other variables in the SUF are also coarsened if necessary, so that each value in the univariate distributions comprises at least 5,000 persons from the target population.
- The values of the variable nationality are aggregated in such a way that each group of nationalities in the target population comprises at least 50,000 inhabitants. In cases where variables are coarsened, the most strongly populated category is shown in the SUF.
- The SUF is a de-facto anonymised 70% sample. Until 2011, the sampling units were households or apartments where all persons in a selected household or apartment were included in the sub-sample. From 2012 onwards, the sampling districts within a rotational quarter will be used as sampling units for the subsample. This, together with longitudinal consistent identifiers, makes it possible to generate panel data sets with the Scientific Use Files.
- For details, see “Zur Abgrenzung der Bevölkerungs- und Erwerbskonzepte" [The demarcation of the population and labour force concepts]
Year Specific Documentation
This document contains the information on this website as well as further details on the Microcensus SUF 2015.
Cross-sectional Data
Sampling Units
Districts
Achieved Sample Size
531738
Units Of Observation
- Persons (in private households and collective dwellings)
- Households
- Dwellings
Units Of Analysis
- Persons
- Living arrangements
- Families
- Households
- Dwellings
Date of Data Collection
01.01.2015 - 31.12.2015
Participation Mandatory
Yes
Interview Mode
- 65 % CAPI
- 10 % CATI
- 25 % Self-administered
Percentage Of Proxy Interviews
ca. 24 %
Design Weight: Method
- The Microcensus is a single-stage, stratified cluster sample with a uniform sampling fraction for all strata. As a rule, the sampling fraction is 1%; it applies to all sampling units (dwellings, households, persons).
- Because the selection probability of the Scientific Use File (SUF) basically remains constant at 70%, design weights can be created on the basis of the inverse of the sampling fraction of the Microcensus (1%) and the Scientific Use File (70%): w = 1 / (0.01 * 0.7).
Final Weighting: Method
- For the final weight a two-stage procedure is employed: in a first step the net sample of the successfully interviewed households is adjusted to the gross sample of all households to be interviewed (compensation). In a second step this gross sample is benchmarked to the update of the current population figures (adjustment). (The extrapolation is based on the results of the current population update, as updated by the Census in 2011.)
- The final weights of the Microcensus result from a combination of this two-stage procedure of compensation and adjustment.
- The standard extrapolation factors of the full Microcensus (EF951 and EF952) are adjusted quarterly at different regional levels. In order to achieve an even better adjustment of the SUF distributions to the published results, the SUF results were subsequently adjusted to the distributions of the weighted original data weighted with the extrapolation factors of the original data (EF951, EF952) according to gender, age groups (under 15 years, 15 to under 45 years, 45 to under 65 years, 65 years or older) and employment status (gainfully employed, inactive) within each federal state. These poststratified extrapolation factors of the SUF were then modified to be the same for all persons within a household.