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Study: MZ 1989
Additional Programs
- Additional Programs
- General and further education (Sampling Fraction: 1% )
- Characteristics of disabilities (Sampling Fraction: 0.5% )
- Working conditions, job characteristics (Sampling Fraction: 1% )
- Health (Sampling Fraction: 0.5% )
- Private and employers´ pension schemes (Sampling Fraction: 0.25% )
- Additional information on foreigners living in Germany (Sampling Fraction: 1% )
Specific Features
Year Specific Documentation
Target Sample Size
| Cross-sectional Data | |
|---|---|
| Sampling Units | Districts |
| Achieved Sample Size | 385831 |
Units
Units Of Observation
- Persons (in private households and collective dwellings)
- Households
Units Of Analysis
- Persons
- Families
- Households
Data Collection
Start Date
24-04-1989
End Date
30-04-1989
Participation Mandatory
Yes
Percentage Of Proxy Interviews
x %
Weighting
Design Weight: Target
Dwelling, Household, Persons
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). Until 2004, by contrast, variables of the supplementary and additional programmes and the European Union Labour Force Surveys (EU-LFS) were implemented using smaller sampling fractions, which sometimes varied from stratum to stratum. For example, from 1996–2004 the national average was around 0.45% but the sampling fractions at administrative-district (Regierungsbezirk) level varied (0.4 %, 0.6 %, 0.8 %, or 1 %).
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 inverses of the sampling fractions of the Microcensus (1 %) and the Scientific Use File (70 %): w = 1 / (0.01 * 0.7).
Non-response Weight: Method
In the Microcensus, as in all surveys, the sampling plan cannot be realised fully. Hence, undercoverage occurs in the form of non-response on the part of the households to be surveyed. Because households and their members are obliged by law to provide information for the Microcensus, non-response is due mainly to the fact that households could not be reached during the survey. Cases of non-response are corrected using the information that is available about the non-responding households.
Until 1989, the household size, the living situation, and the occupation of the head of the household were taken into account. Compensation for non-responding households was carried out by duplicating a surveyed household that had as similar a structure as possible.
Coverage Adjustment Weight: Method
In contrast to compensation, adjustment is carried out at person level.
Until 1989, adjustment to conform with benchmark figures from the intercensal population estimates was carried out by means of random duplication and deletion of person-level records within each administrative district (Regierungsbezirk) by sex and nationality (Germans/foreign nationals). To ensure that the sample corresponded to known population distributions, both duplications and deletions of records were carried out. Within the framework of the updating of the sample, new-construction activity covered only the status until nine months before the survey. Households who moved in in the meantime did therefore not have any chance of being covered. For this reason, duplications from the newly constructed dwellings of the previous year were carried out separately. The population living in institutions was also adjusted separately.
Final Weighting: Method
The final extrapolation factors result from the combination of the two-stage procedure of compensation and adjustment.
Until 1989, both the households duplicated or deleted in the first stage and the persons duplicated or deleted in the second stage were included.
In the Scientific Use Files from 1989 or 1991 onwards, only the final extrapolation factors are included.
For the Scientific Use Files for the years 1989 to 1995, an extrapolation factor is available only at household level. However, test analyses have shown that using the household imputation factor for analyses at person level does not lead to significantly different results than using the correct person-related extrapolation factor.
See [.pdf] (in German)