The German Socio-Economic Panel (SOEP) study is a wide-ranging representative longitudinal study of private households, located at the German Institute for Economic Research, DIW Berlin. Every year, there were nearly 15,000 households, and more than 25,000 persons sampled by the fieldwork organization TNS Infratest Sozialforschung. The data provide information on all household members, consisting of Germans living in the Eastern and Western German States, foreigners, and immigrants to Germany. The Panel was started in 1984. Some of the many topics include household composition, occupational biographies, employment, earnings, health and satisfaction indicators. As early as June 1990—even before the Economic, Social and Monetary Union—SOEP expanded to include the states of the former German Democratic Republic (GDR), thus seizing the rare opportunity to observe the transformation of an entire society. Also immigrant samples were added in 1994/95 and 2013/2015 to account for the changes that took place in Germany society. Two samples of refugees were introduced in 2016. Further new samples were added in 1998, 2000, 2002, 2006, 2009, 2010, 2011, and 2012. The survey is constantly being adapted and developed in response to current social developments. The international version contains 95% of all cases surveyed (see 10.5684/soep.v33i).
Title: Socio-Economic Panel (SOEP), data from 1984-2016
Collection period: 1984-2016
Publication date: 2017-11-29
Principal investigators: Jürgen Schupp, Jan Goebel, Martin Kroh, Carsten Schröder, Charlotte Bartels, Klaudia Erhardt, Alexandra Fedorets, Andreas Franken, Marco Giesselmann, Markus Grabka, Peter Krause, Hannes Kröger, Simon Kühne, Maria Metzing, Jana Nebelin, David Richter, Diana Schacht, Paul Schmelzer, Christian Schmitt, Daniel Schnitzlein, Rainer Siegers, Knut Wenzig
Data collector: Kantar Deutschland GmbH
Population: Persons living in private households in Germany
Selection method: All samples of SOEP are multi-stage random samples which are regionally clustered. The respondents (households) are selected by random-walk.
Collection mode: The interview methodology of the SOEP is based on a set of pre-tested questionnaires for households and individuals. Principally an interviewer tries to obtain face-to-face interviews with all members of a given survey household aged 16 years and over. Additionally one person (head of household) is asked to answer a household related questionnaire covering information on housing, housing costs, and different sources of income. This covers also some questions on children in the household up to 16 years of age, mainly concerning attendance at institutions (kindergarten, elementary school, etc.)
Data set information:
|Number of units||126,804|
|Number of variables||72,709 in 439 data sets|
STATA, SPSS, SAS, CSV
|Distribution format||zip file||all files|
|Stata bilingual||9d7060ce9c558bb04cb12313b3a4e301||| TXT, 19.29 KB|
|Stata German||82dd72b32c4df1537f9eea6ee5e6979e||| TXT, 19.29 KB|
|Stata English||eaac22439a6140535ff8aa38697a94b8||| TXT, 19.29 KB|
|SPSS German||39ebdcfd0ace11126be8adb5fac1e391||| TXT, 19.29 KB|
|SPSS English||bb78f99791cde312300108c1a62e2774||| TXT, 19.29 KB|
|SAS German||80ddb241799719c645b152377c69345e||| TXT, 21.53 KB|
|SAS English||94b0c9c087cdfefb02fccb7c00b45212||| TXT, 21.53 KB|
|CSV||7f59155d2e79c89cfc58ffc2831db986||| TXT, 19.29 KB|
|GGKBOU||dae7d695fc83fa783290a9b9493eb9e3||| TXT, 140 Byte|
|GGKBOU English||2d064fe8b84b42e806d231b46a8b2454||| TXT, 140 Byte|
|SAS English (teaching)||efb0256ff56c97b081e0965b0160f474|
In the process of preparations for the next wave of the IAB-BAMF-SOEP Survey of Refugees, the survey institute determined that an interviewer had not conducted interviews correctly, affecting six percent of the household interviews in the sample. These households were removed from the dataset, but are available upon request for survey methodological analysis at a guest work station at the SOEP Research Data Center. In addition to deleting these lines of all affected datasets, we also made the following modifications:
Datasets from the current BG wave contained errors in the assignment of interviewer IDs. These were corrected.
Inconsistencies between key variables on population assignment in the PPFAD and $$KIND datasets were corrected. There was an error of one year in the definition of the target population in the $$KIND datasets from 2014 to 2016. In some cases, this led to a lack of information on the year of birth in files on children:
These corrections also affect the number of cases in the file KIDLONG, which was corrected correspondingly.
3.1 Change in the $$NETTO codes in 96 cases (children) in the years 2014-2016
In the process of data checks, the $$NETTO codes in PPFAS were also compared and corrected. In survey years 2014 to 2016, some children had been incorrectly assigned the code 20 instead of 30 on the variable $$NETTO in the PPFAD dataset. This error has been corrected in v33.1 with the correction of the variable $$NETTO. The update also made it necessary to correct person weights in the affected survey years (dataset PHRF), because the determination of which individuals in interviewed households should be assigned a valid weight is based on the variable $$NETTO. The updated weight is also contained in v33.1.
In BIOAPREN, a number of missing values in the flag variables for parental (professional) education and the years of death of the parents were updated and filled in.
The algorithm for imputation of missing dates in the spells were optimized. As a result, in v33.1, the imputed variables and the variables imputed from these were changed, specifically all variables with the suffixes _imp and the variable staytime. The changes affected a total of 349 of 15,640 spells.
The variable AUSB16 (“profession requires vocational training”) from BGPGEN were updated. The correction substantially decreased the number of missings [-1].
The new data distribution (1984–2016) “SOEP v36” provides, for the most recent survey year 2016, the usual wave-specific data files BGPBRUTTO, BGP, BGPKAL, BGPGEN, BGHBRUTTO, BGH, BGHGEN, BGKIND, and BFPLUECKE as well as the updated files with a longitudinal component (PFAD files, biography files, spell data, and weighting factors). Additional new samples, datasets, or variables are listed below:
1 New Sample IAB-BAMF-SOEP Geflüchtetenstichprobe (Samples M3/M4)
With version 33 of the SOEP data, we will also be releasing the integrated data from the 2016 IAB-BAMF-SOEP Survey of Refugees in Germany as two supplementary samples to the SOEP. The samples are based on the overall population of refugees, independent of residency status, who arrived in Germany between January 1, 2013, and January 31, 2016. The samples were surveyed through additional funding from BA/IAB/BMAS in the case of M3 and from BMBF in the case of M4. Sample M4 contains a higher number of refugee families containing children and teenagers.
The German Central Registry of Foreigners (AZR) provided the data basis from which the sample was drawn. In this sample, 4,816 adults in 3,554 households were surveyed in 2016, and basic data was collected on 5,717 minors living in the same households. To conduct the survey, the questionnaire was translated into seven languages, in some cases interpreters were available. To address the specific situation of the target group, audio-assisted versions of the survey instruments were developed.
The survey is comprised of an integrated individual—life course questionnaire, a household questionnaire, and a questionnaire for interviewers. As was the case with samples M1 and M2 (IAB-SOEP Migration Surveys), participants were first asked for consent to linking their survey data with the IAB Integrated Employment Biography data. The Research Data Centre of the Federal Employment Agency at IAB will be providing the linked data to researchers as of Spring 2018.
The study design is described in detail in Martin Kroh et al. 2016. Das Studiendesign der IAB-BAMF-SOEP-Befragung von Geflüchteten. SOEP Survey Papers 365: Series C. Berlin: DIW Berlin / SOEP
1.1 Integration into SOEP and original data (BGP and BGP_REF)
The original data from the survey instruments used in Samples M3 and M4 can be found in original format in the dataset BGPREF, where the individual and the biographical questionnaires are combined. The variables are also integrated into the other standard or generated datasets:
2.1 Datasets directly based on survey instrument (like $P and $H)
$PINSTRUMENT and $HINSTRUMENT
Additional variables on occupational codes
2.2 New variables in PPFAD
Bioagel now contains information from the new questionnaire for 13- to 14-year-olds that was introduced in 2016 (v33). The questionnaire contains items on personality, leisure time activities, personal networks, educational aspirations, and family life, and is completed by the young people themselves. Many of the questions included here stem from the questionnaire for 11- to 12-year-olds introduced in 2014 (v31). For those respondents who already completed this questionnaire, we now provide longitudinal information on development in many areas such as personality and educational aspirations.
For migration biographies in the refugee samples, we created the new spell data set REFUGSPELL. The variables in MIGSPELL and REFUGSPELL are derived from different instruments and only partially overlap. The data structure allows the two data sets to be linked if desired. Detailed documentation will be provided by the biographical data documentation of the SOEP.
2.5 New variables in $PGEN
$P_RELIGION (Religious affiliation)
PICORIG[A-C]$$ (Party Identification in Country of Origin)
Current residency status
2.6. New variables in $PEQUIV
2.7 Gripstrength data for 2016
GRIPSTR update: The data on grip strength from the survey year 2016 is now included in the GRIPSTR dataset.
3.1 Variables in PPFAD
GERMBORN, CORIGIN and IMMIYEAR
MIGBACK and MIGINFO
The target population and sample size of the BIOIMMIG dataset has changed. The dataset is no longer limited to respondents who were born abroad and had non-German citizenship. In addition, cases without valid BIOIMMIG information in any wave or only with valid information on BISCGCF, are no longer included in the dataset.
3.3 Update of PWEALTH and HWEALTH
Up to now, the former FiD samples were not integrated into the data for 2012 even though these samples also received wealth questionnaires. With the current data release, these cases have now been integrated.
BIOPAREN was build new from the scratch. We excluded redundant variables and changed the variable names to English for consistency (which means that VNR is now FNR). Please see the documentation for a full list of changes and an overview of the new variable names.
With variables DEGREE$$, FIELD$$, and TRAIN[A-D]$$, discrepancies had appeared in the retrospectively reported data. The classification was improved to deal with inconsistencies in multiple answers. The conversion key for occupational information based on the ISCO-88 classification for TRAIN[A-D]$$ in KldB92 was extended from two to four digits, and the conversion key itself was revised.
In Wave BF, a major change took place in the way respondents were asked about rent, and respondents were asked to provide more detailed information on their rental expenses. It became clear from ex post analysis that the way these questions were asked was too complicated for some respondents and that it had resulted in a discontinuity in the time series. As a result, according to SOEP—as well as in the comparative statistics— the average rent had risen systematically over time, but not in 2014 or 2015. This discontinuity can be explained by the change in the questionnaire. Starting with wave BG, the questions on rent were therefore changed back to those in wave BD. In wave BG, migration samples M3 and M4 were are also part of the SOEP. Since these respondents were not asked what they paid for utilities, no rental variable was generated for this group.
1984-2016 (Wave BG)
|May 18, 2018||
1. Dataset $PGEN: Variable casmin$$
A missing parenthesis in programming led to individuals in CASMIN category 6 (“(2c_gen) general maturity certificate”) being mistakenly placed in CASMIN category 7 ("(2c_voc) vocational maturity certificate").
For wave BG, this means that of the 4,553 observations in category 7, 1,976 actually belong in category 6 and 2,577 in category 7.
This can be corrected with the existing variable in the $PGEN data. For wave BG, it can be done as follows:
2. Dataset [BE-BG]PGEN: Variable [be-bg]pbilla ("Vocational Degree Outside Germany")
The variable $$pbilla (foreign degrees – vocational education) in SOEP v33 was expanded retrospectively to include information on whether the degree had been completed. This revision failed, however, to take into account some of the information covered in certain modules. A correction can be made with the existing variables in the $PGEN data, as shown here: Statement (TXT, 2.72 KB)
3. Dataset BIOAGEL: Variable bioage
In the dataset BIOAGEL,the data type was not adjusted for the variable bioage. The variable shows which questionnaire the row of data was taken from. Since the variable bioage has included values > 99 since v33, this led to values > 99 being cut off in Stata. The cut-off values are:
4. Dataset CIRDEF: Variable rgroup
The variable rgroup divides the SOEP sample into 20 equally sized groups. It is used to select the 50% sample. Since the new samples M3 and M4 were incorrectly assigned, there are no cases from these samples in the teaching version of the SOEP data.
|January 30, 2018||Various updates forced us to distribute a new version. Please see the 'Changes in the Dataset' page for the documentation of the changes.|
Individual (PAPI) 2016: Field-de Var-de Var-en
Household (PAPI) 2016: Field-de Var-de Var-en
Biography (PAPI) 2016: Field-de Var-de Var-en
Catch-up Individual 2016: Field-de Var-de Var-en
Youth (16-17-year-olds, A-L1) 2016: Field-de Var-de Var-en
Early Youth (13-14-year-olds) 2016: Field-de
Pre-teen (11-12-year-olds) 2016: Field-de
Early Youth (13-14-year-olds) 2016: Var-de
Pre-teen (11-12-year-olds) 2016: Var-de
Early Youth (13-14-year-olds) 2016: Var-en
Pre-teen (11-12-year-olds) 2016: Var-en
Mother and Child (Newborns) 2016: Field-de Var-de Var-en
Mother and Child (2-3-year-olds) 2016: Field-de Var-de Var-en
Mother and Child (5-6-year-olds) 2016: Field-de Var-de Var-en
Parents and Child (7-8-year-olds) 2016: Field-de Var-de Var-en
Mother and Child (9-10-year-olds) 2016: Field-de Var-de Var-en
Deceased Individual 2016: Field-de Var-de Var-en
Grip Strength 2016: Field-de
Please find all sample specific questionnaires of this year and all questionnaires of previous years on this site
16) Die Vercodung der offenen Angaben zur beruflichen Tätigkeit nach der International Standard Classification of Occupations 2008 (ISCO08) - Direktvercodung - Vorgehensweise und Entscheidungsregeln bei nicht eindeutigen Angaben
Alle Dokumentationen zum Filtern finden Sie auf dieser Seite