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SOEP-Core v33 (data 1984-2016)

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).

Dataset Information

Title: Socio-Economic Panel (SOEP), data from 1984-2016

DOI: 10.5684/soep.v33
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
 Data format


MD5 fingerprints

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
Teaching versions
Stata German 31e17d165176b7f737ee8c590b1ce5fc
Stata English 7987938078f2b1f6114bd176a801070a
SPSS German 2a5bf6b3d7806110e9833876c9e7c853
SPSS English 33cde96691542e040976ffa1622d127d
SAS German 80e46b7f6e1070ef7068edac369e6d56
SAS English (teaching) efb0256ff56c97b081e0965b0160f474



  • Gert G. Wagner, Joachim R. Frick, and Jürgen Schupp (2007) The German Socio-Economic Panel Study (SOEP) - Scope, Evolution and Enhancements, Schmollers Jahrbuch (Journal of Applied Social Science Studies), 127 (1), 139-169 (download).
  • Schupp, Jürgen (2009): 25 Jahre Sozio-oekonomisches Panel - Ein Infrastrukturprojekt der empirischen Sozial- und Wirtschaftsforschung in Deutschland, Zeitschrift für Soziologie 38 (5),  350-357 (download).
  • Gert G. Wagner, Jan Göbel, Peter Krause, Rainer Pischner, and Ingo Sieber (2008) Das Sozio-oekonomische Panel (SOEP): Multidisziplinäres Haushaltspanel und Kohortenstudie für Deutschland - Eine Einführung (für neue Datennutzer) mit einem Ausblick (für erfahrene Anwender), AStA Wirtschafts- und Sozialstatistisches Archiv 2 (4), 301-328 (download).

Publications using this file should refer to the above DOI infoFind an explanation on the usage of DOI here.and cite following references

  • Goebel, Jan, Markus M. Grabka, Stefan Liebig, Martin Kroh, David Richter, Carsten Schröder, and Jürgen Schupp. 2019. The German Socio-Economic Panel (SOEP). Jahrbücher für Nationalökonomie und Statistik (Journal of Economics and Statistics) 239 (2), 345-360. (

If you do not exclude the cases of the migration samples in your analysis, then please also cite the following reference

  • Herbert Brücker, Martin Kroh, Simone Bartsch, Jan Goebel, Simon Kühne, Elisabeth Liebau, Parvati Trübswetter, Ingrid Tucci & Jürgen Schupp (2014): The new IAB-SOEP Migration Sample: an introduction into the methodology and the contents. SOEP Survey Paper 216 (PDF, 444.25 KB), Series C. Berlin, Nürnberg: DIW Berlin.

If you do not exclude the cases of the refugee samples in your analysis, please also cite: IAB-BAMF-SOEP survey of refugees (M3-M5), data for the years 2016-2021,

  • Herbert Brücker, Nina Rother, Jürgen Schupp. 2017. IAB-BAMF-SOEP Befragung von Geflüchteten 2016. Studiendesign, Feldergebnisse sowie Analysen zu schulischer wie beruflicher Qualifikation, Sprachkenntnissen sowie kognitiven Potenzialen. IAB Forschungsbericht 13/2017.

If you use data from the SOEP-LEE2 surveys, please also cite:

  • Matiaske, W., Schmidt, T. D., Halbmeier, C., Maas, M., Holtmann, D., Schröder, C., Böhm, T., Liebig, S., and Kritikos, A. S. (2023). SOEP-LEE2 : Linking Surveys on Employees to Employers in Germany. Journal of Economics and Statistics Data Observer, 1–14.

If you would like to refer more specifically, please also cite:

  • Schröder, Carsten, Johannes König, Alexandra Fedorets, Jan Goebel, Markus M. Grabka, Holger Lüthen, Maria Metzing, Felicitas Schikora, and Stefan Liebig. 2020. The economic research potentials of the German Socio-Economic Panel study. German Economic Review 21 (3), 335-371. (
  • Giesselmann, Marco, Sandra Bohmann, Jan Goebel, Peter Krause, Elisabeth Liebau, David Richter, Diana Schacht, Carsten Schröder, Jürgen Schupp, and Stefan Liebig. 2019. The Individual in Context(s): Research Potentials of the Socio-Economic Panel Study (SOEP) in Sociology. European Sociological Review 35 (5), 738-755. (
  • Jacobsen, Jannes, Magdalena Krieger, Felicitas Schikora, and Jürgen Schupp. 2021. Growing Potentials for Migration Research using the German Socio-Economic Panel Study. Jahrbücher für Nationalökonomie und Statistik 241 (4), 527-549. (
  • Fedorets, Alexandra, Stefan Kirchner, Jule Adriaans, and Oliver Giering. 2022. Data on Digital Transformation in the German Socio-Economic Panel. Jahrbücher für Nationalökonomie und Statistik 242 (5-6), 691-705. (

For the SOEP data 1984-2016 (v33) -- Wave A - BG -- we provide the following versions:


soep.v33.1i (International Scientific Use Version, 95%)


soep.v33i (International Scientific Use Version, 95%)

SOEP-Core soep.v33.1

1 Deletion of incorrectly conducted interviews in the IAB-BAMF-SOEP Survey of Refugees

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:

  • Due to the deletion of household and individual interviews, the weights had to be updated (dataset HHRF and PHRF) to take the slightly reduced number of cases in the 2016 survey year into account.
  • The new weights were updated or included in the dataset BGPEQUIV.
  • Imputation of monthly household net income (I[1-5]HINC16) was redone for this sample in BGHGEN and in the dataset MIHINC.

2 Update INTID in BG files

Datasets from the current BG wave contained errors in the assignment of interviewer IDs. These were corrected.

3 Corrected number of entries in `$$KIND' (2014-2016)

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:

    • bekgjahr: 1998 for all samples
    • bfkgjahr: 1999 for all samples
    • bgkgjahr: 1999 only for samples M3 and M4 in 2016

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.

6 Update AUSB16 in BGPGEN

The variable AUSB16 (“profession requires vocational training”) from BGPGEN were updated. The correction substantially decreased the number of missings [-1].

SOEP-Core soep.v33

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:

  • Variables equivalent to those in the individual questionnaire in other samples are included in the dataset BGP. Also included in BGP are all variables which will be asked more than once, but specific to the refugee questionnaire.
  • Variables equivalent to those in the biographical questionnaires in other samples are included in the respective biographical datasets (e.g., BIOMARSM).
  • The comprehensively surveyed migration biography can be found in the new dataset REFUGSPELL.

2 New datasets / variables

2.1 Datasets directly based on survey instrument (like $P and $H)


        With the integration of the new migration samples since 2013, the $P and $H datasets include data from more survey instrument. The basis remains the paper version of the questionnaire from samples A-L1, but it is supplemented by data from sample-specific survey instruments. To make it easy for users to understand, there is now a variable in $H and $P identifying the particular instrument from all waves starting with BD (2013).

Additional variables on occupational codes

      There are now many more variables containing coded occupational information in the different questionnaire-specific datasets ($P, $JUGEND, $LUECKE, also $P_MIG and $P_REFUGEES). The variables can be identified by the suffixes denoting the classification used. ISCO-88 and KldB92 are available for all occupations: older $P-files contain ISCO-68, newer files contain ISCO-08 and KldB2010. 


    Since 2000 (wave Q), first-time respondents between the ages of 16 and 17 have received a separate biographical questionnaire with additional age-group-specific questions, for instance, about their relationship to their parents or about what they do in their free time. Up to now, only some of the data collected from this survey have been processed and provided to users in dataset BIOAGE17. Starting with the current data release, the complete data will be provided in individual $JUGEND datasets.

2.2 New variables in PPFAD


      The variable SEXOR combines information on the sexual orientation of respondents from various sources in the SOEP. In 2016 (wave BG), for the first time, the SOEP included a direct question about sexual orientation (self-reported).


    This variable tells which federal state the respondent was born in for respondents who were interviewed after 2012 and who reside in Germany’s current federal states. Data users interested in obtaining more specific information on place of birth at the level of the municipality can access this data on a guest visit to the SOEP Data Research Center (contact for details). 


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)

      An integrated version of religious affiliation variable for all respondents in 2016 since additional differentiations were used to survey the migration samples.

PICORIG[A-C]$$ (Party Identification in Country of Origin)

    • PICORIGA16 - Party Identification in Country of Origin
    • PICORIGB16 - Party Identified with in Country of Origin
    • PICORIGC16 - Party Family of PI in Country of Origin


Current residency status

    This variable will be a harmonized version of the current residency status variable for all immigrants in the corresponding samples including the new refugees sample.


2.6. New variables in $PEQUIV

  • KIDY$$ Income of Children in Household
  • FKIDY$$ Imputation Flag for Income of Children in Household
  • IWITH$$ Profit Withdrawal
  • FWITH$$ Imputation Flag for Profit Withdrawal

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. Revisions and bug fixes

3.1 Variables in PPFAD


    Information on the country of birth (GERMBORN, CORIGIN) and the year of immigration (IMMIYEAR) is no longer compared with and coded according to the previous year’s information in PPFAD. Instead, all information available on a respondent in the SOEP is collected and compared to code these variables. Efforts have been made (1) to give information on all respondents, dramatically reducing the number of missing values, and (2) to avoid group categories for the country of birth such as Eastern Europe (now, e.g., Poland). Three new variables, GERMBORNINFO, CORIGININFO, and IMMIYEARINFO, are introduced in v33 to indicate the quality of information given in GERMBORN, CORIGIN, and IMMIYEAR.



    The changes in GERMBORN also influence MIGBACK and MIGINFO, resulting in some value changes and a stronger focus of miginfo on the availability of parental information.



    Different proxies were used to code the respondents' place of residence in 1989 (variable LOC1989), resulting in some value changes. A new variable, LOCINFO, has been introduced in v33 to indicate the quality of the information in LOC1989.


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.

3.5 $PGEN

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.

3.6 $HGEN

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:

replace casmin16= 6 if  inlist (bgpsbil,3,4) |  bgpsbila==3 |  bgpsbilo==3   

replace casmin16= 7  if (inlist (bgpsbil,3,4) |  bgpsbila==3 |  bgpsbilo==3)  & (inlist (bgpbbila,2,3,5,6,8) | (bgpbbil01>=1 & bgpbbil01<.) | (bgpbbilo>=1 & bgpbbilo<.))

replace casmin16= 8 if inlist (bgpbbil02,1,4)                                    

replace casmin16= 9 if inlist (bgpbbil02,2,3,5,6,7,8) | inlist (bgpbbila,4,7,9)

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)

Dataset Variabel Variable Label
bepgen bepbbila Vocational Degree Outside Germany
bfpgen bfpbbila Vocational Degree Outside Germany
bgpgen bgpbbila Vocational Degree Outside Germany

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:

Variable Value Label
bioage 101 “bioage10a”
bioage 102 “bioage10b(only FID)”

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 Field-en Var-de Var-en
Household (PAPI) 2016: Field-de Field-en 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

1) Documentation on ISCED Generation Using the CAMCES Tool in the IAB-SOEP Migration Samples M1/M2

2) Sampling, Nonresponse, and Integrated Weighting of the 2016 IAB-BAMF-SOEP Survey of Refugees (M3/M4) – revised version

3) SOEP-Core – Documentation of Sample Sizes and Panel Attrition (1984 until 2016)

4) SOEP-Core v33.1 – Biographical Information in the Meta File PPFAD (Month of Birth, Year of Death, Immigration Variables, Living in East or West Germany in 1989)

5) SOEP-Core v33.1 – PPFAD

6) SOEP-Core v33.1 – Documentation of the Household-related Meta-dataset HPFAD

7) SOEP-Core v33.1 – $PBRUTTO

8) SOEP-Core v33.1 – $HBRUTTO

9) SOEP-Core v33.1 – Documentation of Person-related Status and Generated Variables in $PGEN

10) SOEP-Core v33.1 – Documentation of Household-related Status and Generated Variables in $HGEN

11) SOEP 2016 – Codebook for the $PEQUIV File 1984-2016: CNEF Variables with Extended Income Information for the SOEP

12) SOEP-Core v33.1 – BIOIMMIG: Generated Variables for Foreign Nationals, Immigrants, and Their Descendants in the SOEP

13) SOEP-Core v33.1 – HEALTH

14) SOEP-Core v33.1 – BIOPAREN: Biography Information for the Parents of SOEP-Respondents

15) SOEP-Core v33.1 – BIOAGEL: Generated Variables from the “Mother & Child”, “Parent”, and “Pupils” Questionnaires

16) SOEP-Core v33.1 – BIOSIB: Information on Siblings in the SOEP

17) SOEP-Core v33.1 – The Couple History Files BIOCOUPLM and BIOCOUPLY, and Marital History Files BIOMARSM and BIOMARSY

18) SOEP-Core v33.1 – BIOAGE17: The Youth Questionnaire

19) SOEP-Core v33.1 – BIOSOC: Retrospective Data on Youth and Socialization

20) SOEP-Core v33.1 – BIOJOB: Detailed Information on First and Last Job

21) SOEP-Core v33.1 – BIOEDU: Data on Educational Participation and Transitions

22) SOEP-Core v33.1 – BIORESID: Variables on Occupancy and Second Residence

23) SOEP-Core v33.1 – BIOBIRTH: A Data Set on the Birth Biography of Male and Female Respondents

24) SOEP-Core v33.1 – BIOTWIN: TWINS in the SOEP

25) SOEP-Core v33 – INTERVIEWER: Detailed Information on SOEP Interviewers

26) SOEP-Core v33.1 – LIFESPELL: Information on the Pre- and Post-Survey History of SOEP-Respondents

27) SOEP-Core v33.1 – MIGSPELL and REFUGSPELL: The Migration-Biographies of Samples M1/M2 and M3/M4

28) SOEP-Core v33.1 – Activity Biography in the Files PBIOSPE and ARTKALEN

1) Handgreifkraftmessung im Sozio-oekonomischen Panel (SOEP) 2006 und 2008

2) The new IAB-SOEP Migration Sample: an introduction into the methodology and the contents

3) The Request for Record Linkage in the IAB-SOEP Migration Sample

4) Flowcharts for the Integrated Individual-Biography Questionnaire of the IAB-SOEP Migration Sample 2013

5) The Measurement of Labor Market Entries with SOEP Data: Introduction to the Variable EINSTIEG_ARTK

6) Job submission instructions for the SOEPremote System at DIW Berlin – Update 2014

7) SOEP 2015 – Informationen zu den SOEP-Geocodes in SOEP v32

8) Editing and Multiple Imputation of Item Non-response in the Wealth Module of the German Socio-Economic Panel

9) Die Vercodung der offenen Angaben zu den Ausbildungsberufen im Sozio-Oekonomischen Panel

10) Das Studiendesign der IAB-BAMF-SOEP Befragung von Geflüchteten

11) Scales Manual IAB-BAMF-SOEP Survey of Refugees in Germany – revised version

12) SOEP 2010 – Preparation of data from the new SOEP consumption module: Editing, imputation, and smoothing

13) SOEP Scales Manual (updated for SOEP-Core v32.1)

14) Kognitionspotenziale Jugendlicher - Ergänzung zum Jugendfragebogen der Längsschnittstudie Sozio-oekonomisches Panel (SOEP)

15) 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

16) Die Vercodung der offenen Angaben zur beruflichen Tätigkeit nach der Klassifikation der Berufe 2010 (KldB 2010): Vorgehensweise und Entscheidungsregeln bei nicht eindeutigen Angaben

17) Multi-Itemskalen im SOEP Jugendfragebogen

18) Zur Erhebung des adaptiven Verhaltens von zwei- und dreijährigen Kindern im Sozio-oekonomischen Panel (SOEP)

19) Dokumentation zum Entwicklungsprozess des Moduls „Einstellungen zu sozialer Ungleichheit“ im SOEP (v38)

20) SOEP-CoV: Project and Data Documentation

21) Missing Income Data in the German SOEP: Incidence, Imputation and its Impact on the Income Distribution

22) SOEP-Core v34 – PFLEGE: Documentation of Generated Person-level Long-term Care Variables

23) SOEP 2006 – TIMEPREF: Dataset on the Economic Behavior Experiment on Time Preferences in the 2006 SOEP Survey

24) Assessing the distributional impact of "imputed rent" and "non-cash employee income" in microdata : Case studies based on EU-SILC (2004) and SOEP (2002)

25) SOEP-Core v36: Codebook for the EU-SILC-like panel for Germany based on the SOEP

All documentation for filtering can be found on this page