SOEP-Core v37t (Daten 1984-2020, Teaching Edition)

In Publikationen, die diese Datei verwenden, soll auf die oben genannte DOI infoZur Erklärung von DOI und dessen Verwendung gibt es hier Informationen . verwiesen und folgende Referenzen zitiert werden:

• 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 239 (2), 345-360. (https://doi.org/10.1515/jbnst-2018-0022)

Wenn Sie bei Ihrer Analyse nicht die Fälle der Migrations-Stichproben ausschliessen, dann zitieren Sie bitte auch:

• 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.

Wenn Sie bei Ihrer Analyse nicht die Fälle der Geflüchteten-Stichproben ausschliessen, dann zitieren Sie bitte auch: IAB-BAMF-SOEP-Befragung Geflüchteter (M3-M5), Daten der Jahre 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.

Wenn Sie bei Ihrer Analyse die Daten der SOEP-LEE2 Befragungen nutzen, dann zitieren Sie bitte auch:

• 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. Jahrbücher für Nationalökonomie und Statistik Data Observer, 1–14. https://doi.org/10.1515/jbnst-2023-0031.

Wenn Sie bei Ihrer Analyse noch fachspezifischer referieren möchten, dann zitieren Sie bitte auch:

• 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. (https://doi.org/10.1515/ger-2020-0033)
• 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. (https://doi.org/10.1093/esr/jcz029)
• 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. (https://doi.org/10.1515/jbnst-2021-0001)
• 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. (https://doi.org/10.1515/jbnst-2021-0056)

Für die SOEP-Core-Daten 1984-2020 (v37) - Wellen A bis BK - stehen folgende Datensätze zur Verfügung:

soep.core.v37eu (EU Edition, 100%)

soep.core.v37i (International Scientific Use Version, 95%)

soep.core.v37t (Teaching Edition, 50%)

soep.core.v37at (Add-on: Area types)

soep.core.v37pr (Add-on: Planning regions)

soep.core.v37r (Remote Edition)

soep.core.v37o (Onsite Edition)

Ausführliche Informationen zu allen Editionen sind auf dem SOEPcompanion zu finden.

In der aktuellen Datenweitergabe komplett enthalten, auf spezielle Anfrage auch als Einzeldatensatz erhältlich:

soep.iab-soep-mig.2020 (Migrationsstichproben)

soep.iab-bamf-soep-mig.2020 (Geflüchtetenstichproben)

New samples in the main SOEP study

New Sample M6

The 2020 boost sample M6 supplements the samples of the IAB-BAMF-SOEP Survey of Refugees by 1,141 households. To recruit these households, a random sample was drawn from the Central Register of foreigners.
The sample consists of two main groups, namely persons who entered Germany between January 2013 up to the end of December 2016, filed an asylum application and whose last change of asylum status took place in 2013 to the end of 2016 (refreshment). The second group consists of persons who entered Germany between January 2013 and end of June 2019, filed an asylum application and whose last change of asylum status took place in 2017 to the end of June 2019 (enlargement).

New Sample M7

The 2020 boost sample M7 supplements the samples of the IAB-SOEP Migration Survey by 783 households. Similar to the M1 and M2 sample, register data of the Federal Employment Agency was used as a sampling frame. Information is collected on households with recent migrants from Poland, Romania, and Bulgaria between January 2016 and December 2018.

New Sample M8

The 2020 boost sample M8 supplements the samples of the IAB-SOEP Migration Survey by 1,096 households. Register data of the Federal Employment Agency was used to identify the population of third-country nationals who applied for working in Germany as professionals ("Fachkräfte") based on the Residence Act (Zuwanderungsgesetz) and were granted a permission in the time from January 2019 until January 2020. The sample also provides a basis to evaluate the "Fachkräfteeinwanderungsgesetz" becoming effective on March 1, 2020.

New datasets or variables

Dataset COV, COV_BRUTTO, COV_CONTACT - Datasets of SOEP-CoV study

All three datasets are associated with the 9 tranches of the SOEP-CoV in 2020, the SOEP-CoV wave in 2021 and COVID-19-special interviews 2020 from the IAB-BAMF-SOEP Survey of Refugees in Germany. More information about the project can be found online at the SOEP-Cov Homepage or in the references below, which we also recommend to cite if the data is used.

Kühne, S., Kroh, M., Liebig, S. & S. Zinn, (2020): The Need for Household Panel Surveys in Times of Crisis: The Case of SOEP-CoV. In: Survey Research Methods 14(2): 195-203.

Siegers, R., Steinhauer, H.-W. & S. Zinn, (2021): Weighting the SOEP-CoV study 2020. No. 989. SOEP Survey Papers (PDF, 486.06 KB).

• COV contains the survey content
• COV_Brutto contains the brutto information
• COV_CONTACT contains the contact information

Dataset bkbiorki - Dataset of RKI-SOEp study

The dataset contains information about: "How many people have already been infected with the coronavirus, SARS-CoV-2? How many infections have gone undetected?" More information about the project can be found online at Nationwide Antibody “Study Living in Germany - Corona Monitoring” (RKI-SOEP).

bkbiorki contains results of PCR and DBS tests, as well as survey content. Data is available on request.

Old ID Variables no longer distributed

With V34, we introduced a new directory structure by merging our former independently delivered data formats SOEP-wide and SOEP-long. In the top-level (or root) directory, you find all "SOEPlong datasets" (pl, ppfadl, pl, hl, pgen, hgen etc.) as well as all of the biographical or spell datasets (bioparen, artkalen, etc.).

The raw directory provides the datasets in their original wide and cross-sectional SOEP format. What`s new is that we offer identifiers identical to the names in the long data (PERSNR to PID or $HHRNAKT to HID) and an additional variable survey year (SYEAR), so that users can easily merge variables from both data formats.

In order to ensure consistency of data and also to not alienate new users, these traditional "old" ID variables (PERSNR, HHNR, $HHNR, HHNRAKT) will no longer be delivered starting this year. Please use the new identifiers (PID, HID, CID, SYEAR).

Changes in our new main data format, SOEPlong

Dataset PBRUTTO

• New variables reclin_drv_id "ID Record Linkage DRV" to link SOEP data with pension insurance data
• New variable for agreement of linking SOEP data and social data-IAB (SOEP-Record-Linkage)
• New variable to agree to link SOEP data and register data BAmF

Dataset BIOL

• Camces variables were removed from biol
• Recognition of educational qualifications loops have been revised
• Migration to Germany loops have been revised
• In 1984-1995, the „Current Household Number (hid)“ was used when generating the „Original Houshold Number, Case ID (cid)“. Now the „Original Houshold Number, Case ID (cid)“ is used as the information source for the long version.

Dataset PL

• Variables for short-time work, further training/retraining newly added and versioned
• Multiple integrations, versioning and harmonizations for variables on self-employment
• Multiple integrations for Place of residence loops
• Multiple integrations of M1-Sample cases for the survey year 2014
• Multiple integrations for questions on balance sheet assets
• New variables added (digitization labor market)

Dataset JUGENDL

• Integration of Grades
• Integration of School Belonging Scale PISA

Dataset HBRUTTO

• New variables for sample selection

Dataset HBRUTT

• New variables for sample selection
• Versioning of some living environment variables and incentivization

Dataset KIDLONG

• Versioning of variables on language support

Dataset BIOBIRTH

BIOBIRTH now contains one row for each person who has ever lived in a SOEP household and therefore represents the population of PPFAD. Unlike in v36, where BIOBIRTH provided fertility information on every woman and man who has ever provided at least one successful SOEP Biography interview.

Precise identification of individuals and their information quality as well as the respondent´s status is possible via the variables biovalid and the new variable bioinfo. Theses variables provide information on whether individual level information is based merely on information derived from household composition and family relations, or on biographical questionnaire data. This should help data users to better assess how trustworthy a piece of information is. Birth information of persons without a completed SOEP Biography interview can only be inferred and is estimated via household composition and family relations. The variables kidpnr[nn], kidgeb[nn], kidmon[nn], kidsex[nn] were increased from a maximum of 15 possible children to 19 possible children. The information from kidmon[nn] is based on the information from the slightly new generated variable kidmon[nn] from PPFAD.

Dataset HGEN

New variable hgeqpfire introduced. The variable indicates whether a household has a fireplace or ceramic tiled stove.

Dataset PFLEGE

Two variables are no longer part of the file PFLEGE: MULTGRAD and WERPFLGT. Instead, 6 new dummy variables were included. These new variables describe by whom care is provided for a person in need of care in a household:

• WERPFLGT1 “Public, church nurse, social worker”
• WERPFLGT2 “Who cares: friends, neighbors”
• WERPFLGT3 “Who cares: relatives not in the HH”
• WERPFLGT4 “Who cares: relatives in the HH”
• WERPFLGT5 “Who cares: private care service”
• WERPFLGT6 “Who cares: other”

Dataset PEQUIV

The dataset PEQUIV contains two new additional variables. These are:

• BAUK$$ “Building subsidy for new property owners”
• FKAUK$$ “Imputation lag for variable BAUK$$”

Dataset INTERVIEWER

Variable educ_i (surveyed education of interviewer) was recoded and incorrect value labels were corrected.

old (wrong) values:
[1] Secondary School Degree - Sekundarschulabschluss
[2] Intermediate School Degree - Mittlerer Schulabschluss
[3] Upper Secondary School Degree - Abschluss der Sekundarstufe II
[4] Left university without degree - Hochschule ohne Abschluss verlassen
[5] Graduate degree - Hochschulabschluss

new (correct) values:
[1] No School Degree - Ohne Abschluss
[2] Secondary School Degree (GDR: 8th grade) - Hauptschulabschluss (DDR: 8. Klasse)
[3] Intermediate School Degree (GDR: 10th grade) - Mittlere Reife(DDR: 10. Klasse)
[4] Technical School Degree - Fachhochschulreife
[5] Upper Secondary Degree - Abitur/Hochschulreife

Outdated versions of datasets

The following data sets are still at the V36 level and have not been updated. We will update them as far as possible with the next realease of the data:

Individual (PAPI) 2020: Field-de Field-en
Individual (CAPI) 2020: Var-de
Household (PAPI) 2020: Field-de Field-en
Household (CAPI) 2020: Var-de
Biography (PAPI) 2020: Field-de Field-en
Biography (CAPI) 2020: Var-de
Catch-up Individual (PAPI) 2020: Field-de
Corona 2020: Var-de
Corona 2020 Tranche 2: Var-de
Corona 2020 Tranche 4: Var-de
Corona 2020 Tranche 5: Var-de
Corona 2020 Tranche 7: Var-de
Corona 2020 Tranche 9: Var-de
Catch-up Individual (CAPI) 2020: Var-de
Youth (16-17-year-olds, PAPI) 2020: Field-de
Youth (16-17-year-olds, CAPI) 2020: Var-de
Early Youth (13-14-year-olds, PAPI) 2020: Field-de
Early Youth (13-14-year-olds, CAPI) 2020: Var-de
Pre-teen (11-12-year-olds, PAPI) 2020: Field-de
Pre-teen (11-12-year-olds, CAPI) 2020: Var-de
Mother and Child (Newborns, PAPI) 2020: Field-de
Mother and Child (Newborns, CAPI) 2020: Var-de
Mother and Child (2-3-year-olds, PAPI) 2020: Field-de
Mother and Child (2-3-year-olds, CAPI) 2020: Var-de
Mother and Child (5-6-year-olds, PAPI) 2020: Field-de
Mother and Child (5-6-year-olds, CAPI) 2020: Var-de
Parents and Child (7-8-year-olds, PAPI) 2020: Field-de
Parents and Child (7-8-year-olds, CAPI) 2020: Var-de
Mother and Child (9-10-year-olds, PAPI) 2020: Field-de
Mother and Child (9-10-year-olds, CAPI) 2020: Var-de
Deceased Individual (PAPI) 2020: Field-de
Deceased Individual (CAPI) 2020: Var-de
Corona 2020 Round 2: Var-en
Corona 2020 Round 4: Var-en
Corona 2020 Round 5: Var-en
Corona 2020 Round 7: Var-en
Corona 2020 Round 9: Var-en

Alle Sample-spezifischen Fragebögen dieses Jahres und alle Fragebögen der vorherigen Befragungsjahre finden Sie auf dieser Seite

1) Weighting the SOEP-CoV Study 2020

2) SOEP-Core – 2020: Sampling, Nonresponse, and Weighting in Living in Germany – Nationwide Corona Monitoring (RKI-SOEP)

3) SOEP-Core v37 – Documentation of Sample Sizes and Panel Attrition in the German Socio-Economic Panel (SOEP) (1984 until 2020)

4) Sampling, Nonresponse, and Weighting of the 2020 Refreshment Sample (M6) of the IAB-BAMF-SOEP Refugee Panel

5) SOEP-Core – 2020: Sampling, Nonresponse, and Weighting in the IAB-SOEP Migration Studies M7 and M8

6) SOEP-Core v37 – COGDJ

7) SOEP-Core v37 – PPATHL: Person-Related Meta-Dataset

8) SOEP-Core v37 – HPATHL: Household-Related Meta-Dataset

9) SOEP-Core v37 – PBRUTTO: Person-Related Gross File

10) SOEP-Core v37 – HBRUTTO: Household-Related Gross File

11) SOEP-Core v37 – PGEN: Person-Related Status and Generated Variables

12) SOEP-Core v37 – HGEN: Household-Related Status and Generated Variables

13) SOEP-Core v37 – Codebook for the $PEQUIV File 1984-2020: CNEF Variables with Extended Income Information for the SOEP

14) SOEP-Core v37 – BIOIMMIG: Generated Information on Immigration History

15) SOEP-Core v37 – HEALTH

16) SOEP-Core v37 – BIOPAREN

17) SOEP-Core v37 – BIOSIB

18) SOEP-Core v37 – BIOBIRTH

19) SOEP-Core v37 – INTERVIEWER

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 2013 – Documentation of Generated Person-Level Long-Term Care Variables in PFLEGE

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

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

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

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

Alle Dokumentationen zum Filtern finden Sie auf dieser Seite

1) SOEP-Core – 2020: Report of Survey Methodology and Fieldwork