SOEP-Core v32 - Documentation of person-related status and generated variables in $PGEN

DIW Berlin / SOEP (Ed.) Research Report SOEP-Core v32 - Documentation of person-related status and generated variables in $PGEN SOEP Survey Papers, No. 411 Provided in Cooperation with: German Institute for Economic Research (DIW Berlin) Suggested Citation: DIW Berlin / SOEP (Ed.) (2017) : SOEP-Core v32 - Documentation of personrelated status and generated variables in $PGEN, SOEP Survey Papers, No. 411, Deutsches Institut für Wirtschaftsforschung (DIW), Berlin This Version is available at: https://hdl.handle.net/10419/155344 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by-sa/4.0/ The German Socio-Economic Panel study 411 SOEP Survey Papers Series D – Variable Descriptions and Coding SOEP — The German Socio-Economic Panel study at DIW Berlin 2017 SOEP-Core v32 – Documentation of Person-related Status and Generated Variables in $PGEN SOEP Group Running since 1984, the German Socio-Economic Panel study (SOEP) is a wide-ranging representative longitudinal study of private households, located at the German Institute for Economic Research, DIW Berlin. The aim of the SOEP Survey Papers Series is to thoroughly document the survey’s data collection and data processing. The SOEP Survey Papers is comprised of the following series: Series A – Survey Instruments (Erhebungsinstrumente) Series B – Survey Reports (Methodenberichte) Series C – Data Documentation (Datendokumentationen) Series D – Variable Descriptions and Coding Series E – SOEPmonitors Series F – SOEP Newsletters Series G – General Issues and Teaching Materials The SOEP Survey Papers are available at http://www.diw.de/soepsurveypapers Editors: Dr. Jan Goebel, DIW Berlin Prof. Dr. Martin Kroh, DIW Berlin and Humboldt Universität Berlin Prof. Dr. Carsten Schröder, DIW Berlin and Freie Universität Berlin Prof. Dr. Jürgen Schupp, DIW Berlin and Freie Universität Berlin Please cite this paper as follows: SOEP Group, 2017. SOEP-Core v32 – Documentation of Person-related Status and Generated Variables in $PGEN. SOEP Survey Papers 411: Series D – Variable Descriptions and Coding. Berlin: DIW Berlin/SOEP This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. © 2017 by SOEP ISSN: 2193-5580 (online) DIW Berlin German Socio-Economic Panel (SOEP) Mohrenstr. 58 10117 Berlin Germany [email protected] The German Socio Economic Panel study at DIW Berlin SOEP-Core v32 – Documentation of Person-related Status and Generated Variables in $PGEN SOEP Group 2017 The files $PGEN are part of a collection, which is released with doi:10.5684/soep.v32. SOEP Core study (v32) bfpgen (v32) Contents 1 General Information 4 2 Identifiers 4 persnr – Never Changing Person Id .............................. 4 hhnr – Original Household Number .............................. 4 hhnrakt – hhnrakt Current Wave HH Number (=$hhnr) [generic] .............. 4 $hhnr – Current Wave Number (=HHNRAKT) [generic] .................... 4 3 Own Nationality 4 nation$$ – Nationality [generic] ................................ 4 4 Familiy Status and Partnership 5 partz$$ – Partner Indicator [generic] ............................. 5 partnr$$ – Partner Person Number [generic] ......................... 6 $famstd – Marital Status In Survey Year [generic] ....................... 6 5 Wages and Salary 7 labgro$$ – Current Gross Labor Income in Euro [generic] .................. 7 impgro$$ – Imputation flag for Gross Income [generic] ................... 8 labnet$$ – Current Net Labor Income in Euro [generic] ................... 8 impnet$$ – Imputation flag for Net Income [generic] .................... 8 sndjob$$ – Current Gross Secondary Income In Euro [generic] ................ 9 impsnd$$ – Imputation Flag For SNDJOBxx [generic] .................... 9 6 Current Employment Status 9 stib$$ – Occupational Position [generic] ........................... 9 emplst$$ – Employment Status [generic] ........................... 11 lfs$$ – Labor Force Status [generic] .............................. 11 jobch$$ – Occupational Change [generic] .......................... 12 autono$$ – Autonomy In Occupational Actions [generic] .................. 14 7 Current Occupation 15 isco88_$$ – Current Occupational Classification (ISCO-88 Com) [generic] ......... 15 isco08_$$ – Current Occupational Classification (ISCO-08) [generic] ............ 16 isei88_$$ – Last Reached Isei Value (International Socio-Economic Index) [generic] . . . . 17 kldb92_$$ – Current Occupational Classification (KldB92) [generic] ............ 18 kldb2010_$$ – Current Occupational Classification (KldB2010) [generic] ......... 19 mps92_$$ – Last Reached Mps Value (Magnitude-Prestige-Skale, Wegener) [generic] . . . 19 siops88_$$ – Last Reached Siops Value (Std. Internat. Occupational Prestige Scale) [generic] 20 egp88_$$ – Last Reached Egp Value (Erikson, Goldthorpe, Portocarero) [generic] ..... 21 erljob$$ – Working In Occupation Trained For [generic] ................... 22 ausb$$ – Required Training For Job [generic] ......................... 23 $erwzeit – Length Of Time With Firm [generic] ........................ 23 $tatzeit – Actual Work Time Per Week [generic] ........................ 24 $vebzeit – Agreed Upon Work Time Per Week [generic] ................... 24 $uebstd – Overtime Per Week [generic] ............................ 25 oeffd$$ – Civil Service [generic] ................................ 25 nace$$ – 2 Digit NACE Industry, Sector [generic] ...................... 26 betr$$ – Size of the Company [generic] ............................ 27 allbet$$ – Core Category Size Of The Company [generic] .................. 28 SOEP Survey Papers 411 2 SOEP Core study (v32) bfpgen (v32) 8 Last Occupation 28 jobend$$ – Reasons for occupational change [generic] ................... 28 9 Employment History 30 expft$$ – Working Experience Full-Time Employment [generic] ............... 30 exppt$$ – Working Experience Part-Time Employment [generic] ............... 30 expue$$ – Unemployment Experience [generic] ....................... 31 10 School, Higher and Vocational Education 32 isced97_$$ – ISCED-1997-Classification [generic] ...................... 32 isced11_$$ – ISCED-2011-Classification [generic] ...................... 33 casmin$$ – CASMIN Classification [generic] ......................... 34 $bilzeit – Amount Of Education Or Training In Years [generic] ................ 34 $psbil – School-Leaving Degree [generic] ........................... 35 $pbbil01 – Vocational Degree Received [generic] ...................... 35 $pbbil02 – College Degree [generic] ............................. 36 $pbbil03 – No Vocational Degree [generic] .......................... 36 $psbilo – School-Leaving Degree East Germany [generic] .................. 37 $pbbilo – Vocational Degree Received East Germany [generic] ............... 37 $psbila – School-Leaving Degree Outside Germany [generic] ................. 38 $pbbila – Vocational Degree Outside Germany [generic] ................... 38 field$$ – Field of tertiary education [generic] ......................... 39 degree$$ – Type of tertiary degree [generic] ......................... 40 traina$$ – Apprenticeship - two-digit occupation KldB92 [generic] ............. 42 trainb$$ – Vocational school - two-digit occupation KldB92 [generic] ............ 44 trainc$$ – Higher vocational school - two-digit occupation KldB92 [generic] ........ 45 traind$$ – Civil servant training - two-digit occupation KldB92 [generic] .......... 46 fdt_f$$ – Data source FIELD, DEGREE, TRAIN [generic] ................... 47 bilztch$$ – Change in Education since last survey / last year [generic] ........... 47 bilztev$$ – Change in Education, total observed period [generic] .............. 48 11 Information on the Interview 48 month$$ – Month Of Interview [generic] ........................... 48 mode$$ – Interview Method [generic] ............................. 49 SOEP Survey Papers 411 3 SOEP Core study (v32) bfpgen (v32) 1 General Information The $PGEN-files contain user friendly data on the individual level which are consolidated from different sources. The plausibility is in many respects longitudinally validated, therefore the data here are in most situations superior compared to the data in $P. The file contains one row for each person (persnr is unique) with a completed personal or youth questionnaire. These are the persons where in PPFAD $netto has the values 10–17 or 19 which is equivalent for values 1 and 5 in $netold. While frequencies are calculated from the most recent $PGEN the here presented information is basically valid for all $PGEN files. Therefore many variable names depicted here have the generic form $name or name$$ and are flagged with [generic]. From version v32 on ERWTYP is not a part of data delivery. The information related to ERWTYP categories can be found in the variable(s) JOBCH$$, EMPLST$$, LFS$$. 2 Identifiers persnr – Never Changing Person Id The central individual identifier across time is PERSNR, which is fixed over time (and of course datasets). hhnr – Original Household Number The identifier of the household, when it is sampled and selected for interviewing for the first time. The hhnr is attached to all persons living in this household and all new persons inherit this identifier, when they are born or move in a SOEP household. It is fixed no matter how often a person changes the household in the course of time. hhnrakt – hhnrakt Current Wave HH Number (=$hhnr) [generic] This identifier groups all persons into households at the time of the most recent wave. [This information can be related to a specific variable and is not necessary generic.] $hhnr – Current Wave Number (=HHNRAKT) [generic] This identifier groups all persons into households at the time of the most recent wave. [This information can be related to a specific variable and is not necessary generic.] 3 Own Nationality nation$$ – Nationality [generic] 1[1] Germany 23659 2[2] Turkey 473 3[3] Ex-Yugoslavia 6 4[4] Greece 230 5[5] Italy 332 6[6] Spain 119 7[7] Ex-GDR (Country Of Origin Only) 0 10 [10] Austria 71 11 [11] France 45 SOEP Survey Papers 411 4 SOEP Core study (v32) bfpgen (v32) 12 [12] Benelux 0 13 [13] Denmark 11 14 [14] Great Britain 38 15 [15] Sweden 9 16 [16] Norway 5 17 [17] Finland 9 ... (157 rows omitted) 2734 175 [175] Grenada 0 176 [176] Lesotho 0 177 [177] Bhutan 0 178 [178] Rwanda 0 179 [179] Malawi 0 180 [180] Bessarabia 0 183 [183] Niger 2 222 [222] Eastern Europe 0 333 [333] Other Unspecified Foreign Country 0 -1 [-1] No Answer 0 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all This variable is designed to integrate the information on respondent’s nationality for all subsamples. Since some members of Sample B (persons with Turkish, Italian, Spanish, Greek, and Yugoslavian citizenship) received the question items in their own language up to 1995, to carry out an integrated analysis with Sample B, the user must obtain this information from the corresponding $PAUSL files and add it to the individual data. The variable NATION$$ thus offers a variable on nationality for all subsamples. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) 4 Familiy Status and Partnership partz$$ – Partner Indicator [generic] 0[0] No partner 8862 1[1] Spouse, registered partner 15962 2[2] Partner 2666 3[3] Probably spouse, registered partner 137 4[4] Probably partner 111 -1 [-1] No Answer 5 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all SOEP Survey Papers 411 5 SOEP Core study (v32) bfpgen (v32) The variable PARTZ$$ generated in the context of the partner identifier (PARTNR$$) to describe whether a person in a SOEP household has a partner in that household, and if so, the type of relationship existing between the partners. Relationships with persons outside the SOEP household are not covered by this variable. To explain the codes: Code 0 is assigned to all single persons living in households and those with partners outside the household. Codes 1 to 4 describe relationships. To assign Codes 1 and 2, the partnership has to be definable from the perspective of both partners unanimously. If conflicting information exists between partners, the codes 3 or 4 are assigned. If it is unclear whether an individual has no partner or whether she forms a couple with one other household member, we assign the code -1. Registered partnerships (civil unions) for same-sex couples were introduced in Germany in 2001. Though, registered partnerships are legally not equal to marriage, they are listed in the same category. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Martin Kroh (Tel. +49-30-89789-678) partnr$$ – Partner Person Number [generic] Waves: all Partner indicators have the purpose of defining couples in SOEP households and thus to make possible analyses on the dyadic level. Persons without spouse and (cohabitating) partner receive a missing code “-2” (=does not apply). Also, the variable PARTZ$$ is coded -1, 0, 3, 4 in these cases. In couples, PARTNR$$ is the value of the unchanging person ID number (=PERSNR) of the partner. The assignment of the partner ID within households is based on four sources of information: A question in the person-file, that asks (unmarried) respondents to identify their partner in the household (bfp15002 in 2015), the household matrix reported by the head of household at the beginning of the interview (bfstell in 2015), the partnership biography in the lifehistory calendar reported by new respondents (see also, biomars), and self-reports on marital status and life events, such as marriage, move in with partner, separation, etc. In unclear cases, due to temporal non-response for instance, we also consider longitudinal information from previous and prospective waves. Moreover, PARTNR$$ is self-consistent between two individuals. For analyses of partner relationships, this information can be used to link all persons with their respective partners, and all information on both partners can also be stored in a common dataset. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Martin Kroh (Tel. +49-30-89789-678) $famstd – Marital Status In Survey Year [generic] 1[1] Married 15844 2[2] Married, But Separated 269 3[3] Single 7285 4[4] Divorced 2341 5[5] Widowed 1390 6[6] husband/wife abroad 0 7[7] Registered Same-Sex Partnership, Living Together 52 8[8] Registered Same-Sex Partnership, Living Apart 8 -1 [-1] No Answer 27 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 526 SOEP Survey Papers 411 6 SOEP Core study (v32) bfpgen (v32) 2[2] Employed No Change 12666 3[3] Employed No Info If Change 1431 4[4] Employed With Change 2616 5[5] First Time Employed 277 -1 [-1] No Answer 5 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all This variable indicates a change of job since the previous interview for respondents with a follow-up interview, whereas for first-time respondents, the information refers to a change of job since the beginning of the previous year. JOCHCH$$ is generated based on the central filter variable, which indicates whether a respondent has changed jobs since the beginning of the previous year. A job change can be within one firm as well as a change to another firm. Information on the date of job change is then combined with interview month of the previous year’s interview to identify whether a new job change has taken place since the previous interview. Hence, JOBCH$$ indicates whether a respondent has changed jobs since the beginning of the previous year. The variable is calculated for all waves, and the codes are assigned independently of the respondent being a first-time or follow-up respondent. The variable is also designed to identify respondents who have entered employment for the first time. Up to 1993, first-time respondents did not answer the question about job change. Therefore, for first-time respondents up to 1993, the variable was generated by using the information on the start date with the current employer and the respondent’s age at entrance into his/her first job. The variable is also designed to provide consistent longitudinal information on job changes. The JOBCH$$ variable is generated by correcting the original job change information in various ways: 1. We check whether the job changes stated by a respondent in two consecutives interviews refer to one and the same job change. The date of the job change and the interview month are used to correct double entries. 2. If the respondent indicates a job change with a date before the previous interview but did not state a job change in the previous interview, this is coded as a job change in the current interview. 3. If a respondent indicates no job change and was not employed at the time of the previous interview, this is coded as “no job change” despite the seeming implausibility, since there are possible explanations how this information could be plausible, e.g. if there were short-term employment spells between two interview dates. 4. Respondents can be “first-time employed” only once. If a respondent states being “firsttime employed” for a second time, this is coded as “employed, with change”. In 2013 the respondents of the newly introduced migration sample were not asked whether they have changed jobs since the beginning of the previous year, therefore the generation of JOBCH$$ for the migration sample was modified in 2013: 1. Respondents who are not employed were coded (1). 2. Respondents who are still in the same occupation and position and are working for the same employer as they had worked in their first job in Germany were coded (2). SOEP Survey Papers 411 13 SOEP Core study (v32) bfpgen (v32) 3. Respondents who have entered the firm they are currently working after the 31th of December 2011 were coded (4). 4. If a respondent is in her first vocational training this was coded as (5). 5. Respondents who are employed but for whom no further information could be used were coded (3). In 2014 there was again a uniform questionnaire for all respondents. In 2015 the respondents of the newly introduced migration sample (M2) were not asked whether they have changed jobs since the beginning of the previous year. Furthermore respondent within migration sample M1 are decomposed in first-time respondents with and follow-up respondents without question about job change in the previous year embodied by the questionnaire. such that generation of JOBCH$$ for the migration sample in 2015 was following: 1. For follow-up respondents generation as in case of a uniform questionnaire for all respondents to be pursued. 2. In the case of first-time respondents in M1 sample and for all respondents from M2 sample the rule of thumb is as in 2013. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) autono$$ – Autonomy In Occupational Actions [generic] 0[0] Apprentice 860 1[1] Low Autonomy 2253 2 4089 3 5370 4 3431 5[5] High Autonomy 631 -1 [-1] No Answer 356 -2 [-2] Does not apply 10753 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all This variable gives the occupational autonomy for all employed persons. It offers an alternative to the ISCO-based scales on occupational status (ISEI$$), class (EGP$$), or prestige (SIOPS$$). AUTONO$$ is the simplest variable based on the scales of “occupational position” in terms of its construction, and strongly correlated with the Treiman Prestige Scale (SIOPS$$). The basis for the “autonomy in occupational activity” scale is the classification of occupational position. Self-employed persons are categorized according to the size of the company (with the exception of farmers, who are all classified within the same category of autonomy, independent of farm size in hectares). Civil servants are differentiated according to the civil service laws defining each kind of activity and the amount of autonomy connected to it. Workers are differentiated according to their vocational training, and thus categorized hierarchically according to the different tasks they can be expected to carry out and the different amounts of responsibility associated with each task. Similarly, salaried employees are classiSOEP Survey Papers 411 14 SOEP Core study (v32) bfpgen (v32) fied according to how differentiated their tasks are and how much responsibility is associated with each. The value “1” is assigned mainly to manual workers with a low level of status and a low level of autonomy. Group 2 encompasses work in production, services demanding a minimal level of specialization, and farm work. Activities that require completion of the middle track of secondary education and entail a limited amount of responsibility are classified in Group 3. Group 4 includes activities carried out either with or without supervision that require a degree from a college of applied sciences or university, but are not very high in prestige. Managers and freelance academics are both placed in Group 5 (highest autonomy). Depending on the number of employees, self-employed are categorized in Group 3, Group 4, or Group 5. [This information can be related to a specific variable and is not necessary generic.] Detailed description: Hoffmeyer-Zlotnik, Jürgen H.P., and Alfons J. Geis (2003) Berufsklassifikation und Messung des beruflichen Status/ Prestige. In: ZUMA-Nachrichten 52, Jg. 27, Mai 2003. pp. 125-138. For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) 7 Current Occupation Not all employed persons are asked the question about occupation on an annual basis. In years with a partial survey – 1985, 1986, 1987, 1988, 1990 (West), 1992 (West), 1994, 1996, 1999, 2001, 2003, 2005, 2006, 2008, 2010, 2012, and 2014 – only those employed persons who changed jobs and first-time respondents are asked to provide up-to-date information. Therefore, in years with a partial survey or in case of non-response the variables in this section usually contain available information from the previous year (persons with JOBCH$$-category (2) “employed, no change”). For some persons without a job change who updated the information on their current occupation without being asked, up-to-date information is used. The scores which are derived from the occupational scores contain information on the last attained value. The missing values in variables of codes for economic activities or occupations and derived scores (NACE, ISCO, KldB, ISEI, SIOPS, EGP, MPG) should be interpreted as follows. -1: there was a response, but no code could be assigned or no score could be derived, -2: there was no response which could have been coded and -8 means this type of code or score is not available for this year. The information on the current occupation is not neccessarily consistent to the current employment status, because they are based on different sources of information isco88_$$ – Current Occupational Classification (ISCO-88 Com) [generic] 0[0] Soldiers 0 100 [100] Soldiers 43 1000 [1000] Legislators, Senior Officials and Managers 0 1100 [1100] Legislators and Senior Government Officials 0 1110 [1110] Legislators and Senior Government Officials 5 1140 [1140] Senior Officials of Special-Interest Organisations 1 1141 [1141] Senior Officials of Political Party Organisations 0 1142 [1142] Senior Officials of Employers’, Workers’ and Other Economic-Interest Organisations 12 1143 [1143] Senior Officials of Humanitarian and Other Special-Interest Organisations 0 1200 [1200] Corporate Managers 42 1210 [1210] Directors and Chief Executives 109 SOEP Survey Papers 411 15 SOEP Core study (v32) bfpgen (v32) 1220 [1220] Production and Operations Managers 0 1221 [1221] Production and Operations Managers in Agriculture, Hunting, Forestry and Fishing 0 1222 [1222] Production and Operations Managers in Manufacturing 81 1223 [1223] Production and Operations Managers in Construction 0 ... (468 rows omitted) 15800 9212 [9212] Forestry Labourers 0 9213 [9213] Fishery, Hunting and Trapping Labourers 0 9300 [9300] Labourers in Mining, Construction, Manufacturing and Transport 0 9310 [9310] Mining and Construction Labourers 0 9311 [9311] Mining and Quarrying Labourers 0 9312 [9312] Construction and Maintenance Labourers: Roads, Dams and Similar Constructions 3 9313 [9313] Building Construction Laborer 48 9320 [9320] Manufacturing Laborer 260 9330 [9330] Transport Lab., Freight Handler 169 -1 [-1] No Answer 70 -2 [-2] Does not apply 11100 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Hartmann and Schütz (2002) provide detailed information on the conducted occupational coding. This result has been slightly modified to fit to the ISCO-88 version for European Union purposes (ISCO-88(COM)). [This information can be related to a specific variable and is not necessary generic.] Hartmann/Schütz (2002): Die Klassifikation der Berufe und der Wirtschaftszweige im Soziooekonomischen Panel. Neuvercodung der Daten 1984–2001. Infratest Sozialforschung, München. https://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.40132.de/vercodung.pdf For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) isco08_$$ – Current Occupational Classification (ISCO-08) [generic] 110 [110] Commissioned Armed Forces Officers 8 210 [210] Non-Commissioned Armed Forces Officers 3 310 [310] Armed Forces Occupations, Other Ranks 31 1111 [1111] Legislators 4 1112 [1112] Senior Government Official 22 1113 [1113] Traditional Chiefs and Heads of Village 0 1114 [1114] Senior Officials of Special-Interest Organisations 11 1120 [1120] Managing Directors and Chief Executives 86 1211 [1211] Finance Managers 23 1212 [1212] Human Resource Managers 38 1213 [1213] Policy and Planning Managers 14 1219 [1219] Business Services and Administration Managers Not Elsewhere Classified 20 1221 [1221] Sales and Marketing Managers 77 1222 [1222] Advertising and Public Relations Managers 13 1223 [1223] Research and Development Managers 12 ... (412 rows omitted) 16021 9520 [9520] Street Vendors (excluding Food) 0 9611 [9611] Garbage and Recycling Collectors 20 SOEP Survey Papers 411 16 SOEP Core study (v32) bfpgen (v32) 9612 [9612] Refuse Sorters 9 9613 [9613] Sweeper, Related Laborer 3 9621 [9621] Messengers, Package Deliverers and Luggage Porters 71 9622 [9622] Odd Job Persons 0 9623 [9623] Meter Readers and Vending-Machine Collectors 0 9624 [9624] Water and Firewood Collectors 0 9629 [9629] Elementary Workers Not Elsewhere Classified 15 -1 [-1] No Answer 118 -2 [-2] Does not apply 11124 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) isei88_$$ – Last Reached Isei Value (International Socio-Economic Index) [generic] 16 933 19 119 20 359 21 82 22 20 23 533 24 52 25 874 26 200 27 105 28 84 29 831 30 1254 31 101 32 245 ... (33 rows omitted) 12412 69 1589 70 138 71 394 74 83 77 206 78 28 79 27 82 48 83 16 85 121 87 36 88 188 90 13 -1 41 -2 6611 SOEP Survey Papers 411 17 SOEP Core study (v32) bfpgen (v32) Waves: all This variable reflects the Standard International Socio-Economic Index of Occupational Status for all employed persons. The ISEI Index was developed in 1992 by Ganzeboom, De Graaf, Treiman, and De Leew based on information about income, education, and occupation. Technically, ISEI was created by scaling the ISCO88 classification. The values for the variable range between 16 and 90. In contrast to the prestige scores of Ganzeboom and Treiman (1996) and Wegener (1988), ISEI is a measure of socio-economic status. It is derived from the ISCO88 code of the current occupation using the Stata ado iskoisei by John Hendrickx which itself is based on Harry Gaanzeboom’s SPSS algorithms. Also available: occupational prestige scores (SIOPS, MPS) and occupational class (EGP). [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) kldb92_$$ – Current Occupational Classification (KldB92) [generic] 110 [110] Landwirt(e/innen), allgemein 53 111 [111] Obstund Gemuesebauern/-baeuerinnen (nicht Gaertner/innen) 1 112 [112] Ackerbauern/-baeuerinnen fuer Spezial-, Dauerkulturen 0 113 [113] Viehhalter/innen und Gruenlandwirt(e/innen) 0 114 [114] Saat-, Pflanzenzuechter/innen, Vermehrer/innen (nicht Gaertner/innen) 1 115 [115] Pflanzenschuetzer/innen 1 116 [116] Landwirt(e/innen) und Gastwirt(e/innen)/Kaufleute 0 118 [118] Landwirt(e/innen) und Winzer/innen 0 120 [120] Winzer/innen, allgemein 3 121 [121] Rebenveredler/innen 0 129 [129] andere Winzer/innen 0 130 [130] Landarbeitskraefte, allgemein 2 131 [131] Landarbeitsaufseher/innen 0 132 [132] Landmaschinenfuehrer/innen 1 133 [133] Weinbergsarbeiter/innen 1 ... (2261 rows omitted) 16482 9831 [9831] Schulentlassene (arbeitsuchend) mit (noch) nicht bestimmtem Beruf 0 9832 [9832] Sonstige Arbeitskraefte (arbeitsuchend) mit (noch) nicht bestimmtem Be 1 9911 [9911] Facharbeiter/innen o.n.T. 3 9921 [9921] Heimarbeiter/innen o.n.T. 2 9931 [9931] Vorarbeiter/innen, Gruppenleiter/innen o.n.T. 1 9941 [9941] Zivildienstleistende o.n.T. 0 9951 [9951] Selbstaendige o.n.T. 11 9961 [9961] Beratungs-, Planungsfachleute o.n.T. 6 9971 [9971] Sonstige Arbeitskraefte o.n.T. 57 -1 [-1] No Answer 17 -2 [-2] Does not apply 11100 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Current occupation coded as KldB92. Hartmann and Schütz (2002) provide detailed information on occupational coding. [This information can be related to a specific variable and is not necessary generic.] SOEP Survey Papers 411 18 SOEP Core study (v32) bfpgen (v32) Hartmann/Schütz (2002): Die Klassifikation der Berufe und der Wirtschaftszweige im Soziooekonomischen Panel. Neuvercodung der Daten 1984–2001. Infratest Sozialforschung, München. https://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.40132.de/vercodung.pdf For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) kldb2010_$$ – Current Occupational Classification (KldB2010) [generic] 1104 [1104] Officer 7 1203 [1203] Senior Non-Commissioned Officers and Higher 4 1302 [1302] Junior Non-Commissioned Officers 0 1402 [1402] Armed Forces Personnel in Other Ranks 31 11101 [11101] Occupations in Farming (without Specialisation)-Unskilled/Semiskilled Tasks 15 11102 [11102] Occupations in Farming (without Specialisation)-Skilled Tasks 46 11103 [11103] Occupations in Farming (without Specialisation)-Complex Tasks 3 11104 [11104] Occupations in Farming (without Specialisation)-Highly Complex Tasks 13 11113 [11113] Technical Occup. in Farming-Complex Tasks 1 11114 [11114] Technical Occup. in Farming-Highly Complex Tasks 0 11123 [11123] Agricultural Experts-Complex Tasks 0 11124 [11124] Agricultural Experts-High Complex Tasks 1 11132 [11132] Technical Laboratory Occup. in Agriculture-Skilled Tasks 0 11133 [11133] Technical Laboratory Occup. in Agriculture-Complex Tasks 0 11182 [11182] Occupations in Farming (with Specialisation, Not Elsewhere Classified)-Skilled Tasks 2 ... (1262 rows omitted) 16338 94622 [94622] Prop Designers-Skilled Tasks 1 94623 [94623] Prop Designers-Complex Tasks 0 94693 [94693] Supervisors in Stage, Costume and Prop Design 0 94704 [94704] Occupations in Museums (without Specialisation)-Highly Complex Tasks 6 94712 [94712] Technical Occup. in Museums and Exhibitions-Skilled Tasks 1 94713 [94713] Technical Occup. in Museums and Exhibitions-Complex Tasks 0 94714 [94714] Technical Occup. in Museums and Exhibitions-Highly Complex Tasks 0 94724 [94724] Art Experts-Highly Complex Tasks 0 94794 [94794] Managers in Museum 0 -1 [-1] No Answer 150 -2 [-2] Does not apply 11124 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) mps92_$$ – Last Reached Mps Value (Magnitude-Prestige-Skale, Wegener) [generic] 30 2 30.1000003814697 36 30.2000007629395 76 30.2999992370605 8 31 167 SOEP Survey Papers 411 19 SOEP Core study (v32) bfpgen (v32) 31.1000003814697 54 31.2000007629395 16 31.5 312 31.7000007629395 147 31.7999992370605 20 31.8999996185303 2 32 35 32.0999984741211 220 32.2000007629395 12 32.2999992370605 757 ... (155 rows omitted) 18262 123.900001525879 62 125.199996948242 16 132.100006103516 167 135.699996948242 99 138.199996948242 17 138.899993896484 16 139.800003051758 26 145.699996948242 115 152.5 171 153.5 6 191.300003051758 188 207.199996948242 43 216 37 -1 41 -2 6613 Waves: all This variable gives the occupational prestige score developed by Wegener (1988) for all employed persons. Like the SIOPS prestige sore, Wegener’s prestige scala measures a person’s occupational prestige and was developed especially for use in the Federal Republic of Germany. MPS is assigned based on the German Federal Statistical Office’s occupational classification of 1992 (KLDB92$$). The procedure has been documented in Frietsch and Wirth (2001). Also available: occupational prestige scores (SIOPS, ISEI) and occupational class (EGP). [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) siops88_$$ – Last Reached Siops Value (Std. Internat. Occupational Prestige Scale) [generic] 13 19 15 82 17 13 18 1 19 396 20 371 21 968 22 247 23 284 SOEP Survey Papers 411 20 SOEP Core study (v32) bfpgen (v32) 24 62 25 295 26 43 27 19 28 174 29 167 ... (33 rows omitted) 16519 64 51 65 129 66 221 67 83 68 3 69 41 70 301 71 48 72 77 73 84 75 12 76 13 78 368 -1 41 -2 6611 Waves: all This variable gives the occupational prestige score index for all employed persons. SIOPS$$ is based on ISCO-88 and was developed by Donald Treiman et al. The scale ranges from 6 to 78. The alogorithm is based on Fritsche and Wirth (2001). Please also see occupational prestige scores (MPS$$), occupational status (ISEI$$), and occupational class (EGP$$). [This information can be related to a specific variable and is not necessary generic.] Frietsch, Rainer/Wirth, Heike (2001): Die Uebertragung der Magnitude-Prestigeskala von Wegener auf die Klassifikation der Berufe. In: ZUMA Nachrichten 48 (Jg.25): 139–165 For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) egp88_$$ – Last Reached Egp Value (Erikson, Goldthorpe, Portocarero) [generic] 1[1] [I] Higher Managerial and Professional Workers 2850 2[2] [II] Lower Managerial and Professional Workers 5174 3[3] [IIIa] Routine Clerical Work 2743 4[4] [IIIb] Routine Service and Sales Work 2927 5[5] [IVa] Small Self-Employed With Employees 340 6[6] [IVb] Small Self-Employed Without Employees 493 7[7] [V] Manual Supervisors 0 8[8] [VI] Skilled Manual Workers 2852 9[9] [VIIa] Semiand Unskilled Manual Workers 3353 10 [10] [VIIb] Agricultural Labour 286 11 [11] [IVc] Self-Employed Farmers 73 -1 [-1] No Answer 41 -2 [-2] Does not apply 6611 -3 [-3] Answer improbable 0 SOEP Survey Papers 411 21 SOEP Core study (v32) bfpgen (v32) -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all This variable gives the occupational class for all employed persons. EGP$$ is derived from the Standard International Socio-Economic Index of Occupational Status (ISEI). Technically, the variable was created by scaling the ISCO-88 classification. In addition, it is based on information about income, education and occupation. The EGP Index was documented by Ganzeboom/Treiman in 1996 and revised in 2003. Former versions and waves contained additional categories for unemployed persons and pensioners. From wave be (2014) on the egp-variable has a more standard shape. Information on unemployment and retirement can be found in stib$$ (occupational position) and lfs$$ (labor force status). As information about supervisory status is only available from wave X (2007) on, it is not used to generate the corresponding EGP$$ category. Hence, the potential category (7) “Manual workers with supervisory status” is not assigned. Annual information on the occupational position is used to generate the EGP-categories for the self-employed. In case no information on the number of employees is available, the EGP$$-categories (5) and (6) contain information on the firm size for self-employed persons. Based on the new classification developed by Ganzeboom/Treiman (2003), several ISCO values were recoded in EGP$$ as follows: • ISCO 2470 becomes EGP=1. • ISCO 2500 becomes EGP=2. • ISCO 4300, 4400, 4500 become EGP=4. • ISCO 7900 becomes EGP=7. • ISCO 9910-9990 become EGP=9. Please also see occupational status (ISEI$$) and occupational prestige scores (SIOPS$$, MPS$$). [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Knut Wenzig (Tel. +49 30 89789 341, [email protected]) erljob$$ – Working In Occupation Trained For [generic] 1[1] Yes 9024 2[2] No 5860 3[3] In Training 992 4[4] Has No Job Training 903 -1 [-1] No Answer 211 -2 [-2] Does not apply 10753 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all This variable is designed to offer annual data on all employed persons, indicating whether they are working in the occupation they were trained for. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) SOEP Survey Papers 411 22 SOEP Core study (v32) bfpgen (v32) 11 [11] Company closed down 92 12 [12] Old-age pension 168 13 [13] Leave of absence/sabbatical (1999-2010) 0 14 [14] Leave, maternity leave and parental leave (1991-1998), since 2011 230 15 [15] Other incl. early retirement, company closed, old-age pension, leave of absence/sabbatical (1985-1986) 0 16 [16] Other incl. company closed, old-age pension,leave of absence/sabbatical (19871990) 0 17 [17] Other incl. mutual termination (1991-1998) 0 -1 [-1] No Answer 56 -2 [-2] Does not apply 25131 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 560 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 This variable is designed to offer annual data on reasons for an occupational change for all formerly employed persons, persons with a job change or persons on leave. For years 1985– 1991 also persons who changed positions in the same company are considered. Only persons with valid dates for an occupational or positional change are included. Likewise to the questionnaire the variable offers data from interview date to interview date not from one year to the following. Respondents are asked about their annual and possibly same occupational change in two consecutive interviews, duplicate answers are therefore considered only once and the older statement is dominant. If a respondent stated a job termination in the current interview which was before the interview date in the previous year but didn’t reported this in the previous interview this termination has been counted for the current interview. For years 1985 up to 1998 every given reason was coded as separate variable with variable values “Yes” (1) and “Does not apply” (-2), which resulted in up to 13 different variables. Since 1999 all given reasons have been collected in one single variable with diverse values. Within period 1985-1991 the year 1990 is specific due to introduction of sample for East Germany. Since the questionnaire did not contain the information on reasons for end of the job all the observations in Sample C in year 1990 obtained value (-5). Please pay attention to special codes (15), (16), and (17)! These codes were necessary due to the variety of the given values over the years. In any years respondents were asked about reasons for change with more or less given answers and from years 1985–1998 also the answer “Other” was possible. While all explicit reasons have been recoded to uniform values, the answer “Other” then in some years includes reasons for which in other years was separately asked for: “Other” was coded (15) for years 1985 and 1986, (16) for years 1987–1990 and (17) for years 1991–1998. For years 1991–1998 and 2011–2012 there is a variable value “Leave, maternity leave and parental leave” whereas for 1999–2010 the given reason covered only “Leave of absence/sabbatical”. Note that codes (2) and (3) for years 1985–1998 have been merged to code (9) since 1999. In 2013 the respondents of the newly introduced migration sample were not asked about an occupational change, but in 2014 they were. So information on jobend for the migration sample in 2013 were taken from the questionnaire in 2014. Since 2006 youth questionnaires have been embodied in survey tools. Nevertheless, the questionnaires do not contain the information on jobend. Therefore, in order to account for the persons represented by the youth questionnaires the negative value (-5) has been introduced starting from year 2006. [This information can be related to a specific variable and is not necessary generic.] SOEP Survey Papers 411 29 SOEP Core study (v32) bfpgen (v32) For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) 9 Employment History expft$$ – Working Experience Full-Time Employment [generic] Waves: all This variable reflects the total length of full-time employment in the respondent’s career up to the point of the interview in a given year. The variable is created by combining monthly information on employment status from the calendar dataset ARTKALEN (which provides monthly information on activity status since an individual entered the SOEP) and annual information from the biographical dataset PBIOSPE (which provides information on activity status over the individual’s life course). EXPFT$$ gives the length of time in years with months in decimal form. If there is no monthly calendar data available in a given year of a respondent’s career, the annual data from PBIOSPE is used for that year. In the most current wave the variable only uses up-to-date information from the newly answered Biography Questionnaires. If the year in which a spell started and ended is the same, and if there is no monthly data, a spell of 0.5 years is assumed. Persons without annual data (not contained in PBIOSPE) are only assigned a non-missing value for this variable if they joined SOEP by the age of 18 and if there is calendar data on them in ARTKALEN. Persons whose life course has been observed completely but with no spell of full-time employment are assigned the code (0). The code (-1) is assigned to all persons whose life course has not been observed completely. Persons with inconsistent information receive a (-3). Please also see EXPPT$$ and EXPUE$$. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) exppt$$ – Working Experience Part-Time Employment [generic] 0 13055 0.100000001490116 144 0.200000002980232 153 0.300000011920929 307 0.400000005960464 145 0.5 614 0.600000023841858 169 0.699999988079071 132 0.800000011920929 224 0.899999976158142 114 1 956 1.10000002384186 109 1.20000004768372 122 1.29999995231628 202 1.39999997615814 120 ... (353 rows omitted) 10372 43 3 43.7999992370605 1 44.4000015258789 1 44.5 1 SOEP Survey Papers 411 30 SOEP Core study (v32) bfpgen (v32) 44.7000007629395 1 44.9000015258789 1 45.2000007629395 1 45.5 1 45.7999992370605 1 46 1 47 2 47.0999984741211 2 48.7000007629395 1 49 1 -1 787 Waves: all This variable reflects the total length of part-time employment in the respondent’s career up to the point of the interview in a given year. The variable is created by combining monthly information on employment status from the calendar dataset ARTKALEN (which provides monthly information on activity status since an individual entered the SOEP) and annual information from the biographical dataset PBIOSPE (which provides information on activity status over the life course of an individual). EXPPT$$ gives the length of time in years with months in decimal form. If there is no monthly calendar data available in a given year of a respondent’s career, the annual data from PBIOSPE is used for that year. In the most current wave the variable only uses up-to-date information from the newly answered Biography Questionnaires. If the year in which a spell started and ended is the same, and if there is no monthly data, a spell of 0.5 years is assumed. Persons without annual data (not contained in PBIOSPE) are only assigned a non-missing value for this variable if they joined SOEP by the age of 18 and if there is calendar data on them in ARTKALEN. Persons whose life course has been observed completely but with no spell of full-time employment are assigned the code (0). The code (-1) is assigned to all persons whose life course has not been observed completely. Persons with inconsistent information receive a (-3). Please also see EXPFT$$ and EXPUE$$. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) expue$$ – Unemployment Experience [generic] 0 17340 0.100000001490116 356 0.200000002980232 311 0.300000011920929 412 0.400000005960464 190 0.5 1291 0.600000023841858 206 0.699999988079071 170 0.800000011920929 266 0.899999976158142 135 1 884 1.10000002384186 158 1.20000004768372 132 1.29999995231628 172 SOEP Survey Papers 411 31 SOEP Core study (v32) bfpgen (v32) 1.39999997615814 107 ... (205 rows omitted) 4802 23.7000007629395 1 24 7 24.2999992370605 1 24.8999996185303 1 25 3 25.2999992370605 1 25.8999996185303 1 26.1000003814697 1 27 1 27.2000007629395 1 28 3 29.2999992370605 1 33 1 38 1 -1 787 Waves: all This variable reflects the total length of unemployment in the respondent’s career up to the point of the interview in a given year. The variable is created by combining monthly information on employment status from the calendar dataset ARTKALEN (which provides monthly information on activity status since an individual entered the SOEP) and annual information from the biographical dataset PBIOSPE (which provides information on activity status over the life course of an individual). EXPUE$$ gives the length of time in years with months in decimal form. If there is no monthly calendar data available on a given year in a respondent’s career, the annual data from PBIOSPE is used for that year. In the most current wave the variable only uses up-to-date information from the newly answered Biography Questionnaires. If the year in which a spell started and ended is the same, and if there is no monthly data, a spell of 0.5 years is assumed. Persons without annual data (not contained in PBIOSPE) are only assigned a non-missing value for this variable if they joined SOEP by the age of 18 and if there is calendar data on them in ARTKALEN. Persons whose life course has been observed completely but with no spell of full-time employment are assigned the code (0). The code (-1) is assigned to all persons whose life course has not been observed completely. Persons with inconsistent information receive a (-3). Please also see EXPFT$$ and EXPPT$$. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Alexandra Fedorets (Tel. +49-30-89789-321) 10 School, Higher and Vocational Education isced97_$$ – ISCED-1997-Classification [generic] 0[0] in school 775 1[1] inadequately 634 2[2] general elementary 3371 3[3] middle vocational 12228 4[4] vocational + Abi 2090 5[5] higher vocational 1523 SOEP Survey Papers 411 32 SOEP Core study (v32) bfpgen (v32) 6[6] higher education 6365 -1 [-1] No Answer 757 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all The educational variable ($ISCED97) classifies all correspondents’ educational degrees according to the “International Standard Classification of Education (ISCED)” of 1997 in order to make degrees internationally comparable. The variable is generated retrospectively from 1984 onwards taking into account degrees and diplomas attained in both general schooling and in vocational/university education and indicates the highest degree obtained. E.g., persons who did not indicate secondary school degrees/diplomas but a university degree are placed in the highest ISCED category. Please note that, due to a lack of more detailed information on tertiary degrees in earlier waves – in particular on PhD – we include all tertiary degrees in ISCED category 6. Thus, the ISCED variable provided here is not comparable one-to-one with the ISCED levels as defined by the OECD, since we have included the original ISCED level 5A in our ISCED category 6. OECD (1999): Classifying Educational Programmes: Manual for ISCED-97 Implementation in OECD Countries, Paris. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) isced11_$$ – ISCED-2011-Classification [generic] 0[0] in school 775 1[1] Primary education 634 2[2] Lower secondary education 3366 3[3] Upper secondary education 12274 4[4] Post-secondary non-tertiary education 2220 5[5] Short-cycle tertiary education 471 6[6] Bachelors or equivalent level 5094 7[7] Masters or equivalent level 1893 8[8] Doctoral or equivalent level 260 -1 [-1] No Answer 756 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: 2010– The educational variable ($ISCED11) classifies all correspondents’ educational degrees according to the “International Standard Classification of Education (ISCED)” of 2011 in order to make degrees internationally comparable. The variable is generated retrospectively From 2010 onwards taking into account degrees and diplomas attained in both general schooling and in vocational/university education and indicates the highest degree obtained. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) SOEP Survey Papers 411 33 SOEP Core study (v32) bfpgen (v32) casmin$$ – CASMIN Classification [generic] 0[0] (0) In School 779 1[1] (1a) Inadequately Completed 634 2[2] (1b) General Elementary School 2448 3[3] (1c) Basic Vocational Qualification 5551 4[4] (2b) Intermediate General Qualification 1603 5[5] (2a) Intermediate Vocational 6416 6[6] (2c_gen) General Maturity Certificate 1078 7[7] (2c_voc) Vocational Maturity Certificate 1881 8[8] (3a) Lower Tertiary Education 1708 9[9] (3b) Higher Tertiary Education 4657 -1 [-1] No Answer 988 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all Another internationally comparable educational variable is $CASMIN where educational degrees/diplomas are classified according to the scheme “Comparative Analysis of Social Mobility in Industrial Nations (CASMIN)”. As for $ISCED, the variable is generated for all respondents retroactively from 1984 onwards and indicates the highest degree obtained by the respondent. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) $bilzeit – Amount Of Education Or Training In Years [generic] 7 546 8.5 68 9 2503 10 1640 10.5 3887 11 1429 11.5 4187 12 2661 13 1398 13.5 405 14 489 14.5 667 15 2147 16 836 17 98 18 2904 -1 1099 -2 779 Waves: all SOEP Survey Papers 411 34 SOEP Core study (v32) bfpgen (v32) The following statements describe the standard computation for schooling (including years of secondary vocational education). As can be seen, the code is not very differentiated. For example, special schools for health care professions and other kinds of specialized schools are all included in the “technical school” label. However, in Germany, this code is the most commonly used one when earnings functions based on human capital theory are estimated. $BILZEIT is now computed for all samples. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $psbil – School-Leaving Degree [generic] 1[1] Secondary School Degree 6411 2[2] Intermediate School Degree 7293 3[3] Technical School Degree 1515 4[4] Upper Secondary Degree 5729 5[5] Other Degree 4244 6[6] Dropout, No School Degree 673 7[7] Currently In School 779 -1 [-1] No Answer 1099 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all All respondents in all SOEP subsamples are asked about diplomas/degrees attained for completion of secondary/tertiary education (1984–1993 blue questionnaire; since 1994 biographical questionnaire) the first time they participate in SOEP. First: to generate this variable, the different diploma/degree categories provided for Subsamples B and D (see $PSBILA) as well as C (see $PSBILO) are integrated into the West German diploma/degree categories (Subsample A) and continued on in this form. Second: this data is regularly updated to take into account any changes in highest diploma/degree attained. With the survey of 2000, all educational information was collected again and is reflected in the variables. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $pbbil01 – Vocational Degree Received [generic] 1[1] Apprenticeship 9939 2[2] Vocational School 2256 3[3] Health Care School 194 4[4] Technical School 1501 5[5] Civil Service Training 526 6[6] Other Training 1442 7[7] Completed Vocational Training/Education in Germany 256 -1 [-1] No Answer 350 -2 [-2] Does not apply 11279 -3 [-3] Answer improbable 0 SOEP Survey Papers 411 35 SOEP Core study (v32) bfpgen (v32) -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all All respondents in all subsamples are asked about vocational degrees attained the first time they participate in SOEP (1984–1993 blue questionnaire; since 1994 biographical questionnaire). To generate the variable, the different vocational degrees for Subsamples B and D (cf. $PBBILA) as well as C (cf. $PBBILO) are integrated into the West German vocational degree categories (Subsample A). The categories that originally each constituted individual variables are combined to make them compatible with the annual question about changes in vocational degrees attained, and this data is updated annually. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $pbbil02 – College Degree [generic] 1[1] Technical College 1745 2[2] University, Technical College 3016 3[3] College Not In Germany 1001 4[4] Engineering, Techncial School (East) 218 5[5] University (East) 179 6[6] graduation, state doctorate 204 7[7] graduation, state doctorate (foreign country, east) 56 8[8] institution of higher education (youth) 0 9[9] Dual Studies, University of Cooperative Education 24 10 [10] Other Colleges (since 2014) 12 -1 [-1] No Answer 350 -2 [-2] Does not apply 20938 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all All respondents in all subsamples are asked about completed college education the first time they participate in SOEP (1984–1993 blue questionnaire; since 1994 biographical questionnaire). To generate the variable, the different degrees/dimplomas for all subsamples are integrated. Category (3) “college abroad” is only defined for persons who completed a foreignlanguage version of the questionnaire (mainly persons from Samples B and D). Generation of the variable entails combining the categories to make them compatible with the annual question about changes in vocational degrees/diplomas attained. Since 2002, there have been two separate codes (4 and 5) for degrees/diplomas attained in the former GDR. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $pbbil03 – No Vocational Degree [generic] 1[1] No Vocation Degree 5514 2[2] Apprenticeship 938 SOEP Survey Papers 411 36 SOEP Core study (v32) bfpgen (v32) 3[3] University 960 -1 [-1] No Answer 350 -2 [-2] Does not apply 19981 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all In connection with the question about vocational degrees ($PBBIL01 and $PBBIL02), all firsttime respondents to all subsamples are explicitly asked whether they (still) do not possess a vocational degree. In the subsequent years, this data is carried forward or updated. The variable has the Missing Value Code -2 (does not apply) if one of the other two variables on vocational degree has a positive value. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $psbilo – School-Leaving Degree East Germany [generic] 1[1] 8th Grade Completed 987 2[2] 10th Grade Completed 2135 3[3] College Entrance Exam 777 4[4] Other Degree 35 5[5] Dropout, No School Degree 23 6[6] Currently In School 0 -1 [-1] No Answer 0 -2 [-2] Does not apply 23786 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all As a supplement to the variable $PSBIL the highest secondary school degree/diploma in East Germany is provided as a separate variable and updated if necessary for 1991. Since 1992, secondary degrees/diplomas are asked only in the West German version. New SOEP respondents are also asked about secondary degrees/diplomas obtained in the former GDR; and for old respondents, the same codes are carried forward. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $pbbilo – Vocational Degree Received East Germany [generic] 1[1] Vocational Training 1608 2[2] Master Craftsman 171 3[3] Engineering, Technical Degree 358 4[4] Other Training 26 -1 [-1] No Answer 0 -2 [-2] Does not apply 25580 -3 [-3] Answer improbable 0 SOEP Survey Papers 411 37 SOEP Core study (v32) bfpgen (v32) -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all To supplement the variable $PBBIL01 the highest secondary school degree/diploma in East Germany is provided as a separate variable and updated if necessary for 1991. Since 1992 only the West German version has been used for new vocational degrees. For new SOEP respondents, vocational degrees attained in the former GDR are asked as well; for old respondents, the same codes are carried forward. From 2002 on, the questionnaire was expanded and revised, but this led to an operationalization involving more assumptions on the vocational degrees attained in the GDR; (from 2002 on, Code 3 is also listed as the additional category Code 4 in the integrated variables $PBBIL03 if this degree has not been replaced by a more recently attained, higher-level university or college degree). [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $psbila – School-Leaving Degree Outside Germany [generic] 1[1] School, No Degree 374 2[2] School, With Degree 1672 3[3] Vocational Extension School 2431 4[4] School Leaving Degree[Sbil] Acquired Abroad 1 -1 [-1] No Answer 5 -2 [-2] Does not apply 23260 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all As a supplement to the $PSBIL, this variable provides annually updated data on the highest secondary school degree/diploma attained abroad. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) $pbbila – Vocational Degree Outside Germany [generic] 1[1] On-The-Job Training 98 2[2] Vocational Training 390 3[3] Vocational School 494 4[4] College 917 5[5] Other 72 6[6] Vocational Degree[Bbil01] Acquired Abroad 7 7[7] College Education[Bbil02] Acquired Abroad 13 8[8] Completed Vocational Training/Education Other Country 994 9[9] graduation, state doctorate (foreign country) 38 -1 [-1] No Answer 0 -2 [-2] Does not apply 24720 -3 [-3] Answer improbable 0 SOEP Survey Papers 411 38 SOEP Core study (v32) bfpgen (v32) 13 [13] Glass Manufacturing Occupations 1 14 [14] Chemical Industry Occupations 0 15 [15] Plastics Manufacturing Occupations 0 16 [16] Paper Manufacturing and Processing 2 17 [17] Printing Occupations 10 ... (65 rows omitted) 1488 89 [89] Pastoral Occupations 3 90 [90] Personal Care Occupations 22 91 [91] Occupations in Hotels and Hospitality 17 92 [92] Occupations in Domestic and Nutritional Science 68 93 [93] Cleaning and Waste Management Occupations 2 96 [96] Others 47 97 [97] Family members providing assistance,not in agriculture,not otherw. mntnd 0 98 [98] Workers, (still) without specific occupation 0 99 [99] Workers, responsibilities not specified 2 -1 [-1] No Answer 39 -2 [-2] Does not apply 26035 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 The variable is designed to provide information on the occupation of full-time school based vocational training (e.g., Berufsfachschule, Schule des Gesundheitswesens, Handelsschule). See the description of variable TRAINA$$ for more details on the construction and the values of the variable. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) trainc$$ – Higher vocational school - two-digit occupation KldB92 [generic] 1[1] Agricultural Occupations (Crops) 26 2[2] Agricultural Occupations (Livestock) 5 3[3] Administrative/Advisory/Technical Specialist In Agriculture 11 5[5] Horticultural Occupations 11 6[6] Forestry and Hunting Occupations 3 7[7] Mineworkers 0 8[8] Mineral Exploitation and Processing 0 10 [10] Stonemasons 4 11 [11] Manufacturers of Construction Materials 0 12 [12] Ceramicists 2 13 [13] Glass Manufacturing Occupations 0 14 [14] Chemical Industry Occupations 3 15 [15] Plastics Manufacturing Occupations 0 16 [16] Paper Manufacturing and Processing 0 17 [17] Printing Occupations 4 ... (65 rows omitted) 894 89 [89] Pastoral Occupations 3 90 [90] Personal Care Occupations 18 SOEP Survey Papers 411 45 SOEP Core study (v32) bfpgen (v32) 91 [91] Occupations in Hotels and Hospitality 7 92 [92] Occupations in Domestic and Nutritional Science 19 93 [93] Cleaning and Waste Management Occupations 5 96 [96] Others 42 97 [97] Family members providing assistance,not in agriculture,not otherw. mntnd 0 98 [98] Workers, (still) without specific occupation 0 99 [99] Workers, responsibilities not specified 1 -1 [-1] No Answer 21 -2 [-2] Does not apply 26664 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 The variable is designed to provide information on the occupation of higher level vocational training (e.g., Meister, Techniker). See the description of variable TRAINA$$ for more details on the construction and the values of the variable. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) traind$$ – Civil servant training - two-digit occupation KldB92 [generic] 1[1] Agricultural Occupations (Crops) 0 2[2] Agricultural Occupations (Livestock) 0 3[3] Administrative/Advisory/Technical Specialist In Agriculture 0 5[5] Horticultural Occupations 0 6[6] Forestry and Hunting Occupations 2 7[7] Mineworkers 0 8[8] Mineral Exploitation and Processing 0 10 [10] Stonemasons 0 11 [11] Manufacturers of Construction Materials 0 12 [12] Ceramicists 0 13 [13] Glass Manufacturing Occupations 0 14 [14] Chemical Industry Occupations 0 15 [15] Plastics Manufacturing Occupations 0 16 [16] Paper Manufacturing and Processing 0 17 [17] Printing Occupations 0 ... (65 rows omitted) 331 89 [89] Pastoral Occupations 0 90 [90] Personal Care Occupations 0 91 [91] Occupations in Hotels and Hospitality 0 92 [92] Occupations in Domestic and Nutritional Science 0 93 [93] Cleaning and Waste Management Occupations 0 96 [96] Others 20 97 [97] Family members providing assistance,not in agriculture,not otherw. mntnd 0 98 [98] Workers, (still) without specific occupation 0 99 [99] Workers, responsibilities not specified 1 -1 [-1] No Answer 9 -2 [-2] Does not apply 27380 SOEP Survey Papers 411 46 SOEP Core study (v32) bfpgen (v32) -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 The variable is designed to provide information on the occupation of civil servant training (“Beamtenausbildung”). See the description of variable TRAINA$$ for more details on the construction and the values of the variable. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) fdt_f$$ – Data source FIELD, DEGREE, TRAIN [generic] 1[1] Individual Questionnaire 2751 2[2] Gap Questionnaire (temporary drop-outs) 11 3[3] Biographical Questionnaire 12289 4[4] Various Sources 41 -1 [-1] No Answer 0 -2 [-2] Does not apply 12651 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 This is a flag variable which provides information on the data sources used for the construction of the variables FIELD$$, DEGREE$$, TRAINA$$, TRAINB$$, TRAINC$$ and TRAIND$$ (see the description of the respective variables for details). [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) bilztch$$ – Change in Education since last survey / last year [generic] 0[0] Consistent educational information since last survey 22570 1[1] Inconsistent educational information since last survey 11 2[2] Inconsistent educational information since last year 2 -1 [-1] No Answer 0 -2 [-2] Does not apply 5160 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 This is a flag variable which identifies observations with inconsistent changes in the information on highest educational qualification compared to the previous observation or year. Questions on highest educational attainment have been asked in the first survey and were only updated in subsequent years if the respondent reported a change. In the year 2000, every single SOEP participant was asked his highest level of educational attainment which SOEP Survey Papers 411 47 SOEP Core study (v32) bfpgen (v32) produced a number of inconsistencies between the most recent information from 2000 and the generated information from previous years. These inconsistencies include both higher and lower educational attainment and are not just due to repeating the question about educational attainment in 2000. They also occur more generally, although to a lower degree, in the second survey wave of new samples when respondents to individual and life history questionnaires are asked to state their educational attainment. In both situations, respondents are not only asked annual questions about any changes in educational attainment since the previous year, but are also asked to state their highest level of educational attainment. In our view there is no means of unequivocally correcting for these inconsistencies. The flag variable helps researchers to identify observations with inconsistent answers to educational questions in the cross-sectional perspective. Researchers need to decide how to deal with these on a case-bycase basis depending on the research question at hand. So far, we have not found evidence that respondents with a change in the year 2000 differed systematically from other respondents. One possible approach would be to exclude these individuals from the analysis when sample size allows. Alternatively, one could apply the information collected in 2000 to the prior years in which no changes were recorded between two years and test whether the results differ from those obtained when these individuals are left out. Since 2011, a Beta version of BIOEDU has also been made available, containing new data on consistent longitudinally tested educational transitions. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) bilztev$$ – Change in Education, total observed period [generic] 0[0] Consistent educational information 20686 1[1] Inconsistent educational decline 883 2[2] Inconsistent educational increase 1860 3[3] Inconsistent educational decline and increase 136 -1 [-1] No Answer 0 -2 [-2] Does not apply 4178 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: -1985 This flag variable identifies observations with at least one inconsistent change in the information given on individual highest educational qualification over the whole observation period. See the description of variable BILZTCH$$ for more details on the sources of these inconsistencies. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Charlotte Bartels (Tel. +49-30-89789-346) 11 Information on the Interview month$$ – Month Of Interview [generic] 1[1] January 146 2[2] February 5236 SOEP Survey Papers 411 48 SOEP Core study (v32) bfpgen (v32) 3[3] March 6384 4[4] April 3250 5[5] May 2190 6[6] June 3000 7[7] July 2853 8[8] August 1812 9[9] September 1564 10 [10] October 1026 11 [11] November 279 12 [12] December 3 -1 [-1] No Answer 0 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all Month of interview is generated using the answers to the individual questionnaire. Missing answers are filled in using data from the $hbrutto files. Interviews that took place in December and before the 20th of that month were recoded -3. [This information can be related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) mode$$ – Interview Method [generic] 100 [100] With Interviewer Assistance 0 110 [110] Oral Interview 1508 120 [120] Written Ques. Interviewer 3291 130 [130] Mixed Type 0 131 [131] Written Ques. No Interviewer 253 132 [132] Oral And Written 351 133 [133] Proxy 0 134 [134] Third Person Present 0 135 [135] No Third Person Present 0 140 [140] CAPI - Since 1998 (O) 17851 150 [150] Cawi Since 2014 (BE) 1950 200 [200] Telephone Assistance 0 210 [210] Written, By Mail 2538 220 [220] Telephone Interview 1 -1 [-1] No Answer 0 -2 [-2] Does not apply 0 -3 [-3] Answer improbable 0 -4 [-4] Inadmissible multiple response 0 -5 [-5] Not included in this version of the questionnaire 0 -6 [-6] Version of questionnaire with modified filtering 0 Waves: all The interview method is generated via the answers to the questions in the individual questionnaire. Missing answers are filled in from the $pbrutto files. [This information can be SOEP Survey Papers 411 49 SOEP Core study (v32) bfpgen (v32) related to a specific variable and is not necessary generic.] For more information, contact: Peter Krause (Tel. +49-30-89789-690) SOEP Survey Papers 411 50