SOEP-Core v38 - Codebook for the $PEQUIV file 1984-2020: CNEF variables with extended income information for the SOEP

Grabka, Markus M. Research Report SOEP-Core v38 - Codebook for the $PEQUIV file 1984-2020: CNEF variables with extended income information for the SOEP SOEP Survey Papers, No. 1333 Provided in Cooperation with: German Institute for Economic Research (DIW Berlin) Suggested Citation: Grabka, Markus M. (2023) : SOEP-Core v38 - Codebook for the $PEQUIV file 1984-2020: CNEF variables with extended income information for the SOEP, SOEP Survey Papers, No. 1333, Deutsches Institut für Wirtschaftsforschung (DIW), Berlin This Version is available at: https://hdl.handle.net/10419/278806 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. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. 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. https://creativecommons.org/licenses/by-sa/4.0/ 1333 2023 Series D – Variable Descriptions and Coding SOEP-Core v38 – Codebook for the $PEQUIV File 1984-2020: CNEF Variables with Extended Income Information for the SOEP Markus M. Grabka 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. Carina Cornesse, DIW Berlin and University of Bremen Dr. Jan Goebel, DIW Berlin Prof. Dr. Cornelia Kristen, University of Bamberg and DIW Berlin Prof. Dr. Philipp Lersch, DIW Berlin and Humboldt-Universität zu Berlin Prof. Dr. Carsten Schröder, DIW Berlin and Freie Universität Berlin Prof. Dr. Jürgen Schupp, DIW Berlin and Freie Universität Berlin Prof. Dr. Sabine Zinn, DIW Berlin and Humboldt-Universität zu Berlin Please cite this paper as follows: Markus M. Grabka, 2023. SOEP-Core v38 – Codebook for the $PEQUIV File 1984-2020: CNEF Variables with Extended Income Information for the SOEP. SOEP Survey Papers 1333: Series D – Variable Descriptions and Coding. Berlin: DIW Berlin/SOEP This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. © 2023 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 at DIW Berlin SOEP-Core v38 – Codebook for the $PEQUIV File 1984-2020: CNEF Variables with Extended Income Information for the SOEP Markus M. Grabka 2023 2 Preface The $PEQUV-File is based on the Cross-National Equivalent File (CNEF) with extended income information for the SOEP. This file comprises not only the aggregated income figures provided in the CNEF but also further single income components. The CNEF is a joint effort of researchers and staff affiliated with State Ohio University, the DIW Berlin, the University of Essex, Statistics Canada, the Melbourne Institute of Applied Economics and Social Research (MI), the Korea Labor Institute and the Swiss Foundation for research in Social Sciences (FORS) funded by the National Institute on Aging and by the DIW Berlin. For extensive documentation of the CNEF cf. https://cnef.ehe.osu.edu/ or: Joachim R. Frick, Stephen P. Jenkins, Dean R. Lillard, Oliver Lipps, and Mark Wooden (2007): The Cross-National Equivalent File (CNEF) and its Member Country Household Panel Studies. In: Schmollers Jahrbuch (Journal of Applied Social Science Studies), 127(4), 627-654. General notes: • In contrast to the original CNEF-data which is based on the 95% scientific use file of SOEP, the $PEQUIV-files include the full 100%-sample. • The SOEPv37 release of the $PEQUIV-files has been updated to include the 2020 (wave BK) SOEP data. • Population for $PEQUIV is made up by all members of households who were successfully interviewed (i.e., persons with $NETTO-codes 10 to 39 in the file PPFAD and $HNETTO-code 1 in the file HPFAD (since 2021, weighted=1 is used instead of $HNETTO=1). • For longitudinal consistency, all $PEQUIV income variables are consistently expressed in EURO (1 Euro = 1,95583 DM) independent of the currency used in the underlying survey instruments. • Income data is missing for Sample C in 1990 and 1991 (first 2 waves of East German sample). • Income data is missing for Sample M3/M4 (M5, M6, M7) in 2016 (2017, 2020, 2020) as not all income information was collected for this sample in the respective years. • First time respondents of the refugee samples (M3-M5, M7, M8) got a questionnaire with a reduced set of income questions. Thus, for all households with such interviewees, household income will be underestimated and hence all weighting factors for all household members in the respective wave has been set to Nil. An important distinction from the original CNEF data, is that the $PEQUIV-files have been extended to also cover all single income components considered in the aggregated annual income figures of the CNEF. In principle, these single income components correspond to the originally surveyed inforSOEP Survey Papers 1333 v38 3 mation (which is stored in the $P, $PKAL and $H files, respectively) with some important amendments: • Income variables are harmonized with respect to the periodicity, i.e. they give annual income (as of the previous calendar year). Components which are asked at monthly level have been multiplied by the number of months with receipt of the respective income (eventually, this implies imputation of missing number of months in the originally surveyed data as well as a longitudinally verified correction of implausible values). • Any missing income information due to item-non response has been imputed according to the longitudinal and cross-sectional imputation procedures described in: Frick, J.R. and Grabka, M.M. (2005): Item-Non-Response on Income Questions in Panel surveys: Incidence, Imputation and the Impact on the Income Distribution. Allgemeines Statistisches Archiv (AStA) 89, 49-61. • Any missing income information due to partial unit non response (PUNR, non responding individuals in households with at least one successful interview) has been imputed according to the longitudinal and cross-sectional imputation procedures described in: Frick, J.R.; M.M. Grabka and O. Groh-Samberg (2010): Dealing with Incomplete Household Panel Data in Inequality Research. SOEP Papers on Multidisciplinary Panel Data Research at DIW Berlin, No. 290, Berlin (see: http://www.diw.de/documents/publikationen/73/diw_01.c.354683.de/diw_sp0290.pdf forthcoming in Sociological Methods and Research) . Due to lacking detailed information about income receipt, only six income components have been imputed: individual labour income (I11110$$), social security pensions (I11108$$), unemployment benefits (IUNBY$$), maternity benefits (IMATY$$), student grants (ISTUY$$) and private transfers (IELSE$$). This information is also used to generate a more thorough measure for taxes and social contributions paid by private households. • An imputation flag for each of these single income components has been specified. These flags take a value of 1 if item-non-response on the underlying income variable has been imputed and 0 otherwise. General variable naming conventions for the $PEQUIV-variables: (see variable list on page 4): • Variable names are longitudinally consistent using a two-digit suffix – instead of a four-digit suffix used in the original CNEF-files – indicating the survey year (wave A = 84, wave B = 85, ..., wave BL = 21, $$ =84, 85, …, 21). Variable naming conventions for the single income components: • Variable names related to income components at the individual level start with the prefix “I”, e.g., Christmas bonus is given in variable IXMAS$$. • The prefix “F” indicates the imputation flag, e.g. the flag variable for rental income (RENTY$$) is given by FRENTY$$. For further information please contact: Markus M. Grabka ([email protected]). SOEP Survey Papers 1333 v38 4 Variables in the cross-sectional $PEQUIV Files Label Variable List Page Identifiers: Unique Person Number X11101LL 10 Household Identification Number X11102$$ 11 Individual in Household at Survey X11103$$ 12 Sub-sample Identifier X11104LL 13 Person in Household Interviewed X11105$$ 14 Demographics : Age of Individual D11101$$ 15 Sex of Individual D11102LL 16 Race of Household Head D11103$$ 17 Marital Status of Individual D11104$$ 18 Relationship to Household Head D11105$$ 19 Number of Persons in Household D11106$$ 20 Number of Children in Household D11107$$ 21 Education With Respect to High School D11108$$ 22 Number of Years of Education D11109$$ 23 Race of Individual D11112LL 24 Employment: Annual Work Hours of Individual E11101$$ 25 Impute Annual Work Hours of Individual E11201$$ 26 Employment Status of Individual E11102$$ 27 Employment Level of Individual E11103$$ 28 Primary Activity of Individual E11104$$ 29 Occupation of Individual E11105$$ 30 1 Digit Industry Code of Individual E11106$$ 31 2 Digit Industry Code of Individual E11107$$ 32 Equivalence scale inputs: Number HH members age 0-13 H11101$$ 34 Number HH members age 14-18 H11102$$ 34 Number HH members age 0-1 H11103$$ 34 Number HH members age 2-4 H11104$$ 34 Number HH members age 4-7 H11104$$ 34 Number HH members age 8-10 H11106$$ 34 Number HH members age 11-12 H11107$$ 34 Number HH members age 13-14 H11108$$ 34 Number HH members age 16-18 H11109$$ 34 Number HH members age 19+ or 16-18 and indep. H11110$$ 34 Indicator - Wife/spouse in Household H11112$$ 36 Equivalence weight algorithms: OECD Equivalence Weight 37 Modified OECD Equivalence Weight Other Equivalence Weights Location: Federal State of Residence L11101$$ 38 Region of Residence L11102$$ 39 Macro-level variables: Consumer Price Index Y11101$$ 40 SOEP Survey Papers 1333 v38 5 Label Variable List Page Aggregated income variables: Household Pre-Government Income I11101$$ 41 Household Post-Government Income I11102$$ 42 Household Labor Income I11103$$ 43 Household Asset Income I11104$$ 44 Household Imputed Rental Value I11105$$ 45 Household Private Transfers I11106$$ 46 Household Public Transfers I11107$$ 47 Household Social Security Pensions I11108$$ 48 Total Household Taxes I11109$$ 49 Individual Labor Earnings I11110$$ 50 Household Federal Taxes I11111$$ 51 Household Social Security Taxes I11112$$ 52 Household Post-Government Income (TAXSIM) I11113$$ 53 Total Household Taxes (TAXSIM) I11114$$ 54 Household State Taxes (TAXSIM) I11115$$ 54 Household Federal Taxes (TAXSIM) I11116$$ 54 Household Private Retirement Income I11117$$ 54 Household Windfall Income I11118$$ 55 Imputation flag: Share of imputed Household Pre-Government Income I11201$$ 56 Imputation flag: Share of imputed Household Post-Government Income I11202$$ Imputation flag: Share of imputed Household Labor I11203$$ Imputation flag: Share of imputed Household Asset Income I11204$$ Imputation flag: Share of imputed Household Private Transfers I11206$$ Imputation flag: Share of imputed Household Public Transfers I11207$$ Imputation flag: Share of imputed Household Social Security Pensions I11208$$ Imputation flag: Share of imputed Private Retirement Income I11217$$ mputation flag: Total Household Taxes I11209$$ 57 Imputation flag: Household Imputed Rental Value I11205$$ Imputation flag: Share of imputed Individual Labor Earnings I11210$$ 58 Imputation flag: Household Windfall Income I11218$$ 59 Single income components at the household level: Income from rental and leasing RENTY$$ 60 Operation, maintenance costs OPERY$$ 61 Interest, dividend income DIVDY$$ 62 Child allowance CHSPT$$ 63 Housing benefit HOUSE$$ 64 Nursing allowances NURSH$$ 65 Social assistance SUBST$$ 66 Social assistance for special circumstances SPHLP$$ 67 Social assistance for elderly SSOLD$$ 68 Unemployment benefit II ALG2$$ 69 Housing support for owner-occupiers HSUP$$ 70 Losses from renting and leasing LOSSR$$ 71 Losses from capital investment LOSSC$$ 72 Additional child benefit ADCHB$$ 73 Child care subsidy CHSUB$$ 74 Income of children KIDY$$ 75 Benefits from the educational package EDUPAC$$ 76 Asylum seeker benefit ASYL$$ 77 Building subsidy for new property owners BAUK$$ 78 SOEP Survey Papers 1333 v38 6 Label Variable List Page Imputation flag: Income from rental and leasing FRENTY$$ 79 Imputation flag: Operation, maintenance costs FOPERY$$ Imputation flag: Interest, dividend income FDIVDY$$ Imputation flag: Child allowance FCHSPT$$ Imputation flag: Housing benefit FHOUSE$$ Imputation flag: Nursing allowances FNURSH$$ Imputation flag: Social assistance FSUBST$$ Imputation flag: Social assistance for spec. circumst. FSPHLP$$ Imputation flag: Social assistance for elderly FSSOLD$$ Imputation flag: Unemployment benefit II FALG2$$ Imputation flag: Housing support for owner-occupiers FHSUP$$ Imputation flag: Losses from renting and leasing FLOSSR$$ Imputation flag: Losses from capital investment FLOSSC$$ Imputation flag: Additional child benefit FADCHB$$ Imputation flag: Child care subsidy FCHSUB$$ Imputation flag: Income of children FKIDY$$ Imputation flag: Benefits from the educational package FEDUPAC Imputation flag: Asylum seeker benefit FASYL Imputation flag: Building subsidy for new property owners FBAUK$$ Single income components at the individual level: Wages, Salary from main job IJOB1$$ 80 Income from secondary employment IJOB2$$ 81 Income from self-employment ISELF$$ 82 Combined old-age, disability, etc. pensions IOLDY$$ 83 Combined widows and orphans pension IWIDY$$ 84 Combined company pension ICOMP$$ 85 Combined private pension IPRVP$$ 86 Unemployment benefit IUNBY$$ 87 Unemployment assistance IUNAY$$ 88 Subsistence allowance ISUBY$$ 89 Old-age transition benefit IERET$$ 90 Maternity benefit IMATY$$ 91 Student grants ISTUY$$ 92 Military community service pay IMILT$$ 93 Alimony IALIM$$ 94 Advance child maintenance payment IACHM$$ 95 Child support, caregiver alimony ICHSU$$ 96 Divorce alimony, during separation ISPOU$$ 97 Private Transfers received IELSE$$ 98 Profit Withdrawal IWITH$$ 99 Sickness benefit ISICK$$ 100 13th monthly salary I13LY$$ 101 14th monthly salary I14LY$$ 102 Christmas bonus IXMAS$$ 103 Vacation bonus IHOLY$$ 104 Profit-sharing IGRAY$$ 108 Other bonuses IOTHY$$ 106 Commuting expenses, travel grant ITRAY$$ 107 Indemnity payments IDEMY$$ 108 Statutory pension insurance IGRV1$$ 109 Social miners insurance pension ISMP1$$ 110 Civil servant pension ICIV1$$ 111 War victim pension IWAR1$$ 112 Farmer Pension IAGR1$$ 113 SOEP Survey Papers 1333 v38 13 Variable Name X11104LL Variable Label Sub-sample Identifier Unit of Observation Individual Description This variable indicates from which sub sample an individual in the SOEP is drawn. Method The SOEP contains several different samples. (1) 'A 1984 Initial Sample (West)' (2) 'B 1984 Migration (until 1983, West)' (3) 'C 1990 Initial Sample (East)' (4) 'D 1994/5 Migration (1984-1994, West)' (5) 'E 1998 Refreshment' (6) 'F 2000 Refreshment' (7) 'G 2002 High Income' (8) 'H 2006 Refreshment' (9) 'I 2009 Innovation Sample' (10) 'J 2011 Refreshment' (11) 'K 2012 Refreshment' (12) 'L1 2010 Birth Cohort (2007-2010)' (13) 'L2 2010 Family Type (Low-Income, Single-Parent, Large Families)' (14) 'L3 2011 Family Type (Single-Parent, Large Families)' (15) 'M1 2013 Migration (1995-2011)' (16) 'M2 2015 Migration (2009-2013)' (17) 'M3 2016 Refugee (2013-2015)' (18) 'M4 2016 Refugee/family (2013-2015)' (19) 'M5 2017 Refugee (2013-2016)' (20) 'N 2017 Refreshment (PIAAC-L)' (21) 'O 2018 Refreshment (Social City)' (22) 'P 2019 Top Shareholder' (23) 'Q 2019 Lesbian-Gay-Bisexual (LGB) ' (24) 'M6 2020 Refugee (2016)' (25) 'M7 2020 Migration (Bulgarian, Polish, Romanian nationality 2013-2016)' (26) 'M8 2020 Migration (Evaluation the residence act)' The original survey variables provided below can be found in the files PPFAD/PPATHL. Algorithm X11104LL = psample SOEP Survey Papers 1333 v38 14 Variable Name X11105$$ Variable Label Indicator of Whether Person in Household was Interviewed Unit of Observation Individual Description Indicates whether an individual present in the household provided interview responses. Children in the household are counted as interviewed persons. Method Individuals in the household 16 years of age and older who are members of a surveyed household reject to give an interview are given a 0. Format 0 = Didn’t provide information 1 = Provided information The original survey variables provided below can be found in the file PPFAD. This algorithm omits individuals with survey non-responses. Algorithm If Ynetto >= 10 & Ynetto < 30 then X11105$$ = 1; else X11105$$ = 0; SOEP Survey Papers 1333 v38 15 Variable Name D11101$$ Variable Label Age of Individual Unit of Observation Individual Description Indicates the age of the individual in years. Method The SOEP records the birth date (GEBJAHR) of each individual. The current age of an individual is created by subtracting the year of birth from the current year. Format -1 = Item non-response 0 = Newborn up to first birthday The value of this variable ranges from 0 to 105. The original survey variables provided below can be found in the file PPFAD. This algorithm omits individuals with survey non-responses. Algorithm D11101$$ = SYEAR - GEBJAHR ($$=84, 85, …) SOEP Survey Papers 1333 v38 16 Variable Name D11102LL Variable Label Gender of Individual Unit of Observation Individual Description Indicates the gender of the individual. Method The SOEP records the gender (SEX) of each individual. This information is acquired once and is not obtained in subsequent years. Gender is constant through time and therefore does not have a yearly suffix. This variable is missing for the few cases where information about gender was not reported and inferences about gender could not be made. Format -1 = Item non-response 1 = Male 2 = Female The original survey variables provided below can be found in the file PPFAD. This algorithm omits individuals with survey non-responses. Algorithm D11102LL = SEX SOEP Survey Papers 1333 v38 17 Variable Name D11103$$ Variable Label Race of Household Head Unit of Observation Individual Description Indicates the race of the interviewed head of household. Method Race is not available in the SOEP. However, to separate Germans from non-Germans use the variables about o nationality (NATION$$) which can be found in the $PGEN-files or o the information about whether a person was born in Germany (GERMBORN) or o the country of origin (CORIGIN) whereas both can be found in the PPFAD-file. Format -1 = no information available SOEP Survey Papers 1333 v38 18 Variable Name D11104$$ Variable Label Marital Status of Individual Unit of Observation Individual Description This variable indicates the marital status in the current survey year of all individuals in the household 16 years of age and older. Method The married category represents individuals who are legally married and individuals who are living with a partner. Married non-German "guest workers" whose spouses remained in their native countries are given a code of 6 or 7 depending on their ages. Format -1 = N/A – Child / Item non-response 1 = Married / Living with a Partner 2 = Single 3 = Widowed 4 = Divorced 5 = Separated (Legally Married) The original survey variables provided below can be found in the file _PGEN. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: D11101__ = Age of Individual Algorithm if D11101$$ ge 16 then do if Yfamstd = 1,6,7 then D11104$$ = 1 else if Yfamstd = 2,8 then D11104$$ = 5 else if Yfamstd = 3 then D11104$$ = 2 else if Yfamstd = 4 then D11104$$ = 4 else if Yfamstd = 5 then D11104$$ = 3 end if D11101$$ lt 16 then D11104$$ = -1 SOEP Survey Papers 1333 v38 19 Variable Name D11105$$ Variable Label Relationship to Household Head Unit of Observation Individual Description This variable indicates the individual's relationship to the current survey year’s head of household. Method The relation to head variable is created by collapsing the SOEP relationship to head variable into 5 categories. These categories include spouses, life-partners, children, foster children, siblings, parents, in-laws, grandchildren, other relatives, and unrelated persons. Since 2012 (wave 29) the original SOEP variable collects more detailed information about family relationships. Format -1 = Item non-response 1 = Head 2 = Partner 3 = Child 4 = Relative 5 = Non-relative The original survey variables provided below can be found in the file _PBRUTTO. This algorithm omits individuals with survey non-responses. Algorithm if i ge 1 and I le 28 then do; if Ystell = 0 then D11105$$ = 1 else if Ystell = 1,2,13 then D11105$$ = 2 else if Ystell = 3 or 4 then D11105$$ = 3 else if Ystell = 5, 6, 7, 8, 9, 10 then D11105$$ = 4 else if Ystell =11,12,13 then D11105$$ = 5 else D11104$$ = -1 end; if i ge 29 then do; if Ystell = 0 then D11105$$ =1 else if Ystell in (11,12,13) then D11105$$ =2 else if Ystell in (21,22,23,24) then D11105$$ =3 else if Ystell in (25,26,31,36,41,42,43,61,62,63,64) then D11105$$ =4 else if Ystell in (27,32,33,35,45,51,52,71) then D11105$$ =5 else D11105$$ =-1 end; SOEP Survey Papers 1333 v38 20 Variable Name D11106$$ Variable Label Number of Persons in Household Unit of Observation Household Description Indicates the number of persons in the household at the time of the interview. Method This information is obtained from the household head or another household member who knows about the household's composition. Format -1 = Item non-response The value of this variable ranges from 1 to 17. The original survey variables provided below can be found in the file _HBRUTTO. This algorithm omits individuals with survey non-responses. Algorithm D11106$$ = Yhhgr SOEP Survey Papers 1333 v38 21 Variable Name D11107$$ Variable Label Number of Children in Household Unit of Observation Household Description Indicates the number of persons in the household under age of 18 at the time of the interview. Method This variable is created by computing the number of individuals in the household under the age of 18. Format -1 = Item non-response The value of this variable ranges from 0 to 10. The original survey variables provided below can be found in the file $PPFAD. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: D11101__ = Age of Individual Algorithm if age$$ ge 0 and age$$ le 17 then sumkids$$=1 if age$$ = . and $netto in (20-27) then sumkids$$=1 D11107$$ = sum of (sumkids$$) in the household SOEP Survey Papers 1333 v38 22 Variable Name D11108$$ Variable Label Education With Respect to High School Unit of Observation Individual Description This variable indicates the highest level of education (less than high school, completed high school, or more than high school) of all individuals in the household 16 years of age and older. Method This variable is coded as follows: Less than = Intermediate secondary school (Realschule) High School Lower secondary school (Hauptschule) Other None High School = Upper secondary school degree giving access to university studies (Abitur) Certificate of aptitude for specialized short-course higher education (Fachhochschulreife) Apprenticeship (Lehre) Specialized vocational school (Berufsfachschule) More than = School of health care (Schule des Gesundheitswesens) High School Specialized college of higher education, post-secondary technical (Fachhochschule) College Technical university usually requiring practical training as part of the studies (Technische Universität) Civil service training Format -1 = N/A – Child / Item non-response 1 = Less than High School 2 = High School 3 = More than High School The original survey variables provided below can be found in the file _PGEN. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: D11101__ = Age of Individual Algorithm if Ypsbil=.B then Ypsbil=0; if Ypbbil01=.B then Ypbbil01=0; if Ypbbil02=.B then Ypbbil02=0; if Ypsbil in (1,2,5,6) then D11108$$=1; if Ypsbil in (3,4) then D11108$$=2; if Ypbbila in (3) then D11108$$=2; if Ypbbila in (4) then D11108$$=3; if Ypbbilo in (1) then D11108$$=2; if Ypbbilo in (2,3,4) then D11108$$=3; if Ypbbil01 in (1,2,4) then D11108$$=2; if Ypbbil01 in (3,5) then D11108$$=3; if Ypbbil02 in (1,2,3) then D11108$$=3; if D11108$$ lt 0 then D11108$$=.M; SOEP Survey Papers 1333 v38 29 Variable Name E11104$$ Variable Label Primary Activity of Individual Unit of Observation Individual Description This variable indicates primary activity at the time of the survey for all individuals in the household 16 years of age and older. Method This variable is based on the individual's self-reported employment status at the time of the interview. If the individual reported being full-time, part-time, or marginally employed, having short-time work, performing military/civilian service, on maternity leave, or being engaged in in-company training then the individual is considered to be working now. If the individual reported not being employed or being unemployed then the individual is considered to be not working now. Unemployed is not a category in the recoded variable because in the original data individuals were able to choose unemployed as their employment status in 1984 through 1990 only. Format -1 = N/A – Child -2 = Item-non response 1 = Working Now 2 = Not Working Now The original survey variables provided below can be found in the file _P. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: D11101__ = Age of Individual Algorithm 1984-1990: if D11101$$ ge 16 or psample=3 then do if VAR=1, 2, 3, 4 then E11104$$=1 else if VAR=5, 6 or 7 then E11104$$=2 else E11104$$=-2 end else E11104$$=-1 (VAR=ap08, bp16, cp16, dp12, ep12 , fp10, gp12, zp16, $$=84-90) 1991-1995: if D11101$$ ge 16 then do if VAR=1, 2, 3, 4, 5, or 6 then E11104$$=1 else if VAR=7, 8 or 9 then E11104$$=2 else E11104$$=-2 end else E11104$$=-1 (VAR=hp15, ip15, jp15, kp25, lp21, $$=91-95) since 1996: if D11101$$ ge 16 then do if VAR=1, 2, 3, 4, 8 then E11104$$=1 else if VAR=5, 6, 7, 9 then E11104$$=2 else E11104$$=-2 end else E11104$$=-1 (VAR=mp15, np11, op09, pp10, qp10, rp12, sp15, tp34, up09,vp10,wp07,xp13, yp19, zp09, bap09,bbp09,bcp11,bdp18,bep12,bfp32, bg31,bhp_33, bip_43, bjp_29, bkp_34, blp_31 $$=96-…) 30 Variable Name E11105$$ Variable Label Occupation of Individual Unit of Observation Individual Description This variable indicates occupation at the time of the survey for all individuals in the household 16 years of age and older. Method This variable is based on the individual’s self-reported occupation at the time of the interview given by ISCO-88 occupation code (IS88$$ = International standard classification of occupations). Occupation is coded as not applicable for individuals who were not working at the time of the interview. Format -1 = N/A – Child -2 = Item Non-response A documentation for all other values of the ISCO-88 information (IS88$$ is a variable with four digits) can be found at: http://www.ilo.org The original survey variables provided below can be found in the file _PGEN. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: E11104$$ = Primary Activity of Individual Algorithm if X11103$$ = 1 then do if E11104$$ in (5,6,7,8) then E11105$$=0; else if E11104$$ in (1,2,3,4) and is88$$ le 0 then E11105$$=-1; else if E11104$$ in (1,2,3,4) and is88$$ gt 0 then E11105$$=IS88$$; else E11105$$=-2; end; 31 Variable Name E11106$$ Variable Label 1 Digit Industry of Individual Unit of Observation Individual Description This variable indicates industry in which each individual in the household 16 years of age and older is employed at the time of the survey. Method This variable is based on the individual’s self-reported industry of occupation at the time of the interview. This variable is created by collapsing the SOEP industry variable into 10 broad categories. Industry is coded as not applicable for individuals who were not working at the time of the interview. Format -1 = N/A – Child / Item Non-response 0 = Not Applicable 1 = Agriculture 2 = Energy 3 = Mining 4 = Manufacturing 5 = Construction 6 = Trade 7 = Transport 8 = Bank/Insurance 9 = Services 10 = Other The original survey variables provided below (NACE$$/NACE2$$) can be found in the file _PGEN. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: E11104$$ = Primary Activity of Individual Algorithm if X11103$$ = 1 then do if E11104$$ in (5,6,7,8) then E11106$$=0; else if E11104$$ in (1,2,3,4) and nace$$ le 0 then E11106$$=-1; else if E11104$$ in (1,2,3,4) and nace$$ gt 0 then do; if nace$$ in (1,2,5) then E11106$$=1; if nace$$ in (40,41) then E11106$$=2; if nace$$ in (10,11,12,13,14) then E11106$$=3; if nace$$ in (15,16,17,18,19,20,21,22,23,24,25,26,27,28,29, 30,31,32,33,34,35,36,37,96,97,100) then E11106$$=4; if nace$$ in (45) then E11106$$=5; if nace$$ in (50,51,52,55) then E11106$$=6; if nace$$ in (60,61,62,63,64) then E11106$$=7; if nace$$ in (65,66,67) then E11106$$=8; if nace$$ in (70,71,72,73,74,75,80,85,90,91,92,93,95,98,99) then E11106$$=9; end; else E11106$$=-2; end; 32 Variable Name E11107$$ Variable Label 2 Digit Industry of Individual Unit of Observation Individual Description This variable indicates industry in which each individual in the household 16 years of age and older is employed at the time of the survey. Method This variable is based on the individual’s self-reported industry of occupation at the time of the interview (NACE$$, since 2018 NACE2_$$). Industry is coded as not applicable for individuals who were not working at the time of the interview. Format -1 = N/A – Child / Item Non-response -2 = Survey Non-response 0 = Not Applicable 18= Retail 1= Agric.,Forestry 19= Train System 2= Fisheries 20= Postal System 3 = Energy/Water 21= Other Trans. 4 = Mining 22= Financial Inst 5 = Chemicals 23= Insurance 6= Synthetics 24= Restaurants 7= Earth/Clay/Stone 25 = Service Indust 8 = Iron/Steel 26 = Trash Removal 9= Mechanical Eng 27 = Educ./Sport 10= Electrical Eng 28 = Health Service 11= Wood/Paper/Print 29 = Legal Services 12= Clothing/Text 30 = Other Services 13= Food Industry 31 = Volunt./Church 14= Construction 32 = Priv. Househld 15= Constr. Relate 33 = Public Administration 16= Wholesale 34 = Social Security 17= Trading Agents 99= Not attributable The original survey variables provided below (NACE$$) can be found in the file _PGEN. This algorithm omits individuals with survey non-responses. Equivalent Data File Variable Definitions: E11104$$ = Primary Activity of Individual Algorithm if X11103$$ = 1 then do if E11104$$ in (5,6,7,8) then E11107$$=0; else if E11104$$ in (1,2,3,4) and NACE$$ le 0 then E11107$$=-1; else if E11104$$ in (1,2,3,4) and NACE$$ gt 0 and I le 34 then do; if Nace$$ in (1,2) then E11107$$=1; if Nace$$ in (5) then E11107$$=2; if Nace$$ in (40,41) then E11107$$=3; if Nace$$ in (10,11,12,13,14) then E11107$$=4; if Nace$$ in (23,24) then E11107$$=5; if Nace$$ in (25) then E11107$$=6; if Nace$$ in (26) then E11107$$=7; if Nace$$ in (27,28) then E11107$$=8; if Nace$$ in (29,30,33, 34,35,36) then E11107$$=9; if Nace$$ in (31,32) then E11107$$=10; if Nace$$ in (20,21,22) then E11107$$=11; if Nace$$ in (17,18,19) then E11107$$=12; if Nace$$ in (15,16) then E11107$$=13; if Nace$$ in (45) then E11107$$=14; if Nace$$ in (50,51) then E11107$$=16; if Nace$$ in (52) then E11107$$=18; if Nace$$ in (60,61,62,63,64) then E11107$$=21; if Nace$$ in (65) then E11107$$=22; 33 if Nace$$ in (66,67) then E11107$$=23; if Nace$$ in (55) then E11107$$=24; if Nace$$ in (73,74) then E11107$$=25; if Nace$$ in (37,95) then E11107$$=26; if Nace$$ in (80,92) then E11107$$=27; if Nace$$ in (85) then E11107$$=28; if NACE$$ in (70,71,72,93,98,99) then E11107$$=30; if NACE$$ in (91) then E11107$$=31; if NACE$$ in (90) then E11107$$=32; if NACE$$ in (75) then E11107$$=33; if NACE$$ in (96,97,100) then E11107$$=99; end; else E11107$$=-2; end 34 Variable Name H11101$$ Number of Household members age 0-13 H11102$$ Number of Household members age 14-18 H11103$$ Number of Household members age 0-1 H11104$$ Number of Household members age 2-4 H11105$$ Number of Household members age 5-7 H11106$$ Number of Household members age 8-10 H11107$$ Number of Household members age 11-12 H11108$$ Number of Household members age 13-15 H11109$$ Number of Household members age 16-18 H11110$$ Number of Household members age 19+ or 16-18 years old and independent Unit of Observation Household Description These variables indicate the number of household members in the given age category living in the household at the time of the interview. H11109$$ includes 16-18 year old youth who has not completed his or her Abitur and unmarried and living with a parent or married and separated and living with a parent. H11110$$ includes 16-18 year old youth who have completed Abitur or is in college, but exclude the head and the spouse. Only “residual” adults are counted in this variable. Method These variables are the simple count of all individuals in the household whose age is in the listed category. Format The value of this variable ranges from 0 to 20. The original survey variables provided below can be found in the file _P. This algorithm omits individuals with survey non-responses. Algorithm *First collapse variables for waves m-o; * CREATE AGE GROUP VARIABLE *; array ak101{*} age$$; array ak102{*} marst$$; array ak105{*} hrel$$; array age14{*} age14$$; array age15_18{*} age18$$; array chld018{*} chld18$$; array age0_1{*} age1$$; array age2_4{*} age4$$; array age5_7{*} age7$$; array age8_10{*} age10$$; array age11_12{*} age12$$; array age13_15{*} age15$$; array age16_18{*} age16$$; array adults{*} adult$$; array psbil{*} $psbil; do i = 1 to dim(ad101); if ad101{i}=1 then do; age14{i} = 0; age15_18{i} = 0; chld018{i} = 0; age0_1{i} = 0; age2_4{i} = 0; age5_7{i} = 0; age8_10{i} = 0; age11_12{i} = 0; age13_15{i}= 0; age16_18{i} = 0; adults{i} = 0; if 0 <= ak101{i} < 14 then age14{i} = 1; if 14 <= ak101{i} < 19 then age15_18{i} = 1; chld018{i} = sum(age14{i},age15_18{i}); *** Code up indicators for McClements scale ***;; if 0 <= ak101{i} < 2 then age0_1{i} = 1; if 2 <= ak101{i} < 5 then age2_4{i} = 1; if 5 <= ak101{i} < 8 then age5_7{i} = 1; 35 if 8 <= ak101{i} < 11 then age8_10{i} = 1; if 11 <= ak101{i} < 13 then age11_12{i} = 1; if 13 <= ak101{i} < 16 then age13_15{i} = 1; if 19 <= ak101{i} then adults{i} = 1; if 16 <= age{i} < 19 then do; age16_18{i}=1; if ak102{i}=1 | psbil{i} in (3,4) then age16_18{i}=0; if ak105{i} in (1,2) then age16_18{i}=0; end; if age16_18{i}=0 & (16<=age{i} < 19) then adults{i}=1; if age{i} lt 0 then adults{i}=1; if ak105{i} in (1,2) then adults{i}=0; if ak102{i}=1 & (16 <= age{i} < 19) then adults{i}=0; if age16_18{i}=1 then adults{i}=0; end; end; *** All variables are then summed by household id number (X11102$$)*** 36 Variable Names H11112$$ Variable Label Indicator – Wife / spouse is in Household Unit of Observation Household Description These variables indicate the presence of a “wife, spouse or cohabitee” in the household. Method These variables are simple indicator variables that a person who is a “wife/spouse” is present in a given year. Format 0 = Not present 1 = Present The variables provided below can be found in the $PEQUIV files. This algorithm omits individuals with survey non-responses. Algorithm if X11103$$=1 then do; H11112$$=0; if D11105$$=2 then H11112$$=1; end; 37 The following algorithms allow users to take Equivalent file variables and construct equivalence weights commonly used in various countries. To obtain equivalent household income, divide the equivalence scale weight into the household income variable. Here we present three typical example of equivalence weights: Equivalence scale OECD Equivalence Weights Unit of Observation Household Description Scale used by Organization for Economic Cooperation and Development (1982) Method Sets a single adult to be 1.0, each additional adult to be 0.7, and each child to be 0.5. Algorithm NEWVAR$$=(1.0+0.7*(D11106$$-H11101$$-1)+0.5*H11101$$); ---------------------------------------------------------------------------------------------------------------------------------------- Equivalence scale Modified OECD Equivalence Weights Unit of Observation Household Description Scale used by Organization for Economic Cooperation and Development (1982), see also Hagenaars et al. (1994). Method Sets a single adult to be 1.0, each additional adult to be 0.5, and each child to be 0.3. Algorithm NEWVAR$$=(1.0+0.5*(D11106$$-H11101$$-1)+0.3*H11101$$); ---------------------------------------------------------------------------------------------------------------------------------------- Equivalence scale Other Equivalence Weights (e.g. Square root of the Household size) Unit of Observation Household Description Household equivalence weight based upon a single international scale. Method The weight is based upon a scale developed in Buhmann et al. (1988). The scale is characterized by the following equation: EI = D/Se Where equivalent income (El) equals total disposable household income (D) divided by household size (S) raised to the power (e). The parameter (e) represents the elasticity of the scale rate with respect to household size. Recent international studies on income inequality and poverty sponsored by the OECD (e.g., Forster 1990; Atkinson et al. 1994), and the Statistical Office of the European Commission (Hagenaars et al. 1994) and the Ruggles (1990) study of the United States use this type of exponential equivalence scale. We adopt a value of a equal to 0.5, which is most commonly used in international comparisons. Algorithm NEWVAR$$=D11106$$**0.5; 38 Variable Name L11101$$ Variable Label Federal State of Residence Unit of Observation Household Description This variable indicates the German federal state in which the household was located at the time of the survey Method N/A Format -1 = Item non-response 1 = Schleswig-Holstein 2 = Hamburg 3 = Lower Saxony 4 = Bremen 5 = North-Rhine-Westfalia 6 = Hessen 7 = Rheinland-Pfalz 8 = Baden-Wuerttemberg 9 = Bavaria 10 = Saarland 11 = Berlin 12 = Brandenburg 13 = Mecklenburg-Vorpommern 14 = Saxony 15 = Saxony-Anhalt 16 = Thuringia These states can be collapsed into regions. From 1984 through 1989 three regions can be defined to include the following states: North: Schleswig-Holstein (1), Hamburg (2), Lower-Saxony (3), Bremen (4), Berlin (11) South: Hessen (6), Baden-Wuerttemberg (8), Bavaria (9) West: North-Rhine-Westfalia (5), Rheinland-Pfalz (7), Saarland (10) From 1990 to present four regions can be defined to include the following states: North: Schleswig-Holstein (1), Hamburg (2), Lower-Saxony (3), Bremen (4) South: Hessen (6), Baden-Wuerttemberg (8), Bavaria (9) West: North-Rhine-Westfalia (5), Rheinland-Pfalz (7), Saarland (10) East: Berlin (11), Brandenburg (12) Mecklenburg-Vorpommern (13), Saxony (14), Saxony-Anhalt (15), Thueringen (16), This algorithm omits individuals with survey non-responses. Original variables below can be found in _HBRUTTO files Algorithm L11101$$=Ybula 45 Variable Name I11105$$ Variable Label Household Imputed Rental Value Unit of Observation Household Period Annual Description This variable represents the imputed rental value in the previous year of owner occu pied housing and for renters with below markets rent. Method The Imputed Rent (IR) information calculated for the German SOEP data is based on the so called Opportunity Cost Approach. This approach at the micro level yields information equivalent to that given by the Market Value Approach used in National account statistics for determining IR. After generating a fictitious market rent for owner-occupiers, all owner related costs are deducted including operating and maintenance costs, interest payments on mortgages, as well as property taxes (see Yates 1994 / United Nations 1977). In more detail, the implementation of the opportunity cost approach is used here in the following way. Along the lines of Oaxaca (1973), we estimate an OLS (semilog) regression model of gross rent in terms of square meters (not including heating) actually paid by main tenants in privately financed housing (without social housing and households with reduced rent). Independent variables include indicators describing the condition of the house, the year of construction, size of dwelling, length of occupancy, community size and disposable income. Applying these regression coefficients to the population of owner occupiers and individuals living in households with reduced rent such as employer provided flats, social housing or rent-free households. The resulting estimate represents a gross value at market prices (without costs for heating and warm water). For owner-occupiers owner-specific costs for taxation, maintenance and operating costs as well as interest on mortgages were deducted yielding a net value which can be interpreted as the appropriate income advantage of owner-occupied housing. For rent-free households and persons living in households with below market rents no further deductions have to be made. Information on interest and mortgage payments for the previous year from homeowners in SOEP serves as the basis for determining the level of interest payments. We assume an annuity with constant payments based on 7% annual interest and a 1% principal over the course of an average period of 30 years. In addition, we assume that mortgage payments begin at the same time in which the household moves into its new home. Thus, in the beginning of the repayment period interest payments clearly exceed the mortgage repayment. As times goes by, the share of the mortgage paid off increases, leaving an increasing income advantage from IR. For example an average interest burden of 3.29 DM/m2 per month is used for West Germany in 1988 and rises to 5.52 DM/m2 per month in 1998. The average interest burden in East Germany was slightly lower, at 4.14 DM/m2 per month in 1998. In case of owner related costs exceeding the income advantage (especially at the beginning of the mortgage repayment period), IR is assigned a value of zero. For further details see: Frick and Grabka (2001) and Frick and Grabka (2003): Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. Algorithm N/a 46 Variable Name I11106$$ Variable Label Household Private Transfers Unit of Observation Household Period Annual Description This variable represents the combined private transfers in the previous year of all individuals in the household 16 years of age and older. Method Private transfers consists of income received from persons outside of the interviewed household. Starting in wave R an additional question identifies alimony separately (variable $p2o03 in SOEP file $PKAL: $ = R, S, … ) and since 2010 advance child maintenance payment (IACHM$$) is asked separately. The bulk of transfer is likely to consist of alimony and child support payments. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. This algorithm omits individuals with survey non-responses. Algorithm I11106$$ = sum of (IALM$$ + IACHM$$ + ICHSU$$ + ISPOU$$ + IELSE$$) over all individuals in the household 47 Variable Name I11107$$ Variable Label Household Public Transfers Unit of Observation Household Period Annual Description This variable represents the combined public transfers in the previous year of all individuals in the household 16 years of age and older. Method Public Transfers are the sum of individual public transfers -- student grants, maternity benefits, unemployment benefits, unemployment assistance, subsistence allowance and transition pay -- over all individuals in the household, plus household benefits -- housing allowances, child benefits, nursing care insurance, direct housing subsidy, subsistence assistance, support for special circumstances, social assistance for elderly unemployment benefit II and sickness benefit. In 1984 the amount of child benefits is not asked. Child benefits for this year were imputed using information on the number of children in the household and the number of months the benefits were received. In 1992 through 1994 the amounts of subsistence assistance and special circumstances benefits are not asked. These values have been filled in with imputed values for total social welfare income. In 1995 through 2000 amounts of subsistence assistance and special circumstances benefits are imputed using an algorithm developed by Peter Krause (DIW) based on the benefits received in the present survey month. Since 1996 nursing care insurance benefits are included in the sum. In 1996 German law established direct housing subsidy payments. Starting in the 2000 survey a separate question was asked about income from this source. Direct housing subsidy payments for respondents who bought homes between 1996 and 1999 were imputed using information about the year of construction, acquisition of ownership and number of children in the household. In 2005 social assistance for elderly was asked the first time. In 2006 unemployment benefit II was asked the first time and replaced unemployment assistance. Since 2009 additional child benefit was asked the first time. For survey year 2010 HH-public transfers does also include 2500 Euro car scrappage scheme for households which acquired a new car in the previous year. Since 2014 child care subsidy was asked the first time in SOEP. In 2017 benefits from the educational package and asylum seekers benefits were also included. In 2020 benefits from “Baukindergeld” Building subsidy for new property owners were also included. In 2021 sickness benefits were asked for the first time. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. This algorithm omits individuals with survey non-responses. Algorithm I11107$$ = [sum of (IUNBY$$ + IUNAY$$ + ISUBY$$ + IERET$$ + IMATY$$ + ISTUY$$) over all individuals in the household] + HOUSE$$ + CHSPT$$ + NURSH$$ + SUBST$$ + SPHLP$$ + HSUP$$ + SSOLD$$+ ALG2$$ + ADCHB$$ +CHSUB$$ + EDUPAC$$ + ASYL$$ + BAUK$$ + ISICK$$ 2010: I11107$$ = I11107$$ + 2500 if bah7101c=1 48 Variable Name I11108$$ Variable Label Household Social Security Pensions Unit of Observation Household Period Annual Description This variable represents the combined social security pensions in the previous year of all individuals in the household 16 years of age and older. Method Social security pensions are the sum of old-age, disability, and widowhood social security pensions. This include payments of the German Pension Insurance (GRV), Miner’s social Insurance (Knappschaft), Civil Servant Pension (Beamtenpension), War Victim Benefits (Kriegsopferversorgung), Farmer’s Benefits and accident pension (GUV), pensions from abroad and pension for liberal professions (berufsständische Versorgungswerke). In 1993 through 1994 pension income from East German pensions ($p7902o and $p7912o) is assigned to other pension income. In case of partial unit-non responding households this information has been imputed. For details see: Frick, Grabka & Groh-Samberg (2010). Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: I11108$$ = sum of (IOLDY$$ + IWIDY$$ + ICOMP$$ + IPRVP$$) over all individuals in the household 2002: I11108$$ = sum of (IOLDY$$ + IWIDY$$) over all individuals in the household 1986-2001, 2003-2015: I11108$$ = sum of (igrv1$$ + igrv2$$ + ismp1$$ + ismp2$$ + iciv1$$ + iciv2$$ + iwar1$$ + iwar2$$ + iagr1$$ + iagr2$$ + iguv1$$ + iguv2$$) over all individuals in the household ($$=86-01,03,…,15) since 2016 I11108$$ = sum of (igrv1$$ + igrv2$$ + ismp1$$ + ismp2$$ + iciv1$$ + iciv2$$ + iwar1$$ + iwar2$$ + iagr1$$ + iagr2$$ + iguv1$$ + iguv2$$ + iaus1$$ + iaus2$$ + ilib1$$ + ilib2$$) over all individuals in the household ($$=16,…) 49 Variable Name I11109$$ Variable Label Total Household Taxes Unit of Observation Household Period Annual Description This variable includes income taxes and payroll taxes (e.g. health, unemployment, nursing home and retirement insurance taxes) in the previous year of all individuals in the household 16 years of age and older. Method The tax estimates come from Schwarze (1995), the taxes are assigned on a household basis. The estimated tax burdens include income taxes and payroll taxes (health, unemployment, care and retirement insurance taxes). These routines are described in Schwarze (1995). Since 1995 the solidarity surplus tax is also considered in the tax estimates. No algorithms are provided for the tax estimates. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. Algorithm I11109$$ = I11111$$ + I11112$$ 50 Variable Name I11110$$ Variable Label Individual Labor Earnings Unit of Observation Individual Period Annual Description This variable represents the Gross labor earnings in the previous year of individuals in the household 16 years of age and older. Method Labor earnings include wages and salary from all employment including training, primary and secondary jobs, and self-employment, plus income from bonuses, overtime, and profit-sharing. Specifically labor earnings is the sum of income from primary job, secondary job, self-employment, 13th month pay, 14th month pay, Christmas bonus pay, holiday bonus pay, miscellaneous bonus pay, and profit-sharing income. Since 1991 indemnity payments, since 1996 military service payments and since 2006 commuting expenses or travel grants are also considered. In case of partial unit-non responding households this information has been imputed. For details see: Frick, Grabka & Groh-Samberg (2010). Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. This algorithm omits individuals with survey non-responses. Algorithm 1984-2015 I11110$$ = IJOB1$$ + IJOB2$$ + ISELF$$ + IMILT$$ + I13LY$$ + I14LY$$ + IXMAS$$ + IHOLY$$ + IGRAY$$ + IOTHY$$ + IDEMY$$ + ITRAY$$ Since 2016 I11110$$ = IJOB1$$ + IJOB2$$ + ISELF$$ + IMILT$$ + I13LY$$ + I14LY$$ + IXMAS$$ + IHOLY$$ + IGRAY$$ + IOTHY$$ + IDEMY$$ + ITRAY$$ + IWITH$$ 51 Variable Name I11111$$ Variable Label Household Federal Taxes Unit of Observation Household Period Annual Description This variable includes federal income taxes in the previous year of all individuals in the household 16 years of age and older. Method The tax estimates come from Schwarze (1995). Taxes are estimated for each tax unit within the household and then summed over all tax units within the household to arrive at a total household tax burden. The estimated tax burdens include federal income taxes and solidarity surplus tax. These routines are described in Schwarze (1995). No algorithms are provided for the tax estimates. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. Algorithm N/a 52 Variable Name I11112$$ Variable Label Household Social Security Taxes Unit of Observation Household Period Annual Description This variable includes social security taxes (payroll taxes) in the previous year of all individuals in the household 16 years of age and older. Method The tax estimates come from Schwarze (1995). Taxes are estimated for each tax unit within the household and then summed over all tax units within the household to arrive at a total household tax burden. The estimated tax burdens include social security taxes (e.g. health, unemployment, nursing home and retirement insurance taxes). These routines are described in Schwarze (1995). No algorithms are provided for the tax estimates. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. Algorithm N/a 53 Variable Name I11113$$ Household Post-Government Income (TAXSIM) I11114$$ Total Household Taxes (TAXSIM) I11115$$ Household State Taxes (TAXSIM) I11116$$ Household Federal Taxes (TAXSIM) Unit of Observation Household Description This variable represents the combined income after taxes and government transfers, the Total Household Taxes, the Household State Taxes and the Household Federal Taxes of all individuals in the household 16 years of age and older. Method Income taxes and state taxes were not estimated for the SOEP using the National Bureau of Economic Research (NBER) TAXSIM Model. This variable is not available in the SOEP. Format N/A Algorithm N/a 54 Variable Name I11117$$ Variable Label Household Private Retirement Income Unit of Observation Household Period Annual Description This variable represents the combined retirement income in the previous year from private sources of all individuals in the household 16 years of age and older. Method Private pension income is the sum of supplementary civil servant pension income, company pensions, private pensions and pension income from “other” sources. See the algorithm for I11108$$. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The survey variables provided below are part of the $PEQUIV-file. This algorithm omits individuals with survey non-responses. Note also that this information is not available in 1984 and 1985. Algorithm 1984-1985: N/a 2002-2003: I11117$$ = sum of (ICOMP$$ + IPRVP$$) over all individuals in the household ($$= 02-03) 1986-2001, 2004-2014: I11117$$ = sum of (ivbl1$$ + ivbl2$$ + icom1$$ + icom2$$ + iprv1$$ + iprv2$$ + ison1$$ + ison2$$) over all individuals in the household ($$= 86-01, 04,-14) 2015-2016: I11117$$ = sum of (ivbl1$$ + ivbl2$$ + icom1$$ + icom2$$ + iprv1$$ + iprv2$$ + ison1$$ + ison2$$ + irie1$$ + irie2$$) over all individuals in the household ($$= 15,…) 2017-: I11117$$ = sum of (ivbl1$$ + ivbl2$$ + icom1$$ + icom2$$ + iprv1$$ + iprv2$$ + ison1$$ + ison2$$ + irie1$$ + irie2$$) over all individuals in the household 61 Variable Name OPERY$$ Variable Label Operation, maintenance costs Unit of Observation Household Period Annual Description This variable represents the household operation and maintenance costs in the last year. In 1991 operation and maintenance costs were not asked. If the respondent was interviewed in 1990, 1991, and 1992 and reported having operation and maintenance costs for 1990 and 1992, the average of the 1990 and 1992 values are assigned to 1991. If the respondent was interviewed in only two of the years, one of the years being 1991, and reported having operation and maintenance costs, then operation and maintenance costs for that year are assigned to 1991. Method Transcribed variable. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array ct101{*} ah4201 bh3601 ch4801 dh4801 eh3901 fh3901 gh3901 hhopery ih4201 jh4201 kh4201 lh4201 mh4201 nh4201 oh4201 ph4201 qh4201 rh4201 sh4201 th4001 uh4001 vh3901 wh3901 xh3901 yh4001 zh4001 bah4001 bbh4001 bch4001 bdh4001 beh4301 bfh3901 bgh48 bhh_41 bih_41 bjh_42 bkh_54 blp_41 *** imputed values due to item-non response *** array ct102{*} xah4201 xbh3601 xch4801 xdh4801 xeh3901 xfh3901 xgh3901 out xih4201 xjh4201 xkh4201 xlh4201 xmh4201 xnh4201 xoh4201 xph4201 xqh4201 xrh4201 xsh4201 xth4001 xuh4001 xvh3901 xwh3901 xxh3901 xyh4001 xzh4001 x bah4001 xbbh4001 xbch4001 xbdh4001 xbeh4301 xbfh3901 xbgh48 xbhh_41 xbih_41 xbjh_42 xbkh_54 xblp_41 array ct103{*} temp$$ array ct104{*} opery$$; do i = 1 to dim(netto); ct103{i}=.; if netto{i} >= 10 & < 20) then do; if ct102{i} lt 0 then ct102{i}=0; if ct101{i} eq .A or ct101{i} eq .C then ct103{i}=ct102{i}; else if ct101{i} eq .B then ct103{i}=0; else ct103{i}=ct101{i}; ct104{i}=ct103{i}; end; else ct104{i}=.S; end; 62 Variable Name DIVDY$$ Variable Label Interest, dividend income Unit of Observation Household Period Annual Description This variable represents the household income from interest and dividends in the last year. Method After 1984 respondents who could not estimate their interest and dividend income directly were asked to select a range from a set of categories. Their choices were: under 500 DM 500 to 2,000 DM 2,000 to 5,000 DM 5,000 to 10,000 DM 10,000 DM and over Starting in year 2001 (wave R) an additional item was offered: 10,000 to 20,000 DM 20,000 DM and over Since year 2002 (wave S) all items are asked for Euro: under 250 Euro 250 to 1,000 Euro 1,000 to 2,500 Euro 2,500 to 5,000 Euro 5,000 to 10,000 Euro 10,000 Euro and over These respondents are assigned an interest and dividend amount based on uniformly distributed random numbers within their income range. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array cx101{*} ah45 bh3801 ch5001 dh5001 eh4101 fh4101 gh4101 hh4701 ih4401 jh4401 kh4401 lh4401 mh4401 nh4401 oh4401 ph4401 qh4401 rh4401 sh4401 th4201 uh4201 vh4501 wh4501 xh4501 yh4601 zh4601 bah4601 bbh4601 bch4601 bdh4601 beh4901 bfh4501 bgh6401 bhh_57_01 bih_57_01 bjh_57_01 bkh_70_01 blh_56_01 *** imputed values due to item-non response *** array cx102{*} xah45 xbh3801 xch5001 xdh5001 xeh4101 xfh4101 xgh4101 xhh4701 xih4401 xjh4401 xkh4401 xlh4401 xmh4401 xnh4401 xoh4401 xph4401 xqh4401 xrh4401 xsh4401 xth4201 xuh4201 xvh4501 xwh4501 xxh4501 xyh4601; xzh4601 xbah4601 xbbh4601 xbch4601 xbdh4601 xbeh4901 xbfh4501 xbgh6401 x bhh_57_01 xbih_57_01 xbjh_57_01 xbkh_70_01 xblh_56_01 array cx103{*} temp$$; array cx104{*} divdy$$; if ah45=.B then ah45=0; do i = 1 to dim(netto); cx103{i}=.; if netto{i} >= 10 & < 20) then do; if cx101{i} eq .A or cx101{i} eq .C then cx103{i}=cx102{i}; else cx103{i}=cx101{i}; cx104{i}=cx103{i}; end; else cx104{i}=-2; end; 63 Variable Name CHSPT$$ Variable Label Child allowance Unit of Observation Household Period Annual Description This variable represents the household income from child allowances in the last year. Method In 1984 questions related to this topic were not asked. Child benefits for this year were imputed using information on the number of children in the household and the number of months the benefits were received. In 1985 to 2000 there was no information regarding the number of months the children allowance was claimed. In all those cases 12 months of claim was supposed. Since 2001 child allowances is the product of the number of months the children allowance was claimed in the previous year and the average amount per month. In 2020, a one-time supplement of around €300 per child was granted (Kinderbonus). Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array dp101{*} out bh3303 ch4503 dh4503 eh3603 fh3603 gh3603 hh4503 ih4603 jh4603 kh4603 lh4603 mh4603 nh4603 oh4603 ph4603 qh50 rh4603 sh4603 th4503 uh4503 vh4803 wh4803 xh4803 yh4903 zh4903 bah4903 bbh4903 bch4903 bdh4903 beh5203 bfh4803 bgh6603 bhh_59_03 bih_59_03 bjh_59_03 bkh_72_03 blh_58ab_02 *** imputed values due to item-non response *** array dp102{*} out xbh3303 xch4503 xdh4503 xeh3603 xfh3603 xgh3603 xhh4503 xih4603 xjh4603 xkh4603 xlh4603 xmh4603 xnh4603 xoh4603 xph4603 xqh50 xrh4603 xsh4603 xth4503 xuh4503 xvh4803 xwh4803 xxh4803 xyh4903 xzh4903 xbah4903 xbbh4903 x bch4903 xbdh4903 xbeh5203 xbfh4803 xbgh6603 xbhh_59_03 xbih_59_03 xbjh_59_03 xbkh_72_03 x blh_58ab_02 array dp103{*} kg84 out out out out out out out out out out out out out out out out out out out out out out out out out out out out out out array dp104{*} temp$$; array dp106{*} out out out out out out out out out out out out out out out out out rh4602 sh4602 th4502 uh4502 vh4802 wh4802 xh4802 yh4902 zh4902 bah4902 bbh4902 bch4902 bdh4902 beh5202 bfh4802 bgh6602 bhh_60_02 bih_60_02 bjh_60_02 bkh_72_02 blh_58ab_01 array dp105{*} chspt$$; do i = 1 to dim(netto); dp104{i}=.; if netto{i} >= 10 & < 20) then do; if dp102{i} lt 0 then dp102{i} = 0; if dp103{i} lt 0 then dp103{i} = 0; if dp106{i} = .A or dp106{i} = .C then dp106{i}=12; if dp106{i} in (.B,.) then dp106{i}=0; if dp101{i} = .A or dp101{i} = .C then dp104{i}=dp102{i}; else if dp101{i} in (.B,.) then dp104{i}=0; else dp104{i}=dp101{i}; if i=1 then dp105{i}=dp103{i}; * wave A *; else if (i ge 2 and i le 17) then dp105{i}=dp104{i}*12; * wave B-Q *; else if (i ge 18) then dp105{i}=dp104{i}*dp106{i}; * wave R ..*; end; else dp105{i}=-2; end; 64 Variable Name HOUSE$$ Variable Label Housing allowance Unit of Observation Household Period Annual Description This variable represents the household income from housing allowance in the last year. Method Housing allowance is the product of the number of months that benefit was claimed in the previous year and the average amount per month. Format The value of this variable ranges from 0 to 9,999,999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array dl101{*} ah29 bh2802 ch4002 dh4002 eh3102 fh3102 gh3102 hh4002 ih4502 jh4502 kh4502 lh4502 mh4502 nh4502 oh4502 ph4502 qh47 rh4605 sh4605 th4505 uh4505 vh4805 wh4808 xh4808 yh4908 zh4911 bah4920 bbh4920 bch4920 bdh4920 beh5223 bfh4838 bgh6623 bhh_59_23 bih_59_23 bjh_59_23 bkh_72_23 blh_58hb_01 array dl102{*} ah30 bh2803 ch4003 dh4003 eh3103 fh3103 gh3103 hh4003 ih4503 jh4503 kh4503 lh4503 mh4503 nh4503 oh4503 ph4503 qh48 rh4606 sh4606 th4506 uh4506 vh4806 wh4809 xh4809 yh4909 zh4912 bah4921 bbh4921 bch4921 bdh4921 beh5224 bfh4839 bgh6624 bhh_59_24 bih_59_24 bjh_59_24 bkh_72_24 blh_58hb_02 *** imputed values due to item-non response *** array dl103{*} xah30 xbh2803 xch4003 xdh4003 xeh3103 xfh3103 xgh3103 xhh4003 xih4503 xjh4503 xkh4503 xlh4503 xmh4503 xnh4503 xoh4503 xph4503 xqh48 rh4606 xsh4606 xth4506 xuh4506 xvh4806 xwh4809 xxh4809 xyh4909 xzh4912 xbah4921 xbbh4921 xbch4921 xbdh4920 xbeh5223 xbfh4839 xbgh6624 xbhh_59_24 xbih_59_24 xbjh_59_24 xbkh_72_24 xblh_58hb_02 array dl104{*} temp$$4 array dl105{*} temp$$; array dl106{*} house$$; do i = 1 to dim(netto); dl104{i}=.; dl105{i}=.; if dl103{i} lt 0 then dl103{i} = 0; if dl101{i} = .A or dl101{i} = .C then dl101{i} = 10; if netto{i} >= 10 & < 20 then do; if dl101{i} eq .B then dl104{i}=0; else dl104{i}=dl101{i}; if dl102{i} eq .A or dl102{i} eq .C then do; if dl101{i} le 0 and dl103{i} gt 0 then dl104{i}=12; dl105{i}=dl103{i}; end; else if dl102{i} eq .B then dl105{i}=0; else dl105{i}=dl102{i}; dl106{i}=dl104{i}*dl105{i}; end; else dl106{i}=-2; end; 65 Variable Name NURSH$$ Variable Label Nursing allowances Unit of Observation Household Period Annual Description This variable represents the household income from nursing allowances. Nursing allowances was introduced in the German welfare system in 1996. In 1996-2000 questions related to this topic were only asked for the month of the interview but not for the previous year. Nursing allowances for the previous year was imputed using this information. Since 2001 both the numbers of that benefit was claimed in the previous year and the average amount per month were asked. Method Nursing allowances is the product of the number of months that benefit was claimed in the previous year and the average amount per month. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm 1984-2000 : N/a since 2001: array dzc101{*} rh4609 sh4609 th4509 uh4509 vh4809 wh4812 xh4812 yh4912 zh4915 bah4912 bbh4912 bch4912 bdh4912 beh5215 bfh4824 bgh6615 bhh_59_15 bih_59_15 bjh_59_15 bkh_72_15 blh_58eb_02 *** imputed values due to item-non response *** array dzc102{*} xrh4609 xsh4609 xth4509 xuh4509 xvh4809 xwh4812 xxh4812 xyh4912 xzh4915 xbah4912 xbbh4912 xbch4912 xbdh4912 xbeh5215 xxbfh4815 xbgh6615 xbhh_59_15 xbih_59_15 xbjh_59_15 xbkh_72_15 xblh_58eb_02 array dzc103{*} rh4608 sh4608 th4508 uh4508 vh4808 wh4811 xh4811 yh4911 zh4914 bah4911 bbh4911 bch4911 bdh4911 beh5214 bfh4823 bgh6614 xbhh_59_14 bih_59_14 bjh_59_14 bkh_72_14 blh_58eb_01 array dzc104{*} nursh$$; do i = 1 to dim(dzc101); if dzc103{i} eq .A or dzc103{i} = .C then dzc103{i} = 10; if dzc101{i} eq .A or dzc101{i} eq .C then do; if dzc102{i} gt 0 and dzc103{i} gt 0 then dzc104{i}=dzc102{i}*dzc103{i}; end; else if dzc101{i} eq .B then do; dzc104{i}=0; end; else do; dzc104{i}=dzc101{i}*dzc103{i}; end; end; 66 Variable Name SUBST$$ Variable Label Social assistance Unit of Observation Household Period Annual Description This variable represents the household income from social assistance in the last year. Method Social assistance is the product of the number of months that benefit was claimed in the previous year and the average amount per month. In 1992 through 1994 the amounts of subsistence assistance and special circumstances benefits were not asked. These values have been filled in with imputed values for total social welfare income. In 1995 through 2000 amounts of subsistence assistance and special circumstances benefits are imputed using an algorithm developed by Peter Krause (DIW) based on the benefits received in the present survey month. Since 2010 subsistence assistance and special circumstances benefits were asked in one single item. Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array dt101{*} ah34 bh3002 ch4202 dh4202 eh3302 fh3302 gh3302 hh4202 out out out out out out out out out rh4702 sh4702 th4602 uh4602 vh4902 wh4902 xh4902 yh5002 zh5002 bah4914 bbh4914 bch4914 bdh4914 beh5217 bfh4828 bgh6617 bhh_59_17 bih_59_17 bjh_59_17 bkh_72_17 blh_58fb_01 array dt102{*} ah35 bh3003 ch4203 dh4203 eh3303 fh3303 gh3303 hh4203 out out out out out out out out out rh4703 sh4703 th4603 uh4603 vh4903 wh4903 xh4903 yh5003 zh5003 bah4915 bbh4915 bch4915 bdh4915 beh5218 bfh4829 bgh6618 bhh_59_18 bih_59_18 bjh_59_18 bkh_72_18 blh_58fb_02 *** imputed values due to item-non response *** array dt103{*} xah35 xbh3003 xch4203 xdh4203 xeh3303 xfh3303 xgh3303 xhh4203 out out out out out out out out out xrh4703 xsh4703 xth4603 xuh4603 xvh4903 xwh4903 xxh4903 xyh5003 xzh5003 xbah4915 xbbh4915 bch4915 xbdh4914 xbeh5217 xbfh4829 xbgh6618 xbhh_59_18 xbih_59_18 xbjh_59_18 xbkh_72_15 xblh_58fb_02 *** imputed values due to lacking information in the questionnaire *** array dt104{*} out out out out out out out out sozye92 sozye93 sozye94 socast95 socast96 socast97 socast98 socast99 socast00 out out out out out out out out out out out out out array dt105{*} temp1$$ array dt106{*} temp2$$; array dt107{*} subst$$; do i = 1 to dim(netto); dt105{i}=.; dt106{i}=.; if netto{i} >= 10 & < 20 then do; if dt103{i} lt 0 then dt103{i}=0; if dt101{i} eq .B then dt105{i}=0; if dt101{i} in (.A,.C) then dt105{i}=12; if dt101{i} ge 0 then dt105{i}=dt101{i}; if dt102{i} eq .A or dt102{i} eq .C then do; if dt101{i} le 0 and dt103{i} gt 0 then dt105{i}=12; dt106{i}=dt103{i}; end; else if dt102{i} eq .B then dt106{i}=0; else dt106{i}=dt102{i}; if i ge 9 and i le 17 then do; if dt104{i}=. then dt104{i}=0; end; if i ge 9 and i le 17 then dt107{i}=dt104{i}; else dt107{i}=dt105{i}*dt106{i}; end; else dt107{i}=-2; end; 67 Variable Name SPHLP$$ Variable Label Social assistance for special circumstances Unit of Observation Household Period Annual Description This variable represents the household income from Social assistance for special circumstances in the last year. Method Social assistance for special circumstances is the product of the number of months that benefit was claimed in the previous year and the average amount per month. In 1992 through 2000 and since 2010 the amounts of special circumstances benefits were not asked. Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array dx101{*} ah3601 bh3102 ch4302 dh4302 eh3402 fh3402 gh3402 hh4302 out out out out out out out out out rh4705 sh4705 th4605 uh4605 vh4908 wh4908 xh4908 yh5008 zh5008 out out out out out out out out array dx102{*} ah37 bh3103 ch4303 dh4303 eh3403 fh3403 gh3403 hh4303 out out out out out out out out out rh4706 sh4706 th4606 uh4606 vh4909 wh4909 xh4909 yh5009 zh5009 out out out out out out out out *** imputed values due to item-non response *** array dx103{*} xah37 xbh3103 xch4303 xdh4303 xeh3403 xfh3403 xgh3403 xhh4303 out out out out out out out out out xrh4706 xsh4706 xth4606 xuh4606 xvh4909 xwh4909 xxh4909 xyh5009 xzh5009 out out out out out out out out array dx104{*} temp1$$; array dx105{*} temp2$$; array dx106{*} sphlp$$; do i = 1 to dim(netto); dx104{i}=.; dx105{i}=.; if netto{i} >= 10 & < 20 then do; if dx103{i} lt 0 then dx103{i}=0; if dx101{i} eq .B then dx104{i}=0; if dx101{i} in (.A,.C) then dx104{i}=10; if dx101{i} ge 0 then dx104{i}=dx101{i}; if dx102{i} eq .A or dx102{i} eq .C then do; if dx101{i} le 0 and dx103{i} gt 0 then dx104{i}=12; dx105{i}=dx103{i}; end; else if dx102{i} eq .B then dx105{i}=0; else dx105{i}=dx102{i}; dx106{i}=dx104{i}*dx105{i}; end; else dx106{i}=-2; end; 68 Variable Name SSOLD$$ Variable Label Social assistance for elderly (Grundsicherung im Alter) Unit of Observation Household Period Annual Description This variable represents the household income from Social assistance for elderly in the last year. Method Social assistance for elderly is the product of the number of months that benefit was claimed in the previous year and the average amount per month. It was asked the first time in wave V (variable vh4906 in SOEP file VH). Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array dy101{*} vh4905 wh4905 xh4905 yh5005 zh5005 bah4917 bbh4917 bch4917 bdh4917 beh5220 bfh4833 bgh6620 bhh_59_20 bih_59_20 bjh_59_20 bkh_72_20 blh_58gb_01 array dy102{*} vh4906 wh4906 xh4906 yh5006 zh5006 bah4918 bbh4918 bch4918 bdh4918 beh5221 bfh4834 bgh6621 bhh_59_21 bih_59_21 bjh_59_21 bkh_72_21 blh_58gb_02 array dy103{*} xvh4906 xwh4906 xxh4906 xyh5006 xzh5006 xbah4918 xbbh4918 xbch4918 x xbdh4918 xbeh5221 x bfh4834 xbgh6621 xbhh_59_21 xbih_59_21 xbjh_59_21 xbkh_72_21 xblh_58gb_02 array dy104{*} temp1$$; array dy105{*} temp2$$; array dy106{*} ssold$$; do i = 1 to dim(dy101); dy104{i}=.; dy105{i}=.; if aa100{i}=1 then do; if dy103{i} lt 0 then dy103{i}=0; if dy101{i} eq .B then dy104{i}=0; if dy101{i} in (.A,.C) then dy104{i}=11; if dy101{i} ge 0 then dy104{i}=dy101{i}; if dy102{i} in (.A ,.C) then do; if dy101{i} le 0 and dy103{i} gt 0 then dy104{i}=11; dy105{i}=dy103{i}; end; else if dy102{i} eq .B then dy105{i}=0; else dy105{i}=dy102{i}; dy106{i}=dy104{i}*dy105{i}; end; else dy106{i}=.S; end; 69 Variable Name ALG2$$ Variable Label Unemployment benefit II Unit of Observation Household Period Annual Description This variable represents the household income from unemployment benefit II including social benefit in the last year. Method Unemployment benefit II is the product of the number of months that benefit was claimed in the previous year and the average amount per month. It was asked the first time in wave W (variable wh4806 in SOEP file WH). Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array ey101{*} wh4805 xh4805 yh4905 zh4908 bah4908 bbh4908 bch4908 bdh4908 beh5211 bfh4818 bgh6611 bhh_59_11 bih_59_11 bjh_59_11 bkh_72_11 blh_58db_01 array ey102{*} wh4806 xh4806 yh4906 zh4909 bah4909 bbh4909 bch4909 bdh4909 beh5212 bfh4819 bgh6612 bhh_59_12 bih_59_12 bjh_59_12 bkh_72_12 blh_58db_02 array ey103{*} xwh4806 xxh4806 xyh4906 xzh4909 xbah4909 xbbh4909 xbch4909 xbdh4909 xbeh5212 x bfh4819 xbgh6612 xbhh_59_12 xbih_59_12 xbjh_59_12 x bkh_72_12 xblh_58db_02 array ey104{*} temp1$$; array ey105{*} temp2$$; array ey106{*} alg2$$; do i = 1 to dim(ey101); ey104{i}=.; ey105{i}=.; if $netto >= 10 & < 20 then do; if ey103{i} lt 0 then ey103{i}=0; if ey101{i} eq .B then ey104{i}=0; if ey101{i} in (.A,.C) then ey104{i}=11; if ey101{i} ge 0 then ey104{i}=ey101{i}; if ey102{i} in (.A ,.C) then do; if ey101{i} le 0 and ey103{i} gt 0 then ey104{i}=11; ey105{i}=ey103{i}; end; else if ey102{i} eq .B then ey105{i}=0; else ey105{i}=ey102{i}; ey106{i}=ey104{i}*ey105{i}; end; else ey106{i}=.S; end; 70 Variable Name HSUP$$ Variable Label Housing support for owner-occupiers Unit of Observation Household Period Annual Description This variable represents the household income from direct housing support for owneroccupiers in the last year. Method In 1996 German law established direct housing subsidy payments for owneroccupiers. Starting in the 2000 survey a separate question was asked about income from this source. Direct housing subsidy payments for respondents who bought homes between 1996 and 1999 were imputed using information about the year of construction, acquisition of ownership and number of children in the household. Since 2015 information about this income has been no longer collected. Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm array bzc101{*} misses misses misses misses misses misses misses misses misses misses misses misses ms3904 ns3904 os3904 ps3904 qh3904 rh3904 sh3904 th3504 uh3504 vh3602 wh3602 xh3602 yh3702 zh3702 bah3702 bbh3702 bch3702 bdh3702 beh4002 out out out out *** imputed values due to item-non response *** array bzc102{*} misses misses misses misses misses misses misses misses misses misses misses misses xms3904 xns3904 xos3904 xps3904 xqh3904 xrh3904 xsh3904 xth3504 xuh3504 xvh3602 xwh3602 xxh3602 xyh3702 xzh3702 xbah3702 xbbh3702 xbch3702 xbdh3702 xbeh4002 out out out out array bzc103{*} temp1$$; array bzc106{*} hsup$$; do i = 1 to dim(netto); bzc103{i}=.; if netto{i} >= 10 & < 20 then do; if bzc102{i} lt 0 then bzc102{i} = 0; if bzc101{i} eq .A or bzc101{i} eq .C then bzc103{i}=bzc102{i}; else if bzc101{i} eq .B then bzc103{i}=0; else bzc103{i}=bzc101{i}; bzc106{i}=bzc103{i}; end; else bzc106{i}=-2; end; 77 Variable Name ASYL$$ Variable Label Asylum seeker benefit Unit of Observation Household Period Annual Description This variable represents the household income from asylum seekers benefits. In 19842016 this information was not asked. Method Transcribed variable. It was asked the first time in wave BH (variable BHH_71_q66 in SOEP file BHH). Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm 1984-2016: N/a Since 2017: array h101{*} bhh_70_q66 bih_73_q116 bjh_65_q149 bkh_65_q205 blh_65_q292 array h102{*} bhh_71_q66 bih_72_01_q116 bjh_66_q149 bkh_66_q205 blh_66_q292 array h103{*} xbhh_71_q66 xbih_72_01_q116 xbjh_66_q149 xbkh_66_q205 xblh_66_q292 array h104{*} temp1 array h105{*} temp2 array h106{*} asyl17 asyl18 asyl19 do i = 1 to dim(netto); h104{i}=.; h105{i}=.; if h103{i} lt 0 then h103{i} = 0; if h101{i} in (.A,.C) then h101{i} = 12; *** INR ***; if infam{i}=1 then do; if h101{i} in (.,.B,.D) then h104{i}=0; else h104{i} = h101{i}; if h102{i} in (.A,.C) then do; if h101{i} le 0 and h103{i} gt 0 then h104{i}=12; h105{i}=h103{i}; end; else if h102{i} in (.,.B,.D) then h105{i}=0; else h105{i}=h102{i}; h106{i}=h104{i}*h105{i}; end; else h106{i}=.S; end; 78 Variable Name BAUK$$ Variable Label Building subsidy for new property owners Unit of Observation Household Period Annual Description This variable represents the household income from building subsidy for new property owners (“Baukindergeld”). In 1984-2019 this information was not asked. Method Transcribed variable. It was asked the first time in wave BK (variable BKH_28 in SOEP file BKH). Format The value of this variable ranges from 0 to 99.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _H. This algorithm omits individuals with survey non-responses. Algorithm 1984-2019: N/a Since 2019: array bda101{*} bkh_28 blh_27; array bda102{*} bkh_73_03 blh_59ab_02; array bda103{*} bauk$$; array bda105{*} xbauk$$; do i = 1 to dim(aa100); bda103{i}=.; if aa100{i}=1 then do; bda103{i} = 0; if bda101{i} in (2,.A,.B.,.C,.D) then bda103{i}=0; if bda101{i} = 1 & bda102{i} > 0 then bda103{i}=1200*bda102{i}; if bda101{i} = 1 & bda102{i} in (.A,.B,.C,.D) then bda103{i}=1200; end; else bda103{i}=.S; end; 79 Variable Name FRENTY$$ Imputation flag: Income from rental and leasing FOPERY$$ Imputation flag: Operation, maintenance costs FDIVDY$$ Imputation flag: Interest, dividend income FCHSPT$$ Imputation flag: Child allowance FHOUSE$$ Imputation flag: Housing benefit FNURSH$$ Imputation flag: Nursing allowances FSUBST$$ Imputation flag: Social assistance FSPHLP$$ Imputation flag: Social assistance for spec. circumstances FSSOLD$$ Imputation flag: Social assistance for elderly FALG2$$ Imputation flag: Unemployment benefit II FHSUP$$ Imputation flag: Housing support for owner-occupiers FLOSSR$$ Imputation flag: Losses from renting and leasing FLOSSC$$ Imputation flag: Losses from capital investment FADCHB$$ Imputation flag: Additional child benefit FCHSUB$$ Imputation flag: Child care subsidy FKIDY$$ Imputation flag: Income of children FEDUPAC$$ Imputation flag: Benefits from the educational package FASYL$$ Imputation flag: Asylum seeker benefit FBAUK$$ Imputation flag: Building subsidy for new property owners Variable Label Imputation flag for the respective income component Unit of Observation Household Description This variable indicates if the respective income component has been imputed. The predominant imputation technique used to fill in missing values is based on the row and column imputation procedure developed by Little and Su (1989). In the case of lacking longitudinal data purely cross-sectional imputation techniques are applied. For further details, see: Grabka and Frick (2003). Method In the original SOEP data there are three types of missing values. These missing values can be interpreted as: -1 = no answer or do not know -2 = does not apply -3 = original value was deleted because it was found to be implausible The imputation procedures was used to fill in missing values represented by -1 (.A) and -3 (.C) only. Format 0 = Not Imputed 1 = Fully Imputed This algorithm omits individuals with survey non-responses. 80 Variable Name IJOB1$$ Variable Label Wages, Salary from main job Unit of Observation Individual Period Annual Description This variable represents wages or salary from main job of individuals in the household 16 years of age and older. Method Wages or salary from main job is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm IJOB1$$ = ($P2A02 * $P2A03) 81 Variable Name IJOB2$$ Variable Label Income from secondary employment Unit of Observation Individual Period Annual Description This variable represents income from secondary employment of individuals in the household 16 years of age and older. Method Income from secondary employment is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm IJOB2$$ = ($P2C02 * $P2C03) 82 Variable Name ISELF$$ Variable Label Income from self-employment Unit of Observation Individual Period Annual Description This variable represents income from self-employment of individuals in the household 16 years of age and older. Method Income from self-employment is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm ISELF$$ = ($P2B02 * $P2B03) 83 Variable Name IOLDY$$ Variable Label Combined old-age, disability and civil servants pensions Unit of Observation Individual Period Annual Description This variable represents income from combined old-age, disability and civil servants pensions of individuals in the household 16 years of age and older. In 2002 and 2003 separate questions regarding income from private or company pension were asked. Thus these incomes components are not included in old-age, disability and civil servants pensions in the those years. Method Income from combined old-age, disability and civil servants pensions is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm IOLDY$$ = ($P2D02 * $P2D03) 84 Variable Name IWIDY$$ Variable Label Combined widows and orphans pension Unit of Observation Individual Period Annual Description This variable represents income from combined widows and orphans pension of individuals in the household 16 years of age and older. In 2002 and 2003 separate questions regarding income from private or company pension were asked. Thus these incomes components are not included in widows and orphans pension in the those years. Method Income from combined widows and orphans pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm IWIDY$$ = ($P2E02 * $P2E03) 85 Variable Name ICOMP$$ Variable Label Combined company pension (surviving dependants c.p.) Unit of Observation Individual Period Annual Description This variable represents income from combined company pension of individuals in the household 16 years of age and older. In 1984-2001 and since 2004 specific questions related to this topic were not asked. Thus these income component is included in old-age, disability and civil servants pensions (IOLDY$$) in the those years. Method Income from combined company pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2001: N/a 2002-2003: ICOMP$$ = ($P2P02 * $P2P03) ($$=02 – 03, $ = S-T) since 2004: N/a 86 Variable Name IPRVP$$ Variable Label Combined private pension (old-age, accident, disability) Unit of Observation Individual Period Annual Description This variable represents income from combined private pension of individuals in the household 16 years of age and older. In 1984-2001 and since 2004 specific questions related to this topic were not asked. Thus these income component is included in oldage, disability and civil servants pensions (IOLDY$$) in the those years. Method Income from combined private pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2001: N/a 2002-2003: IPRVP$$ = ($P2Q02 * $P2Q03) ($$=02 – 03, $ = S-T) since 2004: N/a 93 Variable Name IMILT$$ Variable Label Military community service pay Unit of Observation Individual Period Annual Description This variable represents income from military community service pay of individuals in the household 16 years of age and older. In 1984-1995 questions related to this topic were not asked. Since 2015 information about this income has no longer been collected. Method Income from military community service pay is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1995: N/a since 1996: IMILT$$ = ($P2L02 * $P2L03) since 2015: N/a 94 Variable Name IALIM$$ Variable Label Alimony Unit of Observation Individual Period Annual Description This variable represents income from alimony of individuals in the household 16 years of age and older. In 1984-2000 specific questions related to this topic were not asked. Alimony is included in private transfers received (IELSE$$) in the those years. Since 2010 alimony and advance child maintenance payments are surveyed separately. Since 2015 information about this income has been no longer collected, but can be found in the variables ICHSU$$ and ISPOU$$. Method Income from alimony is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2000: N/a 2001-2009: IALIM$$ = ($P2O02 * $P2O03) since 2010: IALIM$$ = ($P2S02 * $P2S03) since 2015: N/a 95 Variable Name IACHM$$ Variable Label Advance child maintenance payment Unit of Observation Individual Period Annual Description This variable represents income from advance child maintenance payments of individuals in the household 16 years of age and older. In 1984-2009 specific questions related to this topic were not asked. Advance child maintenance payments is included in private transfers received (IELSE$$) in the those years. Method Income from advance child maintenance payments is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2009: N/a since 2010: IACHM$$ = ($P2T02 * $P2T03) 96 Variable Name ICHSU$ Variable Label Child support, caregiver alimony Unit of Observation Individual Period Annual Description This variable represents income from child support, caregiver alimony of individuals in the household 16 years of age and older. In 1984-2014 specific questions related to this topic were not asked. Child support, caregiver alimony is included in private transfers received (IELSE$$) in the those years. In 2016 information about child support and spousal support are now integrated in one variable. Method Income from child support, caregiver alimony is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2014: N/a 2015: ICHSU$$ = ($P2U02 * $P2U03) Since 2016 ICHSU$$ = ($P2W02 * $P2W03) 97 Variable Name ISPOU$$ Variable Label Divorce alimony, during separation Unit of Observation Individual Period Annual Description This variable represents income from divorce alimony, during separation of individuals in the household 16 years of age and older. In 1984-2014 specific questions related to this topic were not asked. Divorce alimony, during separation is included in private transfers received (IELSE$$) in the those years. Since 2016 this information is no longer collected as a single variable (see ICHSU$). Method Income from divorce alimony, during separation is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2014: N/a 2015: ISPOU$$ = ($P2V02 * $P2V03) Sicne 2016: N/a 98 Variable Name IELSE$$ Variable Label Private Transfers received Unit of Observation Individual Period Annual Description This variable represents income from private transfers of individuals in the household 16 years of age and older. In 1984-2000 alimony is included in private transfers. Since 2001 a specific question regarding alimony (IALIM$$) were asked, thus alimony is no longer included in private transfers received. Method Income from private transfers is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. In case of partial unit-non responding households this information has been imputed. For details see: Frick, Grabka & Groh-Samberg (2010). Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm IELSE$$ = ($P2M02 * $P2M03) 99 Variable Name IWITH$$ Variable Label Profit Withdrawal Unit of Observation Individual Period Annual Description This variable represents income from profit withdrawal of individuals in the household 16 years of age and older. This information was collected in 2016 and 2017 only. Method Income from profit withdrawal is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2015: N/a 2016-2017: IWITH$$ = ($P2X02 * ($P2X03) Since 2018: N/a 100 Variable Name ISICK$$ Variable Label Sickness benefit Unit of Observation Individual Period Annual Description This variable represents income from sickness benefits of individuals in the household 17 years of age and older. This information was collected since 2021. Method Sickness benefits is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2020: N/a Since 2021: ISICK$$ = ($P2Y02 * ($P2Y03) 101 Variable Name I13LY$$ Variable Label 13th monthly salary Unit of Observation Individual Period Annual Description This variable represents income from 13th monthly salary of individuals in the household 16 years of age and older. Method Transcribed variable. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P. This algorithm omits individuals with survey non-responses. Algorithm I13LY$$ = Y13 13th monthly salary variable list by survey year - each entry denoted in algorithm as Y13: ap3902 bp5902 cp5902 dp5902 ep5402 fp7202 gp7202 hp6702 ip6702 jp7702 kp7702 lp8202 mp6802 np6802 op5902 pp7702 qp7702 rp7702 sp7702 tp9502 up8002 vp10102 wp7802 xp9502 yp9602 zp9202 bap8302 bbp9302 bcp8102 bdp9902 bep8602 bfp11502 bgp10102 bhp11902 bip_120_02 bjp_104_02 bkp_119_02 blp_126_08 102 Variable Name I14LY$$ Variable Label 14th monthly salary Unit of Observation Individual Period Annual Description This variable represents income from 14th monthly salary of individuals in the household 16 years of age and older. Method Transcribed variable. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P. This algorithm omits individuals with survey non-responses. Algorithm I14LY$$ = Y14 14th monthly salary variable list by survey year - each entry denoted in algorithm as Y14: ap3904 bp5904 cp5904 dp5904 ep5404 fp7204 gp7204 hp6704 ip6704 jp7704 kp7704 lp8204 mp6804 np6804 op5904 pp7704 qp7704 rp7704 sp7704 tp9504 up8004 vp10104 wp7804 xp9504 yp9604 zp9204 bap8304 bbp9304 bcp8104 bdp9904 bep8604 bfp11504 bgp10104 bhp11904 bip_120_04 bjp_104_04 bkp_119_04 blp_126_09 109 Variable Name IGRV1$$ Variable Label Statutory pension insurance Unit of Observation Individual Period Annual Description This variable represents income from statutory pension insurance of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. Since 2002 the statutory pension insurance did also include the social miners insurance pension (ISMP1$$) and farmers pension (IAGR1$$). In 2016 this information was not asked in subsamples M3/4, in 2017 not for subsample M5. Method Income from statutory pension insurance is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. In case of partial unit-non responding households this information has been imputed. For details see: Frick, Grabka & Groh-Samberg (2010). Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: IGRV1$$ = ($P2D02 * X) Statutory pension insurance variable list by survey year - each entry denoted in algorithm as X: cp6101 dp6101 ep5601 fp7401 gp7401 hp6901 ip6901 jp7901 kp7901 lp8401 mp7001 np7001 op6101 pp7901 qp7901 rp7901 tp9701 up8201 vp10301 wp8001 xp9701 yp9801 zp9401 bap8601 bbp9601 bcp8301 bdp10101 bep8801 bfp11701 bgp10301 bhp_121_01 bip_122_01 bjp_106_01 bkp_121_01 blp_132a_11 110 Variable Name ISMP1$$ Variable Label Social miners insurance pension Unit of Observation Individual Period Annual Description This variable represents income from social miners insurance pension of individuals in the household 16 years of age and older. In 1984-1985 and since 2002 specific questions related to this topic were not asked. Since 2002 this income component is included in the statutory pension insurance (IGRV1$$). Method Income from social miners insurance pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a 1986-2001: ISMP1$$ = ($P2D02 * X) since 2002: N/a Social miners insurance pension variable list by survey year - each entry denoted in algorithm as X: cp6102 dp6102 ep5602 fp7402 gp7402 hp6902 ip6902 jp7903 kp7903 lp8403 mp7002 np7002 op6102 pp7902 qp7902 rp7902 111 Variable Name ICIV1$$ Variable Label Civil servant pension Unit of Observation Individual Period Annual Description This variable represents income from civil servant pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from civil servant pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: ICIV1$$ = ($P2D02 * X) Civil servant pension variable list by survey year - each entry denoted in algorithm as X: cp6103 dp6103 ep5603 fp7403 gp7403 hp6903 ip6903 jp7904 kp7904 lp8404 mp7003 np7003 op6103 pp7903 qp7903 rp7903 tp9703 up8203 vp10303 wp8003 xp9703 yp9803 zp9403 bap8603 bbp9603 bcp8303 bdp10103 bep8803 bfp11703 bgp10303 bhp_121_02 bip_122_02 bjp_106_02 bkp_121_02 blp_132a_12 112 Variable Name IWAR1$$ Variable Label War victim pension Unit of Observation Individual Period Annual Description This variable represents income from war victim pension of individuals in the household 16 years of age and older. This information is collected in 1986-2001, 20032016 only. Method Income from war victim pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985, 2002: N/a 1986-2001, 2003-2016: IWAR1$$ = ($P2D02 * X) Since 2017 .: N/a War victim pension variable list by survey year - each entry denoted in algorithm as X: cp6104 dp6104 ep5604 fp7404 gp7404 hp6904 ip6904 jp7905 kp7905 lp8405 mp7004 np7004 op6104 pp7904 qp7904 rp7904 tp9705 up8205 vp10305 wp8005 xp9705 yp9805 zp9413 bap8613 bbp9613 bcp8313 bdp10113 bep8813 bfp11715 bgp10315 113 Variable Name IAGR1$$ Variable Label Farmer Pension Unit of Observation Individual Period Annual Description This variable represents income from farmer pension of individuals in the household 16 years of age and older. In 1984-1985 and since 2002 specific questions related to this topic were not asked. Since 2002 this income component is included in the statutory pension insurance (IGRV1$$). Method Income from farmer pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a 1986-2001: IAGR1$$ = ($P2D02 * X) since 2001: N/a Farmer pension variable list by survey year - each entry denoted in algorithm as X: cp6105 dp6105 ep5605 fp7405 gp7405 hp6905 ip6905 jp7906 kp7906 lp8406 mp7005 np7005 op6105 pp7905 qp7905 rp7905 114 Variable Name IGUV1$$ Variable Label Statutory accident insurance pension Unit of Observation Individual Period Annual Description This variable represents income from statutory accident insurance pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from statutory accident insurance pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: IGUV1$$ = ($P2D02 * X) Statutory accident insurance pension variable list by survey year - each entry denoted in algorithm as X: cp6106 dp6106 ep5606 fp7406 gp7406 hp6906 ip6906 jp7907 kp7907 lp8407 mp7006 np7006 op6106 pp7906 qp7906 rp7906 tp9707 up8207 vp10307 wp8007 xp9707 yp9807 zp9411 bap8611 bbp9611 bcp8311 bdp10111 bep8811 bfp11713 bgp10313 bhp_121_08 bip_122_08 bjp_106_08 bkp_121_08 blp_132a_18 115 Variable Name IVBL1$$ Variable Label Supplementary benefits for civil servants Unit of Observation Individual Period Annual Description This variable represents income from supplementary benefits for public sector employees of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from supplementary benefits for public sector employees is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: IVBL1$$ = ($P2D02 * X) Supplementary benefits for public sector employees variable list by survey year - each entry denoted in algorithm as X: cp6107 dp6107 ep5607 fp7407 gp7407 hp6907 ip6907 jp7908 kp7908 lp8408 mp7007 np7007 op6107 pp7907 qp7907 rp7907 tp9709 up8209 vp10309 wp8009 xp9709 yp9809 zp9405 bap8605 bbp9605 bcp8305 bdp10105 bep8805 bfp11705 bgp10305 bhp_121_03 bip_122_03 bjp_106_03 bkp_121_03 blp_132a_13 116 Variable Name ICOM1$$ Variable Label Company pension Unit of Observation Individual Period Annual Description This variable represents income from company pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from company pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: ICOM1$$ = ($P2D02 * X) Company pension variable list by survey year - each entry denoted in algorithm as X: cp6108 dp6108 ep5608 fp7408 gp7408 hp6908 ip6908 jp7909 kp7909 lp8409 mp7008 np7008 op6108 pp7908 qp7908 rp7908 tp9711 up8211 vp10311 wp8011 xp9711 yp9811 zp9407 bap8607 bbp9607 bcp8307 bdp10107 bep8807 bfp11707 bgp10307 bhp_121_04 bip_122_04 bjp_106_04 bkp_121_04 blp_132a_13 117 Variable Name IPRV1$$ Variable Label Private pension Unit of Observation Individual Period Annual Description This variable represents income from private pension of individuals in the household 16 years of age and older. In 1984-2002 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from private pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2002: N/a since 2003: IPRV1$$ = ($P2D02 * X) Private pension variable list by survey year - each entry denoted in algorithm as X: tp9713 up8213 vp10313 wp8013 xp9713 yp9813 zp9409 bap8609 bbp9609 bcp8309 bdp10109 bep8809 bfp11711 bgp10311 bhp_121_06 bip_122_07 bjp_106_07 bkp_121_07 blp_132a_17 118 Variable Name IRIE1$$ Variable Label Riester pension plan Unit of Observation Individual Period Annual Description This variable represents income from Riester pension plan of individuals in the household 16 years of age and older. In 1984-2014 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from Riester pension plan is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2014: N/a since 2015: IRIE11$$ = ($P2D02 * X) Riester pension plan variable list by survey year - each entry denoted in algorithm as X: bfp11709 bgp10309 bhp_121_05 bip_122_06 bjp_106_06 bkp_121_06 blp_132a_16 125 Variable Name IWAR2$$ Variable Label Widows and orphans war victim pension Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans war victim pension of individuals in the household 16 years of age and older. This information was collect in 1986-2001 and 2003-2016, only. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans war victim pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985, 2002, 2017, ...: N/a 1986-2001, 2003-2016: IWAR2$$ = ($P2E02 * X) Widows and orphans war victim pension variable list by survey year - each entry denoted in algorithm as YWAR: cp6113 dp6113 ep5613 fp7413 gp7413 hp6913 ip6913 jp7915 kp7915 lp8415 mp7013 np7013 op6113 pp7913 qp7913 rp7913 tp9706 up8206 vp10306 wp8006 xp9706 yp9806 zp9414 bap8614 bbp8614 bcp8314 bdp10114 bep8814 bfp11716 bgp10316 126 Variable Name IAGR2$$ Variable Label Widows and orphans farmer Pension Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans farmer pension of individuals in the household 16 years of age and older. In 1984-1985 and since 2002 specific questions related to this topic were not asked. Since 2002 this income component is included in the statutory pension insurance (IGRV2$$). Method Income from widows and orphans farmer pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a 1986-2001: IAGR2$$ = ($P2E02 * X) since 2001: N/a Widows and orphans Farmer pension variable list by survey year - each entry denoted in algorithm as X: cp6114 dp6114 ep5614 fp7414 gp7414 hp6914 ip6914 jp7916 kp7916 lp8416 mp7014 np7014 op6114 pp7914 qp7914 rp7914 127 Variable Name IGUV2$$ Variable Label Widows and orphans statutory accident insurance Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans statutory accident insurance pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans statutory accident insurance pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: IGUV2$$ = ($P2E02 * X) Widows and orphans statutory accident insurance pension variable list by survey year - each entry denoted in algorithm as X: cp6115 dp6115 ep5615 fp7415 gp7415 hp6915 ip6915 jp7917 kp7917 lp8417 mp7015 np7015 op6115 pp7915 qp7915 rp7915 tp9708 up8208 vp10308 wp8008 xp9708 yp9808 zp9412 bap8612 bbp8612 bcp8312 bdp10112 bep8812 bfp11714 bgp10314 bhp_121_18 bip_122_20 bjp_106_20 bkp_121_20 blp_132b_19 128 Variable Name IVBL2$$ Variable Label Widows and orphans supplement benefits for civil servants Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans supplementary benefits for public sector employees of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans supplementary benefits for public sector employees is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: IVBL2$$ = ($P2E02 * X) Widows and orphans supplementary benefits for public sector employees variable list by survey year - each entry denoted in algorithm as X: cp6116 dp6116 ep5616 fp7416 gp7416 hp6916 ip6916 jp7918 kp7918 lp8418 mp7016 np7016 op6116 pp7916 qp7916 rp7916 tp9710 up8210 vp10310 wp8010 xp9710 yp9810 zp9406 bap8606 bbp8606 bcp8306 bdp10106 bep8806 bfp11706 bgp10306 bhp_121_14 bip_122_15 bjp_106_15 bkp_121_15 blp_132b_14 129 Variable Name ICOM2$$ Variable Label Widows and orphans company pension Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans company pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans company pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: ICOM2$$ = ($P2E02 * X) Widows and orphans company pension variable list by survey year - each entry denoted in algorithm as X: cp6117 dp6117 ep5617 fp7417 gp7417 hp6917 ip6917 jp7919 kp7919 lp8419 mp7017 np7017 op6117 pp7917 qp7917 rp7917 tp9712 up8212 vp10312 wp8012 xp9712 yp9812 zp9408 bap8608 bbp8608 bcp8308 bdp10108 bep8808 bfp11708 bgp10308 bhp_121_15 bip_122_16 bjp_106_16 bkp_121_16 blp_132b_15 130 Variable Name IPRV2$$ Variable Label Widows and orphans private pension Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans private pension of individuals in the household 16 years of age and older. In 1984-2002 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans private pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2002: N/a since 2003: IPRV2$$ = ($P2E02 * X) Widows and orphans private pension variable list by survey year - each entry denoted in algorithm as X: tp9714 up8214 vp10314 wp8014 xp9714 yp9814 zp9410 bap8610 bbp8610 bcp8310 bdp10110 bep8810 bfp11712 bgp10320 bhp_121_17 bip_122_19 bjp_106_19 bkp_121_19 blp_132b_18 131 Variable Name IRIE2$$ Variable Label Widows Riester pension plan Unit of Observation Individual Period Annual Description This variable represents income from widows and orphans Riester pension plan of individuals in the household 16 years of age and older. In 1984-2014 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from widows and orphans Riester pension plan is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2014: N/a since 2015: IRIE2$$ = ($P2E02 * X) Widows and orphans private pension variable list by survey year - each entry denoted in algorithm as X: bfp11710 bgp10310 bhp_121_16 bip_122_18 bjp_106_18 bkp_121_18 blp_132b_17 132 Variable Name IAUS2$$ Variable Label Widows / orphans pensions from another country Unit of Observation Individual Period Annual Description This variable represents income from widows / orphans pensions from another country of individuals in the household 16 years of age and older. In 1984-2016 specific questions related to this topic were not asked. Method Income from widows / orphans pensions from another country is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2016: N/a since 2017: IAUS1$$ = ($P2D02 * X) Widows / orphans pensions from another country variable list by survey year - each entry denoted in algorithm as X: BHP_121_19 bip_122_21 bjp_106_21 bkp_121_21 blp_132b_20 133 Variable Name ILIB2$$ Variable Label Widows / orphans pensions for liberal professions Unit of Observation Individual Period Annual Description This variable represents income from widows / orphans pensions for liberal professions of individuals in the household 16 years of age and older. In 1984-2017 specific questions related to this topic were not asked. Method Income from widows / orphans pensions for liberal professions is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2017: N/a since 2018: ILIB2$$ = ($P2D02 * X) Widows / orphans pensions for liberal professions variable list by survey year - each entry denoted in algorithm as X: bip_122_17 bjp_106_17 bkp_121_17 blp_132b_16 134 Variable Name ISON2$$ Variable Label Other widows or orphans pension Unit of Observation Individual Period Annual Description This variable represents income from other widows or orphans pension of individuals in the household 16 years of age and older. In 1984-1985 specific questions related to this topic were not asked. In 2016 this information was not asked in subsamples M3/4. Method Income from other widows or orphans pension is the product of the number of months that income was received in the previous year and the average amount per month. If the information about the number of months is missing, the sample mean of that variable has been assigned. Format The value of this variable ranges from 0 to 999.999. This variable is in current year EURO. The original survey variables provided below can be found in the file _P and _PKAL. This algorithm omits individuals with survey non-responses. Algorithm 1984-1985: N/a since 1986: ISON2$$ = ($P2E02 * X) Other widows or orphans pension variable list by survey year - each entry denoted in algorithm as X: cp6118 dp6118 ep5618 fp7418 gp7418 hp6918 ip6918 jp7920 kp7920 lp8420 mp7018 np7018 op6118 pp7918 qp7918 rp7918 tp9716 up8216 vp10316 wp8016 xp9716 yp9816 zp9416 bap8616 bbp8616 bcp8316 bdp10116 bep8816 bfp11718 bgp10318 bhp_121_20 bip_122_22 bjp_106_22 bkp_121_22 blp_132b_21 141 Variable Name M11105$$ Variable Label Have had stroke Unit of Observation Individual Description Indicates whether a doctor ever diagnosed a stroke Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = has had a stroke The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11105=-2; replace m11105= 1 if ple0016==1; replace m11105= 0 if ple0016==-2; replace m11105=-1 if inlist(ple0016,-1,-3); replace m11105=-5 if ple0016==-5; 142 Variable Name M11106$$ Variable Label High blood pressure/circulation problems Unit of Observation Individual Description Indicates whether a doctor ever diagnosed a with high blood pressure or circulation problems Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had problem with high blood pressure or circulation The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11106=-2; replace m11106= 1 if ple0018==1; replace m11106= 0 if ple0018==-2; replace m11106=-1 if inlist(ple0018,-1,-3); replace m11106=-5 if ple0018==-5; 143 Variable Name M11107$$ Variable Label Have or had diabetes Unit of Observation Individual Description Indicates whether a doctor ever diagnosed diabetes Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had problem with diabetes The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11107=-2; replace m11107= 1 if ple0012==1; replace m11107= 0 if ple0012==-2; replace m11107=-1 if inlist(ple0012,-1,-3); replace m11107=-5 if ple0012==-5; 144 Variable Name M11108$$ Variable Label Have or had cancer Unit of Observation Individual Description Indicates whether a doctor ever diagnosed cancer Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had problem with cancer The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11108=-2; replace m11108= 1 if ple0015==1; replace m11108= 0 if ple0015==-2; replace m11108=-1 if inlist(ple0015,-1,-3); replace m11108=-5 if ple0015==-5; 145 Variable Name M11109$$ Variable Label Have or had psychiatric problems Unit of Observation Individual Description Indicates whether a doctor ever diagnosed a depressive diseases. Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had problem with depressive diseases The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11109=-2; replace m11109= 1 if ple0019==1; replace m11109= 0 if ple0019==-2; replace m11109=-1 if inlist(ple0019,-1,-3); replace m11109=-5 if ple0019==-5; 146 Variable Name M11110$$ Variable Label Have or had arthritis Unit of Observation Individual Description Indicates whether person has or had problems with arthritis Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had arthritis or arthropathy The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11110=-2; replace m11110= 1 if ple0021==1; replace m11110= 0 if ple0021==-2; replace m11110=-1 if inlist(ple0021,-1,-3); replace m11110=-5 if ple0021==-5; 147 Variable Name M11111$$ Variable Label Angina or heart condition Unit of Observation Individual Description Indicates whether a doctor ever diagnosed angina or heart condition problems Method Transcribed variable Format: 0 = N/A - Child -1 = Item non-response 1 = Has or had problem with depressive diseases The original survey variables provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2008, 2010, 2012, 2014, 2016, 2018: Data not available in SOEP gen m11111=-2; replace m11111= 1 if ple0014==1; replace m11111= 0 if ple0014==-2; replace m11111=-1 if inlist(ple0014,-1,-3); replace m11111=-5 if ple0014==-5; 148 Variable Name M11112$$ Variable Label Have or had asthma or breathing difficulty Unit of Observation Individual Description Indicates whether person has or had problems with asthma or breathing difficulties Method n.a Format: n.a. Algorithm Information is not available in the SOEP 149 Variable Name M11113$$ Variable Label Need help to climb stairs Unit of Observation Individual Description Indicates whether person has trouble with or needs help of others to climb stairs. In several years the question related to this topic were not asked. Method Transcribed variable. Format: -2 = N/A - Child -1 = Item non-response 0 = Doesn’t have trouble with stairs or need help with stairs 1 = Has trouble with stairs or needs help of others with stairs The original survey variable provided below can be found in the file PL. This algorithm omits individuals with survey non-responses. Algorithm 1984-2001, 2003, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2019: Data not available in SOEP gen m11113=-2; replace m11113= 1 if inlist(ple0004,1,2); replace m11113= 0 if ple0004==3; replace m11113=-1 if inlist(ple0004,-1,-3); replace m11113=-5 if ple0004==-5; 150 Variable Name M11114$$ Variable Label Have difficulty or need help of others to bathe Unit of Observation Individual Description Indicates whether person has trouble with or needs help of others to bathe. Method n.a Format: n.a. Algorithm Information is not available in the SOEP