In the course of data processing, some variables were generated based on the raw variables that are surveyed in the field.
Household and personal income manipulation (inc0110, inc0111, inc0401)
Twin families are a special type of family that could be de-anonymized more easily than other families when combining several characteristics known from the data, especially when these characteristics exceedingly diverge from the average, such as a very high or very low income. In order to guarantee the twin families’ anonymity, very high and very low values of the (household and personal) income variables inc0100, inc0101 and inc0400 are manipulated in a way that the incomes cannot lead back to one household or individual, but the income distribution, as well as analyses, are not affected by the alterations. The manipulation follows the recommendations of Wirth (1992)2 and includes the replacement of the five highest and the five lowest income values in each income variable by their average as well as a random 1% error that is put on the 10% highest and 10% lowest incomes. As a result, 80% of the incomes are not affected by the manipulation. Details of the manipulation procedure will be provided in a Technical Report soon.
Net equivalent household income (inc0411)
Besides the (manipulated) household income, we generate and provide the net equivalent household income using the ➔ modified OECD scale. For this generated variable, the household size and composition are taken into account. The concept is based on the assumption that people (e.g., two adults) save money and are fictitiously ‘richer’ by living together in one household and sharing a common budget and the fixed costs instead of living in separate households. For more information about the concept, see OECD (2011).3
For the generation of educational qualifications according to ISCED-1997, the highest educational qualifications reported by the participants are taken into account. The International Standard Classification of Education (ISCED) is a classification of educational qualification and the level of education of individuals. It ranges from 0 (primary education / first step of basic education) to 6 (second stage of tertiary education, leading directly to an advanced research qualification). The ISCED classification takes into account the national educational system – the type of school at which a person has graduated, the individual duration of education, and the type of graduation an individual has reached. For more information about the ISCED classification see OECD (1999).4
The International Standard Classification of Occupations (ISCO) from 2008 classifies occupations (internationally comparable) considering the required skill level (degree of complexity, based on the educational qualification) of an occupation as well as the skill specialization (the type of skills that are needed especially for this occupation). TwinLife delivers the ISCO classification on the sub-major group level (two digits). For more information about the ISCO classification visit the ➔ ILO website. Please note: Because some detailed employment information was missing in CATI 1 (wid2) to code ISCO-08 comparable to F2F 1 and F2F 2, it received a different variable name (emp0513) and should not be directly compared with the ISCO-08 information in F2F 1 and F2F 2. SIOPS (Standard Index of Occupational Prestige Scala) is a classification for a prestige ranking of occupations (ranging from 0 to 100). It is based on the ISCO-88 classification. For more information see Ganzeboom & Treiman (1996).5 ISEI (International Socio-Economic Index of Occupational Status) is a measure for the socio-economic status of a person and considers the individual occupation, income, and education. It ranges from 12 to 90 using the ISCO-88 classification. For more information see Ganzeboom & Treiman (1996). The EGP-classes (Erikson-Goldthorpe-Portocarero classes) is a classification for the socioeconomic status of the parents, considering the type of occupational activity, the occupational status, managerial responsibility, and the kind of qualification needed for the occupational activity. For more information, see Ganzeboom & Treiman (1996).
Housing conditions and household type (liv0210, liv0410)
The housing conditions were surveyed on the household level and the corresponding questions were answered by the person that has filled in the household questionnaire. The variable liv0210 was generated by processing the available information into the twin perspective and on a personal level. The household type was also surveyed in a personal perspective (dependent on the person type that filled in the household questionnaire). This information was processed into the generated variable liv0410 that provides the information in a general and (between person types) comparable perspective.
Regional variables (ewi, gkpol_r)
In order to meet data protection requirements, regional information about a person, household, or family can only be delivered in an aggregated form. Therefore, an east-west indicator (ewi) was generated by dividing the German states (Bundesländer) into two groups depending on their former affiliation to Western Germany (Federal Republic of Germany) or Eastern Germany (German Democratic Republic). Further, the (political) size of the community (politische Gemeindegrößenklasse, gkpol) is classified into four groups and delivered in the SUF data. The regional variables are available on the household level. Please note that the regional variables are generated from context information that are based on the contact address of a household and not on the household ID, which might not be identical and result in a slight inaccuracy in the regional information in some cases, especially in the older cohorts.
Report cards / certificates (cer variables)
We also recorded data on school performance based on photographs of the children’s report cards. For more information on the coding scheme as well as general descriptions of the German school and grading system, please see the ➔ TwinLife Technical Report No. 04.
2Wirth, H. (1992). Die faktische Anonymität von Mikrodaten: Ergebnisse und Konsequenzen eines Forschungsprojektes. [The factual anonymity of microdata: results and consequences of a research project]. ZUMA Nachrichten 16, 30, 7 - 65. 3OECD (2011). What Are Equivalence Scales? OECD Project on Income Distribution and Poverty. 4OECD (1999). Classifying educational programmes: Manual for ISCED-97 implementation in OECD countries. Organisation for Economic Co-operation and Development. 5Ganzeboom, H. B. G., & Treiman, D. J. (1996). Internationally comparable measures of occupational status for the 1988 International Standard Classification of Occupations. Social Science Research, 25 (3), 201-239.