The SFB882-B3 Linked Employer-Employee Panel Survey (LEEP-B3)

Diewald, Martin et al. Article The SFB882-B3 Linked Employer-Employee Panel Survey (LEEP-B3) Schmollers Jahrbuch – Journal of Applied Social Science Studies. Zeitschrift für Wirtschafts- und Sozialwissenschaften Provided in Cooperation with: Duncker & Humblot, Berlin Suggested Citation: Diewald, Martin et al. (2014) : The SFB882-B3 Linked Employer-Employee Panel Survey (LEEP-B3), Schmollers Jahrbuch – Journal of Applied Social Science Studies. Zeitschrift für Wirtschafts- und Sozialwissenschaften, ISSN 1865-5742, Duncker & Humblot, Berlin, Vol. 134, Iss. 3, pp. 379-389, https://doi.org/10.3790/schm.134.3.379 This Version is available at: https://hdl.handle.net/10419/292447 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ The SFB882-B3 Linked Employer-Employee Panel Survey (LEEP-B3) By Martin Diewald, Reinhard Schunck, Anja-Kristin Abendroth, Silvia Maja Melzer, Stephanie Pausch, Mareike Reimann, Björn Andernach, Peter Jacobebbinghaus* 1. Introduction The project B3 “Interactions between Capabilities in Work and Private Life: A Study of Employees in Different Work Organizations”is situated within the Collaborative Research Center 882 (SFB 882) at Bielefeld University. Its goal is to investigate the role of workplaces in the emergence of social inequalities focusing on the interaction between work and family life. To that end the project B3 created a unique and rich linked employer-employee data set, the B3 Linked Employer-Employee Panel Survey (LEEP-B3). The data was gathered in cooperation with the German Institute for Employment Research (IAB) in Nuremberg. LEEP-B3 consists of survey data of employers which are linked to survey data of their employees. The employees’data are further linked to survey data of their partners. Furthermore, employer-, employee-, and the partner-data can be linked to administrative data of the IAB, allowing to reconstruct employees’ and partners’work biographies prior to the survey and the establishments’histories, including administrative information on the establishments’entire personnel. LEEP-B3 is designed as a longitudinal and multilevel survey with at least two waves. The data structure is graphically displayed in figure 1. LEEP-B3 uses a two-stage sampling design. In the first stage, a stratified random sample of establishments with more than 500 employees was drawn out of the universe of establishments in Germany using administrative data of the Institute for Employment Research. Sampling was stratified on region (East- and West-Germany) and industry sector (NACE Rev. 2, see Eurostat, 2008). Schmollers Jahrbuch 134 (2014), 379 –389 Duncker & Humblot, Berlin Schmollers Jahrbuch 134 (2014) 3 *The Collaborative Research Center 882 (SFB 882) “From Heterogeneities to Inequalities”at Bielefeld University is funded by the German Research Foundation (DFG). The authors would like to thank Jan Braukmann, Annika Clausen, Geraldine Döring, Julia Harand, and Fabienne Schlechter for their work in the research project B3 “Interactions between Capabilities in Work and Private Life: A Study of Employees in Different Work Organizations”. OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 Figure 1: LEEP-B3 data structure Interviews with representatives of these establishments were conducted between April and August 2012 (N = 115). In the second stage, employees from all establishments which did not object to an employee survey (N = 100) were randomly selected and interviewed (N = 6,454). These interviews were conducted as computer assisted telephone interviews (CATI) during September 2012 and March 2013. During the same period employees’partners were also interviewed, given that the employees had a partner and allowed for contacting the respective partners (N = 2,185). The data is thus particularly suited to investigate how organizational processes affect the (re)production of social inequality in different life domains. It combines rich information at the establishment level with equally rich information at the level of the employees and their partnerships. The paper is organized as follows. The paper first discusses the LEEP-B3 establishment survey (section 2), explaining the sampling, response rate, and contents of the survey. This is followed by the presentation of the LEEP-B3 employee survey and the partner survey (section 3), similarly giving information on sampling, response rates, and the contents of the survey. Subsequently, in section 4, the paper explains possibilities of data access for interested researchers. Section 5 provides a summary and a short outlook. 2. LEEP-B3 Employer Survey The selection of the establishments for the LEEP-B3 employer survey was based on administrative operational data provided by the Institute for Employment Research (IAB) in coordination with the Research Data Center (FDZ) of the Federal Employment Agency at IAB. The establishments were drawn out of the Employment History Data (Beschäftigten-Historik, BeH, Version 08.07.00–120203) of the IAB. The BeH comprises data on all German employees that are subject to social insurance contribution. This covers the vast Schmollers Jahrbuch 134 (2014) 3 380 Martin Diewald et al. Establishment data Employee data Administrative data (IAB) Survey data Administrative data (IAB) Survey data Partner data Administrative data (IAB) Survey data OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 majority of employees in Germany, about 70% (Bundesagentur für Arbeit 2013), excluding self-employed persons and public servants (so called “Beamte”). Because the BeH also provides information on the employer, the employee data can be aggregated to the level of establishments (Hethey-Maier/ Seth, 2010), allowing to sample establishments from this data. Among all establishments in the data, the sampling was limited to establishments with at least 500 regular employees, in order to retain a sufficient number of cases per establishment for the longitudinal employee survey (Bender et al., 2009; Pausch et al., 2014). 1 Selection of establishments followed a stratified random sampling scheme. Establishments were classified according to the Statistical classification of economic activities in the European Community (Eurostat, 2008).2The population of 3,934 establishments meeting these criteria was stratified according to region (East- and Germany) and industry code, resulting in 34 strata. In order to ensure a sufficient number of East-German establishments, selection probabilities for establishments in East-Germany was doubled. Furthermore, selection probability of establishments form the “new economy”(industry codes: 61100– 63990) was quadrupled (Pausch et al., 2014). The gross sample comprised 539 establishments (see table 1). Table 1 LEEP-B3 employer sample N % Gross sample 539 100.00 Neutral losses 58 10.76 Not contacted 48 8.91 Company no longer exists 5 0.93 Company not found at provided address 2 0.37 Company name correct, company number incorrect 2 0.37 Company name incorrect, company number correct 1 0.19 Continued next page Schmollers Jahrbuch 134 (2014) 3 The LEEP-B3 381 1Marginally employed, trainees, employees in partial retirement, interns, working students, and pensioners without contributions were excluded. 2Establishments from the industries A (agriculture, farming, forestry, and fishing), B (Mining), S (Other service activities), T (private households), and U (extra-territorial organizations and bodies) were excluded from sampling, either because organizational contexts in these industry sectors cannot be compared with the other industry sectors or because employees in these industry sectors are not embedded in establishments. OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 Table 1 continued N % Adjusted net sample 481 100 Refusal 310 64.45 Could not be contacted 53 11.02 Other reasons for nonparticipation 3 0.62 Successful interviews 115 23.91 Consent to employee survey 100 86.96 No consent to employee survey 15 13.04 To maximize the response rate among representatives of the establishments, a notoriously difficult population, we allowed for different interview modes, that is personal interviews, telephone interviews, by mail, and by e-mail (and combinations thereof). The interviews were conducted by IAB personnel (ProIAB) during April and August 2012. The response rate was at 23.91% (see table 1) amounting to 115 establishments. In those 115 establishments, 100 did not object to an employee-survey (Pausch et al., 2014). Table 2 shows the distribution of establishments according to industry sector in the population, in the gross sample, and in the survey sample. A major advantage of sampling through administrative data lies in the fact of having knowledge about the underlying population. This allows assessing possible non-re- sponse bias (Knerr et al., 2009). Multivariate non-response analyses, i.e., predicting sample membership based on administrative information, do not suggest that there is a bias in the sample regarding industry, region, and size of the establishment (Pausch et al., 2014). Thus, the LEEP-B3 covers the distribution of large establishments across industry, size, and region in Germany rather well. The content of the LEEP-B3 employer’s survey covers information on the history of the establishments, their economic situation, their internal structure, including organizational demography (Williams/O’Reilly, 1998), measures to promote equal opportunity, health promotion, and information on the establishments’environment. For details including the questionnaires and information on item non-response see Pausch et al. (2014). Schmollers Jahrbuch 134 (2014) 3 382 Martin Diewald et al. OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 Table 2 Distribution of establishments in the population, gross sample, and survey Population Gross sample Survey Industry sector (WZ 2008) N % N % N % C–Manufacturing 1333 33.88 160 29.68 38 33.04 D,E,F –Electricity; water supply; construction 141 3.58 19 3.53 5 4.35 G–Wholesale and retail trade; repair of motor vehicles and motorcycles 224 5.69 28 5.19 5 4.35 H–Transportation 199 5.60 26 4.82 4 3.48 J–Information and communication activities 141 3.58 54 10.02 11 9.57 K–Financial and insurance activities 249 6.33 29 5.38 5 4.35 M–Professional, scientific, and technical activities 165 4.19 21 3.90 4 3.48 N–Administrative and support activities 166 4.22 23 4.27 2 1.74 O–Public administration and defense; compulsory social security 425 10.80 59 10.95 16 13.91 P–Education 125 3.18 18 3.34 3 2.61 Q–Human health and social work activities 726 18.45 96 17.81 21 18.26 I,L,R –Accommodation and food service; real estate; arts, entertainment and recreation 40 1.02 6 1.11 1 0.87 N3,934 100 539 100 115 100 Note: due to data protection and anonymity considerations industry sectors D,E,F and I,L,R are collapsed. 3. LEEP-B3 Employee Survey The target population of the first wave of the LEEP-B3 Employee Survey was defined as the population of employees working within one of the 100 establishments as of December 31st, 2011 based on the BeH data. The sample was restricted to employees subject to social security contributions, excluding marginally employed and apprentices, who were born 1960 or later (Abendroth et al., 2014). The goal of the survey was to interview approximately 65 employees per establishment. To that end the gross sample comprises on average 500 observations per establishment. The first wave of the LEEP-B3 employee survey was conducted as computer assisted telephone interviews (CATI) between September 2012 and March 2013. Because the survey was carried out as a CATI, all observations for which there was no telephone number available in the administrative data or for which Schmollers Jahrbuch 134 (2014) 3 The LEEP-B3 383 OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 a telephone number could not be researched were excluded (Abendroth et al., 2014), reducing the gross sample from 53,542 to 30,501 addresses. Overall, 6,454 employees could be interviewed, resulting in a response rate of 29.77% (see table 3). Of these respondents 6,314 (97.83%) agreed to participate in the second wave. Table 3 LEEP-B3 employee sample N % Gross sample 30,510 100.00 Neutral losses 8,832 28.95 Not contacted (quota filled) 3,169 10.39 No connection 2,008 6.58 Wrong person 1,887 6.18 Fax/data line 1,177 3.86 Out of sample (not target population) 591 1.94 Adjusted net sample 21,678 100 Refusal 11,856 54.69 Partial interview (break off) 76 0.35 Interview not possible during field time 3,292 15.19 Successful interviews 6,454 29.77 Consent to be re-interviewed 6,314 97.83 No consent to be re-interviewed 140 2.13 Since the administrative data (Integrierte Erwerbsbiographien, IEBs, Version 10.00.00 (2012)) contain information on gender, citizenship, age, education and earnings (Jacobebbinghaus/Seth, 2007), it is again possible to directly compare the distribution of the characteristics in the population and the samples and to assess selectivity in the survey sample (Knerr et al., 2009). Tables 4 and 5 show the distribution of employees according to socio-demographic characteristics in the population, the gross sample, and the survey sample. Multivariate analyses of non-response comparing the survey sample with the gross sample indicate some selectivity (Abendroth et al., 2014): Female respondents, German nationals, respondents with lower levels of education, older respondents, non-high earning respondents (< 5001 €), as well as respondents from industry sectors D,F,F, N, and O (reference C) were more likely to participate in the survey. However, when comparing the survey sample with the Schmollers Jahrbuch 134 (2014) 3 384 Martin Diewald et al. OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 Table 4 Distribution of selected employee characteristics in the population, gross sample, and survey sample Population Gross sample Survey N % N % N % 3,675,780 100.00 53,542 100.00 6,454 100.00 Male 2,141,277 58.25 30,478 56.92 3,439 53.28 German citizenship 3,384,159 92.07 49,975 93.34 6,200 96.06 Age up to 24 years 167,003 4.54 2,480 4.63 288 4.46 25–34 years 969,621 26.38 13,197 24.65 1,477 22.89 35–44 years 1,222,796 33.27 17,241 32.20 1,924 29.81 45–53 years 1,316,360 35.81 20,624 38.52 2,765 42.84 Education Not known 1,451,782 39.50 21,123 39.45 2,281 35.34 Secondary without vocational training 118,815 3.23 1,829 3.42 160 2.48 Lower secondary with vocational training 1,038,621 28.26 15,846 29.60 1,875 29.05 Higher secondary with vocational training 341,048 9.28 5,285 9.87 688 10.66 Tertiary 725,514 19.74 9,459 17.67 1,450 22.47 Monthly earnings in € up to 1,000 129,083 3.51 2,090 3.90 242 3.75 1,001–2,000 431,455 11.74 6,982 13.04 993 15.39 2,001–3,000 823,759 22.41 13,881 25.93 1,698 26.31 3,001–4,000 951,726 25.89 14,571 27.21 1,486 23.02 4,001–5,000 624,614 16.99 7,601 14.20 887 13.74 5,001 and more 715,143 19.46 8,417 15.72 1,148 17.79 Establishment size 500–699 employees 731,566 19.90 18,386 34.34 2,431 37.67 700–999 employees 676,038 18.39 18,383 34.33 2,164 33.53 1,000–1,499 employees 621,765 16.92 11,373 21.24 1,288 19.96 51,500 and more employees 1,646,411 44.79 5,400 10.09 571 8.85 overall population, the sample appears to be less selective (Abendroth et al., 2014). The results indicate that LEEP-B3 does not significantly deviate in most aspects from the underlying population. Only German nationals and employees in industry sector I (see section 2) are more likely to being in the survey and Schmollers Jahrbuch 134 (2014) 3 The LEEP-B3 385 OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17 employees with low or unknown levels education and employees in large establishments (> 1,500 employees) are less likely to being in the survey. None of the other characteristics listed in tables 4 and 5 predict survey participation when comparing the survey sample with the overall population (Abendroth et al., 2014). Thus, although the survey is tailored to providing data for the investigation of intra- and inter-organizational mechanisms, the sample represents the underlying population rather well, at least with regards to the characteristics listed in tables 4 and 5. Table 5 Distribution of employees across industries in the population, gross sample, and survey sample Population Gross sample Survey N % N % N % 3,675,780 100.00 53,542 100.00 6,454 100.00 C–Manufacturing 1,472,602 40.06 17,435 32.56 2,080 32.23 D,E,F –Electricity; water supply; construction 96,640 2.63 1,591 2.97 126 1.95 G–Wholesale and retail trade; repair of motor vehiclesand motorcycles 163,926 4.46 2,687 5.02 312 4.83 H–Transportation 190,995 5.20 2,077 3.88 163 2.53 J–Information and communication activities 119,689 3.26 5,075 9.48 665 10.30 K–Financial and insurance activities 226,060 6.15 1,773 3.31 176 2.73 M–Professional, scientific, and technical activities 166,158 4.52 2,192 4.09 267 4.14 N–Administrative and support activities 101,601 2.76 1,200 2.24 109 1.69 O–Public administration and defense; compulsory social security 305,591 8.31 5,984 11.18 830 12.86 P–Education 181,366 4.93 1,598 2.98 193 2.99 Q–Human health and social work activities 629,484 17.13 11,330 21.16 1,453 22.51 I,L,R –Accommodation and food service; real estate;arts, entertainment and recreation 21,668 0.59 600 1.12 80 1.24 Note: due to data protection and anonymity considerations industry sectors D,E,F and I,L,R are collapsed. 386 Martin Diewald et al. Schmollers Jahrbuch 134 (2014) 3 OPEN ACCESS | Licensed under | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/schm.134.3.379 | Generated on 2023-01-16 13:37:17