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Since January 2020, the COVID‑19 crisis has affected everyday life around the world, and rigorous government lock ‑ down restrictions have been implemented to prevent the further spread of the pandemic. The consequences of the corona crisis and the associated lockdown policies for public health, social life, and the economy are vast. In view of the rapidly changing situation during this crisis, policymakers require timely data and research results that allow for informed decisions. Addressing the requirement for adequate databases to assess people’s life and work situations during the pandemic, the Institute for Employment Research (IAB) developed the High‑frequency Online Personal Panel (HOPP). The HOPP study started in May 2020 and is based on a random sample of individuals drawn from the administrative data of the Federal Employment Agency in Germany, containing information on all labour market par‑ ticipants except civil servants and self‑ employed. The main goal of the HOPP study is to assess the short‑term as well as long‑term changes in people’s social life and working situation in Germany due to the corona pandemic. To assess individual dynamics the HOPP collected data on a monthly (wave one to four) and bi‑monthly (wave five to seven) basis. Furthermore, respondents were divided into four groups. The different groups of a new wave were invited to the survey at weekly intervals (wave two to four) or bi‑ weekly intervals (wave five to seven). This gives us the advan‑ tage of being able to provide weekly data while each participant only had to participate on a monthly or bi‑monthly basis. In this article, we delineate the HOPP study in terms of its main goals and features, topics, and survey design. Furthermore, we provide a summary of results derived from HOPP and the future prospects of the study. 1 Introduction Addressing the demand for adequate databases to Since January 2020, the COVID-19 crisis has affected assess people’s life and work situations during the pan- everyday life around the world, and rigorous government demic, the Institute for Employment Research (IAB) lockdown restrictions have been implemented to prevent developed the High-frequency Online Personal Panel the further spread of the pandemic. The consequences of (HOPP), which started in May 2020. The HOPP study the corona crisis and the associated lockdown policies was designed to flexibly capture short-term individual for public health, social life, and the economy are vast. In dynamics in the labour market and labour market-related view of the rapidly changing situation during this crisis, elements as the COVID-19 crisis unfolds. In addition, policymakers require timely data and research results long-term effects can be evaluated by linking administra - that allow for informed decisions. tive process data from the Federal Employment Agency (FEA), the Integrated Employment Biographies (IEB) (Jacobebbinghaus and Seth 2007). *Correspondence: georg‑ email@example.com In the following, we delineate the HOPP study Institute for Employment Research, Nuremberg, Germany in terms of its main goals and features, topics, and Full list of author information is available at the end of the article © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. 16 Page 2 of 14 G.-C. Haas et al. survey design. Furthermore, we provide a summary 3 Topics and questionnaires of results derived from HOPP and the future pros- The HOPP study collects data on the current employ - pects of the study. ment situation and labour market-related aspects of individuals in Germany. Specifically, the main question - 2 Substantive goals and features of the HOPP naire programme through wave seven includes topics study concerning employment, subsidized short-term work, The HOPP study was initiated to evaluate how the corona childcare, home office, life satisfaction, and health. In crisis is affecting individuals in the German labour addition, focus topics address couples’ division of child- market. To obtain a complete picture of people’s life care and housework before and during the corona crisis and work situations during the pandemic, HOPP was (wave two), vocational training (wave three), experiences designed to flexibly address new topics as the crisis with home office and reasons for not working from evolves. The questionnaire therefore contains a mix of home (wave four), work-life balance (wave five), abuse core modules on employment and labour market-related of legal provisions regarding short-time work (waves aspects of life as well as questions and modules that can six and seven), and trust in institutions and democracy be introduced depending on situational changes due to (wave seven). Appendix Table 2 provides an overview of lockdown measures, e.g., regarding short-time work, the variables in waves one to seven. organization of childcare, home office, health, and atti - Although based on a sample of individuals, the HOPP tudes (Sect. 3). study addresses labour market-related topics in the Apart from this substantive aim, the HOPP has three context of households (e.g., childcare). Therefore, we distinct methodological features that set it apart from collected several household characteristics, e.g., the other corona-related panel studies: a probability sample household composition, the number of children aged 18 design, high-frequency data collection, and linkage with or younger living in the household, and the children’s administrative data. date of birth. Furthermore, respondents who report Probability sample design: To adequately represent being in a relationship are asked to provide information individuals in the German labour market, the HOPP on their partner’s current employment status, short-time study is based on a random sample of individuals drawn work, and working hours and whether and to what extent from the IEB (see Sect. 4.1). This gives it a major advan - their partner works from home. tage over most of the online surveys implemented to The questionnaire modules were developed primarily evaluate the impact of the corona crisis, as the latter by the Institute for Employment Research and in cooper- are based primarily on online convenience samples and ation with external researchers. The questionnaires also therefore lack generalizability due to selection bias (see contain items from other studies, namely, the German 1 2 Schaurer & Weiß 2020). Internet Panel (GIP), the German Family Panel pairfam, High-frequency data collection: As decisions during and the German Socioeconomic Panel (GSOEP). For a the corona crisis have to be made very quickly, the sur- comprehensive list of items and references for the items vey period and frequency of data collection are cru- that were taken or adapted from other studies, please cial to informing such decisions. To closely monitor refer to the HOPP Codebooks and the Data Manual. individual dynamics and to address newly arising data demands in as timely a manner as possible, the HOPP 4 Study design study collected data monthly (waves one to four) and In the following, we describe the study design with bi-monthly (five to seven). Furthermore, to monitor respect to sampling, the panel recruitment and contact changes on a weekly basis, the sample was divided into strategy, the frequency of data collection, panel mainte- four groups of respondents who were surveyed at one- nance and incentives and show how response rates devel- week intervals (see Sect. 4.3). oped over time. Given the rapid setup of the HOPP study, Linkage with administrative data: Another feature some features of the panel were introduced in later waves of the HOPP study is that survey data can be sup- (e.g., incentives, panel software) or modified over the plemented with administrative data from the FEA course of the study (frequency of data collection). These including information on employment spells for all employment that is subject to social security, benefit receipt, job searches, and participation in employment and training measures (Sect. 6). Linked with adminis- https:// www. uni- mannh eim. de/ gip/ das- gip/. trative data, the HOPP study can serve as a database to https:// www. pairf am. de/. evaluate the long-term effects of the corona crisis on https:// www. diw. de/ en/ soep. employment. https:// fdz. iab. de/ de/ FDZ_ Indiv idual_ Data/ HOPP. aspx. Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 3 of 14 16 Fig. 1 Structure of the study changes are displayed in Fig. 1, together with a descrip- 2018 include four categories: (a) individuals who had tion of the respective design features. only employment spells in 2018, with at least one spell of marginal employment, (b) individuals who had only 4.1 Sampling design employment spells in 2018, with no spell of marginal The sample for the HOPP study was drawn from the IEB. employment, (c) individuals who received unemploy- The IEB contains administrative labour market records ment benefit II (means-tested basic income for jobseek - that employers, job centres and employment agencies ers) at least once in 2018, and (d) individuals who did report to the federal employment agency in Germany. not receive unemployment benefit II in 2018 but were at These records contain all individuals who have at least least once registered at the Federal Employment Agency one of the following spells : employment subject to social for other reasons (receipt of unemployment benefit from security, marginal part-time employment, receipt of ben- the unemployment insurance system, participation in a efits, participation in an employment or training measure measure of active labor market policies, registration as or registration as a jobseeker at the Federal Employment jobseeker). Agency (e.g., see Antoni et al. 2019). This excludes indi - The gross sample size was allocated proportionally to viduals within the labour force who are civil servants or the total number of persons within the respective strata self-employed. of the sampling frame, i.e., inclusion probabilities were The sampling frame for the HOPP considers IEB equal for all persons in the sampling frame (0.0043). reports with a reporting date until December 31st, 2018, The exceptions to this rule were older employees in the and limits reports to all individuals who reached their 60–99 age group who were employed in 2018 and mar- 18th year on May 1st, 2020, or before and had at least ginal part-time employees who had a higher sampling one data entry report in 2018. The IEB can be linked to fraction (0.0063) than persons in the other strata. A individual contact data (name and postal address), which higher sampling fraction for those groups was chosen to allows individuals to be sent an invitation letter by mail address research questions requiring a higher number of to participate in an online survey. respondents. A stratified sample with simple random sampling As the distribution of stratification variables is mostly within strata was used, with strata defined by region, proportional to their distribution within the IEB sam- age, gender, and employment status in 2018. Specifi - pling frame, the share of persons in our sample that cally, administrative units, called regional directorates belong to strata with unemployed persons or welfare (Regionaldirektionen), of the Federal Employment recipients is relatively small. This diminishes the statisti - Agency were used for geographical stratification. Age on cal power of any analysis that is specific to one of these May 1st, 2020, was categorized as 18–29, 30–39, 40–49, subgroups, compared to employees. With regard to infer- 50–59, and 60–99. The strata on employment status in ential statistics, it is therefore recommended that analy- ses be conducted either for the whole German labour market or employed individuals only. Spell is the term the IEB uses to describe a reported labour market period. 16 Page 4 of 14 G.-C. Haas et al. Fig. 2 Flowchart showing all of the recruitment, maintenance, registration steps Panel participants were recruited at two times: during design of the HOPP study is non-monotonic, that is, wave one in May 2020 and during wave five in Septem - respondents who did not participate in a given wave are ber/October 2020. The net sample was defined to con - invited to the next wave, provided panel consent was tain approximately 10,000 complete interviews for wave given in the initial interview. one. Judging from other studies at the IAB with a simi- To simplify the field work, panellists were moved lar target population, mode, and sampling and contact to a panel website during the data collection in waves strategy, we expected a response rate of approximately three and four and had to register themselves (see Panel five percent. Therefore, a sample of 200,000 was selected Maintenance and Incentives for more details). To save from our IEB sampling frame. For wave five, we selected a resources, we stopped contacting respondents who did refreshment sample of 99,188 cases with the same design. not register themselves on the panel website from wave five on (Fig. 2). 4.2 P anel recruitment and contact strategy In wave five, we invited a refreshment sample by mail - We recruited respondents by sending them an invita- ing them an invitation letter similar to the one in wave tion by mail on May 8th, 2020. The letter contained one. At the end of wave five, refreshment respondents information about the objectives of the study, informa- were asked for their consent to be contacted for follow- tion on data protection regulations, a short URL link to up waves. If respondents provided their consent for re- the online survey, an individualized randomly generated contact, we asked respondents to register themselves on password to access the survey and a QR code to facilitate the panel website to download their promised incentive participation via smartphone. In addition, a URL link to a and to be invited to follow-up waves. In contrast to wave homepage providing more detailed information, e.g., on one, we did not ask for consent to contact respondents data protection, was included. who did not provide an e-mail address with a postal letter At the end of wave one, respondents were asked for in subsequent waves, to reduce field management costs. their consent to be contacted for follow-up waves. The In the first five waves, we invited panellists on Fridays (letters were mailed on urs Th days). From wave six on, we changed the invitation day to Monday, as we expected higher response rates by inviting people at the beginning The individual password expired after the participant used it for the first time to prohibit a person from participating in the survey more than once. Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 5 of 14 16 Table 1 Response rates (RR) for new recruits and panellists and realized number of analysis cases by wave Wave New recruits Wave 1 panellists Refreshment Panellists Realized number of analysis cases a a a N RR N RR N RR Overall With record invited invited invited linkage consent 1 200,000 5.7 – – – – 11,311 9548 2 – – 9751 48.6 – – 4746 4258 3 – – 9751 41.7 – – 4071 3673 4 – – 9751 37.7 – – 3682 3339 5 99,188 8.2 3739 79.5 – – 11,072 9595 6 – – 3744 82.4 4939 72.3 6659 6141 7 – – 3737 80.6 4931 67.3 6334 5836 AAPOR RR1 of a week based on findings from other studies (Lindgren 2020. At that point, only the survey tool keyingress was et al. 2020; Blom et al. 2020). available. As keyingress is not designed for panel surveys in terms of data management and providing incentives 4.3 F requency of data collection to respondents, we decided to change software. To this To monitor changes during the COVID-19 pandemic, a end, in waves three and four, respondents were invited high frequency of data collection was needed. To meet to register on an online portal designed for the HOPP this demand, we divided the frequency of data collection study and based on the software panelingress. All panel- into two levels and adjusted the frequency of data collec- lists who consented to be recontacted with a postal letter tion over time (see Fig. 1). The first level of data collection received an invitation to register themselves at the end frequency was the interval between each wave containing of the wave four questionnaire. Overall, 3756 respond- the main questionnaire programme and the focus topics ents registered themselves, that is, 1.9% of the individu- (see Topics and Questionnaires). Until wave four, panel- als initially invited in wave one and 38.5% of wave one lists were invited each month. As a monthly invitation respondents who provided panel consent. Panellists who to a survey may be too burdensome for many respond- did not register themselves were not contacted in follow- ents and could have a negative effect on their willingness up waves (see\*MERGEFORMAT Fig. 2). to continue participation, starting with wave five, we Respondents in the refreshment sample were invited increased the interval between each wave to two months. to register themselves at the end of the wave five survey. We introduced a second level of frequency by divid- From wave five on, participants were invited to subse - ing the respondents (who provided panel consent) from quent survey waves only if they successfully registered wave one into four groups. Starting in wave two, each with their e-mail contact in the online portal. Overall, group was invited in a different week of the month, that 4960 (61.2%) of refreshment respondents from wave is, with one-week intervals between each group. With the five registered themselves. To motivate respondents increasing intervals between waves starting in wave five, to register themselves and to respond to future survey we also increased the interval between the four groups invitations, we provided incentives. For registering, par- in each wave. While waves two to four use a one-week ticipants received 500 points, the equivalent of a five- interval between each group, waves five to seven use euro voucher. Participants could exchange their points a two-week interval between each group. To integrate for vouchers redeemable at various (online) shops, such the refreshment sample into our design, we divided the as amazon.de, Thalia, Conrad, and Otto. We rewarded refreshment participants into four groups before inviting panellists with an additional 200 points for participation them to wave five. in each subsequent wave. 4.4 P anel maintenance and incentives The aims of the study were to launch the first wave quickly after the first contact restrictions (“lockdown”) For more details on the software, see: https:// www. ingre ss- survey. co. uk/ in Germany, which were implemented in mid-March Softw are/ Survey- softw are- keyin gress/. For more details on the software, see: https:// www. ingre ss- survey. co. uk/ Softw are/ Panel- softw are- panel ingre ss/. 16 Page 6 of 14 G.-C. Haas et al. For all panellists, registration was a technical prereq- five and no incentives in wave one, we find it likely that uisite to receive the promised voucher. Registered pan- the higher response rate in wave five can be attributed ellists could delete their registration at any time, e.g., to using incentives. Wave one panellists who registered even directly after receiving the voucher. However, this themselves in wave four (N = 3756) had a response rate of rarely occurred, as only 0.3% of the 8716 registered pan- 79.5% in wave five. ellists withdrew their registration within a month after For wave six and wave seven, we calculated the registration. response rates separately for wave one and refreshment panellists. While wave one panellists had a response rate 4.5 R esponse rates across waves of 82.4% in wave and 80.6% in wave, refreshment panel- Table 1 shows the response rates for all waves by panel lists had a response rate of 72.3% in wave six and 67.2% in status, differentiating between newly recruited respond - wave seven. ents and returning panellists. For the sake of simplicity, Table 1 also indicates the number of analysis cases by we refer to wave one respondents who consented to be wave. In waves one and five, respondents were asked to contacted for follow-up waves as wave one panellists provide informed consent for their individual survey and to respondents from the refreshment sample who responses to be linked to administrative datasets of the registered themselves on the panel website as refresh- Federal Employment Agency (IEB) to enrich the survey ment panellists hereafter. We calculated the response data with administrative data. rates according to the AAPOR standard definitions for The design of the HOPP study enables researchers to response rates using the definition for Response Rate 1 evaluate changes over time, using months and calendar (RR1): the number of complete interviews by the number weeks instead of data collection waves. We provide tables of invited cases (see AAPOR 2016). The response rates similar to Table 1 indicating the response rates and real- are based on complete interviews, defined as interviews ized number of analysis cases by month (Table 3) and cal- in which respondents provided an answer to the last sub- endar weeks (Table 4) in the appendix. stantive question. If respondents provided their consent for administrative data linkage, we compared the age and 5 Analysis potential of the HOPP study gender between both data sources. We excluded cases for The HOPP data enable researchers to track the devel - which age and gender did not match between the sur- opment of various labour market-related indicators vey and administrative data (N = 265, N between May 2020 and February 2021. To show the anal- wave one refreshment = 283). ysis potential of the HOPP data, we use an updated anal- sample Of the 200,000 individuals invited in wave one, 5.7% ysis published in Frodermann et al (2021) showing the responded to the survey (AAPOR RR1), and 4.9% initially development of weekly time spent teleworking in relation consented to be contacted again (wave one panellists), to weekly total working time before the COVID-19 pan- resulting in 9751 wave one panellists who were invited demic (see Fig. 3). Each month’s values in Fig. 1 include to waves two to four. Of the respondents who gave panel only individuals who self-reported having the option to consent, 5948 (61%) provided an e-mail address for fur- work from home in a particular month. The share of indi - ther contact, whereas 3803 (39%) agreed to be contacted viduals who have an option to work from home is 39% by mail. Table 1 shows a decreasing response rate from and does not change significantly across months. For the wave two (48.7%) to wave four (37.8%). We found that sake of simplicity, the values for each month are grouped 65.6% of wave one panellists (N = 9751) completed at into five categories ranging from 0, which is working least one questionnaire in waves two to four, 21.2% of solely at the workplace, to 100, which is working solely wave 1 panellists responded to all three waves, and 34.4% from home. completed none of the follow-up waves. Figure 3 shows how the pandemic affected the share In wave four, we moved our panel from keyingress to of time spent working from home in relation to the panelingress by inviting wave one panellists to register total working time for men and women. Before the pan- themselves on the panel website to continue their par- demic, only 4% of men and 7% of women worked com- ticipation. Overall, 3755 wave one panellists registered pletely from home. At the beginning of the crisis, the themselves, that is, 1.9% of individuals initially invited to share increases to 46% for men and 44% for women. wave one and 38.5% of wave one panellists. From May to September 2020, the share of individuals Among the refreshment sample of 99,188 individu- decreases but stays higher than the before corona value als invited in wave five, 8.2% responded (AAPOR RR1), and 61.2% of refreshment respondents registered them- selves on the panel website, that is, 5.0% of the refresh- Note that our analyses may deviate, as Frodermann et al (2021) did not have ment sample. As we used conditional incentives in wave access to the current HOPP data but used a pre-released dataset. Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 7 of 14 16 Fig. 3 Weekly working time in home office in relation to weekly total working time, shares of employed men and women, in percent (based on respondents who have the option to work from home). The number of cases differs by data collection month and ranges between 646 and 2457 for men and between 628 and 1971 for women. Values for “before corona” are based on the quotient of the answers to the two questions from wave 1 (May 2020): “Thinking about the time before the corona crisis, how many hours per week did your usual working hours consist of, including overtime worked, extra work, etc.?” and “Thinking back to before the corona crisis, how many hours a week did you regularly work from home before the crisis?”. Values for each month are based on the quotient of responses to the two questions, “Thinking about your last work week, how many hours did you work at home?” and “Thinking think about your last work week, how many hours did you actually work, including regular overtime, extra work, etc.?” The figure is weighted to represent individuals in Germany who had employment subject to social insurance contributions in 2018 and had the option of working at home during the data collection month (for more details on weights, see HOPP Data Manual: https:// fdz. iab. de/ de/ FDZ_ Indiv idual_ Data/ HOPP. aspx) (men: 26 %, women: 24%) and increases in the following policy-relevant because official data from the FEA con - month reaching a new peak in February 2021 (men: 45%, cerning short-time work are published with a 3-month women: 38%). The shares of the other categories indicat - time lag. ing that individuals work from home at least some of the Fuchs-Schündeln and Stephan (2020) analyse the sub- time increase as well. For individuals who spent more jective strain of employed parents with dependent chil- than 40% of their working time teleworking, the share dren. Three-quarters of working parents state that their increases from 9% for men and women (before corona) workload increased during the pandemic. The propor - to between 20 and 25% for men and between 18 and 30% tion of women whose workload has increased sharply is for women. Compared to before corona (54% of men and higher than the proportion of men. Globisch and Osi- 60% of women), a substantially lower share of men (16%) ander (2020) analyse how respondents who report being and women (19%) still worked completely from their in a relationship share childcare responsibilities among workplace. Although this share increases again in June, it themselves. Their results suggest that women continue remains low during 2020 compared to the before corona to shoulder the greater part of childcare responsibili- value and decreases again in January and February 2021. ties. However, the proportion of men who assume more Preliminary HOPP data were used not only to assess responsibility is increasing somewhat. the changes in teleworking time but also to address the Westermeier (2020) focuses on the effects of the corona effect on other labour market outcome variables, such crisis on the employment of older workers. According as short time work, the subjective strain of employed to his results, the unemployment rate for older people parents with dependent children and the effects on the is rising only moderately. However, they are particularly employment of older workers, reflecting HOPPs’ broad affected by the loss of marginal part-time employment analytic potential. (so-called “minijobs”). Older workers are less likely Short-time work is an important measure of active to work in home offices than younger colleagues. The labour market policy, especially in times of crisis, reduction in working hours is only slightly greater in the because it provides financial assistance for employers to 60+ age group than in the younger age groups. prevent layoffs and secure jobs during economic down - turns. Based on data from HOPP, Kruppe and Osiander 6 Data linkage and access (2020a, 2020b) published empirical findings on the use To enrich the survey data with administrative information of short-time work during the early stage of the COVID- on individuals, the data of those who gave consent are linked 19 pandemic in Germany. These results are especially to administrative data available at the German Institute for 16 Page 8 of 14 G.-C. Haas et al. Employment Research (IAB). This linkage expands research are plans to continue the HOPP study for at least 1 year opportunities by including detailed records on earnings, after the crisis. However, the frequency of data collection labour market participation and unemployment or partici- will decrease, as we assume that most individuals have pation in active labour market policy measures at the daily adapted to the situation. level. In addition, the administrative data also provide sev- The collected HOPP data presented in this paper can be eral pieces of information on the characteristics of the firms combined with administrative data available at the IAB, where respondents work. Finally, the record linkage extends which will be continuously updated. Combining HOPP the observation period to 1975, the earliest year of admin- and administrative data will enable researchers to evalu- istrative data availability. The name of the linked data prod - ate the effects of the situation during the corona crisis on uct is HOPP-ADIAB. For each wave, the number of analysis future employment biographies. Therefore, the analytic cases with record linkage consent corresponds to 84% to potential of the HOPP data will increase in the future. For 91% of the overall number of cases in the analysis sample instance, one research aim might be the evaluation of fur- (see the last column in Table 1). ther education during the corona crisis on finding a job or The data of the IAB-HOPP-study are available to the improving one’s own job position. Another research ques- international research community. After data collection, tion might be whether managing home-office and home the data are subject to strict quality and data protection schooling has a negative effect on parents’ careers. control and are disseminated to the research community Looking back to see ahead: our society has had three from the Research Data Centre (FDZ) at the IAB. Three major crises during the last two decades (the financial access modes are offered according to the degree of crisis in 2008, the migration crisis in 2015 and the corona anonymization. The survey is available as Scientific Use crisis in 2020), and the future crises that will impact the Files (SUF) and can be analysed within the institutional German labour market will certainly come. Especially as environment of the researcher. The linked data are avail - lifes become increasingly globally connected, economic able only via remote execution via JoSuA (Eberle et al. crises everywhere can have a substantial impact on the 2017) or on site. Data access is free of charge; however, life and work situations of people in Germany. As such, users are required to sign a Data Use Agreement with the the HOPP is providing substantial data to assess changes FDZ and must comply with further requirements accord- in the labour market, understand the consequences of the ing to the access mode. Further information is available current crisis and identify the need for policy action. on the homepage of the FDZ, which also provides related survey documentation, e.g., a detailed description of the dataset and frequency tables (https:// fdz. iab. de/). Appendix See Tables 2, 3, 4. 7 Future prospects Currently, the HOPP study is conducting its eighth wave (April/May 2021) and is planning to conduct more waves for the duration of the corona crisis. Furthermore, there Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 9 of 14 16 Table 2 Overview of variables up to wave 7 Variables Wave 1 2 3 4 5 6 7 Covid-19 situation Attitudes towards easing of Corona policy measures: Opening public facilities/opening restau‑ X rants, cafés and bars/opening sports facilities/cancelling event ban of events up to 100 partici‑ pants/cancelling general exit restrictions Attitudes towards Corona policy measures: Closure of schools, kindergartens/prohibiting private X X parties/closure of recreational, cultural facilities/closure of sports facilities/contact restrictions/ waiver of private travel/prohibiting of spectators at professional sports/closure of bars, clubs, pubs/closure of restaurants, cafés/14‑ day quarantine in case of infection/wearing of masks out‑ doors/wearing of masks on public transport, stores/none of these measures appropriate Informed about the Corona policy measures in force in my region X X Germany‑ wide uniform Corona measures useful X X Social inclusion and democracy Position in society X Trust towards: federal government/state government/political parties/Federal Constitutional X Court/ press, media/social media/police/science and research/health policy Political party preference X Life satisfaction and worries Current situation: Worried about … own health/health of relatives/financial situation/economic X X X X X X X situation Satisfaction with … health/sleep/free time/family life/contacts to friends and acquaintances/ X X X X X X democracy in Germany/Crisis management of the government General life satisfaction X X X X X X Satisfaction with current professional activity X X Employment Current employment status: employed (> 450 Euro per month)/employed (< 450 Euro per X X X X X X X month)/self‑ employed (wave 1-5), self‑ employed, with employees (wave 6, 7)/self‑ employed, without employee (wave 6, 7)/unemployed/housewife (husband)/maternity protection status, parental leave/partial retirement (“work phase”)/partial retirement (“release phase”)/retired, early retirement/school, vocational training, apprenticeship/student/federal voluntary service, volun‑ tary military service/other Contact frequency with people (not including colleagues) in professional activity X X Restrictions in professional activity since March 2020 X Current restrictions in professional activity X X Employment lost: No/employment (> 450 euros/month)/employment (< 450 Euro/month)/self‑ X employment New employment found / employment restarted X Worries about job loss X X X X X Current employment status (partner) X X X X X X Supervisor: respects privacy/has understanding for family situation/supports me getting ahead X professionally/is role model of how to be successful professionally and privately/knows how much work I do Worries about future career X Concerns about opportunities regarding education, vocational or further training X Employment with fixed‑term contract X X Employment at temporary employment agency X X Main breadwinner: Current situation X Main breadwinner: Before pandemic X Supervisor function X Span of responsibility X Norms in employer-employee relationship 16 Page 10 of 14 G.-C. Haas et al. Table 2 (continued) Variables Wave 1 2 3 4 5 6 7 Own attitude towards norms: avoiding short‑time work in case of financial reserves of company/ X supplementing short‑time work benefits in case of financial reserves in company/home office also for unfinished tasks (without children)/home office also for unfinished tasks (with children)/ obligation to notify employees of where they are going on vacation Presumed attitude majority of employees: avoiding short‑time work in case of financial reserves X of company/supplementing short‑time work benefits in case of financial reserves in company/ home office also for unfinished tasks (without children)/home office also for unfinished tasks (with children)/obligation to notify employees of where they are going on vacation Working hours Working hours before Corona, per week X X Working hours last working week X X X X X X X Overtime last working week, hours X X Partner’s working hours last working week X X X X X Possibility home office X X X X X X X Possibility home office (partner) X X X X X Working hours home office before Corona, per week X X Working hours home office last working week X X X X X X X Partner’s working hours home office last working week X X X X X Home office within normal working hours or during free time X X Home office before start of Corona crisis X Home office and work-life-balance No home office before pandemic because … employer did not allow it/supervisors did not X allow it/technical requirements were not met/preconditions at home were not given/profes‑ sional activities from home are not possible/worsening of promotion prospects feared / presence important to superiors/wanted to separate work and privatelife/preferred working from home/ other professional reasons/other private reasons Current situation: Not working from home because … employer does not allow it/supervisors X X X do not allow it/technical requirements are not met/preconditions at home are not given/profes‑ sional activities from home are not possible/other professional reasons/other private reasons Last working week: Not worked from home because … employer did not allow it/supervisors X X X did not allow it/technical requirements were not met/preconditions at home were not given/ professional activities from home are not possible/worsening of promotion prospects feared/ presence important to superiors/wanted to separate work and private life/preferred working from home/other professional reasons/other private reasons Previous experiences: Home office … is burdensome/is stressful/is an enrichment/helps to man‑ X X age tasks/helps to cope with work demands/helps to make better use of time/helps to balance work and personal life Preferences: How many days/week home office in the future X Work-life balance 1: Private concerns make it difficult for me to concentrate on work/after work, X lack of energy for private activities/miss out on leisure activities due to workload Work-life balance 2: Work demands interfere with private life/time demands of work make it diffi‑ X cult to meet private commitments/stress at work makes it difficult to meet private commitments/ time spent on private demands leads to postponement of work/unfinished work due to family/ partner demands/private life impaired by work obligations Short-time work Short‑time work: Current receipt of short ‑time work benefits X X X X X X X Share of short‑time work (in total working time) X X X X X X Employer subsidy for short‑time work benefits X Employer subsidy (wording changed compared to wave 1) X X X X X Short‑time work (partner): Current receipt of short ‑time work benefits X X X X X Short‑time work since start of Corona crisis X X Abuse short-time work (crosswise 1): Mother’s birthday in January/February & worked more than X X billing for short‑time work Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 11 of 14 16 Table 2 (continued) Variables Wave 1 2 3 4 5 6 7 Abuse of short-time work (crosswise 2): Father’s birthday in January/February & same amount of X X work as before despite short‑time work Abuse of short-time work (crosswise 3): Mother’s birthday in a leap year & Short‑time work X X although dismissal is announced Abuse of short-time work (direct): Worked more than short‑time allowance/Same amount of X X work as before despite short‑time work/Short ‑time work although dismissal is announced New professional/voluntary/other activities during short-time work: No/employment (> 450 X X euros/month)/employment (< 450 euros/month)/self‑ employment/planning self‑ employment/ further training/voluntary work/other Financial benefits Currently receiving or recently applied for: Unemployment benefits (“ALG”)/Means‑tested basic X income (“ALG II”)/housing benefit/other benefit Already received before or since Corona crisis: Unemployment benefits (“ALG”)/Means‑tested X basic income (“ALG II”)/housing benefit/other benefit Further training Further training since begin of Corona crisis in March 2020: Courses/Information events/Self‑ X directed learning/learning opportunities during work/none Further training already planned or started before Corona crisis X Planned further training not possible due to Corona crisis X Further training: Reasons why participation possible despite Corona crisis X Further training: Reasons why participation impossible due to Corona crisis X Further training: Changed importance since Corona crisis X Change of activities in current job X Job insecurity and consumer behavior How much to spend from unexpected amount of money X X X X X Probability of unemployment in the next 3 months (employed) X X X X X Probability of finding a job in the next 3 months (unemployed) X X X X X Household characteristics Household size X X X Living together with spouse/partner X Number of children under 18 in household X X X Monthly net household income X X X Change in monthly net household income (compared to February 2020) X X Household: Living (with) … alone/spouse/partner/children under 18/other related persons/other X (X) (X) X (X) (X) non‑related persons Year of birth of child 1–4 (children under 18, living in household) X (X) (X) X (X) (X) Childcare and couples’ division of childcare and housework Childcare (before Corona crisis): Full day X Childcare (current situation): Full day X X X X Childcare (before Corona crisis): Half‑ day X Childcare (current situation): Half‑ day X X X X Organization of childcare before the Corona crisis (respondents with partner) X Organization of childcare current situation (respondents with partner) X X X X X X Organization childcare before Corona crisis (respondents without partner) X Organization of childcare current situation (respondents without partner) X X X X X X Childcare: Change in burden due to Corona crisis X Childcare: Change in time load in the last 2 weeks X X X X Childcare: Hours on average working day X Emergency childcare during lockdown: In March 2020/in April 2020/no emergency care X Couples’ division of housework (before Corona): Housework/shopping, running errands/repairs/ X financial affairs, visits to authorities/childcare 16 Page 12 of 14 G.-C. Haas et al. Table 2 (continued) Variables Wave 1 2 3 4 5 6 7 Couples’ division of housework (current situation): Housework/shopping, running errands/ X X X X repairs/financial affairs, visits to authorities/childcare Care of relatives X Care of relatives: Change in burden due to Corona crisis X Socio-demographic variables Gender X Year of birth X Highest school degree X Highest vocational degree X University degree X Born in Germany X Year of arrival X Citizenship: German/other EU country/non‑EU country X Parents born outside Germany X Residence State X Living space X Additional space at place of residence: Balcony, terrace/yard/garden/none X Health Health status last four weeks X X Frequency of feelings in last 4 weeks: Angry/Anxious/Happy/Sad X X X X Frequency of feelings of social isolation: Company of others is missing/left out/socially isolated X X X X X X Feelings regarding childcare: Tired, exhausted/overwhelmed/get along well/worried about X X X children’s health Health during last 4 weeks: depressed, gloomy/calm, balanced/a lot of energy/severe physical X X pain/accomplished less in everyday life due to physical health/less active at work due to health/ accomplished less in everyday life due to mental health/less active at work due to health/limited social contact due to mental health X question asked in respective wave, (X) question asked only if no data from previous wave available Table 3 Response rates and analysis cases by month Month New recruits Wave 1 Panellists Refreshment panellists Number of analysis cases N RR N RR N RR Overall With record invited invited invited linkage consent May 200,000 5.7 – – – – 11,311 9548 June – – 9756 45.0 – – 4391 3943 July – – 9756 38.6 – – 3860 3481 August – – 9756 35.9 – – 3500 3175 September 49,594 7.3 1866 73.5 – – 4972 4319 October 49,594 7.6 1892 79.7 – – 5295 4595 November – – 1860 80.3 2395 68.9 3143 2923 December – – 1884 80.7 2543 71.2 3330 3051 January – – 1852 73.5 2388 58.5 2759 2575 February – – 1885 70.0 2553 56.1 2750 2520 Development of a new COVID-19 panel survey: the IAB high-frequency online personal panel (HOPP) Page 13 of 14 16 Table 4 Response rates and analysis cases by calendar week Wave Month Calendar New recruits Wave 1 Panellists Refreshment Number of analysis cases week Panellists N RR N RR N RR Overall With record invited invited invited linkage consent 1 May 19 200,000 3.9 – – – – 7.702 6.484 2 June 23 – – 2435 39.7 – – 966 872 24 – – 2436 36.5 – – 888 811 25 – – 2444 33.8 – – 826 744 26 – – 2441 32.5 – – 794 726 3 July 27 – – 2435 31.2 – – 760 698 28 – – 2436 31.0 – – 754 684 29 – – 2444 27.5 – – 671 602 30 – – 2441 29.1 – – 710 647 4 August 31 – – 2435 23.4 – – 570 517 32 – – 2436 22.3 – – 543 490 33 – – 2444 21.7 – – 530 480 34 – – 2441 20.8 – – 507 466 5 September 36 24,797 4.6 938 46.5 – – 1575 1355 38 24,797 4.4 928 35.2 – – 1409 1232 October 40 24,797 4.5 926 52.6 – – 1615 1405 42 24,797 4.8 966 56.6 – – 1728 1504 6 November 45 – – 935 62.2 1171 48.1 1145 1064 47 – – 925 62.3 1224 48.5 1170 1093 December 49 – – 921 59.6 1308 49.1 1191 1085 51 – – 963 67.6 1235 54.9 1329 1216 7 January 2 – – 933 64.1 1170 50.1 1184 1092 4 – – 919 67.2 1218 47.7 1199 1133 February 6 – – 919 61.0 1311 47.7 1187 1083 8 – – 960 62.7 1235 46.3 1174 1078 Time of invitation changed from Friday to Monday. Acknowledgements Declarations The data utilized described in this paper has been collected during the corona crisis and was only possible with many researchers contributing. We thank all Competing interests researchers that contributed and made the data collection possible: Adrian The authors declare that they have no competing interests. Arens; Sophie Hensgen, Anna Heusler, Annette Trahms, Christian Westermeier, Dana Müller, Elena Röder, Frauke Kreuter, Gesine Stephan, Johannes Ludstek, Author details 1 2 Lina Metzger, Malte Schierholz, Mark Trappmann, Niklas Büchele, Stefan Zins, Institute for Employment Research, Nuremberg, Germany. University of Man‑ Steffen Kaimer, Thomas Kruppe, Van Phan thi Hong. nheim, Mannheim, Germany. Authors’ contributions Received: 24 March 2021 Accepted: 5 April 2021 The authors contributed equally to the analysis and the writing of the article. All authors read and approved the final manuscript. Funding This study was funded by the Institute for Employment Research. References AAPOR: Standard Definitions. Final Dispositions of Case Codes and Outcome Availability of data and materials Rates for Surveys. The American Association for Public Opinion Research, The data access is described in the section Data Linkage and Access. Data and Oakbrook Terrace (2016) Code for specific analyses in this article is available at the Institute for Employ‑ Antoni, M., Schmucker, A., Seth, S., Vom Berge, P.: Sample of integrated labour ment Research (IAB). Up‑to ‑ date access information can be found here: market biographies (SIAB) 1975‑2017. (FDZ ‑Datenreport, 02/2019 (en)), https:// www. iab. de/ en/ daten. aspx Nürnberg, 72 S (2019) Blom, A.G., Cornesse, C., Friedel, S., Krieger, U., Fikel, M., Rettig, T., Wenz, A., Juhl, S., Lehrer, R., Möhring, K., Naumann, E., Reifenscheid, M.: High Frequency 16 Page 14 of 14 G.-C. Haas et al. and high quality survey data collection. Surv. Res. 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Journal for Labour Market Research – Springer Journals
Published: Jun 23, 2021
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