Labor Market Panel Survey, TLMPS 2014 - Tunisia

Abstract --------------------------- The Egypt Labor Market Panel Surveys (ELMPSs) of 1998, 2006, and 2012 and Jordan Labor Market Panel Survey (JLMPS) of 2010 have become well-recognized data sources for labor market studies in the Middle East and North Africa (MENA). These two surveys have been used in numerous research endeavors including peer reviewed academic publications, dissertations, and international organization reports. As part of the same series of surveys, the Tunisia Labor Market Panel Survey (TLMPS) of 2014 is the first wave of what will eventually become a longitudinal survey of the Tunisian labor market. Being far richer than any currently available data, the TLMPS 2014 is a much-needed addition in a landscape of otherwise scarce publicly-accessible data on the Tunisian labor market. The TLMPS 2014 was collected in partnership between the Economic Research Forum (ERF) and the Tunisian National Institute of Statistics (INS). Similarly to its Egyptian and Jordanian counterparts, the TLMPS 2014 is a nationally representative survey that features detailed information on households and individuals, especially in regards to labor market characteristics. As in other countries in the MENA region, Tunisia suffers from high unemployment, particularly for university graduates, youth, and women, and from low female labor force participation. The survey allows for an in-depth investigation of current employment characteristics as well as analyses of broader labor market dynamics. For instance, analyses have already revealed the particularly long unemployment durations Tunisian youth experience, long even in comparison to other countries in the region. For more information, see the paper(s) cited in the "Citations" section: (Assaad, Ragui, Samir Ghazouani, Caroline Krafft, and Dominique J. Rolando, 2016). Geographic coverage --------------------------- The sample covered urban/rural areas of each of Tunisia's governorates Analysis unit --------------------------- 1- Households. 2- Individuals. Universe --------------------------- The survey covered a national sample of households and all households members. Kind of data --------------------------- Sample survey data [ssd] Sampling procedure --------------------------- The initial sample frame included around 5,160 households drawn from a larger sample that is regularly used to conduct the quarterly survey on population and employment in Tunisia. This larger sample contained 18,000 households as of the last quarter of 2012. The drawing of the sample was done in two stages. In the first stage, 258 enumeration areas were randomly drawn according to the principle of probability proportional to size from the list of enumeration areas drawn up in the 2004 Census. This first sampling stage was carried out using 46 strata comprised of the urban/rural components of each of Tunisia's governorates. The final sample was made up of 253 clusters (out of a possible 40,377 nationally). In the second stage, 20 households were supposed to be drawn at random from each cluster. This procedure was, however, not strictly followed in the field. Mode of data collection --------------------------- Face-to-face [f2f] Research instrument --------------------------- The survey incorporates questionnaires to be administered at both the household and individual levels. At the household level, there was a general household questionnaire, as well as a questionnaire specifically about current migration, transfers, and agricultural and non-agricultural enterprises. At the individual level, there was a detailed questionnaire for working age individuals (15+) and an abbreviated version of the questionnaire for those 6-14 years old. The main household questionnaire and the migration/enterprise questionnaire were designed to be answered by the most knowledgeable individual in the household, usually the head or the spouse of the head. Along with information on the characteristics of the dwelling, access to public services, and ownership of durables, the household questionnaire includes a full household roster with information on basic demographic characteristics, such as age, sex, and relationship to the head of household. The migration/enterprise questionnaire includes information on any family members currently abroad, remittances, and other transfers, such as child support and pensions. Data were gathered on both non-agricultural and agricultural enterprises, including assets used and net revenues. The ELMPS and JLMPS had a single questionnaire for all individuals regardless of age. However, in Tunisia, a distinct questionnaire for individuals 6-14 was designed in order to more carefully incorporate measures of child labor. As very little child labor was detected even with this special design, in future LMPSs we plan to revert to a single questionnaire with a few additional questions targeted to children 6-14. The questionnaire includes a variety of modules on labor market experience and outcomes and related issues. On the labor market side, it elicits information on the current labor market status of the individual, detailed job characteristics (for the employed), wage earnings and non-wage benefits (for wage workers) and participation in domestic and subsistence work. Those who work were asked about both primary and secondary jobs (if any). The questionnaire also includes a detailed labor market history starting from the first labor market status after leaving school and moving forward towards the present for those who ever worked. Further, there is a detailed section on return migration for those who ever worked abroad. The labor market intersects with a number of other important life experiences, such as education, fertility, and marriage, which are also captured in the TLMPS individual questionnaire. For instance, there are modules on family background (parents and siblings), educational experiences, health, and residential mobility. For women, a section is devoted to fertility issues, the status of women in the household, and work-family issues such as child care and maternity leave. Data were also collected from both men and women on marriage and decisions around marriage, such as the incidence of kin marriage and living arrangements at marriage. Finally, there are modules on financial decision-making, with specific questions about savings and borrowing, as well as on the use of information technology. Response rate --------------------------- There were several different problems with non-response during the fielding. First, households often refused to respond entirely. Second, in completing the household survey, some individuals were not captured and some households refused or failed to answer the migration/enterprise questionnaire. In this section we discuss the patterns of non-response, which are incorporated into the weights, discussed below: 1. Non-response of the entire household While the initial goal was to collect data from 5,160 households, time pressures reduced the intended sample to 4,986 households. Of the 4,986 households initially selected, interviews were completed with only 4,521, generating an overall household non-response rate of 9.3%. Additionally, because several clusters were found not to have the requisite twenty households at the end of the data collection stage, additional households were added to some clusters to improve the response rate, leading to wide variation in the number of the households per cluster. The minimum number of households interviewed in a cluster was 8 and the maximum was 34. The mean was 19.7, and the median was 20, with the interquartile range going from 17 to 22 households. After this additional work to add households to the sample, non-response rates at a cluster level ranged from 0% (complete response), which occurred for 29% of clusters, to a maximum of 62.5%. The mean non-response at the cluster level was 10.2%, the median was 6.7%, the 75th percentile was 13.3%, and the 90th percentile was 24.8%. This household non-response is incorporated in the weights at a cluster level, with the households that did respond within a cluster representing those that did not. 2. Non-response to child, adult, and migration/enterprise questionnaires As well as problems with non-response on the household level, there were problems with completing the child, adult, and migration/enterprise questionnaires. We developed weights to account for non-response to each of these questionnaires in their entirety. However, individuals often stopped answering partway through a questionnaire, suffered from incorrect skips, or other data problems, such that data is sometimes missing for a particular question within a questionnaire that contains some data. Additional data imputation techniques, implemented on a question-by-question basis, are required for these problems.