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Web Survey Bibliography

Title Integration of different data collection techniques using the propensity score
Year 2009
Access date 22.11.2009

The present analysis has been made possible by the survey on graduates' condition that is carried out every year by the Inter

‐universities Consortium ALMALAUREA1. The survey makes it possible to analyse the most recent labour market trends through an examination of the career opportunities available for the Italian graduates of the universities taking part in the Consortium during the 5 years on from graduation. All graduates are contacted 1, 3 and 5 years on from graduation. More specifically, the data have been collected during the last survey conducted by ALMALAUREA in 2008 (over 287,000 graduates examined). This survey also involved all first and second level (=cycle of the Bologna Process) graduates from the class of 2007 (about 140,000). The huge number of graduates involved has determined the necessity to use survey methods that allow the reduction of costs and duration. This objective has been achieved through the introduction of two survey methods: CAWI and CATI. More precisely, the graduates having a mailbox (85% of the cohort) have been emailed and asked to answer to a questionnaire on the web site of ALMALAUREA. The survey procedure also included two e‐mail reminders. Afterwards, all graduates who had not answered to the online questionnaire have been contacted by phone. ‐to‐entry into the labour market and so on. These pieces of information are integrated by the huge quantity of data on the sociodemographic characteristics of graduates (e.g. social origins, gender, age), pre‐university studies, academic studies (e.g. degree course, graduation mark) and further experiences made during studies (foreign languages and IT skills, internships, study experiences made abroad and work experiences). It is possible that the survey methods used may have influenced the answer given by graduates. In other words, since the information have been collected through different survey tools (CAWI and CATI), they may have caused distortions that are not casual. For example, the presence/absence of interviewers is an important determinant for the quality of the information collected. On the other hand, because of the cultural level of the cohort involved in the interview, the contribution given by the interviewer may be limited; in some cases it may even be counterproductive, since they may influence the answer of the graduates. In consideration of the complexity of the subject that is dealt with, it has become important to determine if there are significant differences between the answers given by those who filled in the online questionnaire and those who gave their answers during the telephone interview. This need has also been confirmed by the fact that these two groups of graduates have also turned out during some preliminary analysis to be different in terms of their studies and area of residence. The method for evaluating an error deriving from a differentiated treatment (CATI or CAWI) will be developed by following a particular approach that is referred to the typical notions of the so‐called “causal inference”. This problem may be faced by referring to the approach proposed by Rosembaum and Rubin (1983), that is known as propensity score. The authors demonstrate that, having in hand several information which characterise the individuals and which are related to the time that preceded the treatment, it is possible to create groups of individuals having similar characteristics. These groups are, therefore, theoretically deconditioned by the kind of undergone treatment. Within this groups of individuals it is possible to compare the target variable (e.g. the occupational status) among those who have undergone the treatment and those who have not or just have undergone a different treatment. ALMALAUREA has also implemented a monitoring system of selection bias due to different data collection techniques. In this system an innovative approach was used (Camillo and D’Attoma, 2008). It involves a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The aim of ALMALAUREA is to measure and eventually to evaluate the effect of the undergone treatment on the answers given by graduates.

The survey enabled us to collect the main information related to academic and work experiences made after graduation: employment condition at the time of the interview, characteristics of the job (contract, branch of activity, earning), time

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Year of publication2009
Bibliographic typeConferences, workshops, tutorials, presentations