Duration analysis concerns all those methods for the analysis of the length of time until the occurrence of some event. Applications in the social sciences are pervasive, including – but not limited to – economics (e.g. time spent in unemployment until one finds a job), education studies (e.g. time spent in education after completion of compulsory schooling), and demography (e.g. time to divorce since marriage).
Three reasons lie behind the decision to undergo a duration analysis. First, the duration analysis solves the problem of the so-called dynamic selection: the composition of any given sample changes over time, e.g. because best connected individuals find a job earlier – hence the “surviving” sample evolves towards one with lower quality of connections with respect to the original sample – or because students with better parental background survive longer at the university, possibly to completion. Whenever these variables are not observed – labour market connections, parental background – any analysis is at risk to return biased results, due to the fact that the sample evolves over time towards one which is on average different from the one originally chosen for the analysis. Duration analysis techniques control for dynamic selection. Second, duration analysis is informative on the so-called “duration dependence”, i.e. on the fact that in some cases it is persistence in a state per se that determines a higher or a lower probability to move to a different state. Third, through formal modelling durations and estimation techniques described in the Technical Report (OECD/Department of Social Protection, Ireland/European Commission, Joint Research Centre, 2024[1]), composition effects due to gender, age, marital status, nationality and years of registered unemployment are excluded.
In the following, this approach is applied to the study of durations of i) periods of eligibility to CE or Tús, until the eligible individual moves to another of the eight states classified in the present chapter, e.g. CE; ii) CE episodes; iii) Tús episodes. What changes with respect to the above is that instead of fixing ex ante the intervals at which the (potentially new, but not necessarily) state of an individual trajectory is observed, an individual is followed as long as the chosen state (eligibility, CE, Tús) persists, and until some event (a transition to another state) occurs. In the following, duration models are estimated assuming that transitions out of the current state occur discretely at monthly intervals, i.e. that in each month of the process under scrutiny (CE/Tús eligibility, CE, Tús) observed individuals undergo some probability to move out of the current state, and that such probability is constant within the month. In addition, the analysis distinguishes multiple destination states, the specific list of which depends on the process under scrutiny (i.e. CE/Tús eligibility, CE, Tús). So, when CE/Tús eligibility is under scrutiny, each individual in the sample is allowed to persist into the eligibility condition, move to CE, to Tús, to EWS, to EWoS or to any other state. When the duration of CE (Tús) is instead analysed, possible exit states are – beyond persistence – Tús (CE), employment (EWS or EWoS), or the state which has been labelled “other”, and that includes eligibility and non-eligibility to CE/Tús. As anticipated above, all estimated models include controls for gender, age, nationality and marital status. Models of eligibility to CE/Tús also include years accrued in the Live Register. Models of CE/Tús include the initial type of claim. Further details, in particular on how the structure of duration dependence is modelled, are provided in the related Technical Report (OECD/Department of Social Protection, Ireland/European Commission, Joint Research Centre, 2024[1]).