A. Description of the sequence data

Analysis will be focused on the Italian case using data that match information from INPS (Social Security) archives and survey data from Italian section of the European Union Statistics on Income and Living Conditions (Eu-Silc). Data include information about: contract extent, amount of contributions and salary, employment sector, firm dimension. Eu-silc survey collects cross-section and longitudinal data in European Countries on wage, social exclusion, work conditions, quality of life. A retrospective panel has been constructed matching INPS data and Italian Eu-silc data (wave 2005). I am still working on my project, but for the course purposes I decided to focus on employment status and salary. Analysis aim to delineate a typology of different pattern of labour market participation. A subsample of individuals between 40 and 45 years in 2005 will be selected: it will be possible to follow their work career from the beginning to the work maturity phase.

B. Description of the sequences

• one sequence per case

• chronological sequences

• alphabet (no natural order of the symbols) Employment = E Unemployment+no transfers =UNT Unemployment+ transfers=UT Employed+positive change (higher salary than before)=EP Employed+neutral change (same salary than before) =ENU Employed+negative change (lower salary than before)=EE

• Size of the alphabet= 6 states

• Number of sequences: 2253 individuals (1140 men; 1123 women)

• Maximum and minimum sequence lengths: 240 months for each individual

C.The kind of knowledge you expect to extract from your sequences

The analysis will look at some specific variables to define each one-month episode of the sequences representing individuals' work careers in order to account for dynamic of career. Indeed, my first interest is about duration in order to study fragmentation degree and careers trajectories direction.