Understanding duration of unemployment in data

Notes from meeting with Peter Surstedt and other WPI data team members 19 February 2020.

RAAK data: 

  • In RAAK this data is registered as when the uitkering contract starts and ends.
  • The data includes a unique code per person and another code for the ongoing trajectory. So a person can have one unique number and multiple trajectories.
  • We also combine to this data the stadsdeel, gebied, buurtcombi, age group (between 18-27 and 28-32 years) and trede
  • We first look at the year 2019 to see the how the ended trajectories are registered. When we see by chance that a person has twice trajectories, we decide to look at a longer time span and choose since 2002.
  • This way we notice the people in Zuidoost who have multiple entries with their location.

 

To this we add the NUG data

  • We find out that in the NUG trajectories, postcodes are missing.
  • A way to go around can be to add this data to the previous collection we prepared and use the ones that come additional to the already existing unique codes. 

 

Communication types:

  • Could be interesting to study it could give ideas about the rhythm of an unemployed young person that is a client. 
  • These are: document (uitgaand), e-mail (uitgaand), sms (uitgaand), rapportage RIB, gesprek op locatie, e-mail (inkomend), telefoontje (inkomend), rapportage deelname, chat, sms (inkomend), telefoontje (uitgaand), document (inkomend), telefoontje (uitgaand), groepsbijeenkomsten, gesprek aan huis, gesprek, contact BMW

 

Clients and non-clients

  • The RAAK data shows only the people who are registered as a client, which means that they get uitkering.
  • There are also people who are registered on WW, which is the salary a person can get after their employment is ended. These people don’t appear on the gemeente system.
  • Then there are the NUG people, who are a client but don’t get uitkring. WPI has contact with them.
  • If a person above 18 decides not to study or not to work after graduation, they don’t appear on the system. They become a client unless they go to the municipality and declare themselves as a client, by saying the they don’t have a job and they need uitkering, or they need some kind of help.
  • If a young person quits school (leerplicht hebben) then the jongerenpunt gets a notification about it. 
  • So there is an evident gap on the young people the city can reach. 

Research interests

These comparisons below are listed since they may be interesting for the city rhythm research. Creating these vary in difficulty due to how the data is registered and stored. The availability of the data is also a challenge sometimes.

Whenever we mention vs space, we mean that it would be interesting to see the spatial distribution of the data over a map. SAP offers limited solutions where Tableau software could allow for more robust and expressive visualizations.

  • Unemployment vs space (age groups and income)
  • Unemployment duration vs space (based on start and end dates of contracts)
  • Going in and out of unemployment vs space
  • Unemployment type (trede) vs space
  • Doelberoep vs. Space
  • Opleidingsniveau vs. space
  • Activeringsplekken vs. Space
  • Activeringscontracten vs. Space (aanvang en einde)
  • Unemployment age vs space
  • Unemployment gender
  • Employment type (what are the types of jobs people get when they get a job)
  • Unemployed people and family type (maybe also spatial)
  • Within the Begeleidingsperiode how many times has a client been in a job and o