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Modelling methods for forecasting the cross-national labour markets. Challenges and perspectives of labour market research in Oresund Region By Nino Javakhishvili Larsen Special Researcher, Project “Job and Competences in Oresund Region” 21.05.2010 Bornholm. Content.

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  1. Modelling methods for forecasting the cross-national labour markets. Challenges and perspectives of labour market research in Oresund Region By Nino Javakhishvili Larsen Special Researcher, Project “Job and Competences in Oresund Region” 21.05.2010 Bornholm

  2. Content 2 models X 2 cultures X 2 ways: Overview of the models and their differences Data input – challenges and applied solutions Some preliminary results Instruments for application Discussion

  3. Oresunds Region – Commuting area to Copenhagen and to Malmö during a rush-hour by car

  4. 2 models X 2 cultures X 2 ways: Overview of the models and their differences SAM-K-LINE…. rAps is the model system of regional analyses and prognoses that was developed by Statistics Sweden in co-operation with WSP-group (earlier called INREGIA), Sweden and SINTEF, Norway. Currently the model is assigned to NUTEK (Swedish National Board for Industrial and Technical Development). The goals of developing the rAps system were to make regional analytical and forecasting facilities accessible to the central as well as local bodies; and to be applicable for consequence, forecast and policy analyses. rAps system is an input-output macro model. It is built in modules that interact in the complex system. These 5 modules are: demography; labour market; housing market; regional economy; Municipality model.

  5. 2 models X 2 cultures X 2 ways: Overview of the models and their differences

  6. 2 models X 2 cultures X 2 ways: Overview of the models and their differences

  7. Why to calibrate rAps and not LINE? rAps is not updated frequently. Default rAps is not well adjusted to the regional and municipal economy, demography and labour market Top-down approach in rAps becomes problematic when we need to model the parameters at more detailed level (such as, by sector, by education, by gender, by age and etc.)

  8. Data input – challenges and applied solutions

  9. Data input – challenges and applied solutions

  10. Some results – Demand:

  11. Some results – Demand:

  12. Some results – Supply:

  13. Some results – Supply:

  14. Some results – Balance:

  15. Some results – Balance:

  16. Instruments for application Stakeholders: Labour market authorities Regional administrations Education planning institutions Instruments: Monitoring Decision-making Planning

  17. Conclusions – sum up… Methodology – adjusted and calibrated rAps at the different level to make the results comparable Results – discovered the synergy and integration potential for Oresund labour market Application – forward the results for strategic planning of regional development, education and labour market (at the political and institutional level) (Seminar on the 14th of June)

  18. Questions for Discussion What are your experiences to work with the cross-national forecast models and statistical data and what methods do you use to integrate them? What are your suggestions, how can we improve the modelling methods and the results? What are your suggestions how to apply the forecast results in the strategic planning at the cross-national level?

  19. www.jobkompetence.net

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