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Data availability in participating countries

Data availability in participating countries. Sector specificities. Armenia: Other sources of funds are “in-house funds”, “customer funds”, “other funds”. Moldova: covers only Academy of Science of Moldova. Sector specificities.

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Data availability in participating countries

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  1. Data availability in participating countries

  2. Sector specificities • Armenia: Other sources of funds are “in-house funds”, “customer funds”, “other funds”. • Moldova: covers only Academy of Science of Moldova.

  3. Sector specificities • Belarus: “Private non-profit sector includes private non-profit organisations as professional unions, unions, associations, social groups, charity organizations, funds. Excludes organizations financed by government at more than 50%.”

  4. Kazakhstan: sources of funds • own funds • budget funds • contractors (clients) funds • out-of-budget funds • funds from abroad

  5. Sector specificities: Ukraine • Source of funds difficult to trace. Budget instead of expenditure. • “Expenses for performance of R&D are distributed in Ukraine on such sources of financing: • own means, • means of the state budget, • local budgets, • means of the budget for the maintenance of the higher education institutions, and also • means on sectors (according to yours иструкции).”

  6. Key issues to address • FULL-TIME EQUIVALENTS: does it make sense? How can we construct it in the frameworks of CIS countries? Can we propose some guidelines? • Sector breakdown: how to map Frascati Manual sectors to the sectors in the CIS statistical systems. • How to deal with Business Enterprise sector. • Backward comparability: how to deal with old data?

  7. FTEs • Determining the researcher FTE is especially difficult in the former centrally planned economies despite the fact that these countries have well-developed national statistical systems that collect data from all registered research institutions on a regular basis. Generally, ‘double-counting’ occurs because statistical agencies record the primary place of work of a researcher as the equivalent of a full-time job, counting this as ‘one unit’ while other occupations are then added on. In essence, information on employment is gathered institution by institution without reference to particular researchers. This leads to a situation where a researcher could be allocated a headcount more than once despite the fact that a primary place of work is usually fixed according to the legal systems of these states. • This problem could be solved by the introduction of a procedure where persons with extra jobs are counted in one (primary) place only. In the future, the shares of time devoted to different jobs could be distributed among those posts accordingly. Information on a secondary occupation could be reflected in special sections of the statistical forms of the ‘primary’ organization. Persons who are registered at a primary workplace but not on a full-time basis must be counted according to the corresponding diminishing proportion of time spent at this primary workplace. It is essential that the survey metadata provide a note to clarify the procedure that is followed.

  8. Mapping sectors: proposed matrix (based on Ukraine) This column goes to table 3.2 GERD by sector of performance

  9. Proposed matrix

  10. Proposed matrix

  11. Proposed matrix

  12. Proposed matrix This column goes to table 3.2 GERD by sector of performance

  13. Other issues for discussion • How to deal with Business Enterprise sector. • Backward comparability: how to deal with old data?

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