Crowding in and crowding out within a contribution good model of research
In standard economic theory, government support of science is expected to confer external benefits and ‘crowd-in’ additional private sector research. However, higher rates of economic growth from this effect are not easily discerned from the long run data, and government and business financed R&...
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| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2022
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| In: |
Research policy
Year: 2022, Jahrgang: 51, Heft: 1, Pages: 1-16 |
| ISSN: | 1873-7625 |
| DOI: | 10.1016/j.respol.2021.104400 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.respol.2021.104400 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0048733321001967 
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| Verfasserangaben: | Sebastian Damrich, Terence Kealey, Martin Ricketts |
| Zusammenfassung: | In standard economic theory, government support of science is expected to confer external benefits and ‘crowd-in’ additional private sector research. However, higher rates of economic growth from this effect are not easily discerned from the long run data, and government and business financed R&D have moved in opposite directions (as a proportion of GDP) since the early 1960s in the US and elsewhere. This paper looks at potential sources of ‘crowding out’ as well as ‘crowding in,’ and compares standard analysis with a ‘contribution good’ model of science. Two different policy issues are identified - the assembly of ‘critical mass’ for the ‘kick starting’ of commercial science, and the expansion of commercial science beyond its ‘private equilibrium’. We analyse the allocation of scarce business as well as scientific skills between sectors. The model produces regions of both crowding in and out. The latter dominates for very high wages in the public sector as the government deprives the private sector of the means to exploit new knowledge. |
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| Beschreibung: | Available online 23 October 2021 Gesehen am 06.12.2021 |
| Beschreibung: | Online Resource |
| ISSN: | 1873-7625 |
| DOI: | 10.1016/j.respol.2021.104400 |