Impact & Additionality of Innovation Policy

1. Impact & Additionality of Innovation Policy Luke Georghiou http://les.man.ac.uk/PREST

2. Outline • Additionality and Rationales for Innovation Policy • Behaviour of innovative firms • Conclusions

3. What difference? • Aim of additionality to get beyond “success stories” and address actual effect of public policy action • Basis is comparison with null hypothesis or counterfactual • In 1995 identified three manifestations

4. Input additionality • Focus on input resource • Does the firm spend at least an additional Euro for every Euro in subsidy? • 2 scenarios • Diversion to profits (fiscal support risk) • Substitution of marginal project (grant support risk)

5. Timing Attribution Appropriability Problems in calculating returns to R&D INNOVATION RESEARCH EFFECTS

6. Output additionality • Focus on proportion of outputs not achieved without public support. • Impediments • Outputs are essentially intermediates • Innovation outcomes are hard to attribute to intervention • Sensitivity to time profile

7. Behavioural additionality • Observed that innovation policy effect often not stop-go but modification • UK DTI sub-categories: • Scale additionality • Scope additionality • Acceleration additionality • Applicable during project

8. Behavioural Additionality and Policy Persistence • Concept also applies to persistent or permanent changes in firm behaviour as result of policy intervention • Strategic level – move to new area of activity or business process • Acquired competence level

9. Evidence on additionality • Bach & Matt – cognitive capacity • Davenport and Grimes – behavioural perspective shows importance of acquired managerial competence • Luukkonen – critique of identification of high additionality with success • Hervik – Evidence of trade-off between additionality & economic impact – pushing firms beyond competence or into higher risk profile

10. Additionality & Rationales • Market failure providing general rationale but little specific policy guidance • Lipsey & Carlaw identify narrow and “ideal” tests of additionality as derived from neo-classical approach seeking optimality • Information requirements of strong test create undue transaction costs • Weak test (something policymakers are trying to do has happened as a result of expenditure) associated with structuralist-incrementalist perspective • Without optimality criterion can consider less clearly specified effects (firms are variable) and structural capacity changes

11. Firm or system level?

12. Project fallacy Real deliverables Contract Real project Contract deliverables

13. Quantitative Trends in Industrial R&D • 35% real growth 1993-98 • Why? • Wider range of technological opportunities? • Increased R&D productivity? • Increased competitive pressure to innovate? • Greater ability to afford R&D? • Increased returns from stronger IPR? • But declining proportion of government support for BERD

14. Qualitative trends • Qualitative changes in industrial ecology • Increased acquisition of technology rich smaller companies • Growth in outsourcing • Globalisation • Alliances • All stress relationships – fit with central thrust of innovation policy • Policy rationale is not to redress temporary failure to invest but rather to introduce new capabilities leading to self-sustaining cycle of investment in innovation – behavioural additionality

15. Additionality for SMEs and traditional firms • Innovation policy focus on provision of advice, information and infrastructure • Government shift from provider to broker • Additionality harder to pursue by direct investigation as impacts are lighter and “softer”

16. Testing for additionality through the counterfactual • Matched sample • Issue of how similar firms are and attribution of firm performance to intervention • Failed applicants • Different characteristics of “failures” can be managed • Application process itself can have effects • Direct question • Presumes honest reply and self-knowledge in firm

17. Conclusions (application of additionality) • Pursue input and output/outcome additionality as an ex ante policy design criterion • Accept that ex post a full test of these is not cost effective • Build pragmatic strategy around behavioural additionality • Switch focus from immediate events surrounding project to understanding capacity of innovation system • From flow to stock

18. Conclusions (rationale for innovation policy & sustainability) • Possible use of this rationale to influence innovation for sustainability • Project based approach would be subsidy for clean technology development • Regulatory approach setting compliance standards • Empirical evidence of frequent innovation failure from misjudgement of environmental standards • Systems perspective begins by questioning what capabilities and incentives needed for engagement in sustainable innovation

19. Conclusions (Partnership) • Includes • Need for better information & interaction with regulation • Better understanding of social context for innovation • Command of technology (transformation) • Policy need for coordination through public-private partnership • Flexible & pragmatic rationales aiming to achieve persistent shift in capabilities & hence behaviour