1. Do Companies Benefit from Public Research Organizations
Do Companies Benefit from Public Research Organizations? The impact of the Fraunhofer Society in Germany
Diego Comin (CEPR, Dartmouth)
Georg Licht (ZEW)
Maikel Pellens (ZEW, KU LEUVEN)
Torben Schubert (U Lund, FhG ISI)

2. MOTIVATION One way: investment in applied research organizazions
R&D policy has typically focused on compensating for private underinvestment
Lower private cost of R&D: subsidies, tax credits
Invest directly in scientific knowledge
Capibility to apply R&D towards productivity growth matters too (Ortega-Argiles et al. 2014; Castellani et al. 2016)
Mostly overlooked in policy (but gaining attention: EC 2017; ESIR 2017)
Call for „learning-oriented“ innovation policy
One way: investment in applied research organizazions
Leading countries with strong APRO: NL (TNO), FI (VTT), DE (FhG), SE (RISE)
But anecdotal - little empirical work studying this

3. RELATED LITERATURE
Large body on positive effects of fiscal R&D incentives (Berger, 1993; Bloom et al. 2002; Bronzini and Piselli, 2016, van Cappelen et al. 2012, Czarnitzki et al, 2011; David et al. 2000; Hall, 2003; Knoll et al. 2014, Cowling 2016)
Research on investment in public research as policy lever largely focused of universities & basic knowledge (Belderbos, 2004; Cardamone et al. 2015; Darby et al. 2004; Lööf & Broström, 2008; Maietta 2015; Monjon and Waelbroeck 2003; Mizzio and Derwick, 2002)
Idea: generate spillovers to broader economy (e.g. collaboration)
Well-documented positive effects
Studies on extra-universitary public research organizations remain sparse
Robin & Schubert (2013); Kaiser and Kuhn (2012) analyze effect on firm performance, but cannot distinguish U and other PRO

4. (APPLIED) PUBLIC RESEARCH
Why would extra-universitary (A)PRO be different?
Focus on applied research & technological co-development
Closer to market, easier to appropriate
Need less AC to absorb than with U (Toole et al. 2014)
 U and APRO collaboration with firms might have different effects
Stronger direct impact
Higher dissemination to smaller, less R&D intense firms
 Different policy rationale for funding U versus (A)PRO
U: overcome public good market failure of R&D
(A)PRO: overcome knowledge exploitation bottlenecks

5. INSTITUTIONAL CONTEXT
Germany: strong extra-university research landscape
Helmholtz Association, Max Planck society, Leibniz Association, Fraunhofer Society
Employs 35% of PRO R&D employees
Fraunhofer Gesellschaft
Est. 1949
Focus on applied research & knowledge transfer
employees, budget > 2bn
Contract research with industry large part of funding (30%, ~ 600 m)
67 research institutes in 7 thematic clusters: ICT, life sciences, light & surfaces, microelectronics, production, defense & security, materials

6. Data FhG Projects Confidential FhG contract database 131.158 contracts
Duration, volume, institute, description
German C.I.S. Panel
Information on innovation and performance
Representative annual sample of German firms with at least 5 employees
Select firms observed at least three times
Match on name and address
Exclude foreign clients as well as public institutes

7. FhG Projects: overview
Average project lasts 8 months and costs 37k EUR (FhG revenue)
42% of collaborating firms appear once; 31% 3+ times
Tendency towards applied and well-defined projects, but cover full research spectrum
Keyword analysis:
technology generation (75%) technology implementation (25%)

8. Empirical strategy
RQ: how does collaboration with FhG affect firm performance?
Collaboration: FhG expenditures
Performance: Turnover and productivity growth rate [avg: 6.7% & 6.6%]
(Productivity: added value per employee)
Additionally: does firm innovation strategy change?
Change in innovative sales [avg: -0.01%pt]
Change in high-skilled employees [avg: +0.2%pt]
Specification:

9. DESCRIPTIVE STATISTICS

10. Empirical strategy
Identification challenge: unobserved selection into FhG Our approach: identification through scale heteroscedasticity Lewbel (2012) This case: first-stage heteroscedasticity driven by firm size, therefore: 𝑧 𝑖,𝑡−1 = 𝑣 𝑖,𝑡−1 ∗ ln 𝐸𝑀𝑃 𝑖, 𝑡−1 − ln 𝐸𝑀𝑃 𝑡 where 𝑣 is estimated first-stage error term.

11. Empirical strategy

12. Empirical strategy

13. Results
Notes: * p <0.10, ** p<0.05, *** p<0.01. Regression additionally includes controls for R&D intensity, ln(age), and ln(employees), as well as exporter, group, East-German, industry, and year dummies.

14. Results
Notes: * p <0.10, ** p<0.05, *** p<0.01. Regression additionally includes controls for R&D intensity, ln(age), and ln(employees), as well as exporter, group, East-German, industry, and year dummies.

15. Additional results: firm and project characteristics
Firm characteristics:
Small firms little benefit, but young firms profit more than older
Manufacturing and services firms both benefit, but stronger productivity gains for services (less turnover gains)
Also effects for low-R&D intensity firms (but not for non-R&D performers)
Project characteristics:
Innovation success & turnover growth driven by smaller projects focusing on new technology creation & repeated interaction
Efficiency gains driven by large technology implementation projects – no additional benefits from further interations

16. Conclusions
Empirical evidence of effects of Fraunhofer research on firm performance
Unique panel data of German firms with Fraunhofer contracts Identification through scale heteroscedasticity
Policy implications
Support R&D diffusion alongside input
Investing in APRO such as FhG seems effective channel
Macroeconomic extrapolation: FhG contracts yield 2.2 bn EUR of value added compared to annual budget of 2.1 bn (upper bound estimate)
Future research
Further robustness testing – dynamic selection?
Simulate long-term effects