KNOWINNO - Making the most of knowledge Innovation in services: the role of R&D and R&D policy (INNOSERV)

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1 KNOWINNO - Making the most of knowledge Innovation in services: the role of R&D and R&D policy (INNOSERV) Policy indicators and analysis Second expert meeting OECD, Paris March 2012 OECD/STI/EAS

2 This presentation AIM: Provide some clues on the analytical research agenda to inform policy questions raised in workshop Initial overview of policy-related indicators from R&D and innovation surveys Do data show service-proofed policies? (By design & take up) R&D and innovation support to service sector firms Analytical strategies, principally based on CIS microdata

3 Public funding of R&D tax incentives sectoral breakdown Tax incentives for R&D Data collection May-2011 First attempt to collect sector breakdown Only a few countries able to provide data Features: R&D definition, extramural, salaries, capital Government funded BERD by main activity available in RDS, but with gaps Includes procurement and grants, no breakdown. Taxable? Overlap with tax incent.

4 Services and R&D tax incentives GBR*# CAN FRA* USA CZE NDL# FIN& JPN DEU& Share of services in business R&D, main activity Share of R&D tax incentives to service sector Share of services in business R&D, product field Share of services in direct R&D funding, as reported Source: OECD NESTI tax incentives questionnaire 2011, MSTI, RDS Data principally for See notes.

5 Public support for innovation 50% Share of firms receiving public support by country and sector 40% 30% 20% 10% 0% CZ DE* EE* ES FI FR HU IT NL PT SK Total High-tech manuf. Low-tech manuf. KIS Less KIS Source: OECD calculations based on CIS 2008 microdata (Eurostat) for INNOSERV. Note: EU16, weighted except for Germany and Estonia

6 Public support 50% Share of service firms amongst companies receiving public support for innovation 40% 30% 20% 10% 0% CZ DE* EE* ES FI FR HU IT NL PT SK Source: OECD calculations based on CIS 2008 microdata (Eurostat) for INNOSERV. Note: EU16, weighted except for Germany and Estonia

7 Barriers to innovation No information on barriers is available in CIS2008, but available in earlier waves Typically, most engaged firms highlight higher extent of barriers implications for analysis and interpretation Examine differences across sectors, and relationship with service innovation

8 Analysis Micro-data availability In depth descriptive analysis - decomposing sector and other patterns Possible policy indicators to include Econometric research relating data/hypotheses/tests

9 Data CIS-Microdata accessible at Safe Centre, OECD countries: CIS3-2000/1 CIS CIS2006 All years CZ, EE, ES, FI, FR, HU, IT, LU, SE, SI, SK, NO, PT EL, DK BE IS, DE CIS2008 NL DE Attempt replication in other countries, EU and beyond Scope for time series, at country/sector level IE IS

10 Analysis Decomposing variation Innovation (i,c,j,t)= {alternative defs + specs} = g(c,j) + c(t) + e(i,c,j,t) = a(c)+b(j)+c(t)+ e(i,c,j,t) = a(c)+b(j)+c(t)+ d*{size,mne} (i,c,j,t)+e(i,c,j,t) Where i-firm; c-country; j-sector; t-year Country sector specificities: g(c,j)=a(c)+b(j)? Cross country comparisons : a(c)=a(c )? Cross sector comparisons : b(j)=b(j )?

11 Analysis Decomposing observed innovation rates Compare countries c and c : Innovation (c)-innovation (c ) = = Σ (p(j,c)-p(j,c ))*(1/2) (inno(j,c)+inno(j,c )) + (between-sectors effect) + Σ (inno(j,c)-inno(j,c ))*(1/2) *(p(j,c)+p(j,c )) (within-sectors effect) i-firm; c-country; j-sector; t-year

12 Variables for analysis Economic outcomes of interest: Y= {Emp(i,t); Turn(i,t); ΔEmp(i,t); ΔTurn(i,t)} Prices = P(j,c,t) Productivity and prod growth proxies Policy / interest variables: - Firm-level: PubSupport=PS(i,j,c,t) - Sector-level: - DirSupportR&D=DSRD(j,c,t) (RDS, OECD) - ICT intensity= ICT(j,c,t) (OECD, EUKLEMS) - Skills= S(j,c,t) (ANSKILL, OECD) - Country-level policy indices: - Employment Protection in 2008, 2003 (OECD) - Product Market Regulation Database (OECD), 2008, also sectoral dimensions

13 Analysis Background - models Crepon, Duguet and Mairesse (CDM) Harrison et al (2008) Innovation in firms (2009) and Phase 2 results, OECD Lack of good instruments for innovation, difficult to support CDM modelling Pursue basic regression analyses

14 Examples of analyses Impact of support on innovation Inno(i,c,j,t)=a(c)+b(j)+c(t)+ f*pubsupp(i,c,j,t) +d*{size,mne}(i,c,j,t)+e(i,c,j,t) Test differences: f-across sectors / countries / size levels Variation depending on the type of innovation Impact of innovation on performance Y(i,c,j,t)= a(c)+b(j)+c(t)+f*inno(i,c,j,t) + d*{size,mne}(i,c,j,t)+e(i,c,j,t) Potential instrument: RD(j,c,t); RD(c,t)

15 Analyses Examine the mediating role of policies on the impact of innovation on business performance Y(i,c,j,t)= a(c)+b(j)+c(t)+ f*inno(i,c,j,t) +g*inno(i,c,j,t)*pol(c,j,t)+ d*{size,mne}(i,c,j,t)+e(i,c,j,t)

16 Spillovers Key question underpinning status quo: Are R&D and innovation spillovers lower for ser vices? How to address empirically? Y(i,c,j,t)= a(c)+b(j)+c(t)+ +f*inno(i,c,j,t) +g*inno( i,c,j,t) + d*{size,mne}(i,c,j,t)+e(i,c,j,t) g impact of innovation elsewhere in sector: conflates positive and negative effects

17 Exploring causal impacts of policies? Different regulations apply to firms of different sizes compare firms at margin? (Garicano et al, 2012) Do rules break down link innovation-firm size?

18 Final remarks and points for discussion Quantitative description of policies for service innovation. First steps. Right priorities? Analytical approaches focused on CIS microdata. Right focus? Alternative meso/macro approaches? Feasibility of reproducing analysis in other OECD countries and beyond?