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Symposium on Business Dynamics and Innovation: The effects of agglomeration economies Barcelona, 8 October 2008 “Assessing the impact of public funds on private R&D. A comparative analysis between state and regional subsidiesSergio Afcha and Jose Garcia-Quevedo, University of Barcelona

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Symposium on Business Dynamics and Innovation: The effects of agglomeration economies Barcelona, 8 October 2008. “Assessing the impact of public funds on private R&D. A comparative analysis between state and regional subsidies ” Sergio Afcha and Jose Garcia-Quevedo, University of Barcelona. - PowerPoint PPT Presentation

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Page 1: Outline of the presentation

Symposium on Business Dynamics and Innovation: The

effects of agglomeration economies

Barcelona, 8 October 2008“Assessing the impact of public funds on private R&D. A comparative analysis between state and regional subsidies”

Sergio Afcha and Jose Garcia-Quevedo,University of Barcelona

Page 2: Outline of the presentation

Outline of the presentation Motivation: increasing importance of

regional innovation policies Objectives: evaluation of public policies Data and descriptive statistics Methodology and results Conclusions and future lines of

research

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In the last two decades increasing interest has been putting in the relationship between geographical location and innovation (Storper, 1997; Audretsch&Feldman, 1999).

Emergence of different concepts about industrial agglomeration: Clusters, Industrial districts, Innovative Millieu, competitive regions etc. Has contributed to the awareness of regional dimension is a suitable level to promote innovation activity.

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More active role of regional actors (Government, Institutions, firms)

Regional governments: specific regional policies in order to promote regional innovation systems.

However... There is few evidence about: Evaluation studies in innovation policy at

regional level, and comparisons between regional and central government interventions

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This work compares central and regional policies promoting R&D activities:

I. Analyzing determinants (firms characteristics) of receiving subsidies, both at regional and central level.

II. Quantifying the effect of central and regional R&D subsidies on firms’ Innovation effort (financial additionality).

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Data and descriptive statistics

Data: Survey on Business Strategy, ESEE (Encuesta de estrategias empresariales/FUNEP).

Period: 1998-2005.

Sample: Innovative manufacturing firms. R&D >0.

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 Non subsidized firms

Subsidized firms at regional level

Subsidized firms at central level

Year250 employees or less

More than 250 employees

250 employees or less

More than 250 employees

250 employees or less

More than 250 employees

1998 1.59 1.00 3.41 2.38 4.70 2.191999 1.58 1.10 3.80 2.19 5.61 2.932000 1.95 0.85 3.61 1.31 4.87 1.642001 1.89 1.10 3.51 3.40 4.03 3.702002 1.50 0.92 4.19 2.40 5.28 2.962003 1.91 1.11 3.75 1.99 4.74 3.102004 1.59 0.99 2.03 2.70 3.79 4.142005 1.77 1.31 5.16 2.49 5.44 3.10Total 1.71 1.04 3.91 2.31 4.92 2.87

Innovative Effort

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Central RegionalPublic Subsidies state/regional Coef. Std. Err. Z Coef. Std. Err. ZCOOPERATIONJoint Ventures 0.21 0.12 1.77* 0.18 0.13 1.36Coop. Univ. and Tech. Centers. 0.41 0.10 4.05*** 0.50 0.11 4.38***Coop. with Customers -0.11 0.09 -1.23 0.02 0.10 0.26Coop. With Competitors 0.18 0.13 1.32 -0.23 0.15 -1.37Coop. with Providers 0.23 0.09 2.43*** -0.06 0.10 -0.58Part. EU projects 0.72 0.27 2.60*** -0.05 0.27 -0.21RRHHRecruitments of Univ. Graduates and Engineers 0.23 0.09 2.42*** 0.33 0.10 3.10***Recruits personnel with R&D experience. -0.08 0.08 -0.96 -0.09 0.09 -0.98INNOVATIONInnov. New functions -0.00 0.10 -0.07 0.05 0.10 0.54Innov. New materials 0.11 0.11 1.00 -0.05 0.12 -0.42Innov. New components 0.11 0.12 0.91 -0.05 0.13 -0.43Innov. New design -0.11 0.11 -1.05 0.15 0.11 1.36Innovation Indicators 0.03 0.08 0.40 -0.02 0.09 -0.29Tech. Export-Tech. Imports 50.74e-07 40.60e-06 0.12 40.12e-07 50.99e-06 0.07Total Nº of patents 0.04 0.02 2.42*** -0.01 0.02 -0.63Capital Participation in Innovative firms -0.06 0.11 -0.54 0.15 0.12 1.23PUBLIC FINANCESState/Regional subsidies 0.58 0.11 5.20*** 0.58 0.10 5.57***Others subsidies -0.05 0.22 -0.23 0.26 0.22 1.20Innovative effortt-1 0.02 0.01 1.86* 0.000 0.01 0.08Public Subsidiest-1 10.48 0.08 16.64*** 10.71 0.10 17.03***FIRMS CHARACTERISTICSAge 0.0008 0.001 0.50 -0.00 0.00 -1.41<250 emp. -0.26 0.10 -2.54*** 0.18 0.10 1.69*Industry Med-High 0.24 0.09 2.70*** -0.09 0.09 -0.94Nº of competitors 0.04 0.04 1.13 -0.01 0.04 -0.33% Foreign Capital -0.001 0.0009702 -1.38 -0.00 0.00 -0.03REGIONALS DUMMIESCatatonia 0.01 0.10 0.17 - - -Madrid 0.18 0.12 1.49 - - -Basque Country -0.04 0.13 -0.36 - - -Times dummies Included Included

Nºof Obs.=2213 Nºof Obs.=2213LR chi2(38)=787.42Prob>chi2=0.0000Pseudo R2=0.41

LR chi2(38) =566.65Prob> chi2=0.000Pseudo R2=0.3669

Results (Probit estimations)

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If coordination works, relevant variables should not be exactly the same in the Probit regressions.

Coincidence in significant variables could be indicating duplication of goals at different levels of government.

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Summary of results: firm characteristics

Central Subsidies Regional SubsidiesSign Variables

COOPERATION

Equal sign

Cooperative agreements with Universities and Technological centers (+)

Cooperative agreements with Universities and Technological

centers (+)

Significant in only one regression

Joint ventures (+) Cooperation with providers

(vertical cooperation) (+) Participation in UE Projects (+)

HUMAN RESOURCES Equal sign Recent recruitment of

University graduates and engineers (+)

Recent recruitment of University graduates and engineers (+)

R&DSignificant in only one

regression Total patents (+)

FINANCIAL

Significant in only one regression Innovative Effort in t -1 (+)

Equal sign Subsidies from another level of

government (regional)(+) Central subsidies in t-1(+)

Subsidies from another level of government (central) (+)

Regional subsidies in t-1 (+)

FIRMS CHARACTERISTICSDifferent sign More than 250 employees (-) Less than 250 employees

(+)Significant in only one

regression Medium–High Tech. Industry (+)

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Evaluation of central and regional R&D subsidies (additional effects?)

Non parametrical Technique: Propensity score Matching. Nearest neighbor matching algorithm.

Purpose: Establish a valid control group in order to compare innovative effort performed by subsidized and non subsidized firms.

Control Group: Innovative firms without subsidies.

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Results (Evaluation)

CENTRAL REGIONAL

ATT1 (Z-Value) 0.56 (1.7)* 0.66 (1.08)

ATT2 (Z-Value) 0.87(3.59)*** 0.53(1.38)

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Although some common patterns, evidence of differences (firm characteristics) in the participation in regional and national innovation policy. Crowding out effect is rejected for central subsidies. Evidence of additionality (Herrera&Heijs, 2007; Fernandez&Pazó, 2008;) ATT for regional subsidies are not statistically significant. Regional effects should be estimated by region in order to take in account regional differences. Regional innovation policy: Need to analyse other additional effects (behavioral)