Assessing the impact of innovation policies: a comparison between the Netherlands and Italy Elena Cefis and Rinaldo Evangelista (University of Bergamo,

Slides:



Advertisements
Similar presentations
Non-technical innovation Definition, Measurement & Policy Implications Workshop Karlsruhe, October 2008 The employment impact of technological and.
Advertisements

Natale Renato Fazio, Stefano Menghinello, Carmela Pascucci and Carla Sciullo Foreign trade and multinational enterprises statistics Division ISTAT ITALY.
Structural Business Statistics Expert Meeting May 2007 Vladimir López-Bassols Economic Analysis and Statistics Division (EAS) Directorate for Science,
Measuring innovation South Asian Regional Workshop on Science, Technology and Innovation Statistics Kathmandu, Nepal 6-9 December 2010.
KNOWLEDGE CREATION AND ABSORPTION: THE REGIONAL DIMENSION Alessandro Sterlacchini UNIVERSITÀ POLITECNICA DELLE MARCHE KNOWLEDGE.
Linking regions and central governments: Indicators for performance-based regional development policy 6 th EUROPEAN CONFERENCE ON EVALUATION OF COHESION.
A NEW METRIC FOR A NEW COHESION POLICY by Fabrizio Barca * * Italian Ministry of Economy and Finance. Special Advisor to the European Commission. Perugia,
Innovation in Portugal: What can we learn from the CIS III? Innovation and Productivity Pedro Morais Martins de Faria Globelics.
Productivity Perspectives depend on your point of view Eric Bartelsman Vrije Universiteit Amsterdam and Tinbergen Institute Canberra, ABS/PC Dec. 9, 2004.
NIS in Poland current situation and recommendations for the future I. Kijenska Faculty of Materials Science and Engineering, Warsaw University of Technology/PRESAFE.
Fear of Relocation? Assessing the Impact of Italy’s FDI on Local Employment Stefano Federico (Banca d’Italia) Gaetano Alfredo Minerva (Università del Piemonte.
Bogota, August 2011 Innovation surveys and innovation policy: the European experience Anthony Arundel UNU-MERIT, The Netherlands & University of Tasmania,
Industrial transition model Case Slovakia Jaroslav Vokoun Bulgaria, Latvia, Lithuania and Slovakia – Comparison of industrial transition models Sofia,
The Italian System of Continuous On-the-Job Training and the Interprofessional Funds Conference "Financing of Further Professional “ Conference "Financing.
How to Enhance the Innovation Capability in New Member States? PhDr. Miroslava Kopicová National Training Fund European Innovating Minds,
Evidence Based Cohesion Policy Focus on performance incentives Thomas Tandskov Dissing Senior Adviser Ministry of Economics and Business Affairs Danish.
1 “European R&D Benchmarking (2002) “European R&D Benchmarking (2002)” Science, Technology and Innovation Policy Student Presentations Students: Miguel.
Innovation Measurement
Raising EU R&D Intensity Evidences from the Report for the European Commission by an Independent Research Group Ana Paiva Inês Costa Science and Technology.
1 “European Innovation Scoreboard (2002) “European Innovation Scoreboard (2002)” Master in Eng. and Technology Management Science, Technology and Innovation.
Trade and business statistics: use of administrative data Lunch Seminar Enrico Giovannini Italian National Statistical Institute (ISTAT) New York, February,
FRANCISCO VELOSO 1 PEDRO CONCEIÇÃO 2 1 Faculdade de Ciências Económicas e Empresariais Universidade Católica Portuguesa 2 Center for Innovation, Technology.
The measurement of Innovation An historical perspective The “Frascati Manual” and the “Oslo Manual” S&T indicators Innovation indicators Some evidence.
Measuring Innovation The 3 rd Community Innovation Survey in Portugal Manuel João Bóia Innovation and Technology Transfer MSc Engineering.
1 Innovation and Employment: Evidence from Italian Microdata Mariacristina Piva and Marco Vivarelli Università Cattolica S.Cuore - Piacenza.
MEADOW: Guidelines for a European survey of organisations Nathalie Greenan CEE and TEPP-CNRS Exploring possibilities for the development of European data.
INNOVATION AND ECONOMIC PERFORMANCE: AN ANALYSIS AT THE FIRM LEVEL IN LUXEMBOURG Vincent Dautel CEPS/INSTEAD Seminar “Firm Level innovation and the CIS.
Strengthening the Regional Innovation Profile STRINNOP – the Experiences with Regional Innovation Indicators Metropolis II Meeting Helsinki, Finland 24.
Territorial scenarios of the MASST3 model in the ET2050 project Roberto Camagni, Roberta Capello, Andrea Caragliu and Ugo Fratesi Politecnico di Milano.
M. Velucchi, A. Viviani, A. Zeli New York University and European University of Rome Università di Firenze ISTAT Roma, November 21, 2011 DETERMINANTS OF.
Human Capital and the Costs of Non-Research Alfonso Gambardella Sant’Anna School of Advanced Studies Pisa, Italy Research policy - Incentives and Institutions.
The Small-Firm Sector. Defining the Small-firm Sector EU definition of SMEs –by number of employees micro enterprises small enterprises medium enterprises.
How Can Countries Benefit from the Presence of Multinational Firms ? Evidence from EU Member Countries and Some Thoughts on South East Europe Bernhard.
1 The role of Government in fostering competitiveness and growth Ken Warwick Deputy Chief Economic Adviser UK Department of Trade and Industry.
The innovation policy in Bulgaria: trends and challenges Assoc. Prof. Teodora Georgieva Applied Research and Communication Fund 1.
TAFTIE Policy Forum “Measuring innovation” Can we measure innovation? Lessons from innovation scoreboards Hugo Hollanders.
INFLUENCE OF DIFFERENT INFORMATION SOURCES TO INNOVATION PERFORMANCE: EVIDENCE FROM FRANCE, NETHERLANDS AND CROATIA Coordination : Roxane Silberman CNRS/Réseau.
Identification of national S&T priority areas with respect to the promotion of innovation and economic growth: the case of Russia Alexander Sokolov State.
Business environment in Slovenia - how to improve it? Ljubljana, 5 June 2015 Stratis KASTRISSIANAKIS European Commission Directorate-General for Internal.
The Role of Financial Structure and Financial Depth in Economic Growth: A Firm Level Analysis for Turkey By Olcay Yücel ÇULHA Pınar ÖZBAY ÖZLÜ Cihan YALÇIN.
Instituto de Gestión de la Innovación y del Conocimiento 1 The articulation of the Spanish Food Innovation System: measurement of the impacts fostered.
Behavioural Additionality Luke Georghiou PREST, Manchester Business School, University of Manchester.
Evaluation of the Norwegian SkatteFUNN scheme Torbjørn Hægeland, Statistics Norway Jan 22, 2004.
“Assessing the impact of public funds on private R&D. A comparative analysis between state and regional subsidies ” Sergio Afcha and Jose Garcia-Quevedo,
Francesco Crespi University of “Roma Tre” Mario Pianta University of Urbino ISAE - Monitoring Italy 2007, Rome 18th October 2007 New processes, old patterns.
UK INNOVATION SURVEY 2005 CIS4 – Introduction and Guide A brief introduction to the survey Some description of the data and analytical results, special.
Export Spillovers from FDI: Evidence from Polish firm-level data Andrzej Cieślik (University of Warsaw) Jan Hagemejer (National Bank of Poland)
Parramatta Economic Development Board Meeting of 9 June, 2004.
USE OF E- COMMERCE DATA International comparisons and a micro-perspective Michael Polder, OECD-STI/EAS Business Statistics User Event: How E-commerce is.
Kathy Corbiere Service Delivery and Performance Commission
MANAGEMENT OF SECURITY RELATED R&D IN SUPPORT OF DEFENCE INDUSTRIAL TRANSFORMATION NATO SfP Assoc. Prof. Dr Dimitar Dimitrov Department “National.
The Knowledge stock of Greek R&D active manufacturing firms: Based on published financial accounts for the period A. Gkypali a, A. Rafailidis.
1 Commercialization Segment Introduction Ralph Heinrich UNECE Team of Specialists on Intellectual Property Skopje, 1 April 2009.
Methodology: IV to control for endogeneity of the measures of innovation. Results (only for regions with extreme values) Table 2. Effects from the 2SLS.
INSTITUTES OF INNOVATIVE DEVELOPMENT: THEIR ROLE IN REGIONAL CLUSTERS Anna Bykova PhD student, Higher School of Economics Russia 23th September 2011 Milocer,
Razib Tuhin Industry Economics Branch Office of the Chief Economist
Regional Policy Guidance on monitoring TÓTH Gábor DG EMPL – Impact Assessment, Evaluation Unit ESF Evaluation Partnership meeting, Rome, 26 November 2014.
MERIT1 Does collaboration improve innovation outputs? Anthony Arundel & Catalina Bordoy MERIT, University of Maastricht Forthcoming in Caloghirou, Y.,
Network analysis as a method of evaluating support of enterprise networks in ERDF projects Tamás Lahdelma (Urban Research TA, Finland)
1/22 Turning the challenges of INSPIRE implementation into business opportunities for European geo-ICT SMEs Glenn Vancauwenberghe Danny Vandenbroucke KU.
Factors influencing innovativeness of SMEs: the case of emerging transition economy Sonja Radas Ljiljana Božić The Institute of Economics, Zagreb.
INNOVATION AND PRODUCTIVITY: A Firm Level Study of Ukrainian Manufacturing Sector Tetyana Pavlenko and Ganna Vakhitova Kyiv School of Economics Kyiv Economic.
Dynamic capabilities in young entrepreneurial ventures: Evidence from Europe Aimilia Protogerou and Yannis Caloghirou Laboratory of Industrial and Energy.
JRC – Territorial Development Unit Petros Gkotsis 08 March 2017
Evaluating European Social Fund “adaptability” measures
Evaluation of R&D public policy in the European Union: an Expert Knowledge-based and two-stage DEA Approach Dª Mónica de la Paz-Marín D.
Innovation.bg 2007 The Bulgarian Innovation System in the EU
Background information
Innovation and Employment: Evidence from Italian Microdata
Does Innovation and Technology Policy Pay-off? Evidence from Turkey
Presentation transcript:

Assessing the impact of innovation policies: a comparison between the Netherlands and Italy Elena Cefis and Rinaldo Evangelista (University of Bergamo, University of Camerino) The impact of innovation on growth and employment Rome, June 23, 2008 Università di Roma "La Sapienza”, Facoltà di Economia

Under-investigated topic Lack of systematic and reliable data & evidence Little evidence on Italy and the Netherlands International literature focuses on the impact of public support to business R&D (“additionality” issue) No conclusive answers (David et al., 2000; Quevedo, 2004)

Need of broadening the evaluation of innovation policies Beyond R&D… Beyond technological input…. Beyond short term effects

CIS indicators Public support to innovation Access to public support (yes/no) Type of incentive (Regional/local, National, European, EU FP) Innovation strategies and performances Type of innovation, tech. input & outputs Innovation expenditures (beyond R&D) sources of knowledge and external linkages objectives pursued obstacles to innovation Economic performances Growth of sales/employment Export propensity Productivity

CIS Data-sets used Firm level (NL & IT): 2) CIS3 (all sample - manufacturing) 3)Longitudinal CIS2-CIS3 (sub-sample of manuf. firms selected in both surveys) 1)CIS4: descriptive – aggregated figures

Issues addressed 1.What kind of “innovation policy models” are in place in Italy and the Netherlands? (mission vs diffuision; Ergas 1987; Cantner et al., 2001 ) - How many (innovating) firms do get a fianancial support? - What is the innovation profile of the firms receiving financial support? 2.What are the effects of innovation policies? In particular on: the resources devoted to innovation the innovation output the innovative behaviours of firms Are there additional effects?

The weaknesses of the Italian innovation system Specialization in medium and low-tech industries Dominant role of SMEs Low percentage of innovating firms Little R&D Dominant role played by process innovation

The Dutch innovation system Specialization in medium and high-tech industries Dominant role played by large firms (MNCs) High percentage of innovating firms Medium/High level of R&D Dominant role played by product innovations

CIS indicators used in the econometric firm- level analysis Presence of a public financial support (independent variable) Access to different types of public funds (regional, national, EU) (binary yes/no) Innovation performances (dependent variables) innovation expenditure per employee (INPUT) sales related to new products (new to the firm/market) (%) (OUTPUT) technological linkages (importance) Innovation strategy/profile (control factors) product/process innovation presence of intra-mural R&D Firm size Sector

Weaknesses of CIS data No possibility of identifying the exact timing of : - the strategic decision to invest on innovation -> the administrative approval of the funding -> the actual financial transfer -> time span of the innovation process (lag bw tech. input and output) cross-section nature of the data ->endogeneity problem No quantitative figures on the amount of the financial support received by firms: we have just a binary (yes/no) variable

CIS Data-sets used (firm-level) CIS3 ( ) – full sample very short time-lag bw the time firms get the incentives and the time when we observe/measure the innovation performances what do we estimate with these data? -> short term effects (although with severe endogeneity problems) -> innovative performance of the firms receiving public support CIS2-CIS3: longitudinal data-set (sub-sample) - 4 years time lag (more realistic…) -Measurement of the impact in terms of rates of change of innovation performance indicators (1996->2000) - >more reliable indications on the presence of “additional effects”

Conclusions Both Italy and the Netherlands are characterized by a “diffusion oriented” innovation policy model (differences with most of the other EU countries) Differences between the two systems: The Dutch model: - supports a rather stable group of (large) R&D performing firms - strong central Governance The Italian Model: - strongly oriented to support SMEs and process- oriented innovation activities - Governance of the system (???): at least two levels (National/Regional) badly coordinated

Limited impact: - more on the inputs than on outputs - short term rather than long-term effects - no/very limited additionality Limited structural/long term effectiveness - no effects on the long-terms behaviours and strategies of firms - no up-grading of the overall innovation profile of the industrial system Indications on the effects of innovation policy

What is the problem? Issues debated in Italy Timing and effectiveness of the evaluation & funding procedures Poor coordination between the different governance levels (regional/national/EU) Lack of serious/rigorous evaluation procedures (both ex- ante e ex-post) Quality of “demand” (poor innovation profile of applying firms) –> vicious circle Low selectivity Types of policy tools/incentives (dominance of automatic mechanisms)