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 employmentRome, 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 performancesGrowth of sales/employmentExport propensityProductivity

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 innovationthe innovation outputthe 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

Innovating firms receiving public financial supportCIS4: 2002-2004 (% of innovating firms)

Total economy

Manufact. Services

Italy 0.39 0.44 0.24Netherlands 0.38 0.49 0.26

Norway 0.44 0.55 0.34Finland 0.35 0.46 :

Germany 0.14 0.18 :France 0.20 0.26 0.11Denmark 0.15 0.22 0.08Belgium 0.23 0.29 0.14

Spain 0.26 0.28 0.19Greece 0.29 0.32Portugal 0.11 0.13 0.08

Source: Eurostat

Innovating firms receiving public financial support by administrative source of funding. CIS4: 2002-2004 (% of innovating firms)

Italy NL

EU 0.04 0.07

EU IV & V FP 0.01 0.02

Regional/local 0.29 >> 0.09

Central governament 0.17 << 0.43

Source: Eurostat

ManufacturingItaly NL

0.02 0.04

0.01 0.02

0.17 >> 0.05

0.09 << 0.22

Services

Innovating firms receiving public financial support

Manufacturing, 1998-2000 (% of innovating firms)

10-19 26.9 37.9

20-49 41.1 49.0

50-249 56.6 50.4

250 or more 71.1 51.6

Total Manufacturing 49.9 43.9

Firm size (No of employees)

NL IT

Source: Italian and Dutch Statistical Offices

Innovating firms receiving public financial support by type of innovation strategy CIS3: 1998-2000 (% of innovating firms)

Product Process

Innovating firms receiving public financial support

45.7 >> 22.1

from regional/local administr. 3.5 >> 2.4

from central governament 42.1 >> 18.3

from the EU 6.1 >> 2.9

from IV and V EU FP 3.3 >> 1.9

NETHERLANDS

Source: Italian and Dutch Statistical Offices

Type of innovation introduced

Product Process

38.8 << 46.8

22.4 << 26.9

15.5 << 20.5

6.9 6.0

2.3 0.9

ITALY

Type of innovation introduced

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 (1998-2000) – full samplevery 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”

The impact of innovation policies (1998-2000)OLS estimates (without time lag) Dependent variables (2000) % turnover % turnover

due to due to productsnew products new to the market

Indp. variables (1998-2000) B Sig. B Sig. B Sig.

Presence of public financial support

Innovationexpendituresper employee

From local sources 9.019 ** 0.058 *** 0.027 ***

from central.gov sources 8.507 *** 0.037 *** 0.009 **

from EU 7.370 -0.021 -0.007

from EU FP 21.530 *** 0.097 *** 0.060 ***

NL

From local sources 1.560 ** 0.017 * 0.018

from central.gov sources 2.857 *** 0.002 0.002

from EU 1.255 -0.003 -0.011

from EU FP 2.987 ** 0.050 ** 0.039 *

IT

The impact of innovation policies on firms'innovation performances OLS estimates (with time lag -CIS2/CIS3) Dependent variables (2000) % turnover % turnover

due to due to productsnew products new to the market

Indpendent variables (1996) B B B

IT Public financia support 2.833 * 0.024 -0.015

Product innovation 0.103 0.094 ** 0.095 ***

Process innovation 2.588 *** -0.018 0.028

Presence of intra-muros R&D 1.307 0.031 0.000

Intercept -5.544 -0.064 -0.035

No of observations 558 472 472Rsq corrected 0.03 0.11 0.07F. 1.68 ** 3.08 *** 2.23 ***

Innovation

per employeeexpenditures

NLPublic financia support 5.390 ** -0.038 0.004

Product innovation 1.223 0.057 * 0.010 ***Process innovation 2.036 0.004 -0.004Presence of intra-muros R&D 5.760 * 0.043 0.015

Intercept -3.006 0.135 ** 0.027

No of observations 591 591 591Rsq corrected 0.18 0.06 0.06F. 5.82 *** 2.45 *** 2.62 ***

The impact of innovation policies (1994-96) on firms innovation performances (1996-2000)

OLS estimates

Beta t Beta tDependent variables

Rate of change in 1996-2000 of:Innovation expenditures per employee -0.138 -0.673 -0.177 -0.08

Turnover due to new products 0.07 1.379 -0.069 -2.31

Turnover due products new to the market 0.062 1.015 -0.001 -0.06

ITALY NETHERLANDSIndep. Var.

Access to financial support

Indep. Var.

Access to financial support

Logit estimates ^ B Wald B Wald

Increased immportance (in 1996-2000) of:

Interactions with Universities 0.1584 0.516 -0.067 -0.28

Interactions with other R&D Inst. 0.236 1.152 -0.202 -0.86

Cooperation -0.090 0.0012 -0.278 0.99

ConclusionsBoth 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)