Transcript Slide 1

Industrial upgrading in Western Balkans
and policy implications
Prof. Slavo Radosevic
Keynote remarks
The Impact of Economic Crisis in Western Balkans: Implications for Politics,
Innovation and Change
EBRD, Roundtable discussion, Friday 12th February 2010
Outline
• Western Balkans: a brief recap of recent and
not so recent history
• Industrial upgrading: production and
innovation capability and foreign levers to
growth
• Policy lessons
2
Western Balkans: a brief recap of recent and past
history
• After 1989: the SEE/WB has become a new European periphery
• Lesson from history: the growth of periphery is inextricably linked to its
international economic integration (Berend and Ranki, 1982).
• Catch up with the EU core = f (the relative roles of exogenous and
endogenous forces * the nature of their interaction)
• The direct economic ‘pull’ of the old EU through finance, FDI and
intra-industry trade > < the domestic forces (national system of
political economy) which enable the external influences to have spin
off effects
• My lenses today: industrial upgrading
3
Motivation
• A big income gap should enable mixing up of different
‘production functions’ or integration to the EU through
increasingly fragmented industrial networks and value
chains. Why we do not see it happening?
• What hinders exploitation of productive potential which
should emerge from the big income differences between
EU15/WeBa?
• Why WeBa is not location to low cost export oriented FDI
to EU15?
4
WeBa countries: basic factors and their
efficient use as drivers of growth
Factor
driven (FD)
stage
Transition
from FD to ED
stage
Efficiency driven
(ED) stage
Transition
from ED to
ID stage
Innovation
driven (ID)
stage
Albania
Bulgaria
Croatia
Greece
Bosnia and
Herzegovina
Macedonia, FYR
Slovenia
Montenegro
Romania
Serbia
Turkey
Source: WEF (2007)
5
Industrial upgrading: how to move up along
value chain?
• Cost vs. quality vs. technology based competition
• Requirements for technology based competition
–
–
–
–
–
–
–
–
–
competition based on product/process innovation
sophisticated demand
user requirements
certificates and standards
marketing barriers (brand)
after sale services and warranty
IPRs
affordable access of NTBFs to technical infrastructure
available finance to upscale production
• For the time being, upgrading in WeBa is about production
not innovation capability
6
An example of B&H in a comparative perspective
• A recap of the recent history: From relatively
developed industry R&D oriented RTD system
towards decimated and dominantly HES oriented
research system (see next two slides)
• There is not alternative magic route but back
towards enterprise based RTD system
7
Shares in GERD of CEE - 10 (NMS) performed by
different sectors (based on averages)
….. a huge structural gap of B&H
0.60
0.50
0.40
BES
GOV
HES
0.30
PNP
0.20
BES R&D B&H ?
0.10
0.00
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
8
Decimated research system of B&H
Radosevic, S. South Eastern Europe, UNESCO World Science Report 2010, Paris (forthcoming)
9
Collaboration paradox of laggards: science systems
which are highly dependent on foreigners
Share of international collaborations in scientific publications, 2006
100%
100%
90%
85%
79%
80%
78%
70%
65%
63%
60%
52%
50%
42%
38%
40%
37%
35%
G
re
ec
e
lo
ve
ni
a
S
R
om
an
ia
ul
ga
r ia
B
C
ro
at
ia
er
bi
a
S
R
O
M
FY
&H
B
ol
do
va
M
lb
an
ia
A
M
on
te
ne
gr
o
30%
Source : data from Thomson Reuters (Scientific) Inc. Web of Science
10
There is not world frontier technology effort
coming from WeBa
USPTO Patents by Inventor's Country, 2000 - 2007
Country / Territory
1 Albania
2 Bosnia Herzegovina
3 Croatia
2000
2001
2002
2003
2004
2005
2006
2007
6
10
13
14
11
13
22
17
2
1
4 Montenegro
5 Republic of Moldova
6 Serbia
7 The former Yugoslav Republic of Macedonia
5
6
8
5
2
4
2
8
1 Bulgaria
3
5
11
15
7
6
7
10
2 Greece
3 Romania
4 Slovenia
25
7
19
36
11
26
33
5
17
34
10
19
26
13
24
23
15
13
39
22
25
37
21
25
Neighbouring countries
Source : data from Thomson Reuters (Scientific) Inc. Web of Science, (Science Citation Index Expanded - SCI Expanded, Social Sciences Citation Index SSCI and Arts & Humanities Citation Index - AHCI), compiled by Canadian Observatoire des sciences et des technologies for UIS.
11
B&H: What is use of R&D at $4,625 pc (IMF 2008)
(B&H GDPpc) ?
• A limited direct role of R&D to contribute to
economic growth at this income level
• Absorption and diffusion of new technology is the
key driver of growth; RTD as an important
precondition to absorb and diffuse
• R&D as a proxy for absorptive capacity as ‘R&D
not only generates new information, but also
enhances the firm's ability to assimilate and
exploit existing information’ (Cohen and Levinthal,
1989).
12
Different institutional profiles of R&D systems ….
Dominant performing sector < Dominant source sector
Model 1
Model 2
Model 3
Model 4
Model 5
BES < BES
BES < GOV HES < GOVGOV < GOV GOV < BES
USA
Slovakia
Portugal Bulgaria
Kazakhstan
Ireland
Hungary
Estonia
Azerbaijan
France
Poland
Lithuania
UK
Belarus
Turkey
Austria
Croatia
Belgium
Russia
Finland
Romania
Germany
Spain
Korea (Rep)
Slovenia
Czech R
Latvia
13
Institutional structure of funding and performing R&D in
WeBa: Government and HES SEE dominated systems
Funding
Country
Performing
Business Enterprises
sector (59%);
Government (35%);
Slovenia
Business Enterprises sector (60%);
Government (22%); Higher
education sector (16%)
Government (48%);
Business Enterprises
sector (45%)
Romania
Business Enterprises sector (55%);
Government (34%); Higher
education sector (10%)
Government (56%);
Business Enterprises
sector (42%)
Croatia
Business Enterprises sector (43%);
Higher education sector (35%);
Government (22%)
Government (51%);
Business Enterprises
sector (41%)
Turkey
Higher education sector (64%);
Business enterprise sector (29%)
Government (47%);
Business Enterprises
sector (31%)
Greece
Higher education sector (49%);
Business enterprise sector (30%);
Government (21%)
Government (67%),
Business enterprise
sector (27%)
Bulgaria
Government (67%); Business
Enterprises sector (24%)
???
Serbia and
Montenegro
Higher education sector (52%);
Government (44%)
???
Macedonia,
FYR
Government (76%)
??
Bosnia and
Herzegovina
??
??
Albania
??
14
BES dominated R&D systems are feature of countries above
$15Kpc
Model
GDP pc 2003 type
USA
Ireland
France
UK
Austria
Belgium
Finland
Germany
Spain
Korea (Rep)
Estonia
Slovenia
Portugal
Czech R
Latvia
Slovakia
Lithuania
Hungary
Poland
Kazakhstan
Belarus
Croatia
Turkey
Russian Fed
Bulgaria
Romania
Azerbaijan
29,037
24,739
21,861
21,310
21,232
21,205
20,511
19,144
17,021
15,732
14,340
13,995
13,807
9,905
9,722
9,392
7,986
7,947
7,674
7,655
7,387
7,233
6,731
6,323
6,278
3,510
3,394
1
1
1
1
1
1
1
1
1
1
3
1
3
1
1
2
3
2
2
5
2
2
3
2
4
2
4
Model
Dummy
1
1
1
1
1
1
1
1
1
1
0
1
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
15
An indirect R&D content dominates in the EU 10 CEE:
Percentage share of total R&D content in the manufacturing of ICT
equipment
Source: Knell M. (2008), Embodied technology diffusion and intersectoral linkages in
Europe. Europe Innova Sectoral Innovation Watch deliverable WP4. European Commission,
Brussels.
16
Direct and indirect R&D content: policy
implications
• A majority of the NMS and all WeBa are technology users and
have a high indirect technology intensity
Non-EIS pattern of technology upgrading:
-> low overall technology intensity -> high indirect
technology intensity -> average direct and indirect technology
intensity -> high direct technology intensity
Policy implication: integrate FDI / technology transfer into
innovation policy
(increase R&D but in interaction with imported and indirect domestic
R&D (embodied in capital goods and inputs)
17
Production capability as driver of
productivity; the inefficiency of NIS in EE
• Production capability and R&D as drivers of productivity (see next two
slides)
• Given their levels of R&D, innovation and quality related activities
(ISO9000), EBRD economies have lower levels of GNI per capita
compared to the ROW.
• The models that include sub-regional dummies (11 and 12) show
improved explanatory power confirming that inefficiency of the NSI
characterizes all EBRD sub-regions
• EBRD countries sample: ISO certification as a proxy for production
capability significantly contributes to explaining the differences in
productivity. In a catching up context, R&D denotes absorptive rather
than innovative capability
18
Table 3. Determinants of productivity in EE and non-EE countries, 1993-2005
Model_7 Model_8 Model_9 Model_10 Model_11 Model_12
ln_researchers_in_rd
0.34***
0.21***
0.22***
0.16***
0.42***
0.27***
-7.39
-6.41
-6.34
-6.28
-20.27
-13.02
ln_patent_resid
0.02
0.01
-0.47
-0.22
ln_ISO_FDI
0.03***
0.03***
0.10***
-6.7
-7.52
-7.89
Log of ISO standards per capita
0.05***
0.05***
0.21***
-9.44
-11.08
-16.29
cis_dummy
-0.59***
(-4.83)
see_dummy
-0.55***
-0.50***
(-6.31)
(-5.72)
ceb_dummy
-0.37***
-0.38***
(-6.20)
(-6.36)
_cons
7.21***
8.22***
8.28***
8.74***
6.33***
9.61***
-21.94
-33.64
-32.1
-45.92
-17.29
-38.13
Number of observations
364
449
374
471
449
471
R2
0.313
0.243
0.349
0.329
0.755
0.762
note: *** p<0.01, ** p<0.05, * p<0.1
The dependent variable in all the regressions is gross national income (GNI) per capita. Method of estimation: panel data model with fixed effects
(Model 7-10) and step-wise OLS (Model 11 – a reestimation of Model 8 with dummies, and Model 12 - a reestimation of Model 10 with dummies) with
fixed effects for years (year dummies are not reported in the final presentation or results) and groups of EE countries
Source: Kravtsova and Radosevic (2010)
19
Table 4. Determinants of productivity in EE countries, 1996-2005
(Reestimation of table 3 for EE countries)
Model_7.1 Model_8.1 Model_9.1 Model_10.1 Model_11.1 Model_12.1
ln_researchers_in_rd
ln_patent_resid
ln_ISO_FDI
0.17
-1.45
0.1
-1.3
0.09***
-8.9
0.20*
-1.81
0.22**
-2.16
0.1
-1.48
0.23**
-2.44
0.08***
-9.69
Log of ISO patents per capita
0.10***
-12
0.10***
-12.8
ceb_dummy
Number of observations
R2
note: *** p<0.01, ** p<0.05, * p<0.1
8.32***
-9.01
121
0.478
8.65***
-10.24
126
0.497
0.14***
-3.86
0.11***
-10.63
see_dummy
_cons
0.08**
-2.11
8.01***
-10.18
121
0.614
8.46***
-11.79
126
0.625
-0.15**
(-2.53)
0.16***
-2.97
9.68***
-25.67
126
0.827
0.14***
-19.82
-0.26***
(-7.15)
9.63***
-34.31
126
0.832
Note: Dependent variable in all regressions: GNI per capita. Method of estimation: panel data model with fixed effects
{Model 7-10} and step-wise OLS in Model 11 {reestimation of Model 8 with dummies} and Model 12 {reestimation of Model
10 with dummies} with fixed effects for years {dummies for years are not reported in the final presentation} and groups of
EE countries Source: Kravtsova and Radosevic (2010)
20
A shift from production to innovation capability is
not automatic and linear process
•
•
•
•
S and D factors for RTD are driven by different forces (cf. not
significant correlation between aggregates)
Not significant correlation between firm level technology absorption and
company spending on RD across countries* + not significant link between
firm level technology absorption and capacity for innovation > significant
difference between innovation capacity and production
capability/absorptive capacity.
Innovation variables (capacity for innovation and company spending
on RTD ) are strongly and significantly correlated to external RTD
factors (local specialised research and training, quality of scientific
research institutes and to demand) and to demand factors (customer
orientation, buyer sophistication).
*For very similar result see EBRD TR 2009, p. 102: there is not link between management
practises and either % of innovative sales or R&D spending (cf. not, this is not
measurement error)
Source: Radosevic, S (2009) ‘Research And Development and Competitiveness, and European Integration of South Eastern Europe’, EuroAsia Studies, June 2009, Vol. 61, No. 4, June
21
Loc.
availab.of
spec.
R&D/train. Quality of
services
sc. RI
Prod.proce
Extent of Firm-level
ss
Buyer
Degree of Company
staff
technology sophisticati sophisticati customer spending Capacity for
training absorption
on
on
orientation on R&D innovation
Loc. availab.of spec.
R&D/train. services
Quality of sc. RI
1
.874(**)
.874(**)
1
0.545
0.405
.693(*)
0.51
0.592
0.47
.648(*)
0.541
0.572
0.482
.865(**)
.783(**)
.686(*)
.698(*)
Extent of staff training
0.545
0.405
1
.759(*)
.924(**)
.857(**)
.914(**)
.687(*)
.801(**)
.693(*)
0.51
.759(*)
1
.838(**)
.786(**)
.811(**)
0.603
0.545
0.592
0.47
.924(**)
.838(**)
1
.945(**)
.949(**)
.727(*)
.733(*)
.648(*)
0.541
.857(**)
.786(**)
.945(**)
1
.965(**)
.802(**)
.789(**)
0.572
0.482
.914(**)
.811(**)
.949(**)
.965(**)
1
.750(*)
.815(**)
.865(**)
.783(**)
.687(*)
0.603
.727(*)
.802(**)
.750(*)
1
.906(**)
Firm-level technology
absorption
Prod.process
sophistication
Buyer sophistication
Degree of customer
orientation
Company spending on
R&D
Capacity for
innovation
22
.686(*)
.698(*)
.801(**)
0.545
.733(*)
.789(**)
.815(**)
.906(**)
1
Assessment of demand and supply for local R&D in
SEE - Supply of RTD is still above demand for RTD
Source: Radosevic, S (2009) ‘Research And Development and Competitiveness, and European Integration of South Eastern Europe’,
Euro-Asia Studies, June 2009, Vol. 61, No. 4, June
23
Proxies for quality of supply and demand for RTD in SEE
•
Supply
– Quality of education
– Quality of math and science teaching
– Local availability of spec. research
and training
– Quality of public (free) schools
– Quality of scientific research institutes
– Availability of scientists and engineers
•
Demand
– Extent of staff training
– Firm level technology absorption
–
–
–
–
–
Production process sophistication
Buyer sophistication
Customer orientation
Company spending on R&D
Government procurement adv. techn
products
– Capacity for innovation
Note: These are responses of local business communities which are assessing
demand and supply for RTD from the perspective of their economy, Not some
objective external benchmark. Source: WEF data 2006
24
Results
•
•
•
•
•
•
•
The most of the SEE countries have RTD demand gap i.e. they are not
able to employ their RTD capacities effectively
Causes: factors like low sophistication of businesses processes which do not
use new technologies or inappropriate structure or quality of RTD capacities.
Serbia and Montenegro have the biggest demand – supply gap.
SI and TK show signs of RTD supply gap i.e. limited RTD capacities or
possibly types of capacities given state of their demand for RTD.
Greece suffers from weak demand for RTD which probably is caused by its
industry structure which is dominated by small firms in traditional industries.
A small RTD demand – supply gap for Albania is mainly sign of very low levels
and quality of demand and supply for RTD > a ‘low level equilibrium’
A bigger but still small RTD gap in case of Bosnia and Herzegovina should be
interpreted from similar perspective but which have to take into account its
specific post-war situation.
25
SEE: a local demand is much stronger constraint to
growth in software sector than in CEB
Quality of local vs foreign demand for firms'
products and services
5.0
4.54.4
3.93.8
4.0
4.03.9
4.0
4.2
4.4
3.4
4.1
3.4
2.8
3.0
2.4
2.0
Local
1.0
Foreign
0.1
0.1
0.1
Dif f Loc-For
0.0
SI
CZ
EE
SER
-1.0
ROM
BLG
-0.7
All
-0.7
-1.2
-2.0
-2.0
-3.0
Source: Radosevic (2006)
26
The sources of productivity improvements in CEE:
Global value chains and production capability
improvements
1. Productivity of FDI subsidiaries is significantly explained by ‘quality control’
(production capability) (Majcen et al, 2009)(se next slide)
2. Production capability: upgrading quality in existing products seem to be a
more automatic process. Countries converge in quality (measured by unit
prices) with the international leaders at an annual rate of 5-6%
unconditionally (Hausman, Hwang and Rodrik, 2007)
3. This ‘automatism ‘ in the case of CEECs it is actually FDI assisted or
subcontracting driven mastery of production capability
4. Some CEECs (Hungary, Croatia, Lithuania, Romania, Slovenia) have lesser
scope for further quality improvements and must instead move to new
products (EBRD, 2008)
27
CEE subsidiaries are mainly production oriented, i.e. competitive
advantage is based on production, not technological or marketing
capability.
Ordered probit estimates
MODEL 1:
MODEL 2:
MODEL 3:
MODEL 4:
MODEL 5:
BASIC
WITH OVERALL CONTROL
WITH OPERATIONAL
CONTROL
WITH MARKETING
CONTROL
WITH STRATEGIC
CONTROL
With foreign
equity share
VARIABLE
Coefficient
With foreign
equity share
Without
foreign equity
share
With foreign
equity share
Without
foreign equity
share
With foreign
equity share
Without
foreign equity
share
With foreign
equity share
Without
foreign equity
share
Coefficient
Coefficient
Coefficient
Coefficient
Coefficient
Coefficient
Coefficient
Coefficient
Overall control1
0.358
*.619
-1.09
-2
Control of operational functions 2
Control of marketing functions
Control of strategic functions
-0.203
0.086
(-0.56)
-0.25
3
0.314
*.450
-1.37
-2.02
4
Foreign equity share
**.481
**.440
**.550
**.444
*.574
-2.14
-3.02
-2.47
0.206
0.28
0.281
0.236
0.245
0.224
0.22
0.231
-1.35
-1.73
-1.74
-1.52
-1.56
-1.4
-1.38
-1.48
-1.52
Dummy – large size firm
**.568
**.446
**.452
**.538
**.553
**.451
**.444
**.532
**.541
-3.66
-2.7
-2.75
-3.38
-3.49
-2.79
-2.75
-3.33
-3.39
Exports to foreign owner
**.274
**.264
**.263
**.262
**.262
**.277
**.280
**.245
**.243
-3.58
-3.2
-3.19
-3.36
-3.37
-3.44
-3.39
-3.08
-3.07
Exports to other foreign firms
**.269
**.230
*.219
**.246
**.235
**.260
**.253
**.219
*.213
Dummy – medium size firm
-3.26
328
-1.14
**.426
-2.6
-2.42
0.237
-3.05
-2.44
-2.33
-2.73
-2.61
-2.81
-2.75
-2.4
-2.34
Imports of intermediate products from foreign
owner
0.001
0.002
0.001
0.001
0.001
0.001
0.001
0.002
0.001
-0.69
-0.7
-0.63
-0.53
-0.42
-0.6
-0.54
-0.77
-0.71
Imports of interm. products from other foreign
firms
-0.003
-0.002
-0.002
-0.003
-0.002
-0.002
-0.001
-0.002
-0.001
(-1.03)
(-0.61)
(-0.41)
(-0.99)
(-0.76)
(-0.74)
(-0.59)
(-0.60)
(-0.46)
Quality control
**.848
*.765
*.739
**1.11
**1.070
0.669
0.648
**.910
**.885
-2.66
-2.08
-2.01
-3.3
-3.19
-1.92
-1.87
-2.79
-2.72
Patents and licences
0.312
0.433
0.384
0.326
0.258
0.37
0.315
0.386
0.333
-1.43
-1.83
-1.63
-1.45
-1.16
-1.61
-1.38
-1.71
-1.48
People and training
-0.004
-0.004
-0.011
-0.005
-0.001
0.003
0.006
0.04
0.0357
(-0.01)
(-0.01)
(-0.03)
(-0.01)
(-0.00)
-0.01
-0.02
-0.11
-0.1
-0.225
-0.36
-0.399
-0.448
-0.492
-0.315
-0.374
-0.27
-0.297
Management
Sector dummy – high technology intensity
(-0.66)
(-0.97)
(-1.07)
(-1.25)
(-1.39)
(-0.88)
(-1.05)
(-0.76)
(-0.840
**-.612
**-.670
**-.626
**-.672
**-.609
**-.691
**-.6430712
**-.657
**-.615
(-2.79)
Pseudo R2
Number of obs.
-2.83
(-2.66)
(-2.95)
(-2.69)
(-2.93)
(-2.742)
(-2.88)
(-2.71)
0.0831
0.0808
0.0726
0.0887
0.0755
0.082
0.0732
0.083
0.0757
375
332
332
361
361
344
344
354
354
Notes: (i) Dependent variable: productivity growth; (ii) Z-statistics in parentheses; (iii) **, * and + indicate significance at 1%, 5% and 10%, respectively.
1/ Control of subsidiary - overall: Average value of foreign parent company's control of all 13 business functions; 2/ Operational control: Average value of foreign parent
company's control of 4 operational business functions; 3/ Marketing control: Average value of foreign parent company's control of 5 marketing business functions;
4/ Strategic control: Average value of foreign parent company's control of 4 strategic business functions (see Table 2). The rest of dummies including country dummies
are not reported. Based on data on 433 subsidiaries in five CEECs. Source: Majcen, Radosevic and Rojec (2009)
28
Quantity vs. quality of FDI: a further research is needed
FDI brinsg new technology 2006 (quality)
Quantitity vs. quality of FDI
6.5
Serbia & Montengero
6
Romania
5.5
Turkey
5
Greece
Albania
4.5
Bulgaria
Croatia
Slovenia
4
Bosnia and Herzegovina
Macedonia, FYR
3.5
3
0
10
20
30
40
50
60
70
80
90
100
110
Share of FDI in GFCF, average 2004-06 (quantity)
Econometrics of FDI spillovers in CEE: contradictory results, not very helpful
Damijan et al (2008): direct effects from foreign ownership and spillovers from FDI
do substantially depend on the absorptive capacity and productivity level of
individual firms
Ho: Differences explained by differences in levels of local technological capability
and differences in market orientation of FDI.
29
The challenge for ‘periphery’: Missing levers
to growth?
EU Centers of excellence
MNCs: parents and other subsidaries
weak horizontal linkages
National centres of excellence
Local FDI subsidaries
Weak vertical integration & horizontal fragmentation
Vertical and horizontal links do not work in WeBa ?
Policy focus:
- Support to the weakest agent: local business R&D
- Transfer function on supply side (R&D)
- Transfer function on demand side (FDI/local firms)
30
Broaden approach to RTD: innovation policy
focused on country’s innovation capacity and its
elements
Education, training and skills
Labour market
Absorptive capacity
RTO – industry linkages)
Small firms’ linkages (clusters)
Large – small firms linkages
Linkages: foreign and local firms
(vertical and horizontal
Enterprise as a source of supply
and demand for innovation
R&D system and its links to economy
Intra-mural vs. extra-mural R&D
R&D supply
Innovation governance
Diffusion and linkages
Narrow view: capacity of public services (ministry, agency, etc.) to manage cycle of policy development and implementation;
Broader view: capacity to coordinate large number of explicit and implicit policy measures that affect innovation process
Demand (market pull)
Source: Radosevic (2006)
Demand for technology_ large and SMEs
Tax incentives
Macroeconomic stability
Financial system
Competition policy
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Invest in ‘knowledge infrastructure’ but only closely
linked to careful assessment of BES demand
• S&T Parks and dangers of ‘surrogate
modernization’
• Priorities: First: projects and services (functions),
and only than buildings (organisations)
• Give preference to technology specific (critical
mass) vs. generic parks (preferably linked to large
enterprises)
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Support current drivers of technology
upgrading
• Quality (ISO9000 etc is precondition to export) and
vocational training (key to developed production
capability)
• Support for domestic firms to become quality
suppliers for MNEs (cf. Hungarian INTEGRATOR)
• Support programs for engineering and software
33
Support integrated and complementary support to
NTBFs
Public R&D <> Minigrants <> Matching Grants <> Venture Capital
< Business support services >
• Policy support is focused on opposite edges of new technology
venturing
• Funding gap
– mini-grants: to explore commercial feasibility of technical idea
– matching grants: to encourage risk sharing with firm +
potential to create linkages
34
WeBa 2010: how ‘to extend transition
agenda’?
• Policy package of the last 15-20 years: focus on business
environment (market automatism) + add well functioning
state (2009)
• Meagre results: slower X than of CE; large trade and CA
deficits; appreciating ExRat; quality of life worse in 2009
than in 1989 (except Rom and Alb)
• Add dimension of industrial upgrading into analysis and
policy coupled with FDI/industrial networks
• How to address demand shock? Further opening of
regional (EU/SEE) market (cf. ‘jugosfera’ as the remaining
lifeblood of local businesses). EBRD and regional
projects?
35