Tr14c

44
Chapter 3
EBRD | TRANSITION REPORT 2014
DRIVERS of
INNOVATION
R&D increases the likelihood
of introducing new
products or processes by
26%for high-tech
manufacturing firms
Firms that use ICT are
9%more likely
to introduce new
products or processes
29%of exporters have
introduced a new
product or process,
compared with 15%
of non-exporters
At a glance

Chapter 3
DRIVERS OF INNOVATION 45
Firms that innovate are more sensitive to
the quality of their business environment.
They tend, in particular, to complain
about corruption, the limited skills of the
workforce and burdensome customs and
trade regulations. Reducing such business
constraints can have a significant positive
impact on firms’ ability and willingness to
innovate. In countries where constraints
are less binding, firms tend to innovate
more as a result. However, not all firms in
such countries are innovative: the age, size,
ownership structure and export status
of companies also have an impact.
Introduction
Innovation is an important driver of improvements in productivity.
But what drives innovation itself? This chapter looks at the
reasons for the significant variation seen in the rates of
innovation of individual countries and sectors, as documented
in Chapter 1.
Various factors influence firms’ incentives and ability to
innovate, ranging from the prevalence of corruption to the
availability of an adequately skilled workforce and access to
finance. Some of these factors are internal, reflecting either
characteristics of the firm (its size or age, for instance) or
decisions made by the firm (such as the decision to compete
in international markets or the decision to hire highly skilled
personnel). Other factors are external and shape the general
business environment in which firms operate (such as customs
and trade regulations).
In some cases, the two are closely related: each firm makes
personnel decisions that determine its ability to innovate, but
these decisions are, in turn, strongly influenced by the prevailing
skills mix and the availability of a sufficiently educated workforce
in the region where the firm operates. Similarly, Chapter 4 shows
that the local banking structure (an element of the external
environment) has an impact on firms’ funding structures (an
internal aspect), which then affects innovation. Even if firms share
the same business environment, they will not necessarily make
the same business decisions, and these decisions will influence
their innovation activity.
This chapter examines internal and external drivers of
innovation, looking at both firm-level and country-level evidence.
The firm-level analysis builds on the first two stages of the
model discussed in the previous chapter, which explained
firms’ decisions to engage in research and development (R&D)
and introduce new products or processes. This analysis uses
a rich set of data looking at firms’ perceptions of the business
environment. The data were collected as part of the EBRD
and World Bank’s fifth Business Environment and Enterprise
Performance Survey (BEEPS V) and the Middle East and North
Africa Enterprise Surveys (MENA ES) conducted by the EBRD, the
World Bank and the European Investment Bank. The country-
level analysis uses a large sample of countries, including those
from the transition region, to explain both innovation at the
technological frontier (measured as the number of patents
per employee) and the innovation intensity of exports (a broad
measure of innovation and the adoption of technology that was
introduced in Chapter 1).
The chapter starts by considering drivers of innovation within
an individual firm, looking first at firm-level characteristics
(such as a firm’s size and ownership structure), before turning
to decisions made by firms (such as the decision to export or
the decision to conduct R&D). The analysis then moves on to
external factors, first comparing innovative firms’ perception of
the business environment with the views of non-innovative firms.
These views guide the discussion of the key external factors that
affect innovation outcomes at country level.
100%of young firms in Israel
introduce at least one
product which is new to
the international
market, compared
with 0.6% in the
transition
region

46
Chapter 3
1
See Nightingale and Coad (2013) for a discussion of fast-growing “gazelle firms”.
2
See OECD (2009).
3
See, for example, Cohen and Levinthal (1989).
Firm-level drivers of innovation
Size and age of firms
A firm’s willingness and ability to innovate will depend on various
characteristics. In particular, young, small firms are often
perceived to be the main drivers of innovation. While such firms
do make an important contribution to the development of new
products, they are not necessarily more innovative than other
firms when viewed as a whole.
This is partly because when young, innovative firms are
successful, they often grow fast, thereby becoming larger firms.
Google and Amazon were once start-ups with just a handful
of employees, but they have quickly grown and now employ
thousands of people. Innovative start-ups that are not successful,
on the other hand, typically run out of funding and exit the
market.1
Neither of these types of firm will be categorised as
young, small firms in an enterprise survey such as BEEPS V or
MENA ES. In addition, not all young, small firms are innovative
start-ups. Many will be in conventional service sectors (takeaway
restaurants or small convenience stores, for instance).
For these reasons, innovation may be more common among
larger firms that have been operating for a longer period of time.
Chart 3.1, which uses BEEPS V and MENA ES data, shows that
larger and older firms are indeed more likely to introduce new
products. The same is true of new processes and marketing
and organisational innovations. A similarly positive correlation
between the size/age of a firm and its propensity to introduce
new products or processes can also be observed in Israel and
advanced economies more broadly.2
The positive correlation between firm size/age and innovation
also holds in firm-level regressions. Table 3.1 presents estimates
showing the impact of various firm-level characteristics that
influence firms’ decisions to engage in RD and introduce new
products and processes. These results are based on the model
discussed in Chapter 2 (see Box 2.1). Unlike the simple averages
presented above, this model takes into account the industries
and countries where firms operate, as well as various other firm-
level characteristics (such as the type of firm ownership).
BEEPS V and MENA ES data suggest that economies of scale
may also partly explain the positive correlation between firm
age/size and innovation. The development of new products
often involves high fixed costs and investment spikes. This may
simply be easier for larger firms to bear – particularly if large
firms enjoy better access to external finance, as discussed in
Chapter 4. These large firms may also be more able to absorb
new technologies.3
This may be one reason why small firms
(defined as companies with fewer than 20 employees) are less
likely to engage in RD than larger firms (albeit they tend to spend
a higher percentage of their annual turnover on in-house RD;
see Chart 3.2). Larger firms may also conduct more innovation
projects, making them more likely to successfully introduce at
least one new product in the course of a three-year period.
Perhaps unsurprisingly, differences between smaller and
larger firms (and older and younger firms) in terms of innovation
rates are more pronounced in high-tech manufacturing sectors
CHART 3.1. Percentage of firms that have introduced a new product, broken
down by size and age
Source: BEEPS V, MENA ES and authors’ calculations.
Note: Data for the transition region represent unweighted cross-country averages. Small firms have fewer
than 20 employees; young firms are less than five years old.
Note: This table reports average marginal effects. Standard errors are indicated in parentheses. ***, **
and * denote statistical significance at the 1, 5 and 10 per cent levels respectively. The regressions are
estimated using an asymptotic least squares estimator based on the model described in Box 2.1.
Small Medium/large Young Old
0
2
4
6
8
10
12
14
16
18
Transition region Israel
Firm size Firm age
table 3.1. Determinants of RD and innovation
RD
(1)
Technological
innovation (cleaned)
(2)
Non-technological
innovation
(3)
RD 0.2160*** 0.1973***
(0.0678) (0.0328)
Firm age (years) 0.0003 0.0010** 0.0004***
(0.0002) (0.0004) (0.0001)
5-19 employees (dummy) -0.0927*** -0.0549*** -0.0973***
(0.0088) (0.0126) (0.0127)
20-99 employees (dummy) -0.0480*** -0.0315** -0.0605***
(0.0070) (0.0119) (0.0121)
Majority foreign-owned (dummy) 0.0142 0.0235* 0.0428**
(0.0113) (0.0130) (0.0140)
Majority state-owned (dummy) 0.0041 -0.0320** -0.0075
(0.0307) (0.0115) (0.0130)
Direct exporter (dummy) 0.0635*** 0.0317** 0.0339**
(0.0090) (0.0132) (0.0138)
Percentage of working capital financed
by banks or non-bank financial
institutions
0.0004*** 0.0002** 0.0006***
(0.0001) (0.0001) (0.0002)
Percentage of fixed asset purchases
financed by banks or non-bank
financial institutions
0.0004*** 0.0010** 0.0007***
(0.0001) (0.0004) (0.0002)
Percentage of employees with a
university degree
0.0007*** 0.0001** 0.0004***
(0.0001) (0.0000) (0.0001)
Main market: local (indicator) -0.0461*** -0.0423***
(0.0081) (0.0085)
Use email for communication with
clients (indicator)
0.0908*** 0.1430***
(0.0103) (0.0104)

Chapter 3
4
Griffith et al. (2006) find that large firms are more likely to engage in RD in four advanced European
countries.
5
Acemoğlu et al. (2014) show that younger managers are more open to new ideas, so they are more likely to
instigate disruptive, risky innovations.
such as machinery or pharmaceuticals, as complex technologies
are more difficult and costly to absorb and develop.
Similar estimates of the impact of a firm’s size and age emerge
from the regression analysis, which controls for other firm-level
characteristics. Indeed, this analysis suggests that small firms
are 5 percentage points less likely to introduce new or improved
products or processes than large firms (see Table 3.1, column 2).4
This is a substantial impact, given that 27 per cent of large firms
have introduced new or improved products or processes in the
last three years.
What may be surprising is the fact that young and small firms
are also less likely to introduce marketing and organisational
innovations. This probably reflects the fact that larger firms tend
to have employees specialising in marketing (or even whole
marketing departments), whose main task is to review existing
marketing techniques and develop new approaches to marketing.
Scarcity of innovative start-ups
Young, small firms may tend to innovate less, but start-ups still
represent a very important class of innovators. They are the firms
that are most likely to come up with innovations that are new
to the global market. In some cases, the innovation is the sole
reason for the firm’s creation.
In Israel, two-thirds of small firms introduced product
innovations that were new to the international market, compared
with 48 per cent for larger firms (see Chart 3.3). Moreover, all
young firms (defined as companies that were established less
than five years ago) introduced at least one new product that
was new to the international market, hence the fact that Israel’s
start-ups have a reputation as one of the key drivers of economic
growth in that country.
In transition countries, by contrast, such start-ups remain rare.
In fact, young and small firms in the transition region perform
worse than their large and established counterparts when looking
at the percentage of them that introduced product innovations
new to the global market (see Chart 3.3). Younger firms are
somewhat more likely than older firms to introduce world-class
process innovations, but instances of such process innovation
are very rare overall.
The scarcity of start-ups generating world-class innovation
reflects the fact that transition economies are further removed
from the technological frontier than advanced economies such
as Israel. This may be due to a series of factors constraining
the development of innovative start-ups. Among these factors
are a lack of specialist financing (such as angel investors, seed
financing and venture capital), skill shortages, high barriers to the
entry of new firms and weak protection of intellectual property
rights (all of which are discussed in more detail in Chapters 4 and
5), as well as the age of firms’ senior management.5
Faced with these constraints, the most successful innovative
entrepreneurs and small firms in the transition region often
move to Silicon Valley, Boston, New York and other innovation
hubs at the earliest opportunity; some keep their development
centres somewhere in eastern Europe (see Box 3.1 for a further
discussion and examples).
CHART 3.2. Percentage of firms engaged in RD and their level of RD spending,
broken down by firm size
CHART 3.3. Percentage of firms with product innovations that are new to the
global market
Note: Unweighted averages across transition countries. Small firms have fewer than 20 employees.
Note: Data for the transition region represent unweighted cross-country averages. This chart is based on
cleaned innovation data. In Israel, all young firms introduced at least one new product that was new to the
international market. Small firms have fewer than 20 employees; young firms are less than five years old.
Percentage of firms engaged
in in-house RD
RD spending as a percentage
of annual sales
Small firms Medium/large firms Small firms Medium/large firms
0
2
4
6
8
10
12
14
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Transition region Israel
Firm size Firm age
Small Medium/large Young Old
0
10
20
30
40
50
60
70
100
27%of large firms in the
transition region have
introduced new or
improved products or
processes in the last
three years

48
Chapter 3
As transition economies develop and move closer to
the technological frontier, young firms producing world-class
innovation will become more prominent. The economic
environment will need to adapt to this change and become
more supportive of innovative start-ups (as discussed in
more detail in Chapter 5, which looks at policies that can
help start-ups to succeed).
Type of ownership
Another important characteristic affecting innovation is the
type of firm ownership. In general, foreign ownership and the
integration of local firms into global supply chains are expected
to lead to increased innovation (see Box 3.2). On the other hand,
concerns are sometimes raised that multinational companies
may conduct all of their RD activities in their home countries,
outsourcing only lower-value-added activities to emerging
markets, so foreign takeovers may actually result in reduced
spending on RD.6
Evidence from BEEPS V and MENA ES suggests that the first
of these effects tends to dominate in the transition region and
that foreign ownership is associated with an increased likelihood
of innovation and higher levels of spending on in-house RD.
Foreign-owned firms are defined here as firms where foreign
CHART 3.4. Percentages of foreign-owned and domestic firms that are engaged
in innovation
Note: Unweighted averages across transition countries. Cleaned data for product and process innovations;
unadjusted data for organisational and marketing innovations. “Foreign-owned firms” are those where the
foreign stake totals 25 per cent or more. “Domestic firms” include locally owned firms and firms with foreign
ownership totalling less than 25 per cent.
Product innovation Process innovation Organisational innovation Marketing innovation
0
5
10
15
20
25
30
Foreign-owned ﬁrms Domestic ﬁrms
investors hold a stake of 25 per cent or more – that is to say,
at least a blocking minority. The percentage of such firms
that have introduced new products is significantly higher than
the percentage of locally owned firms that have done so. The
same is true of process innovations, as well as marketing and
organisational innovations (see Chart 3.4).
Indeed, in the case of marketing and organisational
innovation, the impact of foreign ownership is pronounced even
when foreign investors own a small stake that falls short of a
blocking minority (in other words, between 0 and 25 per cent),
while foreign ownership does not have a clear impact on product
and process innovations until that stake reaches the 25 per cent
mark. This suggests that foreign owners may be an important
source of information about new organisational arrangements
and marketing methods. At the same time, sharing technological
know-how requires stronger incentives and assurances, which
come with a stake of a certain size in a company.
The results also suggest that increased innovation by
foreign-owned firms is a result of a mixture of “make” and “buy”
strategies when it comes to acquiring external knowledge.
The percentage of foreign-owned firms that invest in RD
(thereby pursuing a “make” strategy) tends to be higher than the
percentage of domestic firms that follow this strategy (see Chart
3.5). This is the case in virtually every country in the transition
region. Foreign-owned firms also tend to spend more on RD
(see Case study 3.1 for details of a joint venture in the Turkish
automotive sector with an active domestic RD programme).
Overall, these findings run counter to the view that foreign
takeovers undermine domestic RD.
Not only do foreign firms “make” more knowledge, they
are also more likely to engage in the acquisition of external
knowledge (through the purchasing or licensing of patents and
non-patented inventions and know-how) than locally owned firms
(see Chart 3.5).
The formal regression results in Table 3.1 confirm that the
relationship between foreign ownership and innovation holds
when other firm-level characteristics are also taken into account.
Everything else being equal, a majority foreign-owned firm is,
on average, 2.3 percentage points more likely to introduce new
products or processes (see column 2) and 4.3 percentage points
more likely to introduce organisational or marketing innovations
(see column 3).7
This is a sizeable difference, given that the
average probability of a majority domestic-owned firm introducing
new or improved products or processes is 17.5 per cent, while
the probability of it introducing organisational or marketing
innovations is almost 27 per cent.
In contrast, majority state-owned firms are significantly less
likely to introduce new products or processes than locally owned
private firms or foreign firms, and this effect is even larger in the
case of new processes. This may reflect the fact that managers
of state-owned firms have weaker incentives to achieve efficiency
savings and improve productivity. Their remuneration, for
example, is not necessarily linked to their firm’s performance, and
these firms can typically rely on the state to bail them out in the
event of poor performance.
6
See, for example, Sample (2014). 7
Crespi and Zuñiga (2012) find mixed results for South America, with foreign ownership having a significant
positive impact on RD in Argentina, Panama and Uruguay, but not in Chile, Colombia or Costa Rica.

Chapter 3
Competition in international markets
In addition to firm-level characteristics such as a firm’s age,
size and ownership structure, various decisions made by firms
are related to their incentives and ability to innovate. One such
decision is whether to compete in international markets.
Firms that export their goods are able to spread the fixed costs
of innovation over a larger customer base, so exports can support
innovation. By the same token, firms in larger economies with
larger domestic markets may find it easier to innovate on account
of higher levels of domestic demand for new products.
Exporting can also expose domestic producers to stronger
competition from foreign products, thereby providing an
incentive to innovate (see Box 3.3 for a discussion of the complex
relationship between competition and innovation).8
Furthermore,
firms’ participation in global value chains, which involves the
exporting of either intermediate or final goods, facilitates the
adoption of foreign technologies, particularly in emerging
markets9
(see Box 3.2).
BEEPS V and MENA ES data confirm the importance of export
markets for innovation. Firms that export their products directly
appear to be more likely to engage in RD and introduce new
products, processes, marketing methods and organisational
innovations than firms that only serve their domestic markets
(see Chart 3.6).
Similar differences can be observed in firm-level regressions.
The estimates in Table 3.1 suggest that once various other firm-
level characteristics are taken into account, exporters are around
3 percentage points more likely to innovate than non-exporters.
This is a sizeable impact, as the probability of a non-exporter
introducing a new or improved product or process is 15 per cent.
The differences between exporters and non-exporters are
particularly large when it comes to in-house RD and process
innovation.10
Regression results indicate that exporters are
6 percentage points more likely to engage in RD. This may be
explained by the fact that exporting and entering new markets
can help firms to improve their knowledge of production
processes, while RD can help firms improve their ability to
absorb new technologies.11
Of the firms that do not export, those that primarily sell in
the national market are more likely to introduce new products,
processes and marketing methods than firms that operate
primarily in the local market. Similar forces may be at play here:
a national market provides a broader customer base, making it
easier to justify the fixed costs of developing new products and
processes, while the higher levels of competition in the national
market provide stronger incentives to seek productivity gains.
RD inputs and innovation outputs
Another important decision that a firm faces is whether to
spend on RD to support the development of new products.
As discussed in Chapter 1, RD is not a prerequisite for the
introduction of new products or processes, as firms may decide to
acquire existing knowledge from elsewhere.
At the same time, RD significantly increases the likelihood of
successful innovation. Firms that invest in RD are an average
CHART 3.5. Foreign-owned firms spend more on obtaining knowledge
CHART 3.6. Percentages of exporters and non-exporters engaging in innovation
and RD
Note: Unweighted averages across transition countries. The acquisition of external knowledge includes the
outsourcing of RD and the purchasing or licensing of patents and non-patented inventions or know-how.
“Foreign-owned firms” are those where the foreign stake totals 25 per cent or more. “Domestic firms”
include locally owned firms and firms with foreign ownership totalling less than 25 per cent.
Note: Unweighted averages across transition countries. Cleaned data for product and process innovations;
unadjusted data for organisational and marketing innovations. “Exporters” are firms that export directly;
“non-exporters” are firms that do not export directly.
Percentage
Percentage
Percentage of firms investing in in-house RD (left-hand axis)
Percentage of firms engaged in acquisition of external knowledge (left-hand axis)
Spending on in-house RD as a percentage of annual turnover (right-hand axis)
Foreign-owned firms Domestic firms
0
5
10
15
20
0
0.1
0.2
0.3
0.4
Product innovation Process innovation Organisational innovation Marketing innovation In-house RD Acquisition of
external knowledge
0
5
10
15
20
25
30
Exporters Non-exporters
Foreign-owned firms
are more likely
to innovate than
domestic ones
8
See also Aghion et al. (2005) and Bloom et al. (2011).
9
See, for instance, Coe et al. (2009) and Baldwin and Gu (2004).
10
These estimates are consistent with the results of studies looking at other regions. For instance, Crespi
and Zuñiga (2012) estimate that exporters in Colombia and Argentina are, respectively, 7 and 15
percentage points more likely to invest in the development of new products (including RD). Meanwhile,
Baldwin and Gu (2004) find that exporters in Canada are 10 percentage points more likely to invest
in RD.
11
Damijan et al. (2010) find evidence that, in Slovenia, exporting increases the probability of becoming a
process innovator for medium-sized and large firms.

50
Chapter 3
of 22 percentage points more likely to introduce new products
or processes.12
They are also an average of 20 percentage points
more likely to introduce marketing or organisational innovations
(perhaps because these types of innovation often go hand in
hand with technological innovation).
Investing in RD has the largest impact on the probability of
introducing a new product in high-tech manufacturing sectors
such as electrical equipment or pharmaceuticals (see Chart
3.7). In these sectors RD increases the probability of product
innovation on average by 26 percentage points, while in less
knowledge-intensive service sectors (such as catering or sales)
RD has virtually no impact on the probability of introducing a
new product.
While RD is closely linked to product innovation in high-
tech manufacturing sectors, RD in low-tech manufacturing
has a large impact on process innovation, which involves
the optimisation of the production of existing products (for
instance, a clothing manufacturer that replaces the manual
cutting of fabric with an automatic fabric-cutting machine).
Conducting RD in these sectors increases the probability of
introducing a new process by an average of 20 percentage points
(compared with an average of 11 percentage points in high-tech
manufacturing sectors).
Human capital
A suitably skilled workforce (including strong management skills)
is one of the key prerequisites for successful innovation – both
innovation at the technological frontier and the adoption of
existing technology – as workers are required to develop and
learn new production techniques.13
The results in Table 3.1 suggest that while the percentage
of employees with a university degree affects the probability
of introducing a new product or process and the likelihood of
investing in RD, this impact is fairly small relative to the effect of
other firm-level characteristics discussed above. The regression
analysis already accounts for the differences between the skill
intensities of the various industries, so this finding suggests that
differences in human capital across firms within a particular
industry do not explain much of the remaining differences in
innovation activity.
While a firm’s human capital reflects its recruitment decisions,
it is also, to a large extent, shaped by the availability of skills in the
market. There is further cross-country analysis of this issue later
in the chapter.
Information and communication technology
Firms that use email to communicate with their clients or
suppliers are, on average, 9 percentage points more likely to
introduce new products or processes and 14 percentage points
more likely to introduce organisational or marketing innovations
(see Table 3.1, column 3). This attests to the importance of both
modern organisational practices and supporting information
and communication technology (ICT) infrastructure in facilitating
innovation.
ICT’s largest impact is on the probability of introducing product
CHART 3.7. The impact of RD on product and process innovation, broken down
by sector
CHART 3.8. The impact of ICT on innovation, broken down by sector
Note: This chart reports the average marginal effect of RD on product and process innovation. Sectors are
based on ISIC Rev. 3.1. High-tech and medium-high-tech manufacturing sectors include chemicals (24),
machinery and equipment (29), electrical and optical equipment (30-33) and transport equipment (34-35,
excluding 35.1). Low-tech manufacturing sectors include food products, beverages and tobacco (15-16),
textiles (17-18), leather (19), wood (20), paper, publishing and printing (21-22) and other manufacturing
(36-37). Knowledge-intensive services include water and air transport (61-62), telecommunications (64)
and real estate, renting and business activities (70-74).
Note: This chart reports the average marginal effect of the use of ICT on product and process innovation.
The use of ICT is estimated using the question about the use of email to communicate with clients or
suppliers. See the note accompanying Chart 3.7 for the list of industries in each sector.
Product innovation Process innovation
0.00
0.05
0.10
0.15
0.20
0.25
0.30
High-tech and medium-high-tech manufacturing
Low-tech manufacturing Less knowledge-intensive services
Medium-low-tech manufacturing
Product and process innovations Marketing and organisational innovations
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
High-tech and medium-high-tech manufacturing
Low-tech manufacturing Less knowledge-intensive services
Medium-low-tech manufacturing
12
These estimates are comparable to those obtained by Crespi and Zuñiga (2012) for South American
countries.
13
See, for instance, Nelson and Phelps (1966).

Chapter 3
and process innovations in high-tech and medium-high-tech
manufacturing sectors (see Chart 3.8). At the same time, in
low-tech manufacturing sectors (such as textiles or food and
beverages) and less knowledge-intensive services (such as
catering or sales), use of ICT has a large impact on the probability
of implementing marketing and organisational innovations.
When it comes to innovation, firms may also benefit from the
expert advice of external consultants (see Box 3.4). Lastly, the
availability of finance also plays an important role, as firms
may abandon the development of new products if the requisite
funding cannot be obtained. Chapter 4 discusses these issues
in more detail.
The business environment as a driver
of innovation
Firms’ ability to innovate also depends on external factors. As
Chapter 2 notes, a poor business environment – widespread
corruption, weak rule of law, burdensome red tape, and so
on – can substantially increase the cost of introducing new
products and make returns to investment in new products and
technologies more uncertain. These factors can undermine firms’
incentives and ability to innovate.
The results of BEEPS V and MENA ES confirm this. As part of
these surveys, each firm was asked whether various factors, such
as access to land or labour regulations, were obstacles to doing
business. Firms responded using a scale of 0 to 4, where 0 meant
“no obstacle” and 4 signified a “very severe obstacle”.
On the basis of these answers, firms that have introduced
a new product in the last three years regard all aspects of their
business environment as a greater constraint on their operations
than firms that have not engaged in product innovation.
This can be seen from the fact that all business environment
constraints lie above the 45-degree line in Chart 3.9. The
differences between the views of innovative and non-innovative
firms are especially large when it comes to skills, corruption and
customs and trade regulations (with these dots lying furthest
away from the 45-degree line). Inadequate skills and corruption,
in particular, are perceived to be among the main constraints
for all firms, and they are even greater constraints for innovative
firms. (These are located towards the top right of the chart and
are marked in red.) In contrast, customs and trade regulations
(in the bottom left of the chart, marked in orange) are not major
concerns at the level of the economy as a whole, partly because
only a relatively small number of firms import production inputs
or export their products directly. However, customs and trade
regulations specifically affect innovative firms, as the introduction
of new products and technologies is often dependent on
imported inputs and the ability to tap export markets.14
Innovative firms are also significantly affected by a number
of other aspects of the business environment (located to the
right of the chart, but close to the 45-degree line, and marked
in yellow). However, these tend to constrain innovative and
non-innovative firms alike, with only a slightly larger impact on
CHART 3.9. Differences between innovative and non-innovative firms’ perception
of the business environment
Note: Values on the vertical axis correspond to the views of firms that have introduced a new product in the
last three years; values on the horizontal axis correspond to the views of other firms. Values are averages
across firms on a scale of 0 to 4, where 0 means “no obstacle” and 4 signifies a “very severe obstacle”.
Obstacles marked in red and orange particularly affect firms that innovate; obstacles marked in red and
yellow are the most binding constraints for all firms.
Average rating by non-innovative ﬁrms
Averageratingbyinnovativeﬁrms
Corruption
Skills Finance
Tax administration
Informal sectorElectricity
Customs/trade regulations
Telecommunications
Access to land
Crime
Licences/permits
Labour regulations
Courts
Transport
0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
innovative firms. These include access to finance, the practices
of competitors in the informal sector, tax administration and,
to a lesser degree, electricity.
The extent to which the various features of the business
environment affect all firms and innovative firms differs from
region to region (see Chart 3.10). In central Europe and the
Baltic states (CEB), for instance, the differences between the
responses of innovative and non-innovative firms are relatively
small (in other words, all dots lie close to the 45-degree line). This
suggests that the business environment in the CEB region is less
hostile towards innovation. However, a number of aspects of the
business environment remain significant obstacles to the growth
of innovative and non-innovative firms alike, including access to
finance, tax administration and inadequate skills.
In south-eastern Europe (SEE) corruption stands out as
an issue, constraining the growth of all firms, but particularly
affecting those that innovate. Inadequate skills also particularly
affect innovative firms, while both innovative and non-innovative
firms frequently complain about the actions of competitors in the
informal sector, access to finance and electricity.
The differences between the views of innovative and non-
innovative firms are larger in eastern Europe and the Caucasus
(EEC), Central Asia and Russia. While corruption and inadequate
skills strongly affect all firms, this negative impact is felt most
strongly by firms that innovate. In addition, innovative firms
feel constrained by a number of aspects of the business
environment that other firms regard as being less binding. These
include customs and trade regulations, telecommunications
and business licensing and permits, all of which are likely to be
important inputs in the innovation process.
14
See Lileeva and Trefler (2010).

52
Chapter 3
CHART 3.10. Differences between innovative and non-innovative firms’
perception of the business environment, broken down by region
CEB
Corruption
Skills
Finance
Tax administration
Informal sector
Electricity
Telecommunications
Crime
Licences/permits
Labour regulations
Courts
Transport
0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6
0.4
0.6
0.8
1.0
1.2
1.4
1.6
SEE
Corruption
Skills
Finance
Tax administration
Informal sector
Electricity
Telecommunications
Access to land
Crime
Licences/permits
Labour regulationsCourts
Transport
0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
EEC, Russia and Central Asia
Corruption
Skills
Finance
Tax administration
Informal sector
Electricity
Telecommunications
Access to land
CrimeLicences/permits
Labour regulations
Transport
0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Source: BEEPS V and authors’ calculations.
Note: See the note accompanying Chart 3.9.
The BEEPS V and MENA ES results suggest that
improvements in the provision of infrastructure, further
deregulation in the area of licences and permits and
improvements in the quality of government services can
specifically help innovative firms. Table 3.2 summarises
innovative firms’ perception of the business environment
in the various regions.
Cross-country analysis
Economic institutions
The previous section shows that innovative firms tend to have
a much more negative view of certain aspects of their business
environment when compared with non-innovative firms. This
raises the question of whether such perceived constraints
negatively affect innovation outcomes. Do they inhibit innovation
in practice? To answer this question, the impact of various
aspects of the business environment is examined in more detail
using cross-country regressions.
The business environment is, to a large extent, shaped by
a country’s deeper economic institutions, such as the rule of
law, control of corruption, the effectiveness of the government
and regulatory quality. This can be captured by the average of
the relevant Worldwide Governance Indicators, as discussed in
Chapter 2. Together with other country-level characteristics, such
as income per capita, RD inputs, financial development and
the quality of human capital, the quality of institutions is used in
this section to explain the number of patents granted per worker
and the innovation intensity of exports in various countries.
The results of these cross-country regressions are presented
in Table 3.3.
These results indicate that better institutions are associated
with increases in patenting and more innovation-intensive
exports. The effect of improving institutions is stronger and has
greater statistical significance in countries where institutions
are relatively weak. This can be seen where the average of the
Note: Excludes tax rates and political instability.
table 3.2. Main obstacles to firms’ operations
Top constraints, affecting...
all firms,
including
innovators
all firms, but
particularly
innovators
specifically
innovators
CEB Tax administration
Informal sector
Access to finance
Skills
SEE Informal sector
Access to finance
Electricity
Corruption
Tax administration
Skills
EEC, Russia and Central Asia Access to finance
Informal sector
Corruption
Skills
Electricity
Telecommunications
Customs and trade
regulations
Licences and
permits

Chapter 3
Source: Authors’ calculations using data from WIPO, World Bank, UNESCO, Penn World Table 8.0, Chinn and Ito (2006) and Barro and Lee (2013).
Note: The dependent variables are the log of total patents granted per 1,000 workers (“patent intensity”) and the log of the innovation intensity of exports (IIE), both of which are
averages over the period 2010-13. “WGIs” denotes the average of four Worldwide Governance Indicators (rule of law, control of corruption, effectiveness of government and regulatory
quality). See tr.ebrd.com for details about other explanatory variables. Robust standard errors are indicated in parentheses. ***, ** and * denote statistical significance at the 1, 5
and 10 per cent levels respectively. Columns 1 to 6 are estimates using ordinary least squares; columns 7 and 8 are estimates using two-stage least squares, with lagged values for
income per capita, openness to trade, and dependence on natural resources used as instruments for contemporaneous values.
table 3.3. Determinants of patent output and the innovation intensity of exports
Variables
(1)
IIE
(2)
Patent intensity
(3)
IIE
(4)
Patent intensity
(5)
IIE
(6)
Patent intensity
(7)
IIE
(8)
Patent intensity
Log of GDP per capita -0.117 1.260*** -0.006 1.062*** -0.078 1.115** -0.229 0.876**
(0.169) (0.385) (0.166) (0.335) (0.168) (0.430) (0.202) (0.442)
Log of population 0.236*** -0.012 0.181** -0.152 0.135** -0.149 0.177*** -0.096
(0.069) (0.108) (0.069) (0.109) (0.064) (0.111) (0.067) (0.126)
Institutions (WGIs) 0.733*** 0.891* 0.333 0.763*
(0.230) (0.459) (0.225) (0.450)
WGIs * high WGI dummy -0.165 0.795* -0.16 0.871*
(0.246) (0.465) (0.262) (0.487)
WGIs * low WGI dummy 1.083** 0.535 1.309*** 0.951
(0.508) (0.980) (0.491) (0.952)
Average years of tertiary education -0.132 1.311** -0.289 0.662 -0.002 0.614 0.144 0.757
(0.372) (0.528) (0.420) (0.467) (0.426) (0.546) (0.418) (0.524)
Ratio of external trade to GDP 0.002 -0.001 0.003* -0.001 0.004** -0.001 0.005** 0.000
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.003)
Financial openness -0.001 -0.086 0.054 -0.164 0.010 -0.156 0.033 -0.146
(0.071) (0.133) (0.071) (0.115) (0.070) (0.117) (0.071) (0.132)
Private credit 0.002 0.008** 0.003 0.011*** 0.003 0.011*** 0.004* 0.011***
(0.002) (0.003) (0.002) (0.003) (0.002) (0.003) (0.002) (0.003)
Natural resource rents -0.029** -0.005 -0.032** 0.009 -0.028* 0.008 -0.014 0.021
(0.012) (0.020) (0.014) (0.016) (0.014) (0.016) (0.013) (0.020)
Ratio of business RD spending
to GDP
0.338 0.834** 0.360** 0.826*** 0.382** 0.839***
(0.209) (0.315) (0.168) (0.309) (0.167) (0.261)
Ratio of government RD spending
to GDP
-0.63 4.845*** -0.35 4.765** -0.221 5.053***
(0.989) (1.763) (0.944) (1.915) (0.907) (1.657)
Ratio of university RD spending
to GDP
-0.191 -1.901 0.416 -1.949 0.550 -1.767
(0.637) (1.272) (0.681) (1.304) (0.704) (1.280)
EBRD dummy 0.606*** 1.325*** 0.522** 0.798* 0.172 0.828* 0.188 0.882**
(0.202) (0.372) (0.244) (0.420) (0.291) (0.481) (0.292) (0.423)
No. of observations 113 68 100 68 100 68 97 65
R2 0.53 0.80 0.54 0.86 0.57 0.86 0.55 0.86
Worldwide Governance Indicators is interacted with (i) a dummy
variable that takes the value of one when that average is above
the mean for the sample (indicating strong economic institutions);
or (ii) a dummy variable that takes the value of one when that
average is below the mean for the sample (indicating weak
economic institutions; see columns 3 to 8).
An improvement of around half a standard deviation in the
quality of economic institutions in a country with below-average
economic institutions (say, from the level of Ukraine to that
of Albania) is associated with a 60 per cent increase in the
innovation intensity of exports. An improvement of this magnitude
is also associated with a 40 to 50 per cent increase in patent
output. These effects are sizeable, considering that they only
capture the direct impact of the quality of institutions, beyond the
indirect effect that it may have through a higher level of income
and of human capital in the country.
Better institutions
are associated with
increases in patenting
and more innovation-
intensive exports

54
Chapter 3
Economic openness
The analysis above shows that innovative firms feel far more
constrained by customs and trade regulations than non-
innovative firms. At the same time, firms that sell their products
in export markets are more likely to innovate. The results of
cross-country analysis confirm that both the size of the market
(measured by population and GDP per capita) and economic
openness (measured by the ratio of exports and imports to GDP)
are important for the innovation intensity of exports. An increase
in openness to trade totalling 30 percentage points of GDP (say,
from the level of Ukraine to that of Latvia) is associated with a 9 to
15 per cent increase in the innovation intensity of exports. At the
same time, no strong links are found between patent output and
economic openness or the size of the economy.
In addition, there is also a positive (albeit weaker) relationship
between the innovation intensity of exports and the financial
openness of the economy (as measured by the Chinn-Ito index,
where higher values correspond to free cross-border movement
of capital and lower values correspond to more restrictive
regimes).15
All in all, these results suggest that a country’s ability
to commercialise innovations and adopt technologies benefits
from openness to trade and a large market.
These results should be viewed as indicating a general
correlation between innovation and country-level characteristics,
rather than a causal relationship. For instance, the causality
may also run from innovation to openness to trade. Indeed,
innovation can support exports, as it can help firms to become
more productive and improve their competitive positions in
international markets, thereby increasing the ratio of exports to
GDP. In order to take some account of such reverse causality,
similar regressions have been estimated using values for
income per capita, openness to trade and dependence on
natural resources with a lag of ten years as proxies for their
contemporaneous values. The results remain broadly unchanged
(see columns 7 and 8).16
Dependence on natural resources
Interestingly, an abundance of natural resources – measured by
calculating natural resource rents (that is to say, revenues net
of extraction costs) as a percentage of GDP – has the opposite
effect to economic openness. Reliance on commodities does not
appear to have an impact on the patent output of an economy,
but the exports of countries that are dependent on natural
resources tend to be significantly less innovation-intensive than
those of other countries (see Table 3.3).
This is, of course, partially a reflection of the fact that
commodity sectors inevitably account for a larger share of such
countries’ exports. However, this negative relationship may also
arise because the economy’s dependence on natural resources
reduces the average firm’s economic incentives to innovate, as
a large percentage of the value added in the economy is derived
from activities that are less reliant on continuous innovation.
For instance, while constant innovation and the adoption of
cutting-edge technologies is a prerequisite for maintaining a
competitive position in the automotive sector, a firm’s competitive
edge in terms of natural resource exports is dependent primarily
on natural resource endowments.17
At the same time, the
availability of natural resource rents may enable governments
(as well as universities and firms) to finance research, which
offsets any negative impact that natural resources may have on
patent output, but does not necessarily strengthen incentives to
commercialise innovations.
Skills of the workforce
The third aspect of the business environment that constrains
innovative firms particularly strongly is the availability of the
right skills. In country-level regressions (such as those reported
in Table 3.3) measures of human capital – including the
percentage of the population that has completed secondary or
tertiary education, the average number of years of schooling
and the average number of years of tertiary education – are not
consistently found to be significant determinants of innovation.
However, a higher average number of years of university
education is generally associated with a higher patent output.
This weaker correlation may be due to the fact that enrolment
ratio-type measures predominantly capture the quantity – rather
than the quality – of education.18
A more nuanced measure of the quality of education and
basic skills is available for a sample of 65 OECD and non-
OECD economies, based on the Programme for International
Student Assessment (PISA) conducted by the OECD. PISA is a
standardised international assessment of 15-year-old students’
abilities in the areas of reading, mathematics and science. It has
been conducted every three years since 2000, with a sample of
schools chosen at random in each country. Higher average scores
across all students in all three subjects generally correspond to a
higher quality of education in a given country.
For the sub-sample of countries participating in PISA, the
average scores achieved by these 15-year-old students are
positively and significantly correlated with innovation, in terms of
both patent output and the innovation intensity of exports (see
Chart 3.11). This relationship is particularly strong for patent
output (with the correlation coefficient standing at around two-
thirds), highlighting the role that the quality of education plays in
facilitating innovation at the technological frontier.
The effect that RD has on innovation outcomes, which was
examined earlier at the level of individual firms, can also be
observed in cross-country data (see Table 3.3). Furthermore,
the results of cross-country analysis reveal that the distribution
of RD spending across firms, academic institutions and
government also plays an important role. Both business RD
spending and government RD spending are associated with
increases in patent output, with the impact of an additional
US$ 1 of RD spending estimated to be higher for government
RD than for business RD. However, only business RD appears
to have a positive impact on the innovation intensity of exports.
This could be because of the poor links between science and
industry in transition countries (see Box 5.3).
This discussion of the links between innovation and RD in the
various sectors also highlights the complexity of the innovation
15
See Chinn and Ito (2006). 16
See EBRD (2010) for a more detailed discussion.
17
See also Welsch (2008) for evidence of a negative correlation between dependence on natural resources
and innovation.
18
Arguably, if higher education is pursued by students in order to obtain a diploma, rather than skills, this
could even waste resources that could have been used to support innovation.

Chapter 3
CHART 3.11. Innovation and PISA scores
Source: OECD, USPTO, UN Comtrade, Feenstra et al. (2005) and authors’ calculations.
Note: PISA scores are averages across mathematics, science and analytical reading. Data are based on the
2012 survey (or the latest survey available).
Average PISA score
Innovationintensityofexports
EST
POL
SLO
CRO
LAT
HUN
LIT
RUS
SVK
TUR
SER
BUL
KAZ
JOR
ALB
TUN
ROM
CHN
AUS
SGP
CAN
KOR
DEU
ISR
USA
JPN
CZE
350 400 450 500 550 600
0
50
100
150
200
250
Transition countries Other countries
Average PISA score
Patentsgrantedper1,000workers(log)
EST
POL
SLO
CRO
LAT
HUN
LIT
RUS
SVK
TUR
SER
CYP
BUL
KAZ
MNG
JOR
ALB
CHN
AUS
SGPCAN
KOR
DEU
ISR
USA
JPN
350 400 450 500 550 600
0.001
0.01
0.1
1
10
Transition countries Other countries
process, which requires a variety of general and specialist inputs.
For this reason, countries that are at a more advanced stage in
their development (measured, for instance, by GDP per capita at
purchasing power parity) may be better placed to innovate. The
cross-country results presented in Table 3.3 confirm that rich
countries do tend to patent more.
However, there does not appear to be any correlation between
income per capita and the innovation intensity of output. This
may be due to the fact that firms in less developed countries have
become increasingly successful at adopting existing technology
over the last few decades.
Overall, the various factors discussed above explain between
60 and 90 per cent of variation in innovation outcomes across
countries. The analysis also suggests that, given their income
per capita, economic openness, human capital, economic
institutions, RD spending and other characteristics, transition
economies innovate at around or slightly above the level that
would be expected of them, in terms of both patent output and
the innovation intensity of their exports.19
The average performances of
15-year-oldstudents in the PISA assessment
are positively correlated with the
innovation intensity of exports
19
The coefficient for the regional dummy variable is positive, but in most cases it is not significantly different
from zero.
Case study 3.1. Ford Otosan
The Turkish automotive sector has gradually evolved over the years. It
used to focus purely on assembly, but it now conducts more higher-
value-added activities, including local RD. So far, however, RD has
focused mainly on the design and development of simple products
(such as plastic and metal vehicle parts) and the optimisation of
manufacturing techniques. Thus, significant challenges remain if its
focus is to shift towards high-tech components (such as engine parts),
which would require an accommodating innovation ecosystem with
strong links between manufacturers, academia and local suppliers.
Ford Otosan has played a leading role in developing local RD
capabilities and establishing and nurturing links with local suppliers
and academia, thereby helping the Turkish automotive industry to move
towards higher-value-added activities.
The company is a joint venture bringing together a global automotive
giant (the Ford Motor Company) and a local industrial conglomerate
(Koç Holding). The firm was set up in 1959 to assemble Ford’s
commercial vehicles. Ford’s stake in the company has gradually
increased, reaching 41 per cent in 1997. Koç Holding also owns 41
per cent, and the remaining 18 per cent is publicly traded. In 2007 the
company opened the Gebze Engineering Centre, which develops new
products and technology. The firm now has the largest private RD
centre in Turkey, employing around 1,300 engineers.
Ford Otosan is currently in the process of further increasing its
local RD activity and strengthening its links with local suppliers and
academia. Specifically, the company has launched a project to develop
a new heavy truck engine that will meet European standards and be
an industry leader in terms of its energy performance, service life and
maintenance costs. As part of the project, high-tech engine components
are being designed and developed locally by Ford Otosan engineers,
in cooperation with local universities and suppliers. Importantly, the
project boasts more than a dozen specialist partnerships with local
universities, using these institutions to verify new technologies and
create an appropriate testing environment.

56
Chapter 3
Conclusion
Successful innovation relies on a supportive business
environment. A poor business environment can substantially
increase the cost of developing new products and make returns
to innovation much more uncertain, undermining firms’ incentives
to innovate. In some cases it may prompt start-ups and other
innovative firms to move their activities elsewhere, resulting in an
“innovation drain”.
Strikingly, firms that have recently introduced a new product
tend to regard all aspects of the business environment as a
greater constraint on their operations and growth than firms
that do not innovate. These differences between the views of
innovative and non-innovative firms are particularly large when
it comes to corruption, the skills of the workforce and customs
and trade regulations.
From a geographical perspective, they tend to be larger in
Central Asia, the EEC region and Russia. In the CEB region, by
contrast, these differences are less pronounced, suggesting
that the overall environment there may be more supportive
of innovation.
Firm-level and cross-country analysis has identified a number
of factors that play an important role in shaping firms’ incentives
and ability to innovate, as well as innovation outcomes at country
level. In the case of the latter, the factors that determine a
country’s patent output are not necessarily the same as those
that determine the innovation intensity of a country’s exports. For
example, countries that are rich in natural resources tend to have
less innovation-intensive exports, despite patenting levels that
are comparable to those of other countries.
Overall, the analysis in this chapter suggests that efforts to
further improve the innovation potential of firms and economies
in the transition region should primarily target reductions in
corruption, greater openness to international trade and cross-
border investment (including effective customs and trade
regulations) and improvements in the skills of the workforce.
Other factors, such as improved access to finance and the
upgrading of ICT infrastructure, also play an important role.
This analysis also reveals the relative scarcity of innovative
start-ups in the transition region. While larger firms that have
been around for a longer period of time tend to innovate more –
particularly in high-tech manufacturing sectors, where innovation
is more dependent on RD – smaller and younger firms are often
the ones developing products that are new to the global market.
In Israel, young, small firms are more likely to introduce
world-class innovations than larger, established firms, but in the
transition region this is not the case. On the contrary, innovations
introduced by young, small firms in the EBRD region are less
likely to target the global technological frontier than those of
larger firms.
The analysis in this chapter supports the view that RD
activities increase the likelihood of successful innovation, but
are by no means a prerequisite for innovation. The impact that
RD activities have on the likelihood of a new product being
introduced is particularly large in high-tech manufacturing
sectors. Meanwhile, RD in low-tech sectors can help to
optimise production processes. Lastly, while both business RD
and government RD increase a country’s patent output, only
business RD has a significant positive impact on the innovation
intensity of a country’s exports.
Insufficient
skillsare regarded as a major
constraint by all firms –
particularly innovative firms

Chapter 3
Box 3.1. Innovation drain
The transition region’s most successful innovative entrepreneurs and
small firms often move to London, Berlin, Silicon Valley, Boston, New
York and other innovation hubs at the earliest available opportunity in
order to take advantage of the resources available there. The investors,
mentors, advisers and clients located in these places help them to
develop products faster and more efficiently (thanks to the benefits
of agglomeration and clustering), while at the same time increasing
the value of their businesses.20
The legacy of socialism means that
entrepreneurship does not have a long tradition in the transition
region, so marketing and business development still lag behind
advanced economies.
Since a country’s development prospects are partly dependent
on its capacity for innovation – which, in turn, depends on human
capital – such “innovation drain” may be damaging. Indeed, research
suggests that the emigration of highly skilled individuals weakens local
knowledge networks.21
However, a highly skilled diaspora can contribute to economic
development through a variety of channels (such as remittances, trade,
foreign direct investment and knowledge transfers), helping innovators
back home to access knowledge accumulated abroad.22
Most successful
start-ups from the transition region are now developing their businesses
in the United States or the United Kingdom, but have development
centres somewhere in eastern Europe.23
The net effect ultimately depends on the country’s economic
development, the degree of transparency within government and public
administration, the business environment, and employers’ business
practices in terms of recruitment and selection.24
It also depends on how
good the country is at establishing links with its citizens abroad.25
One
option here would be to put expats in contact with one another through
social media and networking events and help them to return home if
they so wish.
There are numerous examples of companies from the transition
region that have moved abroad at an early stage.
Toshl Inc., the creator of a personal financial assistant app, was
established in Slovenia in 2012, but moved its headquarters to Silicon
Valley after joining the 500 Startups accelerator programme later
that year. Another example is Double Recall, which helps publishers
to increase the profitability and efficiency of paywalls by monetising
social media, search and email traffic using simple advertisements
that connect and engage with users. The company was established in
Slovenia in 2010, but then graduated from Y Combinator (an American
seed accelerator) in 2011 and now has its headquarters in New York.
Likewise, Croatian-Slovenian start-up Bellabeat (previously
BabyWatch), the creator of pregnancy tracking system Bellabeat,
participated at Startupbootcamp Berlin and raised funds via angel
investors and an Indiegogo campaign in 2013. It graduated from the
Y Combinator accelerator in March 2014 and relaunched its product
in the US market after successfully completing the seed round. Its
headquarters are in Silicon Valley.
Croatian start-up Repsly, a field management software company that
was founded in 2010, moved its headquarters to Boston in 2014 after
securing funding from Launchpad Venture Group, First Beverage Group
and K5 Ventures.
GrabCAD, a company established in 2009 that has created a
collaborative product development tool that helps engineering teams
to manage, view and share CAD files in the cloud, moved its
headquarters from Tallinn to Boston in 2011 in order to benefit from
the start-up scene there.
Codility, which produces software used for testing candidates for
developer positions and was founded in London by a group of Poles
in 2009 after winning the Seedcamp competition, is an example of
movement in the opposite direction. Most of the team is now based in
Warsaw, where they have an RD centre, although they still have an
office in London.
RealtimeBoard, which has developed a cloud-based whiteboard
that facilitates collaboration, was founded in Perm, in Russia, in 2011,
but it now has its headquarters in Las Vegas. Similarly, Jelastic, a cloud
computing service that provides networks, servers and storage solutions
to software development clients, enterprise businesses, original
equipment manufacturers and web hosting providers, was founded in
Zhitomir, in Ukraine, in 2010. It received funding from several Russian
venture funds, but moved its headquarters to Silicon Valley in 2012.
It is interesting to note that several of these start-ups were given
an initial (financial) push by seed financing or boot camp accelerator
programmes in Berlin or London, but nevertheless moved across the
Atlantic to the United States. The pull of the US innovation hubs and
the large US market remains too strong for Europe to compete with,
particularly as there are still many barriers to the free movement of
online services and entertainment across national borders in the EU.
Box 3.2. Global value chains: drivers of innovation?
Over the past two decades, the increased prominence of global value
chains (GVCs) has transformed the world economy. The declining cost
of communication and international shipping has caused production
processes to be broken down into ever smaller parts and spread
across vast geographical areas. As a result, international commerce
is now dominated by trade in intermediate – rather than final – goods
and services. This box looks at how GVCs stimulate innovation among
manufacturing firms in the transition region.26
There are several reasons why participation in GVCs can help firms in
emerging economies to learn and innovate. First, being part of a
GVC means that a firm has to satisfy the chain’s requirements in terms
of the quality of products and the efficiency of processes.27
To do so,
managers may need to adapt their production methods or acquire
technology via licensing arrangements. Second, serving foreign clients
may require improved logistical solutions or delivery methods, as
delivery at the appropriate time is essential for a smooth supply chain.
Third, importing intermediate goods can itself be a channel for the
diffusion of technology where firms import state-of-the-art technology
that has not previously been available in the domestic market. Importing
new technologies can also enhance the technical skills of the
20
See Szabo (2013).
21
See Agrawal et al. (2011).
22
See Agrawal et al. (2011) and Stankovic et al. (2013).
23
EPAM, a global provider of software development services, was one of the first firms to adopt this model
(see Case study 1.1 for more details). See also Khrennikov (2013).
24
See, for example, OECD (2010).
25
See The Economist (2014).
26
See Franssen (2014) for more details.
27
See Pietrobelli and Raballotti (2011).

58
Chapter 3
CHART 3.2.1. Global value chains and innovation
Note: GVC firms are those participating in global value chains.
Product innovation Process innovation RD Acquisition of external knowledge Licensing of technology
0.0
0.1
0.2
0.3
0.4
0.5
Non-GVC ﬁrms GVC ﬁrms
the basis of the relative skill endowments of the countries where they
operate (measured as the percentage of the workforce that has completed
secondary education). This chart suggests that the marginal probability of
innovating on account of participation in a GVC increases with the quality
of the workforce that is at the firm’s disposal. Firms in countries with higher
skill levels are given – via GVCs – more skill-intensive tasks with greater
scope and need for technological spillovers.
However, caution is warranted when it comes to the type of involvement
that firms have in GVCs. As mentioned above, participation in GVCs may
hinder innovative activity and prevent positive spillovers if it only involves
the assembly of components.
All in all, the analysis in this box shows that where participation in
GVCs goes beyond simple assembly, it may allow firms to reap substantial
productivity benefits through international spillovers of technology and
know-how. A good example of this is the automotive industry in central and
eastern Europe.29
In CEB countries where this sector has seen high levels
of foreign direct investment and local car producers are well integrated
into GVCs – such as Hungary and the Slovak Republic – labour productivity
in the automotive sector is substantially higher than the average for the
manufacturing industry as a whole. By contrast, in countries where foreign
investors play no meaningful role in the car industry (such as Bulgaria), the
opposite is true.
The challenge, then, remains unchanged: not only replicating, but also
improving on this paradigm across a variety of industries in the region, in
order to help countries move up the value chain.
workforce if this necessitates further training. These increases in
human capital may, in turn, enable companies to introduce innovative
products of their own.
However, in certain circumstances GVCs can also hamper innovation
within participating firms. This is most likely to occur where firms in
developing countries are involved solely in the assembly of foreign
intermediate goods. As this is the least skill-intensive stage of the
value chain, the potential for technological spillovers is minimal and it
is unlikely that participation in the GVC will encourage these firms to
introduce new products of their own.
Chart 3.2.1 shows the percentage of innovative BEEPS V firms that
are part of a GVC. GVC firms are defined as those that both import at
least 10 per cent of their intermediate goods and export at least 10 per
cent of their output.28
We can see that GVC firms tend to be more innovative than other
firms across all five measures of innovation. In particular, 44 per cent
of GVC firms responding to BEEPS V have introduced a new product in
the last three years, compared with only 31 per cent of firms that do not
participate in an international supply network. Equally striking is the fact
that there is a 15 percentage point difference between the two when
it comes to the percentage of firms that spend money on RD or use
technology via a licensing arrangement.
In order to check that these substantial differences are not driven
by other factors, such as firms’ ownership structures or their access to
finance, Table 3.2.1 presents the results of a multivariate regression
analysis. It shows that these differences in RD, the licensing of
technology, product innovation and process innovation continue to be
observed when other firm-level characteristics are controlled for.
This analysis also determines the precise source of the positive
impact that GVCs have on innovation. All measures of innovation – with
the exception of the acquisition of external knowledge – are positively
and significantly correlated with the importing of at least 10 per cent of
total intermediate goods. However, only product innovation is positively
and significantly associated with the exporting of at least 10 per cent of
total output.
These results suggest that GVCs help firms to expand their product
ranges and upgrade technology primarily by giving them access to better
quality inputs, rather than by expanding the size of their markets.
The detailed innovation module in BEEPS V can help to shed more
light on the mechanisms that are at work here. Firms that reported the
introduction of a product or process innovation or the acquisition of
external knowledge were asked whether they were able to do so as a
result of working with domestic or foreign partners (such as clients or
suppliers). Chart 3.2.2 shows that 22 per cent of GVC firms reported
working with foreign partners on innovation, compared with only 10 per
cent of non-GVC firms. This suggests that the higher levels of innovative
activity among GVC firms can indeed be attributed to their easier access
to foreign technology and knowledge. An important policy implication is
that firms in emerging markets cannot hope to become more innovative
simply by importing physical inputs. Instead, they need to invest in
longer-term relationships with foreign suppliers and clients in order to
allow a continuous flow of knowledge and know-how.
Chart 3.2.3 shows the impact that participation in GVCs has on the
probability of firms innovating. Here, firms are grouped together on
28
Early methods of measuring GVCs focused on vertical specialisation and the flow of intermediate goods
across borders (see, for instance, Hummels et al., 2001), while more recent methodologies focus on the
value-added content of final goods. Identifying two-way trade at the firm level is important in order to
correctly determine whether firms are likely to be part of a GVC.
29
See Pavlínek et al. (2009) and Fortwengel (2011).

Chapter 3
CHART 3.2.2. Sources of innovation
Note: GVC firms are those participating in global value chains.
Per cent
GVCﬁrmsNon-GVCﬁrms
0 10 20 30 40 50 60 70 80 90 100
Domestic partners Foreign partners Other
CHART 3.2.3. The marginal impact that participation in a GVC has on
the probability of innovating, broken down on the basis of countries’ skill
endowment levels
Increasedlikelihoodofinnovating
asaresultofparticipationinaGVC
Product innovation Process innovation RD Organisational
innovation
Marketing
innovation
Acquisition of
external knowledge
Licensing
of technology
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Low
Skill level:
Low/medium Medium/high High
table 3.2.1. Global value chains and innovation
(1)
Product innovation
(2)
Process innovation
(3)
RD
(4)
Acquisition of external
knowledge
(5)
Licensing of technology
Import at least 10% of intermediate goods 0.513*** 0.367*** 0.487*** 0.107 0.437***
(0.063) (0.067) (0.089) (0.097) (0.074)
Export at least 10% of output 0.256** 0.191* 0.089 0.188 0.210*
(0.089) (0.095) (0.120) (0.125) (0.098)
Both import and export 10% 0.421*** 0.359*** 0.531*** 0.218* 0.551***
(0.075) (0.079) (0.096) (0.106) (0.084)
Foreign-owned firm 0.038 -0.007 0.048 -0.007 0.435***
(0.079) (0.083) (0.093) (0.102) (0.081)
Staff training 0.371*** 0.434*** 0.480*** 0.451*** 0.156**
(0.052) (0.054) (0.065) (0.070) (0.059)
Quality certificate 0.184*** 0.189** 0.263*** 0.220** 0.455***
(0.056) (0.059) (0.069) (0.077) (0.061)
External audit 0.108* 0.109 0.066 0.268*** 0.102
(0.055) (0.057) (0.069) (0.076) (0.060)
Managerial experience 0.005* 0.004 0.006* 0.002 -0.002
(0.002) (0.003) (0.003) (0.003) (0.003)
Age of firm 0.002 0.003 0.001 0.004 -0.002
(0.002) (0.002) (0.002) (0.002) (0.002)
OECD country 0.269 -0.403 0.575* 0.071 -0.096
(0.203) (0.238) (0.238) (0.283) (0.269)
Size of firm, where baseline case is small firm (fewer than 20 employees)
Medium size -0.022 0.075 0.041 -0.209* 0.128*
(0.056) (0.059) (0.072) (0.085) (0.063)
Large size 0.071 0.182* 0.269** -0.170 0.260**
(0.077) (0.081) (0.094) (0.107) (0.083)
Whether access to credit is an obstacle to current operations, where baseline case is no obstacle
Small obstacle 0.081 0.022 -0.048 0.118 -0.023
(0.054) (0.057) (0.069) (0.076) (0.061)
Large obstacle 0.171** 0.192** -0.021 -0.052 0.115
(0.065) (0.069) (0.083) (0.094) (0.073)
Constant -1.067*** -1.501*** -2.093*** -1.843*** -1.956***
(0.163) (0.177) (0.215) (0.241) (0.213)
N 3628 3617 3511 2277 3601
Note: Standard errors are reported in parentheses below the coefficients. ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively.

60
Chapter 3
Box 3.3. Competition and innovation: a complex
relationship
Does stronger competition in product markets boost or hamper
technological advances? The relationship between competition and
innovation is complex, as multiple countervailing forces are at work.
On the one hand, concentrated markets with less competition may
be more conducive to innovation. Large firms with substantial market
power may be more willing to carry out innovation-oriented RD
activities because the scarcity of competitors will allow them to reap
higher rents from newly introduced products if those innovations turn
out to be successful. Market power may also help firms to finance RD
activities using retained earnings.
On the other hand, a lack of competition, while enabling firms to
enjoy higher rents from new products, may also lead to complacency.
In other words, firms may have more incentives to innovate in a
competitive environment, in order to get ahead of their rivals and
increase their market share.30
The combination of these two effects may lead to a non-linear
relationship between competition and innovation (such as an inverted
U-shape).31
This shape may reflect the existence of two broad types
of industry: “neck-and-neck” industries, in which companies operate
with similar levels of technology, and “unlevelled” industries, in which a
technological leader competes with a group of followers.
In neck-and-neck industries, competition encourages firms to
innovate, because it allows them to move ahead of their competitors
and increase their market share. In contrast, tougher competition
discourages laggard firms in unlevelled industries from innovating, as the
laggard’s reward for catching up with the technological leader declines.
An inverted U-shape may emerge where neck-and-neck industries are
more prevalent at low levels of competition, but then, as competition
intensifies, more industries become unlevelled and further competition
starts to put a break on innovation.
BEEPS V and MENA ES data broadly confirm the existence of
an inverted U-shape in transition economies (see Chart 3.3.1). This
chart plots innovative output in the SEE and CEB regions against the
distribution of the number of competitors, showing that the average
percentage of firms introducing a new or improved product or process
initially increases with the number of competitors, before then declining
in the third and fourth quartiles of the distribution. The chart also shows
that the inverted U-shaped relationship between competition and
innovation translates into a similar relationship between competition and
firms’ growth.
Empirical evidence suggests that the positive impact that
competition has on innovation is stronger for older firms. This is
consistent with the view that older firms are inherently less likely to
innovate unless they are spurred on by competition.32
Overall, the
literature seems to conclude that some degree of market power appears
necessary for stimulating innovation activity, coupled with competitive
pressure (especially pressure from foreign competitors).
Competition policy
There is a broad consensus that well-designed and properly enforced
competition policies are beneficial to innovation. Competition-enhancing
policies can be broadly divided into two groups. First, product market
deregulation aims to remove barriers to entry, trade and economic activity,
as well as limiting the state’s direct interference in economic activity.
Second, competition laws provide a legal framework for the prosecution of
anti-competitive conduct, cartels and the abuse of dominant positions, as
well as reducing the anti-competitive effect of mergers.
Product market deregulation has consistently been found to increase
the adoption of state-of-the-art production techniques, as well as the
introduction of new technologies. As a result, deregulation may ultimately
translate into stronger total factor productivity growth.33
Conversely, restrictive product market regulations limit the productivity
of the industries concerned. This is particularly true of industries that are
a long way from the technological frontier. In these industries, restrictive
regulations tend to halt the catching-up process.
Recent analysis also shows that anti-competitive product market
regulations in upstream sectors curb productivity growth even in very
competitive downstream sectors. In other words, a lack of competition
in upstream sectors can generate barriers to entry that curb competition
in downstream sectors as well, reducing pressures to improve efficiency
in those sectors. For example, tight licensing requirements in retail or
transport sectors can restrict access to distribution channels, while overly
restrictive regulation in banking and financial sectors can reduce sources
of financing, affecting all firms in the economy.34
When it comes to the enforcement of competition law, the existence
of a complex relationship between competition and innovation has
sometimes been interpreted as meaning that more lenient standards
should be adopted when it comes to innovative industries. The
complicated relationship between competition and innovation does call
for a more comprehensive assessment of the impact that specific actions
have on market participants’ ability to innovate and the incentives they
have. However, it does not justify the blanket dismissal of all concerns
about anti-competitive behaviour in industries that are deemed to be
innovative.
A proper assessment of innovative industries requires well-
designed competition laws and competent competition authorities. The
enforcement of competition law can play an important role in supporting
innovation by allowing actions that promote innovation (such as mergers)
and prohibiting actions that hamper it. Recent evidence from OECD
countries points in this direction, showing that sound competition policies
lead to stronger total factor productivity growth (which may be seen as a
proxy for innovation). 35
Data for the transition region show the positive effect that competition-
enhancing policies have on innovation. Chart 3.3.2 shows that there is
a positive relationship between the quality of competition-enhancing
policies (as measured by the EBRD’s competition indicator, which
assesses the quality of competition law, the institutional environment and
enforcement activities)36
and innovation. While the chart does no more
than indicate a correlation between the two, this nevertheless points
to a link between the quality of competition policy and the strength
of innovation.
All in all, while the relationship between competition and innovation is
a complex one, well-designed competition policies can help to provide the
right business environment, allowing companies to fulfil their competitive
potential and having a positive impact on innovation.
30
See Arrow (1962) for an early discussion of this effect.
31
See Aghion et al. (2005).
32
See Carlin et al. (2004).
33
See Nicoletti and Scarpetta (2005) and Conway et al. (2006).
34
In addition, if there is market power in upstream sectors and firms in downstream industries have to
negotiate the terms and conditions of their contracts with suppliers, some of the rents that are expected
downstream as a result of the adoption of state-of-the-art technology will be taken by providers of
intermediate inputs. This, in turn, will reduce incentives to improve efficiency and curb productivity in
downstream sectors, even if competition in these sectors is strong.
35
See Buccirossi et al. (2013).
36
See Annex 5.1 of this Transition Report for a description of the EBRD’s competition indicator.

Chapter 3
Box 3.4. Consultants as conduits for firm-level innovation
Consultancy firms can play a vital role in facilitating innovation by acting
as conduits for external know-how and providing information about
customers’ preferences.37
They can help a firm adapt its organisational
structure and management practices to changing industry needs, help it
refine its design and packaging in order to appeal more effectively to its
target groups, or provide market research underpinning the development
of new products that better satisfy customers’ needs. For instance,
consultants have helped a Swedish bank to introduce internet banking.38
Consultants can also help firms’ managers to analyse the pros and cons of
developing new products and processes.39
While the percentage of firms using consultants varies greatly across
the countries of the transition region – ranging from just 4 per cent in
Azerbaijan to 54 per cent in Ukraine – consultants are more likely to be
used by innovative firms in almost all countries (see Chart 3.4.1).
Across the region as a whole, 61 per cent of firms that have introduced
a new product in the last three years also hired a consultant during
that period, compared with 20 per cent of firms that did not innovate.
Consultants also assisted 63 per cent of firms that introduced new or
improved organisational management practices.
These relationships do not appear to be driven by particular industries
or specific types of firm. Even when firm-level characteristics are taken
into account, there remains a positive and highly significant correlation
between the use of consultants and all types of innovation – product,
process, organisational and marketing innovations. This is consistent with
evidence that external consultants can help small and medium-sized firms
to improve their productivity.40
Despite these apparent advantages, many firms choose not to use
consultants when developing new products or processes. One reason
for this is that every consultancy contract involves transaction costs,
which may take resources away from the innovation itself. Firms may
also be concerned about leaking information regarding new products and
processes, particularly in countries where intellectual property rights are
poorly enforced.41
CHART 3.3.1. Competition, innovation and growth in transition countries
Number of competitors
Turnovergrowth(percent)
Productand/orprocessinnovation(percent)
Turnover growth (left-hand axis) Percentage of firms introducing product and/or process innovation (right-hand axis)
0-4 5-10 11-100+
0
1
2
3
4
5
6
7
8
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
0.30
Source: EBRD (2013), Cornell University et al. (2014) and authors’ calculations.
CHART 3.3.2. Competition policy and innovation output
EBRD competition indicator
GIIinnovationoutputindicator
ALB
ARM
AZE
BEL
BOS
BUL
CRO
EST
FYR
GEO
HUN
KAZ
KGZ
LAT
LIT
MDA
MON
MNG
POL
ROMRUS
SER
SVK
SLO
TJK
TUR
UKR
UZB
2 2.5 3 3.5
10
15
20
25
30
35
40
45
50
However, the main reason why firms in the transition region do not
hire consultants is that they simply see no need for them. Interestingly,
exposure to consultancy services seems to change this belief:
once firms have employed consultants once, they typically do so again.
Indeed, BEEPS firms that use external consultants have done so an
average of four times in the last three years. Moreover, where clients of
the EBRD’s Small Business Support team have never worked with a local
consultant before, nearly half of these clients then undertake a second
consultancy project independently within a year. Since firms that hire
consultants also tend to be more innovative, their exposure to external
know-how seems to be an important channel in the fulfilment of their
innovation potential.
37
See Thrift (2005).
38
See Back et al. (2014).
39
See Back et al. (2014).
40
See Bruhn et al. (2012) for evidence from Mexico.
41
See Hoecht and Trott (2006).
Note: The percentage of innovative firms is calculated using cleaned data for product
and process innovation.
CHART 3.4.1. Firms that use consultants are more likely to innovate
Innovative firms as a percentage of total firms
Innovativefirmsasapercentageoffirmsusingconsultants
ALB
ARMAZE
BEL
BOS
BUL
CRO
EST
FYR
GEO
HUN
KAZ
KGZ
LAT
LIT
MDA
MON
MNG POL
ROM
RUS
SER
SLO
KOS
UKR
UZB
10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
60
70
80
90
100

62
Chapter 3
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