TRANSITION REPORT 2014 Innovation in Transition






Alexander Plekhanov

Alexander Plekhanov is a Lead Economist at the EBRD Office of the Chief Economist. He has worked on global macroeconomic issues and as a country economist covering a number of countries, including Belarus, Kazakhstan, Mongolia and Russia. Prior to joining the Bank, Alexander worked as an economist at the International Monetary Fund in the Western Hemisphere and Fiscal Affairs Departments.


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.

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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.


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).

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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 R&D 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 R&D than larger firms (albeit they tend to spend a higher percentage of their annual turnover on in-house R&D; 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 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.


Determinants of R&D and innovation
Technological innovation








Firm age (years)







5-19 employees (dummy)







20-99 employees (dummy)







Majority foreign-owned (dummy)







Majority state-owned (dummy)







Direct exporter (dummy)







Percentage of working capital financed by banks or non-bank financial institutions







Percentage of fixed asset purchases financed by banks or non-bank financial institutions







Percentage of employees with a university degree







Main market: local (indicator)







Use email for communication with clients (indicator)







Source: BEEPS V, MENA ES and authors’ calculations.
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.


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.


Source: BEEPS V, MENA ES and authors’ calculations.
Note: Unweighted averages across transition countries. Small firms have fewer than 20 employees.

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.

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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). 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).


Source: BEEPS V, MENA ES and authors’ calculations.
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.


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 R&D activities in their home countries, outsourcing only lower-value-added activities to emerging markets, so foreign takeovers may actually result in reduced spending on R&D.6

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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 R&D. Foreign-owned firms are defined here as firms where foreign 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 R&D (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 R&D (see Case study 3.1 for details of a joint venture in the Turkish automotive sector with an active domestic R&D programme). Overall, these findings run counter to the view that foreign takeovers undermine domestic R&D.

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.


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 R&D. So far, however, R&D 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 R&D 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 R&D centre in Turkey, employing around 1,300 engineers.

Ford Otosan is currently in the process of further increasing its local R&D 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.


Source: BEEPS V, MENA ES and authors’ calculations.
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.


Source: BEEPS V, MENA ES and authors’ calculations.
Note: Unweighted averages across transition countries. The acquisition of external knowledge includes the outsourcing of R&D 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.

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.

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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 R&D 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 R&D and process innovation.10 Regression results indicate that exporters are 6 percentage points more likely to engage in R&D. This may be explained by the fact that exporting and entering new markets can help firms to improve their knowledge of production processes, while R&D 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.


Source: BEEPS V, MENA ES and authors’ calculations.
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.

R&D inputs and innovation outputs

Another important decision that a firm faces is whether to spend on R&D to support the development of new products. As discussed in Chapter 1, R&D 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, R&D significantly increases the likelihood of successful innovation. Firms that invest in R&D are an average 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).

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Investing in R&D 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 R&D increases the probability of product innovation on average by 26 percentage points, while in less knowledge-intensive service sectors (such as catering or sales) R&D has virtually no impact on the probability of introducing a new product.

While R&D is closely linked to product innovation in high-tech manufacturing sectors, R&D 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 R&D 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).


Source: BEEPS V, MENA ES and authors’ calculations.
Note: This chart reports the average marginal effect of R&D 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).

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 R&D, 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.

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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 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.


Source: BEEPS V, MENA ES and authors’ calculations.
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.

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”.

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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 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.

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.


Source: BEEPS V, MENA ES and authors’ calculations.
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.

CHART 3.10

Source: BEEPS V and authors’ calculations.
Note: See the note accompanying Chart 3.9.


Main obstacles to firms’ operations
  Top constraints, affecting…
  all firms, including innovators all firms, but particularly innovators specifically innovators


Tax administration

Informal sector

Access to finance




Informal sector

Access to finance



Tax administration


EEC, Russia and Central Asia

Access to finance

Informal sector





Customs and trade regulations

Licences and permits

Source: BEEPS V and authors’ calculations.
Note: Excludes tax rates and political instability.


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, R&D 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 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.


Determinants of patent output and the innovation intensity of exports
Variables (1)
Patent intensity
Patent intensity
Patent intensity
Patent intensity

Log of GDP per capita

















Log of population

















Institutions (WGIs)











WGIs * high WGI dummy











WGIs * low WGI dummy











Average years of tertiary education

















Ratio of external trade to GDP

















Financial openness

















Private credit

















Natural resource rents

















Ratio of business R&D spending to GDP















Ratio of government R&D spending to GDP















Ratio of university R&D spending to GDP















EBRD dummy

















No. of observations


















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 (based on WIPO data; “patent intensity”) and the log of the innovation intensity of exports (IIE; see Chapter 1 for a definition), 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). Financial openness is measured using the Chinn-Ito index. Private credit is the ratio of domestic private-sector credit to GDP and is obtained from the World Bank’s Financial Development and Structure Dataset. Other sources include: Penn World Table 8.0 (GDP, population and external trade); Barro and Lee, 2013 (average years of schooling); the World Bank’s World Development Indicators (natural resource rents); and UNESCO (R&D spending). 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 being used as instruments for contemporaneous values.

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 R&D 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 R&D spending across firms, academic institutions and government also plays an important role. Both business R&D spending and government R&D spending are associated with increases in patent output, with the impact of an additional US$ 1 of R&D spending estimated to be higher for government R&D than for business R&D. However, only business R&D 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 R&D in the various sectors also highlights the complexity of the innovation 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, R&D 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

CHART 3.11
  • Transition countries
  • Other countries

  • Transition countries
  • Other countries

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).



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 R&D – 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 R&D activities increase the likelihood of successful innovation, but are by no means a prerequisite for innovation. The impact that R&D activities have on the likelihood of a new product being introduced is particularly large in high-tech manufacturing sectors. Meanwhile, R&D in low-tech sectors can help to optimise production processes. Lastly, while both business R&D and government R&D increase a country’s patent output, only business R&D has a significant positive impact on the innovation intensity of a country’s exports.

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

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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 R&D 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 workforce if this necessitates further training. These increases in human capital may, in turn, enable companies to introduce innovative products of their own.

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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 R&D 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 R&D, 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 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.

TABLE 3.2.1

Global value chains and innovation
Acquisition of
external knowledge
of technology

Import at least 10% of intermediate goods











Export at least 10% of output











Both import and export 10%











Foreign-owned firm











Staff training











Quality certificate











External audit











Managerial experience











Age of firm











OECD country











Size of firm, where baseline case is small firm (fewer than 20 employees)

Medium size











Large size











Whether access to credit is an obstacle to current operations, where baseline case is no obstacle 

Small obstacle











Large obstacle











Constant -1.067*** -1.501*** -2.093*** -1.843*** -1.956***
(0.163) (0.177) (0.215) (0.241) (0.213)







Source: BEEPS V and authors’ calculations.
Note: Standard errors are reported in parentheses below the coefficients. ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively.

CHART 3.2.1

Source: BEEPS V and authors’ calculations.
Note: GVC firms are those participating in global value chains.

CHART 3.2.2
  • Domestic partners
  • Foreign partners
  • Other

Source: BEEPS V and authors’ calculations.
Note: GVC firms are those participating in global value chains.

CHART 3.2.3

Source: BEEPS V and authors’ calculations.

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 R&D 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 R&D 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

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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.

CHART 3.3.1

Source: BEEPS V, MENA ES and authors’ calculations.

CHART 3.3.2

Source: EBRD (2013), Cornell University et al. (2014) and authors’ calculations.

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).

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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

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.

CHART 3.4.1

Source: BEEPS V and authors’ calculations.
Note: The percentage of innovative firms is calculated using cleaned data for product and process innovation.


D. Acemoğlu, U. Akcigit and M.A. Celik (2014)
“Young, restless and creative: Openness to disruption and creative innovations”, NBER Working Paper No. 19894.
P. Aghion, N. Bloom, R. Blundell, R. Griffith and P. Howitt (2005)
“Competition and innovation: an inverted U relationship”, Quarterly Journal of Economics, Vol. 120, No. 2, pp. 701-728.
A. Agrawal, D. Kapur, J. McHale and A. Oettl (2011)
“Brain drain or brain bank? The impact of skilled emigration on poor-country innovation”, Journal of Urban Economics, Vol. 69, No. 1, pp. 43-55.
K. Arrow (1962)
“Economic Welfare and the Allocation of Resources to Invention”, in R.R. Nelson (ed.), The Rate and Direction of Economic Activity, Princeton University Press.
Y. Back, K. Praveen Parboteeah and D.I. Nam (2014)
“Innovation in emerging markets: The role of management consulting firms”, Journal of International Management, forthcoming.
J.R. Baldwin and W. Gu (2004)
“Trade liberalization: Export-market participation, productivity growth and innovation”, Oxford Review of Economic Policy, Vol. 20, No. 3, pp. 372-392.
R. Barro and J.W. Lee (2013)
“A new data set of educational attainment in the world, 1950-2010”, Journal of Development Economics, Vol. 104, pp. 184-198.
N. Bloom, M. Draca and J. Van Reenen (2011)
“Trade induced technical change? The impact of Chinese imports on innovation, IT and productivity”, NBER Working Paper No. 16717.
M. Bruhn, D. Karlan and A. Schoar (2012)
“The Impact of Consulting Services on Small and Medium Enterprises: Evidence from a Randomized Trial in Mexico”, Economic Growth Center Working Paper No. 1010, Yale University.
P. Buccirossi, L. Ciari, T. Duso, G. Spagnolo and C. Vitale (2013)
“Competition Policy and Productivity Growth: An Empirical Assessment”, The Review of Economics and Statistics, Vol. 95, No. 4, pp. 1324-1336.
W. Carlin, M. Schaffer and P. Seabright (2004)
“A minimum of rivalry: Evidence from transition economies on the importance of competition for innovation and growth”, B.E. Journal of Economic Analysis & Policy, Vol. 3, No. 1, pp. 1-43.
M.D. Chinn and H. Ito (2006)
“What matters for financial development? Capital controls, institutions, and interactions”, Journal of Development Economics, Vol. 81, No. 1, pp. 163-192.
D. Coe, E. Helpman and A. Hoffmaister (2009)
“International R&D spillovers and institutions”, European Economic Review, Vol. 53, No. 7, pp. 723-741.
W.M. Cohen and D. Levinthal (1989)
“Innovation and learning: The two faces of R&D”, Economic Journal, Vol. 99, No. 397, pp. 569-596.
P. Conway, D. De Rosa, G. Nicoletti and F. Steiner (2006)
“Regulation, Competition and Productivity Convergence”, OECD Economics Department Working Paper No. 509.
Cornell University, INSEAD and WIPO (2014)
The Global Innovation Index 2014: The Human Factor in Innovation, Fontainebleau, Ithaca and Geneva.
G. Crespi and P. Zuñiga (2012)
“Innovation and productivity: Evidence from six Latin American countries”, World Development, Vol. 40, No. 2, pp. 273-290.
J.P. Damijan, Č. Kostevc and S. Polanec (2010)
“From innovation to exporting or vice versa?”, World Economy, Vol. 33, No. 3, pp. 374-398.
EBRD (2010)
Transition Report 2010: Recovery and Reform, London.
EBRD (2013)
Transition Report 2013: Stuck in Transition?, London.
The Economist (2014)
“The British diaspora: And don’t come back”, The Economist, 9 August 2014. Available at: (last accessed on 5 September 2014).
R. Feenstra, R. Lipsey, H. Deng, A. Ma and H. Mo (2005)
“World trade flows: 1962-2000”, NBER Working Paper No. 11040.
J. Fortwengel (2011)
“Upgrading through integration? The case of the Central Eastern European automotive industry”, Transcience – A Journal of Global Studies, Vol. 2, No. 1, pp. 1-25.
L. Franssen (2014)
“The effect of global value chains on the relative skill-employment of firms in emerging economies”, EBRD working paper, forthcoming.
R. Griffith, E. Huergo, J. Mairesse and B. Peters (2006)
“Innovation and productivity across four European countries”, Oxford Review of Economic Policy, Vol. 22, No. 4, pp. 483-498.
A. Hoecht and P. Trott (2006)
“Innovation risks of strategic outsourcing”, Technovation, Vol. 26, No. 5-6, pp. 672-681.
D. Hummels, J. Ishii and K.-M. Yi (2001)
“The nature and growth of vertical specialization in world trade”, Journal of International Economics, Vol. 54, No. 1, pp. 75-96.
I. Khrennikov (2013)
“Ex-Soviet programmers take on India in $48 billion market”, Bloomberg, 17 September 2013. Available at: (last accessed on 5 September 2014).
A. Lileeva and D. Trefler (2010)
“Improved access to foreign markets raises plant-level productivity… for some plants”, Quarterly Journal of Economics, Vol. 125, No. 3, pp. 1051-1099.
R.R. Nelson and E. Phelps (1966)
“Investment in humans, technological diffusion and economic growth”, American Economic Review, Vol. 56, No. 1-2, pp. 69-75.
G. Nicoletti and S. Scarpetta (2005)
“Regulation and Economic Performance: Product Market Reforms and Productivity in the OECD”, OECD Economics Department Working Paper No. 460.
P. Nightingale and A. Coad (2013)
“Muppets and gazelles: political and methodological biases in entrepreneurship research”, Industrial and Corporate Change, Vol. 23, No. 1, pp. 113-143.
OECD (2009)
Innovation in Firms: A Microeconomic Perspective, Paris.
OECD (2010)
Investment Reform Index 2010: Monitoring policies and institutions for direct investment in South East Europe, Paris.
H. Pavlínek, B. Domański and R. Guzik (2009)
“Industrial upgrading through foreign direct investment in Central European automotive manufacturing”, European Urban and Regional Studies, Vol. 16, No. 1, pp. 43-63.
C. Pietrobelli and R. Raballotti (2011)
“Global value chains meet innovation systems: Are there learning opportunities for developing countries?”, World Development, Vol. 39, No. 7, pp. 1261-1269.
I. Sample (2014)
“If Pfizer’s AstraZeneca takeover succeeds, bad news for UK research”, The Guardian, 28 April 2014. Available at: (last accessed on 25 August 2014).
M. Stankovic, B. Angelova, V. Janeska and B. Stankovic (2013)
“Science and innovation policy in Southeast Europe: Brain drain as brain gain”, International Journal of Technological Learning, Innovation and Development, Vol. 6, No. 3, pp. 262-282.
B. Szabo (2013)
“How Central Eastern Europe is transforming from outsourcing to a real tech hub”, Forbes, 10 February 2013. Available at: (last accessed on 5 September 2014).
N.J. Thrift (2005)
Knowing Capitalism, SAGE Publications, Thousand Oaks, California.
H. Welsch (2008)
“Resource dependence, knowledge creation, and growth: Revisiting the natural resource curse”, Journal of Economic Development, Vol. 33, No. 1, pp. 45-70.