Knowledge Economy in the Western Balkans

8/13/2019 Knowledge Economy in the Western Balkans

1/37

KNOWLEDGE ECONOMY INTHE WESTERN BALKANS

Exploringviable solutions to address

the key challenges to develop and

strengthen a knowledge-based

economy in Serbia and Macedonia

Copyright 2012 Dennis KellerContact:[email protected]
mailto:[email protected]:[email protected]:[email protected]://www.linkedin.com/in/dennisikellerhttp://www.linkedin.com/in/dennisikellerhttp://www.linkedin.com/in/dennisikellerhttp://www.twitter.com/denniskellerhttp://www.twitter.com/denniskellerhttp://www.twitter.com/denniskellerhttp://www.twitter.com/denniskellerhttp://www.linkedin.com/in/dennisikellermailto:[email protected]


2/37

Dennis Keller: Knowledge Economy in the Western Balkans

Page 1

TABLE OF CONTENTS

ABSTRACT ................................................................................................................................................................... 2

INTRODUCTION ................................................................................................................................3

1. KNOWLEDGE AS DRIVER IN THE ECONOMY................................................................................4

The components of a knowledge economy .................................................................................. 5

Macedonia, Serbia, and Western Balkan peculiarities ............................................................. 7

2. DETERMINANTS OF INNOVATION IN THE WESTERN BALKANS ................................................ 12

Methodology and data ................................................................................................................ 12

Assumptions ..................................................................................................................................... 16

Results ............................................................................................................................................... 16

3. PUBLIC POLICIES AND BUSINESS SOLUTIONS ........................................................................... 22

Why policy intervention? .............................................................................................................. 22

The way forward: direct enterprise support? ........................................................................... 24

CONCLUSION ................................................................................................................................. 28

BIBLIOGRAPHY ....................................................................................................................................................... 30

APPENDIX................................................................................................................................................................. 34

FIGURES

Figure 1: Map of Macedonia and Serbia ........................................................................................................... 8

Figure 2: Knowledge economy ranking Macedonia and Serbia .................................................................. 10

Figure 3: A simple knowledge economy function ............................................................................................. 12

Figure 4: Innovation production function ........................................................................................................... 13

TABLES

Table 1: Components of a knowledge economy ................................................................................................ 4

Table 2: Business environment and enterprise performance survey ............................................................. 13

Table 3: Descriptive data .................................................................................................................................... 14

Table 4: Probit models for the probability of undertaking innovation ....................................................... 17

Table 5: Probit models BEEPS 2005 .................................................................................................................. 18

Table 6: The Western Balkans in 2005 and 2009 ......................................................................................... 20


3/37

Page 2

ABSTRACT

A knowledge-based economy is an economy in which knowledge and knowledge-based technologies

and practices are used to produce economic benefits. The knowledge-based economy goes beyond

simply information and communication technology (ICT), otherwise referred to as information society,in that it also encompasses the key aspects of innovation (and R&D), education and the economic

incentive regime (rules and regulations in relation to incentivising entrepreneurship and innovation).

This MPA dissertation looks at the knowledge economy in the Western Balkans, in particular in

the Republic of Macedonia (henceforth referred to as Macedonia)and the Republic of Serbia

(henceforth Serbia). It seeks to provide an answer to the question of what viable solutions look like

for addressing the key challenges to develop and strengthen a knowledge-based economy in the

Western Balkans in general, and in these two countries in particular. Based on this research question,there are two main issues arising that are covered in turn in order to tackle the overall question:

1. What are the key economic challenges facing Macedonia and Serbia today inimplementing a successful knowledge-based economy strategy?

2. Based on these challenges, what are the key policy areas where Macedonia and Serbianeed to develop practical public policy or business solutions?

The paper will utilise the Business Environment and Enterprise Performance Survey by the

World Bank and European Bank for Reconstruction and Development (EBRD 2005; 2009) to identifydeterminants of innovation and, in conjunction with economic and literature analysis, provide an

answer to the first two questions. In its approach, following first attempts by Roper (2010),a bivariate

probit model of the innovation production function is used.

The paper will show that there are marked differences in the Western Balkan countries to

other European countries both with regards to determinants of innovation as well as potential solutions

to address the key challenges. Furthermore, it will show that focusing on direct enterprise support and

individual innovation production functions appear to be sensible micro solutions to address macrochallenges and indeed strengthen the overall knowledge economy. This can only be successful,

however, if accompanied by horizontal public policies focusing predominantly on strengthening

education and firm linkages with relevant knowledge creating and disseminating institutions, such as

universities, research centres, and chambers of commerce.


4/37


Page 3

INTRODUCTION

The paper is divided into the following three chapters:

1. Knowledge as driver in the economyThis chapter will outline the composition of the knowledge economy, differentiate between a

knowledge economy and a knowledge-based economy, and map out the peculiarities and

particular case of the knowledge-based economy in Macedonia and Serbia. The chapter will

be mainly based on the current academic literature on knowledge economy, on the innovation

production function and determinants of innovation, as well as regional-specific literature.

2. Determinants of innovation in the Western BalkansThis chapter will look in greater detail at Macedonias and Serbias knowledge economy and

its composition: using the econometric model, what are the determinants of innovation in theseeconomies and based on the current state of the economies in the fields of ICT, education, R&D

and rules and regulations what are thus the challenges for these two countries?

3. Public policies and business solutionsBased on the challenges identified in the previous chapter, this section will outline viable

strategies the two countries can follow that make economic and political sense. These policy

solutions will be based on the academic analysis.

The paper will then bring together all three chapters in a final section that includes concluding

remarks as well as an outlook in terms of further potential research and recommendations to go

forward.


5/37

Page 4

1. KNOWLEDGE AS DRIVER IN THE ECONOMY

The term knowledge economy does not have a clear-cut definition and in current literature it appears

that two concepts can be associated with it. One uses knowledge as a productknowledge economy

thus refers to an economy in which the aim is to produce knowledge as an end product. The othermeaning refers to knowledge as a tool that is used to contribute to the growth of the economy, or

produce economic benefit. The latter is sometimes also referred to as a knowledge -based economy.

In this dissertation attention is drawn solely on the latter concept of a knowledge-based economy. For

the sake of easier reference, both terms knowledge economy and knowledge-based economy are

used interchangeably here and are understood as described above in the sense of a knowledge-

based economy.

There are a number of key aspects that build a knowledge economy. While there is no onedefinition this paper adopts the variables identified by the World Bank, used in their knowledge

economy index (World Bank 2011). These variables roughly correspond with what the EBRD identified

in a recent Issues paper as well (EBRD 2011) as shown in table 1.

TABLE 1: COMPONENTS OF A KNOWLEDGE ECONOMY

EBRD (2011) World Bank (2011)

ICT ICT

InnovationInnovation1

R&D

Skills and human capital Education

Technology absorption capacity (e.g. FDI, trade)Economic Incentive Regime2

Related institutional and regulatory frameworks

This definition with the components above are largely in line with the definition of the

Organisation for Economic Co-operation and Development (OECD), that states that a knowledge-

based economy shows trends in advanced economies towards greater dependence on knowledge,

information and high skill levels, and the increasing need for ready access to all of these by the

business and public sectors. (OECD 2005) They further specify in regards to the context in which a

1The World Banks definition of innovation includes Research and Development (R&D)

2

This aspect encompasses a number of variables, such as tariff and nontariff barriers, regulatory quality, and rule of law.For a full list of variables and clustering see appendix.


6/37


Page 5

knowledge economy can be identified, summarising that both technology and the various types of

knowledge have become increasingly complex. Therefore, a new concept or component is mentioned,

namely that of networks or the inter-linkage between firms and other organisations, as a way to

acquire specialised knowledge (ibid.). While some of the above components, such as human capital

or innovation may not always be very straightforward to measure accuratelyin fact, for most cases

proxies will have to suffice, it is even more complicated for the network aspect. In the methodology

section in the next chapter we will dive further into this issue.

The components of a knowledge economy

A knowledge economy comprises five main components, four of which are identified by the World

Bank (most prominently in its Knowledge Economy Index; ICT, innovation, education, and the economic

incentive regime). One is added in this paper (networks), based on academic literature on innovation

and knowledge economy.

ICT: information and communication technology enables the effective creation, distribution,

and processing of information. The World Banks Knowledge Economy Index (KEI) measures telephones

per 1,000 people, computers per 1,000 people and Internet users per 10,000 people to arrive at a

composite measure of ICT usage in a society (World Bank 2011a).

Innovation: Roper (2010: 5) defines innovation as the process of introducing new products,

services or business models upon using new or existing knowledge. In detail, the innovation system

(Autio 1998; Metcalfe 1997) comprises three components: knowledge generation, knowledge

application, and linkages between the two. In the KEI, the World Bank uses the following three

variables to measure innovation: royalty and license fees payments and receipts, patent applications

granted by the US Patent and Trademark Office, and scientific and technical journal articles (World

Bank 2011a). These three variables encompass a certain aspect of innovation within a society, the

same way that measuring the proportion of new products at the firm level provides a snapshot of thewider picture. Hence, it would be best, if innovation were to be measured more wholesomely, to take

both approaches and combine them.

Education: a knowledge-based economy needs an educated workforce that possesses the

knowledge to drive the economy further, stimulate innovation and produce economic growth. An

underlying component, thus, is education and human capital. The KEI looks at: average years of

schooling, secondary enrolment, and tertiary enrolment (World Bank 2011a).


7/37

Page 6

Economic incentive and institutional regime: this component looks at the overall public

policies and laws in place that incentivise citizens to use existing and newly generated knowledge in

an efficient manner. It should also promote entrepreneurship and innovation. Three proxies used to

measure such an incentive regime are: tariff and nontariff barriers, regulatory quality, and the rule of

law (as used in the KEI; World Bank 2011a).

Networks:for a knowledge economy to function properly, knowledge needs to be created

and disseminated. It needs to be shared across the economy so that it can result in innovation. Roper

(2010: 5) terms it the social and interactive nature of the innovation process, and it is a well -

accepted view in the current literature that inter-organisational knowledge flows play a key role in

this (Chesbrough 2003; 2006). Recent developments in the Western Balkan region has seen an

increase in business, innovation and technology centres, as well as inter-firm clusters to transfer

knowledge (OECD 2009: 124-132). Networks, or the extent of cooperation and interaction, play a

key role for a successful knowledge economy (Gentzoglanis 2000: 8; Dobrinsky 2008; Cooke and

Morgan 1998); unfortunately, cooperation between science and industry remains rather weak in the

Western Balkan region (and emerging economies in general; Leskovar-Spacapan and Bastic 2007;

Simonen and McCann 2008).

Implications for the structure of the economy: All of the above implies that an economy that

is based on knowledge looks inherently different from an economy based on manufacture or the

service industry. For once, knowledge (and its generation, dissemination and access to it) becomes the

most valuable commodity. Hence, the creation of intellectual capital is increasingly deemed as the

most valuable asset of a firm (Gentzoglanis 2000: 2). The intangible assets of a firm are what

matters most, and which as a variable is most certainly the most difficult to measure3. At the same

time, the rising importance of innovation lets one believe that there must be a shift from large firms to

small ones, in particular entrepreneurial start-ups. This is true to a certain extent only.Knowledge

economies do not imply a shift in economic activity to small firms. They do imply that knowledge

based SMEs can thrive alongside large firms often in networked relationships. The composition of the

SME base and of self-employment is changing and changing at a faster rate than in the economy as

a whole. (London School of Economics 2011) At the same time it is crucial to acknowledge that the

majority of innovation comes indeed from small start-ups (Gentzoglanis 2000: 5).

3An approach Gentzoglanis (2000) takes is to consider the value of intangible assets incorporated into a firms value as a

way to measure the importance of intellectual capital. The theory goes that when the base in intangible assets increases,

the market value of a company grows. The author thus employs the Tobin Q ratio, measuring the ratio of the market

value to the replacement cost of capital. The paper confirms the theory, seeing that firms in knowledge-intensiveindustries showcase a higher Tobin Q ratio.


8/37


Page 7

Macedonia, Serbia, and Western Balkan peculiarities

In 2009, Macedonia was ranked 4thbest reformatory state by the World Bank (World Bank 2009).

Indeed, Macedonia has seen considerable efforts to modernise and transform its economy towards an

open and free market economy. More than 90% of the countrys GDP is accounted for by trade, and

active public policies have focused on attracting considerable amounts of FDI and supporting SMEs. At

the same time, unemployment has been rampant. Albeit with a decreasing trend, the figures are very

high: in 2009 the total unemployment rate stood at 32% (down from 37% in 2005, 35% in 2004)

(World Bank 2012b). Equally alarming are figures for poverty and the so called grey economy: the

2006 poverty rate was at 22%, indeed a high figure considering Macedonias location in Eastern

Europe. The economy has been plagued by corruption and a number of inefficiencies, such as a slow

and cumbersome legal system that is ultimately not effective. The grey market, according to estimates,

ranges between 20% and 45% of Macedonias GDP (CIA 2012). An immediately obvious challenge

is thus to transform employment from the grey market into official, legal employment (which now

distorts official unemployment rates upwards as they do not take into account the grey economy). In

tune with the statistics above, Macedonias GDP per capita stood at 36% of the EU average in 2010

(Eurostat 2011).

On a more positive note, Macedonia has been experiencing steady and healthy growth in its

IT market and achieved to be the fastest growing (+64%) in the Adriatic Region in 2007. That is a

hopeful statistic in terms of developing a knowledge economy. Further below we shall examine theindividual components of a knowledge economy for Macedonia.

Serbia, compared to Macedonia, has been performing slightly better on average, albeit its

GDP per capita stood at just 35% of the EU average in 2010, as compared to Macedonias 36%

(Eurostat 2011). Serbia is considered an upper-middle income economy and its economy has been

growing at about just above 8% in 2008, about double that of Macedonia (National Account

Statistics 2008). Unemployment is high at 17% (up from 14% in 2008, and down from 21% in 2005;

World Bank 2012b), but given the solid growth rates over the last few years, Serbia can indeed belabelled the Balkan Tiger. In terms of IT usage, just about half of the population own computers and

56.2% used the Internet in 2010, placing Serbia on top of all Balkan nations (Internet World Stats

2012).


9/37

Page 8

FIGURE 1: MAP OF MACEDONIA AND SERBIA

(Google Maps 2012)

How do the two countries fare in terms of the development of a knowledge economy? And

where does Macedonia and Serbia stand in terms of the individual knowledge economy components?

Both countries show an active interest in moving towards a greater knowledge-based economy, as

shown by several relevant public policies. The most notable effort for Macedonia has been the

National Strategy developed in 2004-2005 that emphasises on implementing public policies that

foster the ICT sector. According to a country-based manager of the European Bank for Reconstruction

and Development (EBRD), this effort, however, was met with a general lack of coordination in the

country, as well as all-encompassing redundancy to take a strategy and translate it into practical

work. She says: nothing was implemented, the strategy was defined but it is out-dated and with no

actual activity.4One indeed seeks in vain for actual results of the strategy. Another public policy is

the A Computer for Every Student Initiative, a joint initiative between the Government and a private

sector IT company. Ivo Ivanovsky, the Minister of Information Society refers to the project as the

4

The quotes are based on a personal interview conducted on 30. November 2011 with a country manager at the EBRDwho requested to remain anonymous.


10/37


Page 9

largest and most important education project undertaken in the 15-year history of the Republic of

Macedonia, with the goal to build a knowledge-based economy in which our entire workforce is

educated in using information and communication technology (PR Newswire). Besides the public sector

efforts to build a knowledge economy, there are two other notable actors that must be mentioned:

one is MASIT, the Macedonian ICT Chamber of Commerce that conducts a wide range of trainings and

networks to help develop the ICT sector, and fosters links with research institutes, universities and the

private sector. MASIT also has a dedicated training academy targeted solely at the private sector.

The second notable actor are international organisations, such as the EBRD or the German

development agency GIZ (formerly GTZ). The latter has been involved in a large ICT project in close

cooperation with MASIT and GOPA (a German development consulting firm) to promote the

Macedonian Software and IT Industry. The project is currently underway with the goals to increase the

international competitiveness of the national software industry, position it in export markets, providespecialised export promotion and training services (with MASIT), and achieve tangible results for the

industry and companies (GTZ 2010).

Serbias most notable public policy is its Innovation Serbia Project, funded by the EU Instrument

for Preaccession Assistance that began in 2011 (and is due to be completed in November 2014;

World Bank 2011b). Its goals are to develop and foster emergence of an innovative entrepreneurial

sector, to address elements that are missing in the national innovation system, and to improve the

general awareness that technological development and innovation play in the overall economy.Overall, the instruments used to address these issues are a combination of financial instruments,

capacity building, and technical assistance to R&D institutes in the country (Innovation Fund 2012).

Both Macedonia and Serbia, and the Western Balkan region as a whole, must be treated

separately from other European countries however. Indeed, current academic literature points out that

the Western Balkan countries show marked differences to other European countries both with regards

to determinants of innovation (being a key aspect of a knowledge-based economy; Roper 2010) as

well as potential solutions to address key challenges to further develop a knowledge economy

(Radosevic 2006). We shall now analyse the individual components of a knowledge economy in both

countries, which is then followed by the next chapter that looks at how exactly the Western Balkans

are different from its neighbours.


11/37

Page 10

FIGURE 2: KNOWLEDGE ECONOMY RANKING MACEDONIA AND SERBIA

Rankings taken from World Bank (2012)

The graph above shows how Macedonia and Serbia are positioned within the World Banks

Knowledge Economy Index, in which countries are ranked according to individual performance in each

components variables (see appendix for a breakdown of components). Both countries are roughly

within the top third of all countries (146 in total). Macedonias rank in 2012is 57 and Serbias is 49.

Comparing figures from 1995 to 2012 shows that the vast majority of components have increased in

their scoring. However, most components, such as ICT and innovation, experience a decrease in 2000,

but then recover or surpass the earlier levels from 1995 in 2009. The last two rows, KI (Knowledge

Index)and KEI (Knowledge Economy Index), are composite components. KI is a weighted total of

ICT, Education and Innovation, while KEI also takes into account the Economic Incentive Regime (fully it

is called the Economic Incentive and Institution Regime Index and comprises three variables: tariffand nontariff barriers, regulatory quality, and rule of law). Largest growth can be observed in the

economic incentive regime, which, despite only minor increases in the other components, is a good

indication for a growth potential for both countries as a knowledge-based economy. It means that

both countries are developing economic incentives so that a knowledge-based economy can be fully

developed, supported and maintained. The economic incentive regime is a pre-requisite for all other

aspects to flourish and is therefore a crucial underlying component in a knowledge-based economy.

0 5 10

KEI

KI

Economic IncentiveRegime

Innovation

Education

ICT

Macedonia

Global Rank (2012): 57

0 5 10

Serbia

2012

2009

2000

1995

Global Rank (2012): 49


12/37


Page 11

While both countries have progressed further towards more comprehensive and nation -wide

enterprise policy implementation (OECD 2009: 15-16), and while there is a general positive outlook

on start-up opportunities in the region (Global Entrepreneurship Monitor 2008)5, there are certainly

specific weaknesses that can be identified. One for Macedonia is certainly innovation, showing the

lowest score in its KEI in both 2009 and 2012. This can be confirmed by the literature that emphasise

inherent weaknesses in the innovation system of Macedonia, both institutionally and structurally

(Polenakovik and Pinto 2009). Serbia has been struggling, relative to its other components, with the

economic incentive regime. While there have been marked improvements between 2000 and 2009,

the country is on the right track in terms of providing better policies for incentivising entrepreneurial

and innovative activity, as evidenced by its 2011 Innovation Serbia Project.

5

In 2008, 56% of adults perceived good opportunities for start-up in the next six months in Serbia (compared to 47% inMacedonia and 48% in the USA)


13/37

Page 12

2. DETERMINANTS OF INNOVATION IN THE WESTERN BALKANS

In order to provide a sensible answer to the question of what policies should be favoured to advance

a knowledge economy, it is indispensible to look at what drives innovation. Innovation certainly is a

key component in a knowledge economy. Growth in a knowledge economy depends on a firmscapacity and, overall, the nations capacity to convert rapidly the knowledge into valuable new

products with a high value-added content (Gentzoglanis 2000: 14), hencedescribing innovation6.

Following this widely accepted theory that innovation is a key driver in a knowledge economy, this

chapter seeks to explore what the determinants of innovation are.

The components that have been identified above that make up a knowledge economy, and

hence contribute to growth of the economy and knowledge access, dissemination and creation, may all

or partly be determinants of innovation themselves as well. If we thus want to explain growth in aknowledge economy as a function of all five components (as illustrated in the figure below), we may

have a considerable measurement error given that, for instance, the creation of networks is already

implicitly measured through the innovation variable. This is why this section dives into the determinants

of innovation so to be able to identify specific areas that need to be addressed in a potential policy

solution.

FIGURE 3: A SIMPLE KNOWLEDGE ECONOMY FUNCTION

= + + + +

But: = , , , ?

Methodology and data

The methodology employed in this paper follows an attempt by Roper (2010), in which the author

utilises a joint survey by the World Bank and the EBRD, called the Business Environment and Enterprise

Performance Survey (or BEEPS in short). According to the EBRD (2010), BEEPS objective is to gather

feedback on the state of the private sector [and to build] a panel of enterprise data that will make

it possible to track changes in the business environment over time. The survey has been carried out

four times so far: in 2000, 2002, 2005, and 2009.

6

This is especially true in the five key industrial sectors, namely computers, telecommunications and information,medical equipment, pharmaceuticals and biotechnology, and semiconductors (Gentzoglanis 2000: 14).


14/37


Page 13

TABLE 2: BUSINESS ENVIRONMENT AND ENTERPRISE PERFORMANCE SURVEY

Year Number of enterprises surveyed In number of countries

2000 4,000 enterprises 26 countries

2002 6,500 enterprises 27 countries2005 9,500 enterprises 28 countries

2009 11,800 enterprises 29 countries7

The countries surveyed are in the EBRDs region of operation, which covers Eastern Europe,

Central Asia, and the Western Balkans. Roper (2010) uses the 2005 data and the so called

innovation or knowledge production function (Griliches 1992; Love and Roper 1999; Roper 2010) as

shown in the figure below.

FIGURE 4: INNOVATION PRODUCTION FUNCTION

= + + + + +

Where is an individual firm, Iiis an innovation output indicator, FC iis a set of firm-specific

characteristics, LMiis a set of location and market specific characteristics, PSiindicates public support,

ODiare firm specific operating difficulties, and is the error term. The methodology used in this

paper replicates Ropers effort but differentiates itself in two ways: one, it uses BEEPS 2009 which

provides both a point of comparison to the data in 20058and a way of highlighting potential

concerns in the methodology used, and two, additionally looks specifically at Macedonia and Serbia

in comparison with the Western Balkans9and the other neighbouring countries, grouped as CEEE

(Central and Eastern European Economies, excluding WBC)10and CIS (Commonwealth of Independent

States)11.

7The 2009 BEEPS covers: Albania, Belarus, Georgia, Tajikistan, Turkey, Ukraine, Uzbekistan, Russia, Poland,

Romania, Serbia, Kazakhstan, Moldova, Bosnia and Herzegovina, Azerbaijan, FYR Macedonia, Armenia, Kyrgyz

Republic, Mongolia, Estonia, Kosovo, Czech Republic, Hungary, Latvia, Lithuania, Slovak Republic, Slovenia, Bulgaria,

Croatia, and Montenegro.8All BEEPS data in this paper that refer to the year 2005 are taken directly from Roper (2010). All BEEPS data that refer

to the year 2009 are taken directly from BEEPS 2009 by the author of this paper.9The WBC consist of Albania, Bosnia and Herzegovina, Croatia, Serbia, Kosovo, Montenegro, and Macedonia

10Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Hungary, Romania, Bulgaria, and Slovenia

11

Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyz Republic, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine,and Uzbekistan


15/37


16/37


Page 15

In 2005, only 39.3% of firms in the Western Balkans responded yes to the question has this

establishment introduced new products or services in the last 3 years? (Indicator new product.) In

2009, this number rose to almost 58 per cent in the region, and even 61 per cent in Macedonia and

Serbia combined. The indicator on improved product or service (measuring whether a firm has

upgraded an existing product or service within the last three years) is above 70 per cent across the

region, a rise in more than 40 percentage points on average, although this may be due to differences

in measurement. What the data on innovation shows is that the Western Balkans are slightly above the

countries in CEEE and CIS, which follows a similar trend in 2005.

On top of innovation data, the dataset includes a variety of other variables that are worth

looking at. These are firm characteristics such as plant age, which may provide an indication as to the

potential for cumulative accumulation of knowledge capital by older establishments (Klette and

Johansen 1998). Firm size (employment) and skill level (workforce with graduate qualifications) also

provide insights into absorptive capacity and the hypothesis is thus for these variables to be positively

correlated with an innovation output variable. Interestingly, while firm size was larger in the Western

Balkans in 2005 (108 compared to 83 and 95 in CEEE and CIS respectively), this is no longer the case

in 2009 (82 compared to 116 and 145 in CEEE and CIS respectively). Macedonia and Serbia,

however, come closer to the average in CEEE and CIS with 113. Skill levels in both the Western

Balkans in general, and in Macedonia and Serbia in particular, are rather low, especially compared

to CIS (13.5 in WBC compared to 31.9 in CIS in 2009).

In terms of firm ownership, comparative trends between the regions have stayed the same

between 2005 and 2009. What has changed considerably, however, is the breakdown of types of

ownership throughout the entire dataset. Most notably, limited companies have a considerable bigger

share compared to 2005 and both partnerships and single proprietors declined. Other variables

(location and markets and public support) are included to account for differences in the operating

environment of the companies surveyed. A proxy used for potential access to knowledge centres and

resources, such as universities or research institutes, is whether a firm is located in a capital or large

city (Asheim and Isaksen 1996). While this is by no means a precise proxy, it may give an

approximate hint as to whether or not the potential access (since universities, research centres, skilled

labour etc. are more likely to be in larger cities and the capital cities) does in fact (positively)

correlate with innovation output, and confirm the assumption that greater linkages and networks are

correlated with a greater likelihood to innovate.


17/37

Page 16

Assumptions

The assumptions underlying this paper are that at least some (aspects of the) components that form

part of a knowledge economy are determinants of innovation, and therefore, if we would like to

explain how a knowledge economy can grow and be strengthened, we need to understand what

these determinants look like, in what way they influence innovation (positive or negative correlation)

and whether it is a general phenomenon (experienced across the entire region) or a specific one for

Macedonia and Serbia (or the Western Balkans).

Using the bivariate innovation production function for the dataset of 2009, this paper can

compare results with those results obtained using data from 2005. Given the significant results in the

2005 dataset, this paper predicts to obtain similar results in terms of overall trends and significance.

Hence, firm vintage and firm size should positively correlate with innovation, high skills are expected

to also contribute to new product development. Similarly, a proxy for access to knowledge and

networks (location in a large city or capital) would positively influence innovation, as well as,

potentially subsidies. The latter follows from the theory that state intervention and policy support, most

dominantly because of assumed market failure, does have a direct and good impact on innovation

(Dobrinsky 2008; Griliches 1995; Czarnitzki and Licht 2005; Mamuneas and Nadiri 1996; Hewitt-

Dundas and Roper 2009).

Results

Tables 4 and 5 below summarise the significant and non-significant results from this papers regression

models.


18/37


19/37

Page 18

TABLE 5: PROBIT MODELS BEEPS 2005

Source: Roper (2010: 19)


20/37


Page 19

Results 2009: as predicted in the assumptions made above in this paper, the size of the firm

(employment) has a statistically significant, albeit only marginally small, positive effect on innovation

(for all models, with the exception of WBC) and a slightly larger effect in Macedonia and Serbia

compared to the other regions. Possessing a workforce that has attended university shows a small

positive increase in probability to innovate in the CEEE and CIS economies, however not so in the

Western Balkans, including Macedonia and Serbia. This is counter-intuitive and contrasts with other

literature (see for example Freel 2005), but confirms results found in 2005. In terms of a firms current

legal status, only privately held limited liability companies have a significant negative effect on

innovation. If companies export any share of their products into foreign markets, it is correlated with a

significant positive relationship across all regions. This strong relationship (increasing the probability to

innovate by 46% in Macedonia and Serbia, and 49% in the Western Balkans) confirms the theory of

a crucial relationship between innovation and export activity (Bleaney and Wakelin 2002). It appearsthat this can confirm the theory that exposure to the export market is more important than external

ownership in terms of influencing innovation capability as brought forward by Filatotchev et al.

(2003). A firm that was set up as originally private from time of start-up is also more likely to have a

higher probability of undertaking innovation (with the exception of CIS). This effect is highest in

Macedonia and Serbia and lowest in the CEEE region.

Location of a firm has no effect, which is in contrast to what has been predicted. The closest to

statistical significance is the CIS group (with a 7% positive effect), which in 2005 had the samepositive effect but was indeed statistically significant. It may well be that location as such is not a

good enough proxy to determine networks, access and links to and with universities, research centres,

etc. However, as predicted, public support also increases the probability to innovate across all

regions. Interestingly, this effect is not significant for Macedonia and Serbia as a group alone. In terms

of operating difficulties, we see a positive relationship between customs and trade regulation as well

as skills and education, which may be due to reverse causality. This resul t is not uncommon in other

innovation studies (Roper 2010: 12) and may be due to innovating firms struggling more with skill

constraints.

Results 2005:comparing the results above with results obtained from the dataset in 2005 one

can see some similarities and some striking differences. While Macedonia and Serbia were not

analysed separately, the three other groups can be compared to each other. The overall differences

to the 2009 results are as follows: employment has no significant effect, a limited company has a

positive rather than a negative effect, exporting has a smaller positive effect, an initially privately set

up firm at start-up has no effect, and public support is only significantly positive in the CEEE region.


21/37

Page 20

The table below further contrasts differences in the Western Balkans between 2005 and 2009.

TABLE 6: THE WESTERN BALKANS IN 2005 AND 2009

Indicator12 2005 2009

Employment 0.06% (MK, RS)

Single proprietor -32.4%

Limited company -30.4%; -31.1% (MK, RS)

Exporting firm 7.9% 48.8%; 45.8% (MK, RS)

Private start-up 57.1%; 63.1% (MK, RS)

Joint venture with ext. partner -71%

Public support 37.9%

Customs and trade difficulties -10% 24.6%; 31.4% (MK, RS)

Skills difficulties 9.9% 29.5% (MK, RS)

Functioning of judiciary 7.7%

It appears that, in 2009, a higher probability of innovating is associated with a firm that

exports, was private at the time of start-up, and is publicly supported. At the same time, higher

innovation is also correlated with higher customs and trade difficulties and obstacles experienced in

relation to limited skills. The latter two can both be explained as a type of reverse causality, where

higher innovation may lead a firm to realise that the perhaps previously sufficient level of skills is no

longer adequate, and given that most innovating firms export there may be a natural obstacle with

customs and trade.

One also has to keep in mind that the location of a firm (in a larger city or capital) turned out

to be non-significant, both in 2005 and 2009. Since the literature unequivocally suggests that the

network aspect of innovation is a key determinant, we must come to the conclusion that location alone

is not a good enough proxy to measure linkages and networks. Some of the literature goes so far as

to say that knowledge accumulation and [the] innovation process are better explained though

through the creation of networks, the establishment of inter-relationships and feedback procedures

with the firms clients, suppliers, competitors, government and Universities and research institutes.

(Gentzoglanis 2000: 8) Hence, the model presented above may very well suffer from omitted

12

Showing only statistically significant indicators, at 10%, 5% or 1% level; empty cells are non-significant in thatparticular year.


22/37


Page 21

variable bias, which distorts the results. We therefore have to be very careful in how we interpret the

results.

In terms of the next chapter, potential policy solutions, this has been taken into account in that

significant results do inform the chapter, however the magnitude of these results is interpreted withcare. In the following, cross-checks with the current literature on the topic is undertaken so to avoid too

heavy reliance on the results from above and come to proposed solutions based on a balanced

middle-ground between the 2005 and 2009 results as well as other literature.


23/37

Page 22

3. PUBLIC POLICIES AND BUSINESS SOLUTIONS

Some of the literature suggests that introducing innovative business tools and enhanced technological

processes within firms, as well as support in general of innovative firms, is the way forward for the

Western Balkans (see for example Roper 2010; Radosevic 2006). Direct enterprise support, with aspecific focus on knowledge as a tool, does in fact present a solution to the key economic challenges

of the Western Balkans to develop and strengthen their knowledge economies. It is this approach that

is favoured by international organisations and governments alike: the European Bank for

Reconstruction and Development (EBRD) focuses on direct enterprise support, introducing management

best practices, new business tools and knowledge sharing enhancing tools, as well as careful

investments into the innovation and ICT sector, which is due to be promoted even further in line with a

new multi-pronged approach to ICT and the knowledge economy (EBRD 2011). The GIZ focuses on

improving businesses capacity directly in Macedonia, and Serbia is seeking to develop an innovative

entrepreneurial sector working closely with enterprises via technical assistance.

Utilising the innovation production function in analysing micro solutions for macroeconomic

challenges elucidated the regional particularities as opposed to a blueprint and generically

applicable approach to developing a knowledge-based economy. We have seen a number of

Western Balkan peculiarities, and particular challenges for both Macedonia and Serbia.

Why policy intervention?

There are three key underlying reasons for the state to intervene in the market: 1. The invisible hand

does not work properly, 2. Steer the economy into a certain direction to support objectives such as

economic development and social justice, 3. Good intentions. (Maluste 2011)

The first reason rests on the assumption that there are market failures, which create distortions,

giving the government legitimacy to intervene with targeted public policies. Furthermore, the

government may introduce policies to achieve objectives of social justice and growth, when otherwise

the market does not naturally support these objectives of reducing inequality, education,

infrastructure, improved standards of living or a better health system. Lastly it may be the goal of the

government to serve its people or catch up with competitors (that is, surrounding economies) in

particular sectors such as ICT or export capacity in this case.

The first chapter has shown that what matters most for a knowledge-based economy is that

first of all the creation of networks highly matters. Then, education (that is, skills and human capital) is

integral for appropriate knowledge creation and dissemination. Lastly, start-ups (entrepreneurial


24/37


Page 23

firms) require public support in Macedonia and Serbia, based on inadequate access to finance and

lacking management skills to transform an entrepreneurial management style into a sustainable

management of a larger firm. Macedonia suffers particularly from a poor state of education, low

innovation in general, corruption, and a large unemployment rate, which is highly related to the big

shadow economy. Serbia is particularly low performing in its economic incentive regime, lacking the

overall policy incentives for firms to be entrepreneurial and innovative. The workforce in both

Macedonia and Serbia of university educated employees, as captured in BEEPS, is well below that of

the rest of the region, and public support as percentage of all locally owned firms also falls short

relative to firms in the Western Balkans and the overall Central and Eastern European region (see

table 3). However, while positioned at the low end of the top third of countries in regards to the

ranking of the knowledge economy index, both Macedonia and Serbia have a long way to go to

improve all aspects relevant: education, ICT, innovation (including R&D) and the economic incentiveand institutional regime.

Further hints with regards to peculiarities in Macedonia and Serbia have been highlighted by

the results of a probit model using the BEEPS survey in chapter two. The key findings are that

innovation is positively and significantly correlated with enterprises that:

1. Export outside the domestic market2. Have a larger workforce3. Are publicly supported, either from government or international institutions (such as the EU)4. And are privatised firms, most dominantly from the start-up already

As has been established above, there is a clear need for policy support to enterprises to

further develop innovation capacity, capability, gain better access to knowledge and be able to

disseminate it, focus on research and development, and possess the right international quality

standards and certifications, as well as the knowledge and network, to be able to export to foreign

markets. If this policy support is not provided, in the context of the market failure of Macedonia and

Serbia, there will be an underprovisionof entrepreneurial activity in diversification activities and/or

innovation entrepreneurship (Dobrinsky 2008). Since the private cost of establishing an

entrepreneurial firm, and ICT innovation, seems to outweigh the social gain (therefore rendering it too

expensive to innovate), the underprovision of such innovation activity occurs. As a result, Macedonia

and Serbia suffer from a low score in the knowledge economy index and general low scores, in

relation to its neighbours and highly industrialised countries, on innovation variables in BEEPS (EBRD

2009; 2010).


25/37

Page 24

However, providing direct enterprise support brings about two potential risks that must be

mitigated in order to not distort the economy and create the public equivalent to a market failure, a

public sector failure if you will. One is crowding out: this must be taken into account and is indeed a

high risk that occurs when government does not carefully select the recipients of its support. Where

good market access to finance exists, there should be no incentive for the public sector to support an

enterprise with better rates, thereby crowding out and distorting the free market. In fact, public

support does not necessarily have to take the form of financial support, and Dobrinsky (2008) even

concludes that the role of the public sector is not in providing financing support but in systemic

coordination and facilitating linkages between potential key stakeholders.

The second risk is the danger of piecemeal (Roper 2010a), which refers to the phenomenon

of supporting individual enterprises and thereby not achieving a systemic effect that impacts the

wider regional or national economy. While direct enterprise support may indeed help propelling an

individual firms performance and growth, there may notalways and inherently be spill-over effects

onto the economy. Spill-overs that are particularly relevant here are that of knowledge dissemination

and sharing, creation of networks, and the dissemination of innovation that benefits the wider

economy. Direct enterprise support therefore has to focus on supporting the capacity and capability

to foster innovation, with all associated components that form part of the knowledge-based economy.

In the case of both Macedonia and Serbia, however, crowding out is not an immediate

concern, albeit one that should not be forgotten about. In the Serbian innovation study conducted in

the period between 2004 and 2006, the Republic Statistics Office of Serbia in cooperation with the

Mihailo Pupin Institute found that the most important restricting factor of innovation is lack of

financial support from public funds (the second most pressing issues for enterprises, as stated by

34.16% of respondents), thereby making it clear that better financial support is indeed a requirement

(Ministry of Economy and Regional Development 2008: 112). Until the private sector catches up in

being able to match the supply to the demand, the government (and international organisations)

ought to step in to provide much needed financing.

The way forward: direct enterprise support?

There is a strong positive relationship between investment in intangibles and overall average growth

rates (Gentzoglanis 2000; Summers and Heston 1991). Investments in intangibles lead to innovation,

and Gentzoglanis (2000: 13) shows that the overall rate of return for some 17 successful innovations

[] in the U.S. averaged 56%, a promising figure.


26/37


Page 25

Research and development (R&D) is an important component in a firms process towards more

innovation and knowledge sharing. However, there are a few issues with regards to R&D that need to

be taken into consideration. Firstly, as Roper (2010; 2010a) concludes, R&D does not have a

significant role as driver of innovation in the Western Balkans. This is indeed contrary to other

countries in Central and Eastern Europe, and also the more industrialised countries in Western Europe.

Therefore, by supporting R&D through subsidies, channelled financing or tax relieves, it is questionable

whether innovation would actually increase. The key issue in the Central and Eastern European

countries in relation to knowledge creation and absorption does not lie in the push factors but rather

the pull factors: firms exhibit a low level of innovative behaviour and there is weak demand from the

economy (Orlowski 1999). Therefore, an arbitrary increase in public sector support of financing R&D

does not really solve the problem. A proper solution needs to address the underlying issues to create

the right activities and growth. Orlowski (ibid.) thusly concludes that more structural and horizontal,macro-level policy options are required to address the core of the problem, namely firm sector

demand.

Such a solution could be comprised of a lowering of taxation levels, which in turn can

encourage investments, and a general move towards a more open economy in which competition of

the market is strengthened and increased. The policies of [] effective privatisation, restructuring,

and de-monopolisation should be strengthened and accelerated. (ibid.) On the other hand, as

elucidated above, the risk of a public-sector equivalent market failure can emerge at worst. AnotherR&D specific risk can, however, also emerge as a result of a non-market approach, which is that

research is being produced that is not economically viable or actually relevant for the market. It is

therefore crucial to take into account the efficiency at which the research funding is carried out with.

Furthermore, by supporting R&D institutes specifically, two goals can be achieved which is on the one

hand strengthening the private sector and competition (creation of [a] competitive R&D market will

also help in improving the offer that the domestic R&D sector delivers to the domestic economic

agents, [and] demand may be also stimulated; Orlowski 1999). On the other hand, it support the

creation of networks and inter-linkage within the economy, a key aspect to a knowledge economy, as

has been emphasised multiple times throughout this paper.

Currently, as has been shown in chapter two and in line with conclusions by Roper (2010;

2010a), public support for research and development is quite limited, albeit developing. While in

2005, no significant effect can be found that public support correlates with a higher likelihood to

innovate, the results from 2009 suggest otherwise. The latter proves that additionality of public

support is indeed in line with evidence from industrialised economies.


27/37

Page 26

Overall, this paper recommends five key aspects to further develop and strengthen a

knowledge economy in Macedonia and Serbia.

1. Improve management quality and skillsThis point refers to a particular aspect of the business environment in which an enterprise is

operating. As we have seen above, innovation comes about most dominantly in entrepreneurial start-

ups and small, newly created firms. There is a tangible risk that entrepreneurial activity misses its

transition to transform itself into a well-managed larger firm. This recommendation is therefore

twofold: one, entrepreneurial activity is not enough without management capacities and the

availability of venture capital and markets that reward risk. Many start-ups fail because their owners

are unable to make the transition from entrepreneurs to managers. (Gentzoglanis 2000: 6)And two,

generic skills within management of the firm need to be developed and strengthened to support theconversion of knowledge into actual valuable products.

2. Link with networksSupporting networks is both an activity that needs to be undertaken at the enterprise level as

well as a structural level. This point refers to direct support within an enterprise to build relationships.

This can be done for instance in the form of establishing new business partners, preferably abroad,

which can also help in the next point of creating markets for export. Business matching trips are

another way to create networks, either within the country or in the region. It remains to be said that

knowledge creation and access is crucial, and as such networks help with this. Innovation can only

occurs based on information provided within the enterprise itself or the group it belongs to. (Ministry

of Economy and Regional Development 2008: 112)

3. Help export and privatiseThroughout this paper it has been established that exporting firms are much more likely to

innovate (see for example Bleaney and Wakelin 2002). In fact, it may even be the case that the

exposure to the export market is more important than external ownership in terms of influencing the

innovation capability of a firm (Filatotchev et al. 2003). At the same time, the empirical results in

chapter two have confirmed that exporting does play a crucial role, as well as privatisation of firms.

This point thus stresses the importance of assisting enterprises in their capacity and capability to be

able to focus sales on international markets, and to gain proper certifications and quality standards

to be able to export, particularly into the EU for instance.


28/37


Page 27

4. Align the business environment with international best practicesThis point refers to the wider business environment, not solely focused on turning around

management practices as elucidated in point one above. As was seen in chapter two, the business

environment negatively affects innovation outputs (Roper 2010; 2010a). Also, in general, there is acase for more innovating firms that more obstacles to skills and trade are experienced. Albeit

showcasing a higher level of innovation, something needs to be done to mitigate these obstacles. The

recommendation is therefore to align business practices to those that are internationally recognised as

best practices.

5. Focus on horizontal policies to support the aboveAs we have shown above in this chapter, direct enterprise needs to be supported by more

general, macroeconomic and structural public policies to affect a sustainable solution and steady

growth through a knowledge-based economy. In particular, such a horizontal public policy ought to

encompass three components: rule of law, networks, and education.

Rule of law refers to the economic incentive and institutional regime, in which it is imperative to

have business-friendly and entrepreneurial-friendly laws in place to incentivise entrepreneurs to start

a business. A part of this is for instance reducing the number of steps required to open a new

business13, which is particularly relevant for Serbia. Creating, maintaining and supporting new

networks is another aspect required for innovation (Muller 1999: 100; Nelson 1999): Innovation

requires interaction and technological cooperation among firms and access to new knowledge through

collaborative networks (Dobrinsky 2008). This is in line with other authors, emphasising on the

importance of a creation of networks (Gentzoglanis 2000) and stressing that collaborative

innovation works best (Roper 2010a).This can be done for instance by supporting horizontally

targeted workshops through chambers of commerce or international organisations events.

Lastly, education of a society is another key component, and the safest way of channelling

additional public funds [to] promote knowledge-led growth (Orlowski 1999). What remains to benoted, however, is that investment into education produces a slow response, rather than a fast big-

bang result. Focus needs to be put on increasing the number of students and improving the quality of

education, while emphasising the need to cooperate with the private sector to meet the needs of the

market. This then produces knowledge that is required by the market and qualified students that can

find employment in the private sector, supporting the growth of a knowledge-based economy.

13Macedonia is ranked number 22 for ease of doing business and number 6 for starting a business, out of 183

economies. Serbia is ranked number 92 for ease of doing business and also number 92 for starting a new business, outof 183 nations. This is according to the World Banks Doing Business survey (World Bank 2012c).


29/37


30/37


Page 29

differences in its results and only very few commonalities. It is unlikely, however, that within four years

between the dataset of 2005 and the newer one of 2009 all firms have so radically changed that

innovation is now associated with completely different determinants, or some of the same

determinants but showcasing correlations in the opposite direction (such as obstacles to trade, with a

negative correlation in 2005 but a positive one in 2009). This is a case where one needs to carefully

analyse what variables need to be included to avoid distortion by omitted variable bias. Further,

some variables are bad proxies, such as locationfor access and linkage to networks.

For the sake of this paper, and assessing and devising generic policy recommendations, the

above-utilised model was sufficient to provide general trends in terms of innovation determinants.

Again, no causality can be assumed and the results were taken in an informative rather than

authoritative manner. However, much more can and ought to be done and this paper thus serves as a

stepping-stone for further research into this matter.


31/37

Page 30

BIBLIOGRAPHY

ADB (2007), Moving Toward Knowledge-Based Economies: Asian Experiences, Technical Note, Regional and Sustainable

Development Department, September 2007,http://www.adb.org/documents/reports/technical-notes/knowledge-

based-economies/knowledge-based-economies.pdf,accessed 13 September 2011

Asheim, B., and Isaksen, A. (1996), Location, agglomeration and innovation: Towards regional innovation systems in

Norwat, in: Studies in technology, innovation and economic policy, Report 13, Oslo

Barkham, Patrick (2008), What is the knowledge economy?, in: The Guardian, 17 July 2008,

http://www.guardian.co.uk/business/2008/jul/17/economics.economicgrowth,accessed: 13 September 2011

Bleaney, M., and Wakelin, K. (2002), Efficiency, Innovation and Exports, Oxford Bulletin of Economics and Statistics 64

Chesbrough, Henry (2003), Open Innovation: The New Imperative for Creating and Profiting from Technology, HBS Press

Chesbrough, Henry (2006), Open Business Models: How to Thrive in the New Innovation Landscape, HBS Press

CIA (2012), World Factbook: Macedonia,https://www.cia.gov/library/publications/the-world-factbook/geos/mk.html,

April 3 2012, accessed: 12 April 2012

Cooke, Philip and Morgan, K. (1998), The associational economy: Firms, regions and innovation, Oxford University Press

Cooke, Philip (2002), Knowledge economies: clusters, learning and cooperative advantage

Czarnitzki, D., and Licht, G. (2006), Additionality of public R&D Grants in a Transition Economy, Economics of Transition

14: 101-131

Dobrinsky, Rumen (2008), Knowledge-Oriented Diversification Strategies: Policy Options for Transition Economies,

Presentation by UN Economic Commission for European Economic Cooperation and Integration Division,

http://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.

pdf,accessed: 12 September 2011

Dolfsma, Wilfred (2008), Knowledge economies: innovation, organization and location

EBRD (2010), Business Environment and Enterprise Performance Survey, 29 April 2010,

http://www.ebrd.com/pages/research/analysis/surveys/beeps.shtml,accessed: 12 March 2012

EBRD (2011), A Multi-Pronged Approach to ICT and the Knowledge Economy, Draft Issues Paper, 20 June 2011Eurostat (2011),http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-13122011-BP/EN/2-13122011-BP-EN.PDF,

accessed: 10 April 2012

Filatotchev, L., M. Wright, K. Uhlenbruck, L. Tihanyi, and R. E. Hoskisson (2003), Governance, organizational capabilities,

and restructuring in transition economies, Journal of World Business 38

Freel, M. (2005), Patterns of innovation and skills in small firms, Technovation 25: 123-134

Gentzoglanis, Anastassios (2000), Les defis pour le travail a l'ere des technologies de l'information - Innovation and

Growth in the Knowledge-based Economy, University of Sherbrooke, Department of Economics, and Centre for the

Study of Regulatory Economics and Finance (CEREF), Quebec, Canada
http://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdfhttp://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdfhttp://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdfhttp://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdfhttp://www.guardian.co.uk/business/2008/jul/17/economics.economicgrowthhttp://www.guardian.co.uk/business/2008/jul/17/economics.economicgrowthhttps://www.cia.gov/library/publications/the-world-factbook/geos/mk.htmlhttps://www.cia.gov/library/publications/the-world-factbook/geos/mk.htmlhttps://www.cia.gov/library/publications/the-world-factbook/geos/mk.htmlhttp://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.pdfhttp://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.pdfhttp://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.pdfhttp://www.ebrd.com/pages/research/analysis/surveys/beeps.shtmlhttp://www.ebrd.com/pages/research/analysis/surveys/beeps.shtmlhttp://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-13122011-BP/EN/2-13122011-BP-EN.PDFhttp://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-13122011-BP/EN/2-13122011-BP-EN.PDFhttp://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-13122011-BP/EN/2-13122011-BP-EN.PDFhttp://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-13122011-BP/EN/2-13122011-BP-EN.PDFhttp://www.ebrd.com/pages/research/analysis/surveys/beeps.shtmlhttp://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.pdfhttp://www.un.org/en/development/desa/policy/publications/general_assembly/eitconference/4aprpm_dobrinsky.pdfhttps://www.cia.gov/library/publications/the-world-factbook/geos/mk.htmlhttp://www.guardian.co.uk/business/2008/jul/17/economics.economicgrowthhttp://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdfhttp://www.adb.org/documents/reports/technical-notes/knowledge-based-economies/knowledge-based-economies.pdf


32/37


Page 31

Griliches, Z. (1995), R&D and Productivity: Econometric Results and Measurement Issues. Edited by P. Stoneman, Handbook

of the Economics of Innovation and Technological Change, Oxford: Blackwell

GTZ (2010), Promotion of the Macedonian Software / IT Industry, Project Planning Workshop, internal Powerpoint

presentation, June 2010, Skopje, Macedonia

Hewitt-Dundas, N., and Roper, Stephen (2009), Output Additionality of Public Support for Innovation: Evidence for Irish

Manufacturing Plants, European Planning Studies

Innovation Fund (2012), Innovation Serbia Project,http://www.innovationfund.rs/innovation-serbia-project/,accessed: 26

February 2012

Internet World Stats (2012), Internet World Statistics,http://www.internetworldstats.com/europa2.htm#rs,accessed: 12

April 2012

Klette, T., and Johansen, F. (1998), Accumulation of R&D Capital and Dynamic Firm Performance: a not-so-Fixed Effect

Model, Annales de Economie et de Statistique 49-50: 389-419

Leibold, Mariues (2002), Strategic management in the knowledge economy: new approaches and business applications

London School of Economics and Political Science (2011), Kuwait and the knowledge economy,

http://www2.lse.ac.uk/government/research/resgroups/kuwait/research/projects/knowledgeeconomyproject.aspx,

accessed: 16 August 2011

Loof, Hans (2002), The Knowledge Production Function, Evidence from New Micro Data, Essays in the Economics of

Innovation, Department of Industrial Economics and Management, Royal Institute of Technology, Stockholm, Sweden

Lundvall (2002), The New knowledge economy in Europe: a strategy for international competitiveness and social cohesion

Maluste, Dr Rajiv G (2011), Industrial Policy in Developing Countries, Powerpoint Presentation, Lecture at the London

School of Economics in MN425 Business in the Global Environment, 28 November 2011

Mamuneas, T. P., and Nadiri M. I. (1996), Public R&D policies and cost behaviour of the US manufacturing industries,

Journal of Public Economics, 63, 57-81

Metcalfe, S. (1997), Technology Systems and Technology Policy in an Evolutionary Framework, Edited by D. Archibugi,

Michie, J, Technology, Globalisation and Economic Performance: Cambridge University Press

Ministry of Economy and Regional Development (2008), Report on Small and Medium-Sized Enterprises and

Entrepreneurship 2007, Serbia

Muller, Karel (1999), Knowledge Based Society and its Socio-Cultural Pattern: Situation of Post-Socialist Countries, in: The

Knowledge-Based Economy, the European Challenges of the 21stCentury, State Committee for Scientific Research,

Republic of Poland

National Account Statistics (2008),www.Webrzs.stat.gov.rs,30 June 2008.

Nelson, R. (1992), National Innovation Systems: a Perspective on a Study, in: Industrial and Corporate Change, Vol. 1, No.

2: 347-374
http://www.innovationfund.rs/innovation-serbia-project/http://www.innovationfund.rs/innovation-serbia-project/http://www.innovationfund.rs/innovation-serbia-project/http://www.internetworldstats.com/europa2.htm#rshttp://www.internetworldstats.com/europa2.htm#rshttp://www.internetworldstats.com/europa2.htm#rshttp://www2.lse.ac.uk/government/research/resgroups/kuwait/research/projects/knowledgeeconomyproject.aspxhttp://www2.lse.ac.uk/government/research/resgroups/kuwait/research/projects/knowledgeeconomyproject.aspxhttp://www.webrzs.stat.gov.rs/http://www.webrzs.stat.gov.rs/http://www.webrzs.stat.gov.rs/http://www.webrzs.stat.gov.rs/http://www2.lse.ac.uk/government/research/resgroups/kuwait/research/projects/knowledgeeconomyproject.aspxhttp://www.internetworldstats.com/europa2.htm#rshttp://www.innovationfund.rs/innovation-serbia-project/


33/37

Page 32

OECD (2005), The Measurement of Scientific and Technological Activities: Guidelines for Collecting and Interpreting

Innovation Data: Oslo Manual, Third Edition, prepared by the Working Party of National Experts on Scientific and

Technology Indicators, OECD, Paris

OECD (2009), Progress in the implementation of the European Charter for Small Enterprises in the Western Balkans, Paris:

OECD/European Commission/European Training Foundation/European Bank for Reconstruction and Development

Orlowski, Witold M. (1999), Knowledge Economy and Knowledge-Based Growth: Some Issues in a Transition Economy, in:

The Knowledge-Based Economy, the European Challenges of the 21 stCentury, State Committee for Scientific

Research, Republic of Poland

Orlowski (2000), The knowledge-based economy: the global challenges of the 21st century

Polenakovik, R. and Pinto, T. R. (2009), The National Innovation System and its Relation to Small Enterprisesthe Case of

the Republic of Macedonia, World Review of Science Technology and Sustainable Development

PR Newswire (undated), 'One Computer for Every Student' Vision Nears Completion After Three Year Partnership Between

Macedonia Ministry for the Information Society and NComputing,http://www.prnewswire.com/news-releases/one-

computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-

the-information-society-and-ncomputing-95750794.html,accessed: 18 February 2012

Radosevic (2006), The knowledge-based economy in Central and Eastern Europe: countries and industries in a process of

change

Roper, Stephen (2010), Moving on: From Enterprise Policy to Innovation Policy in the Western Balkans, Working Paper No.

108, Warwick Business School,

http://www2.warwick.ac.uk/fac/soc/wbs/research/csme/research/working_papers/wp108.pdf,accessed: 19

August 2011

United Nations, Towards a knowledge-based economy - country readiness and assessment report, (available for several

countries and regions)

World Bank (2009), Macedonia Country Brief,

http://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenD

ocument,24 April 2009, accessed: 2 September 2011

World Bank (2011), Knowledge for Development (K4D), Knowledge Economy Index,http://info.worldbank.org/etools/kam2/KAM_page5.asp,accessed: 16 August 2011

World Bank (2011a), Variables and Clusters, Knowledge for Development (K4D),

http://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:2058428

8~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.html,accessed: 12 September

2011

World Bank (2011b), YF Innovation Serbia,http://www.worldbank.org/projects/P126229/yf-innovation-

serbia?lang=en,accessed: 7 March 2012
http://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www2.warwick.ac.uk/fac/soc/wbs/research/csme/research/working_papers/wp108.pdfhttp://www2.warwick.ac.uk/fac/soc/wbs/research/csme/research/working_papers/wp108.pdfhttp://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenDocumenthttp://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenDocumenthttp://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenDocumenthttp://info.worldbank.org/etools/kam2/KAM_page5.asphttp://info.worldbank.org/etools/kam2/KAM_page5.asphttp://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:20584288~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.htmlhttp://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:20584288~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.htmlhttp://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:20584288~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.htmlhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://www.worldbank.org/projects/P126229/yf-innovation-serbia?lang=enhttp://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:20584288~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.htmlhttp://web.worldbank.org/WBSITE/EXTERNAL/WBI/WBIPROGRAMS/KFDLP/EXTUNIKAM/0,,contentMDK:20584288~menuPK:1433258~pagePK:64168445~piPK:64168309~theSitePK:1414721,00.htmlhttp://info.worldbank.org/etools/kam2/KAM_page5.asphttp://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenDocumenthttp://lnweb90.worldbank.org/eca/eca.nsf/Countries/Macedonia/fffd3db0d7306bfd85256c250061ac88?OpenDocumenthttp://www2.warwick.ac.uk/fac/soc/wbs/research/csme/research/working_papers/wp108.pdfhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.htmlhttp://www.prnewswire.com/news-releases/one-computer-for-every-student-vision-nears-completion-after-three-year-partnership-between-macedonia-ministry-for-the-information-society-and-ncomputing-95750794.html


34/37


Page 33

World Bank (2012), Knowledge for Development (K4D),http://info.worldbank.org/etools/kam2/KAM_page5.asp,

accessed: 10 April 2012

World Bank (2012b), WDI,http://databank.worldbank.org/,accessed: 25 January 2012

World Bank (2012c), Doing Business,http://doingbusiness.org/,accessed: 22 April 2012
http://info.worldbank.org/etools/kam2/KAM_page5.asphttp://info.worldbank.org/etools/kam2/KAM_page5.asphttp://info.worldbank.org/etools/kam2/KAM_page5.asphttp://databank.worldbank.org/http://databank.worldbank.org/http://databank.worldbank.org/http://doingbusiness.org/http://doingbusiness.org/http://doingbusiness.org/http://doingbusiness.org/http://databank.worldbank.org/http://info.worldbank.org/etools/kam2/KAM_page5.asp


35/37

Page 34

APPENDIX

WORLD BANK KNOWLEDGE ECONOMY INDEX VARIABLES

Component Variables

Performance of economy GDP GrowthHDI

Economic regime Tariff & Nontariff Barriers

Governance Regulatory Quality

Rule of Law

Innovation Royalty and License Fees Payments and Receipts

Scientific and Technical Journal Articles

Patent Applications Granted by the USPTO

Education Adult Literacy Rate

Secondary Enrolment

Tertiary Enrolment

ICT Telephone per 1000 peopleComputer per 1000 people

Internet Users per 10000 people

For details of measurement seeWorld Bank (2011a)

LIST AND DEFINITIONS OF BEEPS 2005/2009 VARIABLES

Variable Definition

New product Has this establishment introduced new products or services in the last 3 years?

Improved product or service In last 3 years, has this establishment upgraded an existing productline/service?

Plant age In what year did this establishment begin operations in this country?

Employment No. of permanent, full-time employees of this firm at end of last fiscal year

Workforce with graduate quals % Employees at end of fiscal year with a university degree

Single proprietor What is this firm's current legal status?

Partnership What is this firm's current legal status?

Cooperative What is this firm's current legal status?

Limited company What is this firm's current legal status?

Exporting firm What % of establishment's sales were: direct exports? (% of total > 0)

Women-led enterprises Are any of the owners female? (% of female owners > 0)

Privatised state company How was this firm established?

Private start-up How was this firm established?

Private subsidiary of former state co. How was this firm established?

Joint venture with external partner How was this firm established?


36/37


Page 35

Large city or capital Citypopulation (above 1 million)

Medium-sized city Citypopulation (> 50,000 and < 1 million)

Subsidies from state Over the last 3 years, has this establishment received any governmentsubsidies?

Access to finance How much of an obstacle is: access to finance (moderate, major, or severe)

Tax rates Obstacle to the current operations: tax rates (moderate, major, or severe)

Tax administration Obstacle to the current operations: tax administrations (moderate, major, orsevere)

Customs and trade regulations How much of an obstacle is: customs and trade regulations? (Moderate,major, or severe)

Skills and education How much of an obstacle is inadequately educated workforce to your firm?(Moderate, major, or severe)

Functioning of judiciary Obstacle to the current operations: courts (moderate, major, or severe)


37/37

Documents

Knowledge Economy in the Western Balkans