High-skilled emigration and innovation in Central and East European countries

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Department of Economics and Business

M.Sc. Business Administration – International Management

High-skilled emigration and innovation in Central and East

European countries

The roles of country absorptive capacity and intellectual property rights

protection

Student: Michael Kolev Student ID: 11236183

Supervisor: Dr. Mashiho Mihalache Second reader: Dr. Niccolo Pisani Date: 22.06.2018

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Statement of Originality

This document is written by University of Amsterdam student Michael Kolev who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text

and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Acknowledgments

I would like to express my sincere gratefulness to Dr. Mashiho Mihalache for the valuable guidance, enthusiasm, and promptitude in providing feedback during the entire research process.

I also wish to thank my mother, who supported me and believed in me throughout my studies far from home.

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Abstract

Nowadays, there is an unprecedented interest in the role of innovation in the economic development process of the countries. Innovation is considered as a key driver for economic and scientific advancement, enhancing competitive advantage and stimulating the productivity of firms in developed and developing countries alike. Nonetheless, there is a relevant topic that has not received much attention and needs to be addressed. This topic refers to the impact of

international migration on innovation performance in developing countries. Does the emigration of high-skilled individuals necessarily reduce innovation capacity in developing countries due to the loss of human capital? Although emigration may directly cause a brain drain, it contributes to cross-border knowledge flows and technology diffusion and thus stimulates domestic innovation and help poorer countries to catch up to the technology frontier. Previous studies have

approached this topic, however, there is no agreement among scholars about whether migration causes “brain drain” or “brain gain”. Therefore, this thesis attempts to fill this gap in the

literature. Moreover, an examination of whether the aforementioned relationship is moderated by country absorptive capacity and intellectual property rights (IPRs) protection complements the focal research.

Using a sample of ten Central and East European developing countries and a study of ten years period of time, it is concluded that neither the main relationship is confirmed nor the moderating effects on it. Nevertheless, the study has been a useful channel direction to further research on that promising topic.

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1.Introduction

A factor that is commonly seen as one of the main pillars of economic growth and development on firm, industry, regional and national level is innovation (Frank, Cortimiglia, Ribeiro, & de Oliveira, 2016). Innovation enhances the position of emerging and developing economies in global markets and is a sustainable driver of the economic growth of a country (Govindarajan & Ramamurti, 2011). A key determinant of the innovation capacity of a country is its human capital. Human capital contributes significantly to productivity and plays a key role in fostering technological progress, notably in developing countries. However, the globalization of world economies, provided opportunities for free cross-border movement of human capital, mainly from developing to developed countries. Consequently, the outward transfer of human capital has become a key concern for the developing countries.

This thesis examines the impact of high-skilled emigration on innovation capacity in Central and East European emerging and developing countries. Evidence on the influence of skilled emigration on source countries has been rather mixed. The traditional literature on migration argues that skilled emigration is detrimental to growth (Berry & Soligo, 1969;

Bhagwati & Hamada, 1974; Miyagiwa, 1991). Developed countries would gain at the expense of developing countries, as human capital is assumed to be a key pillar of economic growth and development. Consequently, the movement of high-skilled labor would be harmful to the developing economies and would increase the inequality across countries (Mountford & Rapoport, 2011a).

Nevertheless, recent studies are less pessimistic as the migration of skilled human capital might positively impact the innovation capacity of source countries through various channels

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(Docquier & Rapoport, 2012). The first channel, through which developing countries can benefit, is return migration. Better trained managers and entrepreneurs, scientists and engineers who have worked abroad may decide to return back to their countries of origin and continue their activities there, thus they will contribute to local innovation (Breschi, Lissoni, & Tarasconi, 2014a). The second way developing countries could benefit is through cross-border knowledge flows. When skilled workers move or collaborate across different countries, geographical knowledge transfer occurs (Miguélez & Moreno, 2015a). Kerr (2008) stresses the importance of migrants

communities in developed countries for conveying new knowledge and technologies back to their home countries. Knowledge flows are important because they increase the efficiency of the innovation process by reducing the need to re-create what already exists elsewhere (Oettl & Agrawal, 2008a). Furthermore, knowledge flows from technologically leading nations are necessary for the economic development of poorer countries and the achievement of global prosperity.

The conceptual framework we adopt argues that although emigration can initially result in the loss of valuable human capital, it also can induce channel through which more advanced knowledge can flow back to the developing countries. In order to verify this framework, this thesis aims to examine the relationship between high-skilled emigration and innovation in Central and East European (CEE) developing economies and examine the moderating effect of intellectual property rights (IPRs) protection and country absorptive capacity on this relationship.

By conducting this research, this thesis will contribute to the existing literature in a number of ways. Firstly, the majority of previous studies about the impact of skilled migration on innovation focused on destination countries, namely developed economies. Our study will examine data from ten Central and East European countries in order to shed more light on the

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impact of skilled migration on innovation in developing countries. Secondly, previous studies hypothesized that country absorptive capacity and intellectual property rights (IPRs) protection might have a positive influence on the relationship between skilled migration and innovation. Therefore, these variables are included as moderators in the current thesis in order to fulfill the existing gap in the literature. Finally, this research has some important implications for the CEE countries governments, as it shows that skilled emigration has a negative impact on innovation performance. Therefore, policymakers should develop policies against high-skilled emigration, if they want to achieve economic growth and development through innovation. Furthermore, national governments should develop better policies with regards diaspora networks abroad, as these networks can foster innovation performance and bring CEE countries closer to the technology frontier.

In this thesis, the following structure will be followed: first, the main concepts are explicitly described and previous literature contribution to the topic is cited. Second, the hypotheses are presented and discussed in the theoretical framework. Followed by the

methodology section in which the method and the data of this thesis are described, along with the explanation of the different variables of interest. Next, the results of the statistical analyses are described followed by the discussion in which the hypotheses are discussed together with the limitations of the study and the implications for future research. Finally, a conclusion of this study is provided in the last chapter.

2.Literature review

This chapter provides insight into the main variables that are investigated in this study. A discussion of the literature on migration, innovation, and the impact of emigration on innovation

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is provided, describing the relevant concepts and theories. Lastly, a research question is proposed that will be further examined in this study.

2.1 Migration

The new social and economic environment and, on a broader scale, the globalization of world economies, provide new opportunities for free-cross border movement (Rangelova & Vladimirova, 2004). Contemporary migration processes are of great significance with regards to the shaping of the social, demographic and economic situation of individual countries and regions (Organiściak-Krzykowska, 2017). In the literature concerning the topic, a variety of theoretical models have been proposed to explain why international migration occurs. The oldest and best-known theory of international migration is the neoclassical economic model, which emphasizes the fact that migrations are caused by variations in pay rates, which in turn, results from geographic differences in the supply of an demand for labor in countries receiving and sending migrants (Massey et al., 1993). In accordance with this model, the decision to migrate is based upon individual’s own profits and losses. According to “new economics of migration” model, the migration decisions are not made solely by individual actors, but by larger units of related people – typically families or households (Massey et al., 1993). This approach

emphasizes that migration can serve as risk-sharing strategy, as a household is in a position to control to their economic well-being by diversifying the allocation of household resources, such as family labor (Massey et al., 1993).

When analyzing the reasons for labor migration, the theory of push and pull factors proposed by Lee (1966) “A Theory of Migration”, is of key importance. According to Lee (1966), the causes of labor mobility should be considered in the context of “push” factors of the country of origin and “pull” factors on the part of the destination country. Relying on this

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conceptual framework, the World Bank proposed a set of factors explaining motivations for cross-border migration. They were classified according to various reasons, i.e. economic and demographic, political, social and cultural (see Table 1, Appendix). Alongside the push and pull factors, Lee (1966) presented two other dimensions, respectively “intervening obstacles” and “personal factors”, which play a significant role with regards migration decision. Lee argues that migration decision is based on an evaluation of the factors occurring in the country of origin compared to factors related to country of destination. Furthermore, the decision is based on personal factors too, for example, individual’s sensibility and intelligence, awareness of the situation at home, and knowledge about the situation at the destination country. The process of migration is influenced also by the so-called “intervening factors” such as the distance between countries and different laws. In general, migration theories imply the significance of countries differences, such as earnings and income levels, unemployment rates, cost of living, the quality of public goods and the generosity of the welfare systems (Kahanec, Zaiceva, & Zimmermann, 2009).

An important part of the picture is the sub-topic of skilled migration, i.e. the migration of persons with at least tertiary education. Well-educated individuals are important “carriers of knowledge”, transferring expertise and know-how by means of their cross-border mobility (Trippl, 2013). The international mobility of high-skilled people and the knowledge flows related to their movements can have a strong influence on the innovation capacities of the regions

involved in such processes (Trippl, 2013).

2.1.1 Migration from Central and Eastern Europe (CEE)

In 2004 the biggest enlargement in the history of European Union (EU) took place. As a result, eight new countries joined the old members, namely Czech Republic, Estonia, Hungary,

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Latvia, Lithuania, Poland, Slovakia and Slovenia (EU8). Three years later the Union accepted Bulgaria and Romania (EU2). While cheered by many, due to increased foreign direct

investments, trade, and stronger connections with old EU members, the enlargement brought about a number of concern as well (Kahanec et al., 2009). One of the main pillars of European Union is the free movement of goods, people, services, and capital. The differences in economic factors between West and East European countries, such as wages, unemployment rates, and better standards of living led to significant migration flows from CEE countries.

The scale of these flows was indeed remarkable, the migrant population from the eight new members states who joined the European Union in 2004 has increased from about 0.9 million by the end of 2003 to 1.9 million by the end of 2007 (Baas, Brücker, & Hauptmann, 2009). That means an average inflow, i.e. net immigration of around 250,000 people from the Central and East European countries per year since 2004, compared to 62,000 per year between 2000 and 2003 (Kahanec et al., 2009). At the same time, the number of migrants from Bulgaria and Romania has increased from about 0.7 million to 1.9 million (Kahanec et al., 2009). To further emphasize the picture of post-enlargement migration flows, we present available

evidence from the source countries. Figure 2 (Appendix) shows that emigration to the EU15 has increased in all EU8 and EU2 countries since the year 2000. In 2007, the largest share of

emigrants in proportion to the home population was in Romania (7.2%), Bulgaria (4.1%) and Poland (3.4%) (Kahanec et al., 2009).

In order to achieve domestic economic growth and development, and thus maintain appeal to foreign investors, CEE developing countries need high-skilled scientists, engineers, and managerial talents (Tung & Lazarova, 2006). The significant outflows of skilled individuals could have a negative long-term impact on CEE countries’ economic growth and development.

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According to Avato (2009), about 57% of total emigrants moving from CEE countries to the old EU-member states were highly skilled. Given the strong increase in the number of high-skilled migrants over the last decade (see Figure 3, Appendix) it is important to understand the

implications for CEE countries innovation performance.

2.2 Innovation

Nowadays, there is an unprecedented interest in the role of innovation in the economic development process of the countries. Innovation has been considered as a key driver for

economic growth, enhancing competitive advantage and stimulating the productivity of firms in developed and developing countries alike (Barasa, Knoben, Vermeulen, Kimuyu, & Kinyanjui, 2017). Innovation is associated with economic and scientific advancement and involves the creation of new products, better processes, and technology, all of which lead to growth and prosperity (DiRienzo & Das, 2015a). But what does the term innovation actually mean? The first and most influential researcher on innovation was the economist Joseph Schumpeter. According to Schumpeter innovation is a “process of industrial mutation, that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one” (Śledzik, 2013, p.90). Schumpeter argues that innovation is an essential driver of

competitiveness, and in order to achieve profits, firms must innovate. He divided innovation into five types: launch of a new product or a new species of an already known product, the

application of new methods of production or sales of a product, the opening of a new market, the acquirement of new sources of supply of raw materials or semi-finished goods and a new

industry structure such as the creation or destruction of a monopoly position (Śledzik, 2013). Crespi (2004) states that innovation is a complex process, which is affected by a great number of

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factors like economic development, economic freedom, democracy, and property rights protection.

A great part of literature is dedicated to innovation at the national level. The innovative capability of a country is the basic driving force behind its economic performance and a key determinant of long-term growth. Freeman (1989) argues about national system innovation “the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify, and diffuse new technologies”. Nelson (1993) describes national system

innovation as a set of institutions whose interaction determine the innovation performance of a country. A national system of innovation is a system where different entities like private and public firms, universities, and government agencies interact with each other in order to create science and technology within national borders (Niosi, Saviotti, Bellon, & Crow, 1993). To sum up, national system of innovation can be regarded as a set of components of the national

ecosystem that foster and supports a country’s innovational output.

A broad perspective on national innovation capabilities was shared by Furman et.al (2002), who introduced a concept he termed a “national innovation capacity”

(Kondratiuk-Nierodzińska, 2016). National innovative capacity is “the ability of a country – as both a political and economic entity - to produce and commercialize a flow of new-to-the-world technologies over the long term” (Furman, Porter, & Stern, 2002, p.900). National innovative capacity depends on the technological sophistication, the size of the scientific and technical labor force, and the government's investments and policy choices that impact the incentives for and the productivity of a country’s research and development (R&D) activities (Porter & Stern, 2001). Furman et. al (2002) argue that a country national innovative capacity depends on strong common innovation infrastructure, cluster-specific environment for innovation, and the quality

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of linkages between them. A country common innovation infrastructure consists of three factors: human and financial resources a country dedicated to scientific and technological advances, the government policies promoting innovative activity, and the economy’s level of technological sophistication (Porter & Stern, 2001). The availability of scientists and engineers is crucial for the country’s common innovation infrastructure as they contribute to innovation throughout the economy.

As mention above, human capital is a key determinant of the innovation capacity of a country. Human capital is embedded in the skills, knowledge, and expertise that people possess, it has been seen as an important source of competitive advantage to individuals, organizations, and countries (Dakhli & De Clercq, 2004). Human capital contributes significantly to

productivity and plays a key role in fostering technological change and diffusion (Teixeira & Fortuna, 2004). Furthermore, a country’s ability to adopt and implement new technology from abroad is a function of its domestic human capital stock (Benhabib & Spiegel, 1994). According to Benhabib & Spiegel (1994), a country which lies below the innovation leader, but possesses a higher human capital stock will eventually catch-up and overtake the leader. Also, a country with the highest stock of human capital will always eventually emerge as the technological leader nation in a certain time and will maintain its leadership as long as its human capital advantage is sustained. The above arguments emphasize the importance of human workforce for innovation processes within a country. However, what would be the implications for a country’s innovation performance when a substantial part of its best and brightest brains emigrate?

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2.3 The impact of high-skilled migration on innovation

2.3.1 Brain drain

Brain drain, skilled migration, in developing countries is becoming one of the major threats to sustainable economic development and innovation. The term “brain drain” indicate the international transfer of relatively high educate individuals from developing to developed

countries (Beine, Docquier, & Rapoport, 2008). These are people with special talents, high skills and specialized knowledge in the scientific, technological and cultural areas (Solimano, 2002). The traditional literature on migration and brain drain (Berry & Soligo, 1969; Bhagwati & Hamada, 1974; Miyagiwa, 1991) argue that high-skilled emigration is detrimental to growth. By depriving developing countries of human capital, one of their scarcest resources, brain drain is usually seen as a drag on economic development and innovation (Docquier, Lohest, & Marfouk, 2007). Kielyte (2010) states that R&D investments in Central and Eastern European developing countries are funded by public funds. Consequently, the loss of human capital will result in less government revenue collected through tax payments, hence the government budget share spent on R&D will decrease.

Nevertheless, a growing body of literature highlights the many benefits to the developing countries from international migration. More precisely, the brain drain cost can be mitigated through remittances, benefits from diaspora knowledge spillovers or brain circulation and return migration. Although the immediate consequence of skilled migration is a brain drain, migrants are provided with the opportunity to learn better skills and up-to-date technologies in more advanced economies, in result they can transform the brain drain into a brain gain.

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2.3.2 Brain gain

There is little doubt today about the contribution of emigration in creating potential gains for the developing countries. Early studies placed special emphasis on emigrant’s financial remittances as an important source of income for less developed countries and regions. More recently, due to the increasing importance of high-skilled migration, scholars paid more attention to emigrant’s contribution to knowledge formation and innovation (Breschi et al., 2014a). This can happen through different channels. The most direct channel is the physical return of the emigrants. Emigrant scientists and engineers who have worked as academic or industrial researchers may decide to move back to their home countries and continue their activities over there, thus they contribute to local innovation (Breschi et al., 2014a). A secondary way is

through knowledge spillovers. Kerr (2008a) argue that there are ethnic scientific communities in advanced economies and that these communities facilitate the transfer of knowledge to their countries of origin. In migration literature, the term “diaspora” is often used for these scientific communities. Diasporas are people and communities that do not live in their home countries for various reasons such as wars, political and ethnic persecutions, natural disasters and other causes (Solimano, 2002). Diasporas constitute invisible nations that reside outside their origin countries. The purpose of these networks is to connect professionals and scientists, who are interested to maintain contact among themselves and are interested to foster innovation and development in their home countries (Solimano, 2002). The use of “diaspora” rather than “migrant” is to emphasize knowledge transfer as a particular activity performed by a group of migrants in connection with their country of origin (Siar, 2014a). Diaspora raise the possibility that the migration of skilled human capital from developing countries may not just be a negative “brain

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drain”, it could also have a positive effect as a “brain gain”, accumulating knowledge abroad and conveying it back to domestic inventors (Kerr, 2008a).

2.4 Research gap

Migration and innovation are two phenomena whose ties date back a long time in history. What makes the study of migration and innovation a relevant research topic nowadays, is the increase in emigration flows of scientists and engineers, executives, and other professionals from developing to developed countries (Breschi, Lissoni, & Tarasconi, 2014b). This raises a number of questions on the role these migrants might play in innovation performance of both the

destination and origin countries. Scholars are even far from a consensus on the question: “ What is the impact on innovation when a developing country loses a large fraction of its high-skilled workforce through emigration?” (Agrawal, Kapur, McHale, & Oettl, 2011, p.43).

Evidence on the impact of skilled emigration on source countries has been rather mixed. One school of thought argues that emigration is detrimental to developing countries (Berry & Soligo, 1969; Bhagwati & Hamada, 1974; Miyagiwa, 1991). According to Pires (2015), emigration can be harmful to economic growth through a set of negative externalities, for example, reduced productivity, higher costs of public goods and loss of the investment made in human capital. Furthermore, human capital is assumed to be an important driving force to innovation, consequently, the movement of skilled labor would increase inequality between developed and developing countries (Mountford & Rapoport, 2011b).

Nevertheless, the outflow of knowledge and highly skilled people may not necessarily mean a loss for their home countries because their skills and knowledge can be channeled back (Siar, 2014a). Kerr (2008b) argue that emigrants have access to up-to-date technologies and

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foreign produced knowledge, thereby through knowledge spillovers, they can foster innovation in their countries of origin. This knowledge has the potential to increase innovation and bring the developing countries closer to the technology frontier, thus mitigating the negative effects of the reduction in human capital due to emigration. In other words, the migration of skilled

professionals may not be detrimental to home countries as their knowledge and skills can be better exploited overseas (Siar, 2014a). However, Agrawal et al. (2011) did not find a strong relationship between Indian high-skilled workers in the United States and the transfer of their knowledge back to their homeland. Breschi et al. (2017) add that while inventors in India do not benefit from their expatriates abroad, other countries like Russia and China experience

substantial advantages coming from knowledge flows from their labor abroad. Both authors assumed that the different findings across countries may be related to specific country characteristics such as country absorptive capacity and intellectual property rights (IPRs) protection. Therefore, this study aims to fulfill this gap in the literature by investigating the role of country absorptive capacity and intellectual property rights (IPRs) protection in determining the effect of high-skilled emigration on innovation. In order to clarify the relationship between these variables, the following research question will be examined in this thesis:

“Do high-skilled emigration foster innovation in Central and East European countries? And what is the moderating effect of country absorptive capacity and intellectual property rights protection in this relation?”

3.Theoretical framework

In this chapter, an overview will be provided of the current literature on the relationship between high-skilled emigration and innovation. Furthermore, intellectual property rights

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protection and country absorptive capacity are proposed as moderators for the relationship between high-skilled emigration and innovation. For each of these relationships, a hypothesis is provided. At the end of the chapter, a theoretical model is presented.

3.1 High-skilled emigration and innovation

Although there have been some studies in the research field concerning the relationship between high-skilled emigration and innovation, there is a lack of consensus about the effect of high-skilled emigration on innovation in developing countries. The traditional “brain drain” literature state that high-skilled emigration is detrimental to a country’s innovation performance, as these individuals possess valuable knowledge and capabilities needed for the innovation process. Emigration leads to a reduction in labor and this has a direct negative impact on innovation. Nevertheless, there might be, an indirect effect, since international migration increases the exchange of ideas and knowledge flows across borders. Knowledge flows are economically important because they increase the efficiency of the innovation process and reduce the need to re-create what already exists somewhere else (Oettl & Agrawal, 2008b). When skilled workers move or collaborate across different countries, geographical knowledge diffusion occurs (Miguélez & Moreno, 2015b). Migrants who settled themselves in developed countries can share knowledge about new technologies, new processes, or new products with their former colleagues and friends at home. This knowledge has the potential to increase innovation and bring the developing countries closer to the technology frontier, thus mitigating the negative effects of the reduction in human capital due to emigration.

This inconsistency in the literature will be clarified in this thesis by investigating the nature of the relationship between these two variables. In this study, it is hypothesized that high-

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skilled emigration has a positive effect on home country innovation. Therefore, the first hypothesis is as follows:

Hypothesis 1: High-skilled emigration has a positive effect on innovation in Central and East European countries.

3.2 Country absorptive capacity

For the learning process from international activities to take place and affect innovation performance, two conditions are necessary: there must be knowledge spillovers; and the firm or country at the receiving end must possess the necessary absorptive capacity to capture the knowledge spillovers (Filippetti, Frenz, & Ietto-Gillies, 2017). According to W. M. Cohen & Levinthal (2000, p.128), absorptive capacity refers to the “ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial end”. Firms that possess higher levels of absorptive capacity can manage external knowledge more efficiently, and therefore stimulate innovative outcomes (Escribano, Fosfuri, & Tribó, 2009). The concept of absorptive capacity has been more extensively analyzed at the firm level, however, the notion of absorptive capacity has also been applied to more aggregate context, such as at the country level. According to Dahlman & Nelson (1995), country absorptive capacity is the ability to learn and implement technologies and associated practices of already developed countries. Wegloop (1995, p.419) define country absorptive capacity as “those institutions and actions that allow firms within national systems of innovations (NSI) to recognize the value of new external knowledge, assimilate it, and apply it to commercial ends”. Keller (1996) argue that raising the absorptive capacity of a country will facilitate the implementation of technologies and knowledge invented abroad.

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In light of the above arguments, this paper argues that the impact of high-skilled

emigration on innovation performance is critically determined by the level of country absorptive capacity. The following hypothesis is formulated to investigate the influence of absorptive capacity on the relationship between high-skilled emigration and innovation:

Hypothesis 2: The presence of high country absorptive capacity, will positively influence the relationship between high-skilled emigration and innovation in Central and East European countries.

3.3 Intellectual property rights

The protection of intellectual property rights (IPRs) creates incentives to innovate by granting monopoly rights to inventors through a patent, thus governments try to ensure that inventors can profit from inventing. The standard economic analysis suggests that stronger IPRs increase the incentives of foreign companies to invest in knowledge related activities and also create more incentives for domestic companies to innovate (Montobbio, Primi, & Sterzi, 2015). Likewise, stronger IPRs can stimulate trade, foreign direct investments and international joint ventures, thus IPRs may increase the probability of direct international collaboration between inventors and the probability of international knowledge transfer (Park and Lippoldt, 2008, in Montobbio et al., 2015). Strong intellectual property rights protection increase directly the use of technology facilitating the establishment of domestic technological capabilities not only through higher incentives for domestic firms to perform R&D but also through technology markets, licenses, technology outsourcing and contracts, enhancing the overall capacity of a country to absorb foreign produced knowledge (Montobbio et al., 2015).

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This paper argues that strong intellectual property rights protection will facilitate the absorption of foreign-produced knowledge by high-skilled migrants, hence will positively influence the relationship between high-skilled emigration and innovation. Therefore, the third hypothesis is as follows:

Hypothesis 3: The presence of strong intellectual property rights protection, will positively influence the relationship between high-skilled emigration and innovation in Central and East European countries.

3.4 Theoretical model

In figure 1, a presentation of the proposed relationships is provided and the hypotheses are illustrated. As can be seen, high-skilled emigration is expected to have a positive effect on innovation, and country absorptive capacity and intellectual property rights protection both are expected to strengthen this positive effect.

Figure 1. Theoretical Model

+

High-skilled emigration IPRs protection Innovation Country Absorptive Capacity

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4.Methodology

In this chapter, at first, the process and criteria of data collection are described. Thereafter, an overview is provided of the operationalization and data sources for the

independent variable, dependent variable, moderating variables, and control variables. At last, the procedure for analyzing data is described.

4.1 Sample and data collection

The variables in this thesis are measured at country level. The overall sample population consists of ten emerging and frontier market economies. The term “emerging market” refers to a country that has some characteristics of a developed market, but does not meet standards to be a developed market. The term “frontier market” is used for developing countries which has slower economies than emerging market countries. Overall emerging and frontier market countries both fall into the same general sector, namely developing economies. The starting point for selecting countries in the sample was the list of emerging and frontier markets developed by Morgan Stanley Capital Index (MSCI). Only countries included on the list were included in the dataset. Data were collected for all countries over a ten year time period, from 2004 to 2013. See Table 2 on the next page for an overview of all countries included.

In addition to this, we choose Central and East European countries as the region experienced substantial emigration flows, mainly due to the enlargement of European Union (EU). The difference in economic factors between West and East European countries, such as wages, unemployment rates, and in general better standards of living led to a significant movement of people towards West European developed countries (see Figure 2 and 3, Appendix).

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1. The Czech Republic 7. Romania 2. Hungary 8. Slovenia 3. Poland 9. Bulgaria 4. Croatia 10. Latvia 5. Estonia

6. Lithuania

4.2 Variables and measures

4.2.1 Dependent variable

Innovation. One of the most common methods scholars use for measuring national

innovative activities is through capturing patent data. Patent records contain highly detailed information on the innovation itself, the technological area to which it belongs, and the geographical location of the inventors (Hall, Jaffe, & Trajtenberg, 2001). Furthermore, patent data include citations to previous patents and to the scientific literature. Through these citations, scholars have the possibility of tracing multiple linkages between inventions, inventors,

scientists, firms, and locations (Hall et al., 2001). In particular, patent data allow researchers to measure the transfer of codified and published knowledge, thus researchers capture the

international knowledge spillovers (Montobbio et al., 2015). This study will use data on

innovative activity from the European Patent Office (EPO). The main outcome of interest is the number of patent applications in CEE countries.

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4.2.2 Independent variable

High-skilled emigration. We use stocks of emigrants abroad, as a measurement of

high-skilled emigration. The data are annual. Our data for emigration stocks come from Eurostat database. Eurostat is the statistical office of the European Union (EU) and its mission is to provide high-quality statistics for Europe. Eurostat offers a whole range of important and interesting data that enable comparisons between countries and regions.

4.2.3 Moderating variables

Country absorptive capacity. In this thesis, it will be examined whether a country

absorptive capacity has an influence on the relationship between high-skilled emigration and innovation in developing economies. A good indicator of the absorptive capacity of a country is its global competitiveness (Siar, 2014b). The global competitive index (GCI) released by the World Economic Forum will be used to measure a country’s absorptive capacity. The GCI is a yearly report, which consists of variables such as the strength and reliability of institutions, overall quality of infrastructure, health and education, efficiency of markets, ability to harness existing technology, business sophistication, and level of innovation. It can be assumed that countries that have a high score on global competitiveness index also have a high capacity to absorb knowledge flows and skills, including those from migrants (Siar, 2014b).

Intellectual property rights (IPRs) protection. The second moderator used in this study is

the intellectual property rights protection. Intellectual property rights are regulatory frameworks embodied in the socio-economic systems of a country (Montobbio et al., 2015). The IPRs protection creates incentives to innovate by granting monopoly rights to inventors through a patent, thus governments try to ensure that inventors can profit from inventing. One of the potential benefits of strong IPRs in developing countries is that such protection may encourage

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the transfer of advanced knowledge and technology from developed countries (Branstetter, Fisman, & Foley, 2006). The data for intellectual property rights protection will be obtained from World Economic Forum.

4.2.4 Control variables

In this study, GDP per capita, R&D expenditure, and population size are used as control variables. These control variables are used to “control” the effects on the dependent variable and will control for any possible bias.

GDP per capita. The quality of the innovation environment in a country is dependent on

its economic development. (DiRienzo & Das, 2015b). High levels of economic development encourage more innovative and entrepreneurial activities (DiRienzo & Das, 2015b). Measuring economic development by GDP per capita allows for the “capture of the ability of a country to translate its knowledge base into a realized state of economic development” (Stern, Porter, & Furman, 2000, p.20). GDP per capita is often added as a control variable for possible biases in previous studies (Naghavi & Strozzi, 2015; Stern et al., 2000). Therefore, GDP per capita is included in the analysis and the data will be obtained from The World Bank.

R&D expenditure (total). We also add R&D expenditure, as it is another proxy for a

country’s potential for innovation. R&D expenditure is defined as the total expenditure on R&D carried out by a country’s residents, companies, research institutes, and universities. The R&D expenditure performed in a country is used as a control variable because innovation feeds on the knowledge that results from cumulative R&D experience on the one hand, and it contributes to this stock of knowledge on the other (Coe & Helpman, 1995). The data for measuring R&D expenditure as % of GDP will be obtained from the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.

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Population size. The third control variable that could cause bias in the study is the size of

the country in terms of population. The data for the population size will be obtained from The World Bank.

Table 3. Summary Variables

Variable Description Data Source

Innovation Measured by patent

applications to the European Patent Office (EPO)

European Patent Office (EPO)

High-skilled emigration Measured by emigration stocks abroad

Eurostat database

Country absorptive capacity Measured by Global Competitive Index

Global Competitive Index (GCI) – World Economic Forum

Intellectual property rights (IPRs) protection

Score from 1 to 7. 1 represents extremely weak IPRs, and 7 represent extremely strong IPRs

World Economic Forum

GDP per capita Control Variable The World Bank data

R&D expenditure (total) Control Variable UNESCO Institute for Statistics

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4.3 Method

In order to test the formulated hypotheses, a quantitative method of analysis will be used which provides several advantages. First, it generates more reliable, objective and countable results. Second, it simplifies a problem to a limited number of variables and identifies the relationship between them. In addition, quantitative modes have been the dominant methods researchers use to test hypotheses (Newman & Benz, 1998).

A multiple hierarchical regression analysis will be conducted with SPSS, in order to test the three hypotheses of the study. This type of analysis provides the opportunity to predict the relationship between the independent and dependent variable, therefore it is the optimal type of analysis for our study. It also provides the opportunity to add control variables (J. Cohen, Cohen, West, & Aiken, 2013).

5. Results

In this chapter, the previously presented hypotheses are analyzed by conducting several tests in SPSS. Firstly, a bivariate analysis is presented which reports the means, standard

deviations, and correlations. Following, a multiple hierarchical regression analysis is described to determine the nature of the direct and indirect effects of this study and test the hypotheses.

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5.1 Bivariate analysis

Table 4. Means, standard deviations and correlations

Variable MEAN SD 1 2 3 4 5 6 7 1.HS emigration 48469.59 73372.609 1 2. Patent applications 124.82 126.865 .180 1 3. Country AC 4.388 .2407 -.268* .183 1 4. IPRs protection 3.828 .5173 -.518* .278** .752** 1 5. GDP per c5pita 13997.103 4819.7695 .-155 .375** .551** .715** 1 6. R&D expenditure 1.034302 .5118783 -.363** .383** .597** .750** .814** 1 7.Population Size 9386103.45 11039994.23 .-560** .533** -.399** -.497** -.389** -.400** 1 *= Correlation is significant at the 0,05 level.

**= Correlation is significant at the 0,01 level.

In the following paragraph, the significant correlations will be discussed. As seen in table 4, there is a moderate positive relationship between the independent variable HS emigration and dependent variable patent applications (r= 0,180). Looking at the possible moderating variables country absorptive capacity and intellectual property rights protection, there are significant correlations. Country absorptive capacity correlates significantly with both HS emigration (r= -.268) and patent applications (r= .183), which is medium strength relationship. IPRs protection is also significantly correlated with both HS emigration (r= -.518) and patent applications (r= .278). The first control variable GDP per capita is negatively related to HS emigration (r= -.155) and positively related to the patent application (r= .375). The second and third control variables are both negatively related to HS emigration (r= -.363 ; r= -.560) and both are positively related to patent applications (r= .383 ; r= .533). Thus, as all of the control variables show significant

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correlations with some of the variables in the study, all three of them are included in the regression analysis.

5.2 Regression analysis

In this paragraph, the results of the hierarchical regression analysis are presented. In total, four models were added in order to test the direct and indirect effects and test the hypotheses of this study. In table 5, an overview is provided of the results.

Table 5. Regression results on patent applications

Model 1. GDP

per capita, R&D expenditure, Population Size Model 2. Country AC, IPRs protection Model 3. High-skilled emigration Model 4. Moderators Beta (SE) β Beta (SE) β Beta (SE) β Beta (SE) β Control Variables GDP per capita 3.937 E-5(.00 01) .393 3.821E-5 (.0001) .381 4.108E-8 (.0001) .410 4.009E-5 (.0001) .400 R&D expenditure .244 (.098 ) 259 .228 (.105) .241 .203 (.104) .215 .200 (.106) .212 Population Size 3.470 E-8 (.000 1) .792 3.498E-8 (.0001) .799 3.925E-8 (.0001) .896 3.833E-8 (.0001) .875 Moderators Country AC - -0.42 (.176) -.021 -.004 (176) -.002 -.102 (.218) -.051 IPRs protection .054 (.101) .058 .026 (.101) .027 .078 (.117) .083 Independent Variable HS emigration - 9.992E-7 (.0001) -.152 - 7.947E-6 (.0001) -1.206 Moderator effect

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Note: *** result is significant at p<0,001

In table 5, the results of the hierarchical regression analysis are presented. Considering the model of the current research, it is obvious that four models are needed for the regression. In each model, a new set of predictors is added, starting from the less important predictors and ending up with the main question in the investigation of this study and the interaction effects.

Firstly, in model 1 of the regression analysis, the control variables of GDP per capita, R&D expenditure, and population size were included. Table 5 shows that the R square in model 1 is 0.683 which means that 68 percent of the variance of patent applications is been accounted by control variables. Furthermore, the entire model has a significant p-value (p<0,001) with an F-value of 59.586.

Then, in the second model, the two moderators country absorptive capacity and intellectual property rights protection were added to the regression. The entire model is

significant (p<0,001), and has an F-score of 35,082. While adding the moderating variables, the variance explained did not improve, model 2 explains 68 percent of the variance.

Following, in model 3, the independent variable high-skilled emigration was added to the regression analysis to test hypothesis 1. The model is significant (p<0,001) with an F-value of 30.471. High-skilled emigration has a negative effect on patent applications (β= -.152). Thus,

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when a country loses some of its highly skilled labor due to emigration, it will mitigate a country’s ability to engage in innovation, rejecting Hypothesis 1. The variables in model 3 together explain 69,6 percent of the variance, with an R square change of 1,2 percent.

Lastly, in model 4, the two possibly moderating variables country absorptive capacity and IPRs protection were added. The entire model is significant (p<0,001), with an F-value of

22.606. However, both country absorptive capacity and IPRs protection do not significantly moderate the effect of high-skilled emigration on innovation. Thus, no support was found for Hypothesis 2 and 3.

6. Discussion

In this section, the main findings will be addressed by discussing the hypotheses that were tested in the regression analysis. Following, the theoretical and practical implications of these results are discussed. Lastly, the limitations of this study are presented and directions for future research are suggested.

6.1 Findings

The current study aimed to specify whether high-skilled emigration could stimulate the innovation capacity of Central and East European developing countries. Three hypotheses were tested in this study in order to clarify the nature of the relationship between high-skilled

emigration and innovation in CEE countries, and investigate the possibly moderating roles of country absorptive capacity and intellectual property rights protection. The first hypothesis predicted a positive influence of skilled emigration on a country’s ability to innovate. In the literature, there was no consensus on this relation. While some scholars support the “brain drain” hypothesis, which argues that skilled emigration is detrimental to country’s economic

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development and innovation capacity. However, other scholars support the “brain gain” hypothesis, according to which migrants have access to up-to-date technologies, and through knowledge spillovers, they can positively contribute to the innovation capabilities of their origin countries. The results of this study supported the “brain drain” hypothesis, high-skilled

emigration negatively affects a country’s ability to innovate.

Hypothesis 2 and 3 investigated the potential moderating variables country absorptive capacity and IPRs protection. Country absorptive capacity refers to county’s ability to implement new technologies and associated practices of already developed countries. High absorptive capacity facilitate the implementation of technologies and knowledge invented abroad.

Therefore, country absorptive capacity was investigated as a potential moderator. However, the results of this study did not support Hypothesis 2, thus, country absorptive capacity does not moderate the influence of skilled emigration on innovation. The second moderator was

investigated by testing Hypothesis 3, which tested whether intellectual property rights protection has a moderating influence on the direct effect. The expectation was that IPRs protection might play a moderating role because strong IPRs in a country facilitate the absorption of foreign-produced knowledge. Therefore, IPRs was hypothesized as a potential moderator of the relationship between skilled emigration and innovation. However, no significant interaction effects were found for intellectual property rights protection.

Overall, skilled emigration has a negative influence on innovation and country absorptive capacity and intellectual property rights protection do not moderate the strength of the

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6.2 Theoretical and practical implications

This study provided more insight into how high-skilled emigration impact innovation in emerging and developing Central and East European countries. Previous literature often

investigated the impact of migration on innovation in destination countries, namely developed economies. Although there have been some studies concerning the influence of skilled migration on innovation in developing countries, there is a lack of consensus on the precise nature of the relationship. This study confirmed a negative relationship between skilled emigration and innovation. Furthermore, previous literature argues that country absorptive capacity and IPRs protection might impact the relationship between skilled emigration and innovation in

developing countries. However, this study provides insight that these variables do not moderate the relationship between skilled emigration and innovation.

The results of this study express the need for national governments to develop better policies concerning high-skilled emigration. As stated before, innovation is considered as a key driver for economic growth, enhancing competitive advantage and stimulating the productivity of firms in developing countries. Therefore, it is essential for Central and East European

countries to try to prevent the emigration of skilled individuals, if they want to achieve economic growth and development. Moreover, policymakers should develop better policy with regards diaspora networks abroad. These networks have untapped knowledge potential that could foster innovation performance and help Central and East European countries to catch up Western European economies.

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6.3 Limitations and future research

At this point, the limitations of the study are discussed. One major limitation of the research is the relatively small sample size, which was composed of only 10 countries and covered a ten-year period. Furthermore, there were some statistic results that were not

significant. Meaning that more research is needed to verify these. Another major limitation is the use of secondary data for the analyses instead of collecting primary data. Secondary data has two major disadvantages. First, the data is collected with another study and objective in mind, and second, there is no control over the quality of the data. The innovation measure we use in this study is patent applications. Although patents are one of the most common method researchers uses to measure innovation, there are some limitations. First, not all inventions are patentable. Also, in many instances, inventors prefer other means to protect their inventions.

Nevertheless, the former limitations could be addressed in future research. In particular, the sample size could be enriched with more developing countries, from a different region than Europe and innovation activity could be captured with a different measure.

This study can be seen as a starting point for further research. We established that countries in Central and East Europe do not benefit from their diaspora networks abroad, consequently the innovation capacity decrease due to emigration. However, it would be interesting to investigate the impact of return migrants on innovation. Return migrants might accelerate the innovation as they bring newly gained knowledge from developed economies. We leave this for further research.

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7.Conclusion

In this final chapter, a summary of this study is provided. The findings and implications for practice are reported. By analyzing data from ten Central and East European countries over a time period of ten years, this thesis investigated the relationship between international migration and innovation and investigated whether country absorptive capacity and intellectual property rights protection moderated this relationship. This paper answer the question of how innovation in CEE developing countries is influenced by losing skilled workers as a result of emigration. The results of the study confirmed the “brain drain” hypothesis, according to which the migration of skilled workers negatively influences innovation performance of countries. However, country absorptive capacity and IPRs protection did not significantly moderate this relationship.

This results clarified the gap in the literature by providing more insight into the relationship between high-skilled emigration, innovation, country absorptive capacity, and intellectual property rights protection. Innovation has been considered as a key driver for economic growth and development, hence is of most importance for developing countries. The negative impact of skilled emigration on innovation has some important implications.

Policymakers should develop more strict policies against high-skilled emigration in order to mitigate the negative impact it has on innovation since innovation has been known to foster economic growth in developing countries. Furthermore, national governments should develop better policies as regards diaspora networks abroad. Migrants abroad have access to up-to-date technologies and foreign produced knowledge, thus through knowledge spillovers, they can foster innovation in their countries of origin. This knowledge has the potential to increase innovation in CEE countries and bring them closer to the technology frontier.

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9.Appendix

Table 1

Motivations for Migration according to the World Bank

Kind of motivation Push factors Pull factors

Economic and demographic Poverty

Unemployment Low wages

High fertility rates Lack of basic health and education

Prospects of higher wages The potential for an improved standard of living

Personal and professional development

Political Conflict, insecurity, violence Poor governance

Corruption

Human rights abuses

Safety and security Political freedom

Social and cultural Discrimination based on ethnicity, gender, religion, and the like

Family reunification

Ethnic (diaspora migration) homeland

Freedom from discrimination Source: Migration and Remittances. Eastern Europe and the Former Soviet Union, (Eds.) A. Mansoor, B. Quillin, World Bank, 2006

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Figure 2

The share of emigrants to the EU15 in the new member states

High-skilled emigration and innovation in Central and East European countries

Department of Economics and Business

M.Sc. Business Administration – International Management