Applied Science and Innovative Research ISSN 2474-4972 (Print) ISSN 2474-4980 (Online) Vol. 2, No. 4, 2018 www.scholink.org/ojs/index.php/asir 129 Original Paper Foreign Direct Investment and Economic Growth in the Republic of Kosovo—Empirical Evidence Lumnije Thaçi1* & Merita Rushiti2 1 Department of Economic Engineering, University of Mitrovica “Isa Boletini”, Kosovo 2 Payment Sector Specialist at the Company “Unioni Financiar Prishtinë”, Master in Banking, Finance and Accounting - “Fama” College, Prishtina, Kosovo * Lumnije Thaçi, Assistant Professor, Faculty of Mechanical and Computer Engineering, Department of Economic Engineering, University of Mitrovica “Isa Boletini”, Kosovo Received: August 27, 2018 Accepted: September 9, 2018 Online Published: September 20, 2018 doi:10.22158/asir.v2n4p129 URL: http://dx.doi.org/10.22158/asir.v2n4p129 Abstract Whether Foreign Direct Investment (FDI) is beneficial to host country growth or not, it is a question debated since a long time (Acaravci & Ozturk, 2012). This paper will examine the flow of FDI and their impact on economic growth in the Republic of Kosovo. This correlation between FDI and economic growth will be studied through regression (Quantile Regression Median). The results of the study will be obtained using multiple regression to evaluate the effect of FDI on the economy, using secondary annual data from 2007 to 2017. In addition to the basic model to be used to assess the impact of FDI on total growth amount, we have also decomposed them into the second model: FDI in manufacturing and FDI in services as well as other FDI. The research results show that the impact of total FDI and FDI in manufacturing is negative and insignificant while the impact of FDI in services and other FDI is positive but insignificant to economic growth in Kosovo. Due to the importance of FDI, as an important source of capital in a transition country such as Kosovo, these results are informational for decision-makers to improve policies in order for the country to become more attractive in attracting FDI. Keywords Foreign Direct Investment, economic growth, multinational enterprises, developing countries 1. Introduction The last two decades have witnessed large amounts of Foreign Direct Investment (FDI) inflows in the developed and emerging world (Asteriou & Moudatsou, 2014). FDI is often considered to be an www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 130 Published by SCHOLINK INC. important catalyst for economic growth in developing countries (Trinh, 2015; Owusu-Antwi, Antwi, & Poku, 2013; Alfaro, Ozcan, & Sayek, 2009; Suleiman & Kaliappan, 2013). Therefore, some countries adopted new policies to liberalize their capital accounts and make regulatory changes in order to create more favourable conditions for attracting FDI (Asteriou & Moudatsou, 2014). The net benefits from FDI accrue automatically, and their magnitude differs according to host country and context. The factors that hold back the full benefits of FDI in some developing countries include the level of general education, the technological level of host-country enterprises, insufficient openness to trade, weak competition and inadequate regulatory frameworks. Conversely, a level of technological, educational and infrastructure achievement in a developing country does equip it better to benefit from a foreign presence in its markets. Finally, FDI—like official development aid—cannot be the main source for solving poor countries’ development problems. With average inward FDI stocks representing around 15% of gross domestic capital formation in developing countries, foreign investment acts as a valuable supplement to domestically provided fixed capital rather than a primary source of finance (OECD, 2002). Theoretically, capital formation and technological improvement are the engines of economic growth (Wang, 2009). Indeed, the transfer of technology has perhaps become the predominant issue around which discussions of multinational corporations (MNCs) and their dealings with developing countries evolve. This is because technology is believed to be a vital source of economic growth, capital accumulation, trade, and even changes in the organization of social relations and the relations of production (Moosa, 2002). In fact, multinational firms are often considered as the most technologically advanced firms. However, transfer of technology can also have negative effects. According to Sen (1998), multinationals may have a reverse reaction to the R & D of the host country in order to continue to maintain a technological edge compared to local firms. In addition, FDI promotes economic development in the host country by increasing productive capacity as a result of improved of labour force, cited in (Moura & Forte, 2010). Namely, when foreign companies enter new markets, they disturb the existing market equilibrium, causing a range of domestic firm reactions. Additional competition leads to efficiency improvements, which are needed if a firm holds its shares in the market. On the other hand, local firms learn from foreign companies about new products, technology, marketing and organizational skills as well as about foreign markets (Elvisa, 2004). From 1995 to 2015, the world had a dramatic increase in FDI. FDI inflows in 2015 were 8.6 times higher than those in 1995, reaching from around $ 0.2 trillion in 1995 to around $ 1.8 trillion in 2015. While FDI inflows in developed countries increased 8.6 times, in developing countries and transition economies they increased 23 times. In 1995, the inflows of developing and transition economies were 17% of the world’s total and in 2015, they accounted for 45%. FDI flows to OECD countries peaked in 2007, to about $ 1.3 trillion. Between 2013 and 2014, for the first time, developing countries received more FDI than developed countries (UNCTAD, 2016), although the developed world regained its position as the largest FDI recipient in 2015 (quoted in Feng, 2017). www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 131 Published by SCHOLINK INC. The most attractive sectors for FDI in developing and transition countries are: mining, minerals, metals, food production and traditional industry sectors, public infrastructure and services (especially power generation and telecommunications). Experts believe that when FDI is a large part of overall investment in a developing country, it is a sign that other sources of investment and financial instruments (financial market, credit market, etc.) are underdeveloped and have less potential (Finance and Development, 2001, IMF), quoted in Riinvest (2002). According to the Kosovo Agency of Statistics (KAS, 2017), the nominal GDP value in Kosovo reached to 6.3 billion euros. In real terms, Kosovo economy has increased by 3.7 percent. The growth of the economic activity was mainly generated by the growth of investments by 10.7 percent (mainly FDI growth and investment loans), as well as the increase in export of goods and services by 23.8 percent against the increase in the import of goods and services by 5.5 percent. Current account and capital account deficit in 2017 reached the value of 425.1 million euros, which is by 9.0 percent lower compared to 2016. This decrease in current account deficit is attributed to the increase of positive balance of services, primary and secondary income account (Figure 1). On the other hand, the balance of the goods account has deteriorated, quoted in (CBK, 2018). Figure 1. Trade Balance in Kosovo Source: CBK (2018) and calculation of authors. FDI received in Kosovo in 2016 have decreased by 24% compared to 2015. FDI received in Kosovo by September 2016 amounted to 182.3 million euros, representing a low level of FDI compared to the same period last year (2015: 268.5 euros). FDI in Kosovo during 2011-2016 is mainly concentrated in the following economic sectors with the respective averages: real estate with 56.3%, construction by 12.7%, financial sector with 12.7% followed by trade sector with 4.5% of total FDI. Regarding FDI origin, the majority of FDI in 2016 came from Switzerland (EUR 62 million), followed by Turkey (EUR 35 million), United Kingdom (EUR 33 million), Germany (EUR 29 million) and Albania (EUR www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 132 Published by SCHOLINK INC. 29 million) (KPMG, 2017). However, FDI in Kosovo in 2017 amounted to 287.8 million euros, representing an increase of 30.8 percent compared to 2016. Within the structure of FDI, the capital and the investment fund in stocks were characterized by increase in value, while investment in debt instruments marked a decrease. The capital and the investment fund in stocks, which account for about 91.9 percent of total FDI, amounted to 264.5 million euros, which is 44.9 percent more compared to the previous year. FDI in the form of debt instruments marked the value of 23.2 million euros, or 37.9 percent less compared to the previous year. FDI growth was mainly evidenced by the financial services sector, real estate and the construction sector, while the trade and industry sector declined (CBK, 2018) (Figure 2). Figure 2. Capital and Investment Funds in Stocks and Debt Instruments Source: KAS (2018) and calculation of authors. The relationship between FDI and economic growth has long been a topic of great interest in the field of international development (Trinh, 2015). The macroeconomic findings on growth and FDI must be viewed sceptically, however (Carkovic & Levine, 2002). A recent literature survey by Bruno and Campos (2013) shows that 50% of empirical studies report a significantly positive effect of FDI on growth, 11% find a negative effect while 39% find growth to be independent of FDI. It thus seems that FDI plays an ambiguous role in generating economic growth, with little support for an independent positive effect (Jude & Levieuge, 2015). Wang (2009) suggests that the ambiguous (or doubtful) results related to the FDI impact on economic growth may be caused by the use of FDI total. According to Wang (2009), previous studies underestimate the effect of increased output from FDI due to aggregation. According to the author, the results show that the effect of increased output from FDI is much stronger than the effect of total FDI growth. Furthermore, without the decomposition of total FDI inflows, the effect of manufacturing FDI 286.10 222.30 207.10 257.80 287.20 157.10 96.00 46.60 139.10 87.60 163.80 113.00 91.40 23.20 37.40 39.20 26.40 104.20 34.60 80.80 37.40 23.20 - 50.00 100.00 150.00 200.00 250.00 300.00 350.00 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Capital and Stock Investment Funds Debt Instruments www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 133 Published by SCHOLINK INC. on host country’s economic growth is understated by at least 48%. In this research, we have taken a case study about Kosovo to estimate the impact of FDI on economic growth. The section below will be organized as follows: Chapter 2 contains the theoretical aspect about the FDI. Chapter 3 presents a review of literature describing the role of FDI in the economy. Chapter 4 contains the methodology and interpretation of the data and at the end, Chapter 5 includes conclusions and recommendations. 2. Theoretical Aspect FDI occurs when an individual or firm acquires controlling interest (typically defined as at least 10% ownership) in productive assets of another country. The study of FDI can be divided into two broad categories. The first is the inquiry into why multinational production occurs and the factors that determine the patterns of worldwide FDI. The second is the impact that FDI and MNEs have on the parent and host countries, including economic growth, returns to factors of production, and externalities for innovative activity (Blonigen, B.A.). The rapid growth of FDI has resulted from global competition as well as from the tendency to free up financial, goods and factor markets. It has been observed that FDI flows continue to expand even when world trade slows down. The choice between exporting and FDI depends on the following factors: opportunities for market growth, production cost levels, and economies of scale. FDI allows a firm to circumvent actual or anticipated barriers to trade. Another motive is the real appreciation of the domestic currency, which reduces the competitiveness of exports (Moosa, 2002). Different perspectives imply different classifications of FDI. From the perspective of the investing country, FDI can be classified into horizontal FDI, vertical FDI and conglomerate FDI (Caves, 1971) quoted in (Tvaronaviciene, Kalašinskaité, & Šimelyté, 2009). Vertical FDI is undertaken for the purpose of exploiting raw materials (backward vertical FDI) or to be nearer to the consumers through the acquisition of distribution outlets (forward vertical FDI), Moosa (2002). Horizontal investments replicate the complete production process of the home country in a foreign country. The horizontal FDI seeks to take advantages of a new large market, which is considered as traditional motive for the FDI (Botric & Skulic, 2005), quoted in (Kurtishi-Kastrati, 2013). Conglomerate FDI, involves both horizontal and vertical FDI (Moosa, 2002). Recognising that there are other reasons for FDI than differences in factor endowments and factor prices, trade economists have begun to embrace increasing returns, imperfect competition and product differentiation in addition to the traditional comparative advantage paradigm and where multinationals have been incorporated and made endogenous. The first attempts were by Helpman (1984) who integrated vertical multinationals and Markusen (1984) who integrated horizontal multinationals into the trade theory. Horizontal Multinational Enterprises (MNEs) dominate if nations are similar in size and relative endowments and if transport costs are high. Vertical MNEs appear with headquarters in the skilled labour abundant country, provided that transport costs are high enough, quoted in (Danja, 2012). www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 134 Published by SCHOLINK INC. Multinational enterprises (MNEs) are the focus of much attention as they are central players in the world economy. However, their scientific analysis constitutes a young discipline. Most studies on multinational enterprises (MNEs) begun in the 1960s, a period in which FDI was experiencing an enormous growth, which attracted economists’ attention. This was not, however, the first moment in which FDI had grown dramatically (Latorre, 2008). In the late 50s, FDI was explained in the framework of neoclassical theories (Buckley & Hymer, 2006), quoted in Tvaronaviciené, Kalašinskaité and Šimelyté (2009). The first formalisations of FDI tended to model it as capital (i.e., a production factor) moving across countries. This idea was a logical extension of the traditional theory of investment responding to differences in the expected rates of return on capital. This view, therefore, predicted that FDI would go from capital abundant countries (where its return was low) to capital scarce countries (where its return was high). Two early theoretical contributions in this line are Mundell (1957) and MacDougall (1960). The theories discussed above are based on the assumption of perfect competition in domestic factor and/or product markets. They belong to the traditional trade theory that has dominated for decades, based on competitive, constant-returns models, quoted in (Latorre, 2008). Hymer made a profound and enduring distinction between portfolio and direct foreign investment. The distinguishing feature between the two is that FDI implies control of the operation whilst portfolio foreign investment confers a share of ownership, but not control. This is important because the traditional theory of investment based on differential interest rates, after accounting for the risk premium, does not explain FDI. Hymer (1960) in profound empirical observation prepared the ground for a separate and separable theory of FDI. It was supported by the following facts: 1. There was little, or no, correlation between high interest rates and inflows of FDI. 2. Cross FDI occurred. Firms of country A were investing in country B at the same time (and often in the same industry) as country B’s firms were investing in country A. 3. Most FDI (in Hymer’s observation period) was undertaken by firms of one nationality—the USA. Thus, the motivation must be other than interest rate differentials. 4. There was distinct, definite pattern of industrial composition of FDI. Some industries were characterised by a great deal of FDI, others by little. And, FDI took place in both directions between countries simultaneously, quoted in (Buckley, 2006). However, over the years, economic, social and political factors, cultural aspects as well as government policies have all turned out to be equally significant in establishing a proper environment to attract FDI. The dynamic macroeconomic FDI theory suggests that FDI is a long term function of multinationals’ strategies. Time plays an important role and timing of investment depends on the macroeconomic environment at that particular period in the host country as well as its degree of openness and rate of economic growth. Risk perceptions also lie as a determinant (Sanjaya Lall, 1997), quoted in (Beghum, Sannassee, Seetanah, & Lamport, 2011). According to Hymer (1960 published in 1976) the reasons for internationalization of companies are of two kinds: variables associated to the company’s dimension and ownership of specific assets and variables resulting from the existence of market failures. Hymer demonstrated that FDI only takes www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 135 Published by SCHOLINK INC. place when the benefits of exploiting firm-specific advantages (FSAs) across borders allow overcoming the additional costs of doing business overseas. According to Hymer’s ideas, it has been argued that MNEs have firm specific advantages allowing them to operate profitably in foreign countries, quoted in (Kastrati, 2013). While FDI theory thus largely builds on assumptions of market imperfections, these assumptions have rarely been extended to explicitly include financial markets, or - when they have - focus has been on explaining the effect of exchange rates (rather than firm-level financial characteristics) on FDI (Kogut & Kulatilaka, 1994; Froot & Stein, 1991; quoted in Forssbaeck & Oxelheim, 2008). International production theory suggests that the propensity of a firm to initiate foreign production will depend on the specific attractions of its home country compared with resource implications and advantages of locating in another country. This theory makes it explicit that not only do resource differentials and the advantages of the firm play a part in determining overseas investment activities, but foreign government actions may significantly influence the piecemeal attractiveness and entry conditions for firms. A related aspect of this foreign investment theory is the concept of internalisation which has been extensively investigated by Buckley (1982, 1988) and Buckley and Casson (1976, 1985; quoted in Morgan & Katsikeas, 1997). Hymer’s analytical framework involved a focus on the superior profitability which he perceived internalisation would confer on firms: first from their ownership of, or access to, particular assets, competences, co-ordinating abilities; and second, from an increase in market power through the reduction of competition. Hymer treated these two benefits arising from control as being the same. He claimed that the control of the foreign enterprise is desired in order to remove competition between that foreign enterprise and enterprises in other countries (Hymer, 1976). This treatment is questionable. While any reduction of rivalry or inter-firm collusion are practices almost exclusively concerned with power-control, rather than with efficiency enhancement (Dunning & Pitelis, 2008; quoted in Dunning & Pitelis, 2009). Understanding the factors behind FDI has become an interesting research issue, mainly because, although with some misgivings, FDI is considered to be a key driver of economic growth. Consequently, there is a vast literature devoted to the study of FDI determinants and to explain the existence of significant disparities in the distribution of FDI flows across countries (Portilla, Maza, Villaverde, & Hierro, 2016). The eclectic paradigm (Dunning, 1981, 1988a, 1993a) offers a framework to explain patterns and the extent of international production undertaken by firms involved in foreign value adding activities. The eclectic paradigm suggests that the extent and nature of the overseas activities of a firm of a particular nationality depends on the extent to which they possess or can gain access to, technology, know-how, resources or some other form of income generating asset/s which their competitors either do not possess or do not have access to. These are referred to as ownership (O) specific advantages. Second, given that the firm possesses certain (O) advantages, to engage in FDI, it must consider it advantageous to own or control these value adding activities. These advantages are called internalization (I) specific advantages. Third, there must exist natural endowments or created www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 136 Published by SCHOLINK INC. assets in a foreign country that firms find beneficial to combine with or add value to their ownership advantages, rather than undertake the production in their home country. These are called locational (L) specific advantages, quoted in (Dunning & Narula 1993). Some commentators (e.g., Vernon, 1985) have alleged that the eclectic paradigm is couched in static terms and is unable to explain the dynamics or the process of change of international production. Dynamics can be interpreted and modelled in various ways; Vernon’s particular concern is that the eclectic paradigm fails to allow for the behavioural interaction between international oligopolists, which both affect and are affected by their foreign activities, quoted in (Dunning, 1987). Calvet (1981) explains the theories of FDI that included: FDI in the context of the theory of markets. The market imperfection theory asserts that market disequilibrium hypothesis provides an incentive to invest abroad. The factor markets such as labour and capital markets persuaded organizations to invest in other countries. The cheap labour persuaded firms to move investment from high labour cost to countries with low labour costs. The governments in the home countries imposed distortions such as policies, tariffs, prices and wage rigidities some of which led by trade unionised industries that impeded FDI, quoted in (Sikwila, 2014). Buckley and Casson (1976) identified five types of market imperfections that result in internalization: (a) the co-ordination of resources requires a long time lag: (b) the efficient exploitation of market power requires discriminatory pricing; (c) a bilateral monopoly produces unstable bargaining situations; (d) a buyer cannot correctly estimate the price of the goods on sale; and (e) government interventions in international markets creates an incentive for transfer pricing, quoted in (Nayak & Choudhury, 2014). Drawing upon strategic management, in which FDI strategy cannot be explained by straight-on economic reasoning or asset-based arguments, but requires viewing FDI as part of its broader context, e.g., allowing for managerial discretion or a firm’s competitive situation. The strategic management literature questions the view that MNCs react in similar ways on similar constraints and opportunities. The perspective brings to the fore the role of the manager in navigating through complexity to make decisions regarding global allocation of resources. Moreover, the perspective moves from a focus on the firm to a focus on interaction of firms (Nielsen, 2005; quoted in Hoenen & Hansen, 2009). However, the locational strategies actually chosen by firms are likely to be highly contextual; and to vary according to industry specific characteristics, the motives for FDI, and the functions being performed by MNE subsidiaries. According to Dunning, quite apart from the impact of the current economic slowdown and the events of September 11th, the internet, the widening scope of the knowledge based economy, and regional integration schemes are also affecting the geography of FDI. As to the role of governments as they seek to attract MNE activity, Dunning believes they need to recognise that the location specific advantages sought by mobile investors are changing. While in some countries, e.g., the larger developing countries, such traditional economic variables, e.g., the availability of cheap labour, natural resources and market size, remain important, in others, e.g. the more advanced industrialised countries, MNEs are increasingly seeking complementary knowledge www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 137 Published by SCHOLINK INC. intensive resources and capabilities, a supportive and transparent commercial, legal communications infrastructure, and a gamut of government policies favourable to globalisation, innovation and entrepreneurship (Dunning). Dunning (2000) has suggested that, for the most part, the many and varied explanations of the extent and structure of FDI and MNE activity are complementary, rather than substitutable for, each other, and are strongly context specific. The author has further observed that, as the international production by MNEs has grown and taken on new patterns, as the world economic scenario has changed, and as scholars have better understood the raison d’être for FDI, so new explanations of the phenomena have been put forward, and existing explanations have been modified and, occasionally, replaced. 3. Empirical Aspect Aim of Asteriou and Moudatsu (2014) was to examine whether the contribution of FDI on growth is relatively more important in countries with well-developed financial markets compared to those with the less-developed ones, including the time period from 1988-2009, using yearly macroeconomic data for a sample of 73 developing countries. Empirical methodology consists of panel-growth regressions. Results suggest that the FDI make substantial contribution to growth where financial systems function effectively, such as high-income countries, while the FDI impact is found to be insignificant in cases where relatively weaker financial systems exist. Authors also looked at the direct effect of the FDI and found that it is significant for the high and middle-income countries rather than for the low-income countries examined. Carkovic and Levine (2002) used the simple OLS regression for the period 1960-1995 in 72 different countries to re-evaluate the relationship between economic growth and FDI. Second, a dynamic panel procedure was used with average data over the five-year period, with seven possible observations for each country during the period 1960-1995. Also, the GMM estimator developed for dynamic panel data was used. After resolving biases plaguing past work, authors found that the exogenous component of FDI does not exert a robust, independent influence on growth. Acaravci and Ozturk (2012) empirically investigated the short-term and long-term causal relationship (Granger causality test) among economic growth, exports and FDI in ten transition European countries (Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic and Slovenia) by using quarterly data from 1994 to 2008. The ARDL bounds testing approach was used to investigate the existence of long-run relationship between FDI, export and economic growth for these countries. These causality results reveal that there is causal relationship between FDI, export and economic growth in four out of ten countries considered. The main results are as follows: 1) There is evidence of FDI-led growth in Czech Republic and Slovak Republic. 2) There is evidence of growth-led FDI for Latvia. 3) The causality runs from FDI to export only for Poland. 4) There is two-way causality between economic growth and export for Latvia and Slovak Republic. 5) There is two-way causality between export and FDI in Latvia. 6) There is no unique long-term or equilibrium www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 138 Published by SCHOLINK INC. relationship among real GDP, real export and FDI in Bulgaria, Estonia, Hungary, Lithuania, Romania and Slovenia. The main objective of Wach and Wojciechowski (2016) was to verify the impact of inward FDI on domestic entrepreneurship in four Visegrad countries in the years 2000-2012, using OLS regression. There is a statistically significant positive correlation between the stock FDI and the entrepreneurship rate, however the impact of FDI was different in different analysed countries—the strongest in Slovakia, while the weakest in Hungary. In the case of Poland and the Czech Republic, notable positive relationships between GDP and FDI stock per capita were found. In the Czech Republic and Slovakia, FDI/GDP ratio and FDI per capita is correlated strongly with the level of FDI, especially in Poland and Slovakia. Pandya and Sisombat (2017) examined the relationship between FDI and economic growth of Australia through regression analysis between FDI and different measures of economic growth from 2001 to 2013. The results highlight that FDI inflows contribute to the Australian economy including a growth in GDP, export performance and employment. Mining and quarrying has been identified as an attractive sector in which it has contributed to 7% of GDP, a large amount of capital has been invested and employed intensive labour. The result reflects absence of relationship between FDI and economic growth of Australia as two out of three variables show poor relationship with FDI. Torlak (2004) tested the FDI hypothesis as the best channel for technology transfer, not only across national boundaries but also between firms—in particular, between foreign and domestic companies for five transition countries in Eastern Europe using panel data on more than 8000 plants in the Czech Republic, Poland, Hungary, Romania and Bulgaria from 1993 to 1999 (For Hungary from 1994 to 2000). In a log-linear model, the Cobb-Douglas production function is estimated to examine the productivity effect of: a) foreign ownership in firms, and b) foreign presence in industries and regions. In the first case, regression coefficients indicate a positive correlation between foreign equity participation of forms and plant productivity. In the second case, the impact of foreign investment on productivity of domestically owned firms turns out to be either negative or insignificant. Thus, the study corroborates the hypothesis that technology is transferred internationally through multinational companies, but provides no evidence of diffusion of technology from foreign to domestic firms. Jude and Levieuge (2015) using a Smooth Regression Panel and the GMM model were helped to configure the existence of heterogeneity and identify an endogenous institutional quality threshold that influences the effect of FDI growth, using a sample of 94 developing countries during the period 1984-2009, with 11 institutional indicators. According to research results, institutional quality clearly modulates the effect of FDI on economic growth in developing countries. Results show that FDI alone has no significant effect on economic growth, while a favourable institutional environment induces a growth enhancing effect. This implies an elasticity of economic growth with respect to FDI that is time and country varying. Hanafy (2015) investigated the effect of sectoral FDI on economic growth in Egypt, using a novel www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 139 Published by SCHOLINK INC. panel dataset of 26 Egyptian governorates for the period 1992-2007. The author argued that one possible reason for the ambiguous effect is the use of aggregate FDI data across different sectors. The results show no significant effect of aggregate FDI stock in economic growth in Egyptian governorates, which can be partly explained by the contradictory growth effects of FDI at the sectoral level. Author finds a positive effect of manufacturing FDI, a negative effect of agricultural FDI and no significant effect of services FDI on economic growth. Buitrago and Leon (2015) analysed the effect of FDI on economic growth in Colombia and it was shown that these flows caused effects, both direct and indirect, in the national economy between 2000 and 2010, using OLS model. Results showed that FDI had a positive effect on the growth of the economy during this period. On the other hand, Gross Capital Formation (GCF) macro-economic variables and the financial portfolio were determinants of economic growth with positive effects. Likewise, the economic openness index and public expenditure explained the growth in production for the decade; however, the relationship was determined by negative signs, which could be explained by the short temporality used. Antwi, Antwi and Poku (2013) empirically determined the factors influencing FDI flows in Ghana, using the Time Series data from 1988 to 2011, and the OLS regression model. Macroeconomic variables such as inflation and per capita GDP have an impact on the FDI flows determinants in Ghana. The significance of the trade opening coefficient confirmed that foreign investment makes export-oriented investments in Ghana. The exchange rate coefficient is positive and significant at the level of .01. The infrastructure indicator is seen as negative and important. Gunby, Jin and Reed (2015) in this study conducted a research through regression that estimated the relationship between FDI and Chinese economic growth. The sample included 37 studies and a total of 280 estimates. The initial “raw” finding is that FDI has had a substantial, positive impact on Chinese economic growth. Furthermore, our results suggest that the effect is not inflated by endogeneity, nor impacted by publication bias. However, the positive effect is found to be smaller for more recent and better designed studies. When the authors adjusted for preferred study and sample characteristics, they found that the estimated economic effect of FDI on Chinese economic growth is much smaller than indicated by the overall literature, and statistically insignificant. Adegboyega and Odusanya (2014) tried to examine the relationship between trade openness, FDI, capital formation and economic growth rate in Nigeria over a period of 25 years (i.e., 1986 to 2011) by using time series data analysis. Also, the result of the study shows a long-term equilibrium relationship of the gross domestic growth rate and explanatory variables. The study shows a positive, but insignificant, relationship between the volume of FDI and the growth rate of gross domestic product. On the other hand, the opening of trade in capital formation also shows a positive effect on economic growth, while it is still statistically significant. Ekanayke and Ledgerwood (2010) analysed the effects of FDI on the economic growth of developing countries by using annual data on a group of 85 developing countries covering Asia, Africa, and Latin www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 140 Published by SCHOLINK INC. America and the Caribbean for the period 1980-2007, using panel data series for FDI, while accounting for regional differences in Asian, African, Latin American, and the Caribbean countries as well as the differences in income levels. While the findings of previous studies are generally mixed, the research results indicated that FDI has positive and significant effect on economic growth. When the model was estimated for different time periods and when the model was estimated for different regions, it indicated that FDI appears to have a positive effect on economic growth in developing countries. Finally, when the model was estimated for different income levels, FDI has a positive sign in three out of four cases. However, this variable is negative for low-middle-income countries indicating that foreign aid has a negative effect on economic growth in these countries. Borensztein, Gregorio and Lee (1997) tested the effect of FDI on economic growth in a cross-country regression framework, on FDI flows from industrial countries to 69 developing countries over the last two decades. Their results suggest that FDI is an important vehicle for the transfer of technology, contributing relatively more to growth than domestic investment. However, the higher productivity of FDI holds only when the host country has a minimum threshold stock of human capital. There is a strong positive interaction between FDI and the level of educational attainment. The authors also found some evidence that FDI is complementary to domestic investment. This effect, however, seems to be less robust than authors’ other findings. Mun, Lin and Man (2008) studied the relationship between FDI and economic growth in Malaysia for the period 1970-2005 using time series data and OLS regression. The results show that there are significant relationships between the economic growth and FDI inflows in Malaysia. FDI has direct positive impact on RGDP. Haseeb, Hartani, Bakar, Azam and Hassan, (2014) empirically investigated the relationship between exports, FDI and the economic growth in Malaysia. Records of annual time series data from the year 1971 till 2013 have been utilized for this purpose. ARDL model has been applied for the purpose of empirical investigation. The results support Exports Led Growth (ELG) and FDI-Led economic Growth (FLG) in Malaysia. Suleiman and Kaliappan (2013) studied the impact of FDI on economic growth for the Southern Africa Custom Union (SACU) countries namely; Botswana, Lesotho, Namibia, South Africa and Swaziland, employing panel data from the period of 1980-2010 and using Dynamic OLS. The findings reveal satisfactory evidence that there is a positive and significant impact of FDI on the economic growth for the SACU countries. Besides FDI, capital stock also contributes positively to economic growth of these countries. Muritala (2011) empirically examined the impact of investment and inflation on economic growth performance in Nigeria from 1981 to 2006 using econometrics model with OLS technique. In an attempt to establish long-run relationship between investment, inflation and economic growth, the result of the regression reveals that the coefficient of inflation is negative and significant at 10% while that of Gross Capital Formation (GCF) is positive and significant at 1%. A positive relationship also exists between investment (GCF) and RGDP (economic performance). Also, gross capital formation www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 141 Published by SCHOLINK INC. growth was positively related to GDP growth rate. Wang (2009), studied the heterogeneous effects of different sector-level FDI inflows on host country’s economic growth, employing data from 12 Asian economies over the period of 1987 to 1997, using the regression model, the empirical analysis included 12 Asian economies: Bangladesh, Mainland China, Hong Kong, India, Korea, Malaysia, Pakistan, Philippines, Singapore, Thailand and Taiwan. Research findings show that FDI in the manufacturing sector has a significant and positive effect on economic growth in the host economies. FDI inflows in the non- manufacturing sector do not play an important role in economic growth. Trinh (2015) examined the impact of FDI inflows into economic growth in Vietnam over the period 1990 to 2013 using Time Series analysis techniques. According to empirical results, FDI inflows, domestic investment, trade openness and secondary education have positive impacts on economic growth, while the inflation rate seems to have a negative effect. In addition, the impact of government consumption on economic growth is negative and statistically insignificant. Alfaro, Ozcan and Sayek (2009) investigated the effect of FDI on growth through financial markets by investigating whether this effect operates through factor accumulation and/or improvements in TFP (total factor productivity—where 62 countries are included), while 72 countries are involved in analysis. The analysis of results was carried out through the regression model. Factor accumulation—physical and human capital—does not seem to be the main channel through which countries benefit from FDI. Instead, the authors find that countries with well-developed financial markets gain significantly from FDI via TFP improvements. Shah (2014) studied the importance of many factors in developing countries as host countries for attracting foreign investors by using annual data for a panel of 90 developing countries during the period of 1980-2007. According to the author, it was found that population, sound macroeconomic management, exchange rate, and infrastructure availability have positive effects on FDI inflows, while high inflation, signalling economic disruption, hampers foreign investors. Also, with regard to language and geographic location, the results confirm that foreign firms prefer Anglophones, and are reluctant to invest in South Asia, MENA and Francophone countries. Anastassopoulos (2007) studied the reality of a country’s international competitiveness and its accumulation of inward FDI stock on a sample of European Union (EU)-15 Member-Countries for the period 2003-2006 which coincides with processes of enlargement, structural changes, increased global competition for EU, and pressure for relocation of their economic activities. South Member-Countries (SMCs) are examined separately from North Member-Countries (NMCs) taking into account structural and regional differences. Evidence suggests a heterogeneous response of FDI towards the two EU regions—considered as country groups—in the processes of globalization, as well as the discriminating effects of different aspects of competitiveness on FDI e.g. economic performance, government efficiency, government in influencing international competitiveness and consequently the levels of FDI is more important in SMCs than in NMCs. The distribution of inward FDI within the two groups of www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 142 Published by SCHOLINK INC. countries is uneven and has been highly concentrated within a relatively few countries, i.e. United Kingdom, France and Germany for NMC and Ireland for SMC. The determinants of FDI differ between NMCs and SMCs. NMCs’ accumulation of FDI mostly depends on their market size, government efficiency in reducing bureaucracy, openness and efficiency of the business sector. SMCs’ accumulation of FDI depends less on the importance of their market and more on the efficiency of the government and the reduction of investment risk. Factors that determine FDI inflows in terms of fiscal, economic, political and institutional dimensions, were empirically explored by Gedik (2013) on 11 OECD countries over the period 1995-2008, using the Dynamic Data Model Panel and GMM. Regarding the findings of the first model aimed at determining the corporate tax, individual tax and tax burden on work and FDI management relationship, FDI does not prefer high tax environments. In the second model, the growth of debt stock and inflation put a risk on investment. In addition, as high labour costs will increase costs, such an environment is not preferred to the investor. The coefficient of these three indicators found as a result of the analysis has a negative value, which is simultaneously parallel to theoretical forecasters. Also, political and institutional factors are of great importance to be considered along with economic and fiscal factors. 4. Data and Methodology The main objective of this study is to assess the impact of FDI flows on the growth and economic development of the Republic of Kosovo. In this empirical analysis, the secondary annual data provided by the Kosovo Agency of Statistics for the period 2007-2017 will be used. The multiple regression model for data analysis to assess the impact of FDI on economic growth is used in most of the empirical research, so we will use the QRM (Quantile Regression Median) regression model in this research. According to empirical literature, most studies have researched the total impact of FDI on economic growth, and many other researchers have pointed out that to accurately estimate the impact of FDI on growth and economic development, their disaggregation in the manufacturing and service or even in a particular sector should be done, where the number of such researches is much smaller. Taking this into account, we will use the impact of the total amount of FDI flows on the economic growth as a core model, while in the second model we will disaggregate FDI data into: FDI in manufacturing, FDI in services and other FDI (Tables 1, 2 and 3). Table 1. Data on Nominal GDP, Total FDI, Inflation, Exports and Imports (in Millions of Euros) Years Nominal FDI Total FDI Inflation Exports Imports 2007 3,379,441 440,700,000 4.40% 165,112 1,576,186 2008 3,710,746 369,900,000 9.40% 198,463 1,928,236 2009 4,076,997 287,400,000 -2.40% 165,328 1,937,539 2010 4,136,474 368,500,000 3.50% 295,957 2,157,725 2011 4,485,994 384,400,000 7.40% 319,165 2,492,348 www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 143 Published by SCHOLINK INC. 2012 4,891,000 229,100,000 2.50% 276,100 2,507,609 2013 5,232,860 280,200,000 1.70% 293,842 2,449,064 2014 5,391,751 151,200,000 0.40% 324,543 2,538,337 2015 5,795,498 308,800,000 -0.50% 325,294 2,634,693 2016 6,043,370 220,000,000 0.30% 309,627 2,789,491 2017 6,297,000 287,800,000 1.50% 378,010 3,047,018 Source: KAS (2018). Table 2. Nominal GDP, FDI in Manufacturing, FDI in Services, other FDI, Inflation, Imports and Exports (in Millions of Euros) Years Nominal GDP FDI Manufacturing FDI Services Other FDI Inflation Exports Imports 2007 3,379,441 131,900,000 292,000,000 16,900,000 4.40% 165,112 1,576,186 2008 3,710,746 109,800,000 237,100,000 23,000,000 9.40% 198,463 1,928,236 2009 4,076,997 121,900,000 162,400,000 3,200,000 -2.40% 165,328 1,937,539 2010 4,136,474 173,900,000 107,100,000 87,600,000 3.50% 295,957 2,157,725 2011 4,485,994 175,600,000 145,600,000 63,200,000 7.40% 319,165 2,492,348 2012 4,891,000 36,000,000 182,100,000 11,000,000 2.50% 276,100 2,507,609 2013 5,232,860 63,900,000 210,200,000 6,200,000 1.70% 293,842 2,449,064 2014 5,391,751 (31,700,000) 185,900,000 1,400,000 0.40% 324,543 2,538,337 2015 5,795,498 43,000,000 264,300,000 1,400,000 -0.50% 325,294 2,634,693 2016 6,043,370 18,300,000 202,100,000 (600,000) 0.30% 309,627 2,789,491 2017 6,297,000 34,800,000 246,630,000 1,500,000 1.50% 378,010 3,047,018 Source: KAS (2013, 2017, 2018) and calculation of authors (2018). Table 3. FDI by Activity (in Millions of Euros) Investments by Sector Years Sectors Value 2007-2017 Agriculture 32,000,000.00 2007-2017 Mines (17,400,000.00) 2007-2017 Industry 490,000,000.00 2007-2017 Energetics 106,800,000.00 2007-2017 Construction 389,200,000.00 2007-2017 Trade Services 126,000,000.00 2007-2017 Hotels and Restaurants 20,600,000.00 2007-2017 Transport and Communication 267,700,000.00 2007-2017 Financial Services 566,200,000.00 2007-2017 Real Estate, Leasing and Bus. Activities 1,211,400,000.00 2007-2017 Other Sevices 48,000,000.00 2007-2017 Other Unclassified Bus. Activities 214,800,000.00 * Data for the energy sector as well as hotels and restaurants are missing for 2010. Source: KAS (2018). www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 144 Published by SCHOLINK INC. The econometric model used is as follows: ∆GDP=β1+ β2∆INV aggregate+β3∆INF + β4∆EXP + β5∆IMP + u Where GDP shows the annual GDP at constant prices expressed in millions of euros, β1 is the parameter for intercept, INV aggregate represents the real value of foreign direct investments expressed in millions of euro, which are expected to have a negative impact, INF is the inflation rate obtained from the price range index (from 2015 = 100 - base year), which is expected to have a negative value, EXP and IMP represent exports and imports, also expressed in millions of euros, where exports are expected to have a negative impact and imports a positive impact and u - is the unexplained part. To estimate the effect of FDI on the economy, the value of the coefficients “p” of independent variables is of 5 percent significance. GDP is taken as a variable dependent on this model, while as independent variables are INV Totals, INVs in manufacturing and services, INF, EXP and IMP. 4.1 Results of the Analysis and Their Interpretation Table 4. Statistical Analysis NOMINAL GDP TOTAL FDI INFLATION EXPORTS IMPORTS Mean 4858285. 3.03E+08 0.025636 277403.7 2368931. Median 4891000. 2.88E+08 0.017000 295957.0 2492348. Maximum 6297000. 4.41E+08 0.094000 378010.0 3047018. Minimum 3379441. 1.51E+08 -0.024000 165112.0 1576186. Std. Dev. 977369.2 84126195 0.034653 70311.97 427814.1 Skewness 0.002256 -0.117152 0.667940 -0.593081 -0.346420 Kurtosis 1.724954 2.304302 2.661119 2.126853 2.359191 Jarque-Bera 0.745141 0.246993 0.870565 0.994292 0.408221 Probability 0.688961 0.883825 0.647082 0.608264 0.815372 Sum 53441131 3.33E+09 0.282000 3051441. 26058246 Sum Sq. Dev. 9.55E+12 7.08E+16 0.012009 4.94E+10 1.83E+12 Observations 11 11 11 11 11 Source: Calculation of authors (2018). In Table 4, we have the statistical description obtained with the dependent variables, i.e., GDP and independent variables - total amount of foreign direct investments, inflation, export and import as: average, median, maximum, minimum and other results as described above. The Jarque - Bera test - according to the rule of the decision if Jargue Bera ≤ 4.61, at 5% of significance level, then in our analysis Jarque Bera is 0.745141, which means that the value 0.745141 ≥ 4.61. www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 145 Published by SCHOLINK INC. Table 5. Regression Results Dependent Variable: NOMINAL GDP Method: Quantile Regression (Median) Date: 08/03/18 Time: 20:13 Sample: 2007-2017 Included observations: 11 Huber Sandwich Standard Errors & Covariance Sparsity method: Kernel (Epanechnikov) using residuals Bandwidth method: Hall-Sheather, bw = 0.43686 Estimation successfully identifies unique optimal solution Variable Coefficient Std. Error t-Statistic Prob. C 650078.5 2102073. 0.309256 0.7676 TOTAL FDI -9.72E-05 0.003115 -0.031184 0.9761 INFLATION -7667747. 8910401. -0.860539 0.4225 EXPORTS -3.763435 9.256082 -0.406591 0.6984 IMPORTS 2.367073 1.350142 1.753203 0.1301 Pseudo R-squared 0.802721 Mean dependent var 4858285. Adjusted R-squared 0.671201 S.D. dependent var 977369.2 S.E. of regression 365476.0 Objective 884878.7 Quantile dependent var 4891000. Restr. objective 4485414. Sparsity 1159522. Quasi-LR statistic 24.84151 Prob(Quasi-LR stat) 0.000054 Source: Calculation of authors (2018). The multiple regression method used estimates the impact of total FDI flows on economic growth. As for the total of FDI, the effect is negative and insignificant at 5% level of significance for the period 2007-2017. The determination coefficient of 0.80 indicates that the model is well defined and that 80 percent of the variation in the dependent variable depends on the variation of independent variables. The inflation rate coefficient is negative and insignificant at 5 percent level of significance. Also, exports are negative and insignificant, while imports have a positive effect with a 2.367073 share but insignificant. F-statistics (0.000054) indicates that the model is well-adjusted. To estimate whether the research results are significant, we have also used the Anova analysis (Table 6). For F = 29. 78344901, “p” value for 29.78344901 is 0.000425093, which means that this statistical analysis is significant. www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 146 Published by SCHOLINK INC. Table 6. ANOVA Test Regression Statistics Multiple R 0.975731173 R Square 0.952051323 Adjusted R Square 0.920085538 Standard Error 276293.9363 Observations 11 ANOVA df SS MS F Significance F Regression 4 9.09448E+12 2.27362E+12 29.78344901 0.000425093 Residual 6 4.5803E+11 76338339226 Total 10 9.55251E+12 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 200745.2431 1090816.994 0.184032009 0.860050507 -2468387.786 2869878 -2468388 2869878.3 Total FDI 6.1249E-05 0.001606431 0.038127363 0.970823064 -0.003869546 0.003992 -0.00387 0.003992 Inflation -6537234.726 3251842.061 -2.010317415 0.091114438 -14494205.6 1419736 -1.4E+07 1419736.2 Exports -0.772708962 3.522968285 -0.219334635 0.833660589 -9.393101811 7.847684 -9.3931 7.8476839 Imports 2.11950078 0.649073519 3.265424824 0.017132037 0.531275095 3.707726 0.531275 3.7077265 Source: Calculation of authors (2018). In Table 7, the correlation analysis shows that GDP has a negative correlation with total FDI and inflation. The results show that GDP has a strong positive correlation with exports and imports. Also, exports and imports have a high correlation between them. While total FDI has a negative relationship with imports and exports. Table 7. Correlation Analysis CORRELATION Nominal GDP Total FDI Inflation Exports Imports Nominal GDP 1 Total FDI -0.672000906 1 Inflation -0.523279897 0.611191331 1 Exports 0.835773666 -0.435174082 -0.16950316 1 Imports 0.949359741 -0.603396842 -0.32782831 0.920906092 1 Source: Calculation of authors (2018). From Annex 1 can be seen that the foreign investment and GDP direction is not the same, but even though since 2012 there is a decline in investment, GDP growth does not decrease, which means that www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 147 Published by SCHOLINK INC. investments do not affect GDP growth. The decline in the inflation rate affects GDP growth. Also, the growth of exports and imports has a positive effect on GDP. In addition to the analysis of the impact of the aggregate FDI flows on economic growth, we have also analysed the allocation of total FDI in manufacturing and services to determine their impact on the economy, also using the QRM (Quantile Regression Median). The annual data from the Kosovo Agency of Statistics and authors’ calculations are also used in this model for the period 2007-2017. The econometric model used is as follows: ∆GDP=β1+ β2∆INV manufacturing+β3∆INV service + β4∆INF + β5∆EXP + β6∆IMP + u Also in this model dependent variable is GDP, while independent variables are - FDI in manufacturing, FDI in services, inflation, exports and imports for the period 2007-2017. Also, in Annex 2 we have the statistical description of dependent variables and independent variables. Table 8. Regression Results Dependent Variable: NOMINAL GDP Method: Quantile Regression (Median) Date: 08/03/18 Time: 00:57 Sample: 2007-2017 Included observations: 11 Huber Sandwich Standard Errors & Covariance Sparsity method: Kernel (Epanechnikov) using residuals Bandwidth method: Hall-Sheather, bw = 0.43686 Estimation successfully identifies unique optimal solution Variable Coefficient Std. Error t-Statistic Prob. C -954289.8 1692124. -0.563960 0.6029 FDI IN MANUFACTURING -0.004917 0.005381 -0.913789 0.4125 FDI IN SERVICES 0.005407 0.004419 1.223526 0.2883 OTHER FDI 0.015415 0.020912 0.737135 0.5019 INFLATION -7480624. 4532614. -1.650399 0.1742 EXPORTS -6.791383 10.29313 -0.659798 0.5454 IMPORTS 2.914291 1.501688 1.940677 0.1243 Pseudo R-squared 0.914033 Mean dependent var 4858285. Adjusted R-squared 0.785081 S.D. dependent var 977369.2 S.E. of regression 237519.6 Objective 385599.6 *The value of coefficients “p” of independent variables is of 5 percent significance. Source: Calculation of authors (2018). www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 148 Published by SCHOLINK INC. The method used estimates the flow of FDI in manufacturing and services and their impact on economic growth. The results of analysis show that FDI in manufacturing is of a negative and insignificant effect at the 5% level of significance for the period 2007-2017. The determination coefficient of 0.91 indicates that the model is well-defined, indicating that the 91 percent of the variation in the dependent variable depends on the variation in independent variables. While FDI in services and other FDI are with positive effect taking part with 0.005407 and 0.015415 but statistically insignificant. The inflation rate and export rate variable coefficients are with negative and insignificant effect. Also, the import variable has a positive effect taking part with 2.914291 but statistically insignificant. To assess whether the research results are significant, we have also used Anova analysis (Annex 3). For F = 49. 62349854, the “p” value for 49.62349854 is 0. 001035849, which means that this statistical analysis is significant. In Annex 4, the correlation analysis shows that GDP has a negative correlation with FDI in manufacturing, other FDI and Inflation. Also, GDP has a very weak correlation with FDI in services. The results show that GDP has a strong positive correlation with exports and imports. Also FDI in manufacturing and services has a negative relationship with imports and exports. FDI in manufacturing has a positive correlation with other FDI, while FDI in services has a negative correlation with other FDI. Also, exports and imports have a strong relationship with each other. 5. Conclusions and Recommendations The main objective of this study is to estimate the flow of FDI and its impact on economic growth and development, using secondary annual data from 2007 to 2017 in the Republic of Kosovo. The data were analysed using the QRM (Quantile Regression Median) with “p” value of 5% significance. The results of the study showed that total FDI has a negative and insignificant effect on economic growth. Inflation and exports have a negative and insignificant effect. While for imports, the effect is positive taking part with 2.367073, but the impact is insignificant. As for the disaggregation of total FDI, there is a negative and insignificant relationship for FDI impact in manufacturing. While for FDI in services and other FDI, the effect is positive, taking part with a very low value of 0.005407 and 0.015415, but with insignificant impact. Also, inflation and exports are negative and insignificant, while imports have a positive effect, taking part with 2.914291, but not important for the economy. One of the main factors that has affected decline of Kosovo in foreign investment in recent years is the lack of political stability in the country. Regarding the impact of foreign direct investment on economic growth, the results of this study do not match the empirical literature that total FDI impact on economic development in developing and transition countries, but our survey results match the empirical literature that FDI does not have a positive effect on low-income countries. Also, according to FDI decomposition empirical literature, FDI in manufacturing impacts on economic development, while the results of our study show the www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 149 Published by SCHOLINK INC. opposite that FDI in manufacturing does not have a positive effect on the economy, while FDI in manufacturing and other FDI have a positive effect but without significant impact. This positive effect of FDI in services is due to the fact that foreign banks in Kosovo account for 90.0 percent of capital within the total capital of all the banks operating in the country and the successful business activity of the banking system. Since FDI is an important source of capital in developing and transition countries, as in the case of Kosovo, policy makers have to do policy reforms, improve infrastructure and law on investments, and increase trade performance. According to Pandya and Sisombat (2017), export performance is an indicator of the country’s ability to attract FDI to the country. Also, various fiscal favourable conditions should be offered, where they are still considered as barriers for foreign investors in Kosovo. According to Owusu-Antwi, Antwi and Poku (2013), every aspect of host countries’ economic and governance practices affects the investment climate. According to KAS (2018), the unemployment rate in Kosovo is 26.5 percent, so considering that FDI can affect employment growth, the government should attract foreign investments, especially in the manufacturing sector, in order to reduce unemployment in the country. Due to the importance of FDI flows in Kosovo, future research should also focus on FDI study in every economic sector. It is also important that research be expanded, including other variables such as: different institutional factors and human capital. 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Wang, M. (2009). Manufacturing FDI and Economic Growth: Evidence from Asian Economies (Vol. 41, No. 8, pp. 1-23). Appendix Annex 1. Flows of Total FDI, Inflation, Exports and Imports in GDP Nominal GDP TOTAL FDI INFLATION EXPORTS IMPORTS www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 153 Published by SCHOLINK INC. Annex 2. Statistical Description of GDP, FDI in Manufacturing, Services, other FDI, Inflation, Exports and Imports Annex 3. Regression Analysis Regression Statistics Multiple R 0.993349685 R Square 0.986743598 Adjusted R Square 0.966858994 Standard Error 177926.857 Observations 11 ANOVA Df SS MS F Significance F Regression 6 9425874305321 1.57098E+12 49.62349854 0.001035849 Residual 4 126631865705 31657966426 Total 10 9552506171027 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 17730.89354 918405.1019 0.019306179 0.98552149 -2532170.456 2567632.243 -2532170.456 2567632.243 IHD-Prodhim -0.001508826 0.002550095 -0.591674383 0.585889528 -0.008589026 0.005571374 -0.008589026 0.005571374 IHD-Shërbim 0.003132546 0.002390008 1.310683994 0.260151598 -0.003503181 0.009768272 -0.003503181 0.009768272 IHD-Tjera 0.001536459 0.010219836 0.150340837 0.887772188 -0.026838356 0.029911274 -0.026838356 0.029911274 Inflacioni -6494153.378 2593242.535 -2.504259933 0.066463381 -13694148.92 705842.165 -13694148.92 705842.165 Eksportet 0.663551418 4.796600186 0.138337863 0.896658195 -12.65394569 13.98104853 -12.65394569 13.98104853 Importet 1.80533566 0.72009195 2.507090463 0.066262812 -0.19396011 3.80463143 -0.19396011 3.80463143 GDP MANUFACTURING SERVICES OTHER INFLATION EXPORTS IMPORTS www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 2, No. 4, 2018 154 Published by SCHOLINK INC. Annex 4. Correlation Analysis CORRELATION Nominal GDP FDI Manufacturing FDI Services Other FDI Inflation Exports Imports Nominal GDP 1 FDI Manufacturing -0.741177028 1 FDI Services 0.119490726 -0.328541868 1 Other FDI -0.472855109 0.776834229 -0.629475538 1 Inflation -0.523279897 0.515510539 0.016220425 0.542021842 1 Exports 0.835773666 -0.442672133 -0.148218481 0.026630615 -0.1695032 1 Imports 0.949359741 -0.60204117 -0.062731912 -0.258859435 -0.3278283 0.920906092 1 Annex 5. Flows of FDI in manufacturing, services and other FDI, inflation, exports and imports in GDP Nominal GDP INFLATION EXPORTS IMPORTS FDI in Manufacturing FDI in Services Other FDI