66 THE IMPACT OF FOREIGN DIRECT INVESTMENT ON GDP AND AGRICULTURE IN KOSOVO: AN EMPIRICAL STUDY Fatjona PARALLANGAJ ¹ University “UKSHIN HOTI” Prizren, Faculty of Life and Environmental Science, MSc. Student, fatjona.parallangaj@outlook.com Article history: Submission 11 December 2022 Revision 27 March 2023 Accepted 17 April 2023 Available online 30 April 2023 Keywords: FDI, Economic Growth, Agriculture. DOI: https://doi.org/10.32936/pssj.v7i1.412 A b s t r a c t This study examines the effect of FDI on economic growth and agriculture in Kosovo in the years 2010-2021. To quantify the effects of the explanatory variables on the explanatory variables, data was generated for the variables collected by the World Bank and the Kosovo Statistical Agency. The results of analysis (OLS robust) show is performed with two models. Two models, OLSR1 and OLSR2, were developed to analyze the impact of independent variables on GDP and agriculture. OLSR1 found agriculture land and government expenditure positively affect GDP, while OLSR2 found GDP positively affects agriculture land, while inflation has a negative impact. The negative coefficients for FDI, interest rate, and government expenditure in OLSR2 suggest they negatively impact agriculture land but are not significant. The results have important implications for policymakers in Kosovo, who aiming to attract more FDI and boost economic development. 1. Introduction One of the most significant areas of an economy is foreign direct investment because of the impact it brings. Specifically, to commercialization and globalization, FDI is a source of funding and a driving force behind economic development in underdeveloped nations. For many countries, especially developing and transition countries, FDI has been an important component of country’s development initiatives. FDI is a crucial step in the process of integrating the world's economies and is motivated by market liberalization, international competition, and technological development. They have an impact on both the investing and host nations. Academics and policymakers frequently make the case that developing nations should draw in FDI to boost economic growth by giving local businesses access to direct capital funding and beneficial productivity externalities (Alfaro & Matthew, 2012). In many nations throughout the world, FDI has become increasingly important in driving economic development and prosperity. In recent years, particularly in emerging countries, there has been increased interest in the relationship between FDI, GDP, and agriculture. FDI is currently a major factor in the expansion and growth of the economy of Kosovo. The link in Kosovo between Investment, GDP, and agriculture has attracted greater attention. The aim of this study is to empirically examine the effect of foreign direct investment on both the economic growth (GDP) and the agricultural sector in Kosovo. The study aims to determine how much FDI impacts economic development and growth, as well as how it specifically affects the country's agriculture sector. By analyzing the connection between FDI and GDP and agricultural growth, Understanding the possible benefits and drawbacks of FDI in Kosovo will be improved by the findings of this study, and provide insights into how the government and policymakers can best leverage FDI to support sustainable economic growth and agricultural development. This paper has the following format. The study’s relevant literature is reviewed in Part 2. Part 3 covers the methodology for the study and analyzes the data and sources of the variables. The study’s empirical findings are justified economically in Part 4 of the paper. The discussion and conclusions reached in Part 5 are outlined considering the paper’s results. mailto:fatjona.parallangaj@outlook.com https://doi.org/10.32936/pssj.v7i1.412 https://orcid.org/0009-0003-6721-6201 67 2. Literature Review Foreign direct investment (FDI) is an investment abroad by a company or individual from another country. In many countries, FDI has played a significant role in the growth and prosperity of the economy. The relation between FDI and economic growth has been the topic of several studies. Foreign direct investment is now widely acknowledged to have a significant role in both the industrial development of developed and emerging nations as well as contributing to economic growth, for example through raising overall factor effectiveness (Bartels & Crombrugghe, 2009). Evidence suggests that the Nigerian economy’s market size or GDP, attracts foreign direct investment due to increased production leading to an increase in FDI inflows by about 2.35% (Maku, 2015). Several emerging nations have seen exceptional economic growth thanks to foreign direct investment. In general, FDI not only expands capital supply, but can also accelerate technology transfer, subject to host country’s regulations. Technology transfer contributes to human resource development, that in turn can increase opportunities for economic progress. In other words, FDI can use both direct and indirect channels to promote economic growth (Anwar & Nguyen, 2010). Foreign direct investment has a favorable and statistically significant influence on economic growth in MENA nations, according to Omri (2014). Using panel data for Latin America, Bengoa and Sanchez-Robles (2003) examined the relationship between foreign direct investment, economic freedom, and economic development. They concluded that foreign direct investment has a significant positive effect on host country economic growth by comparing fixed and random effects estimates. Research has also been conducted on how foreign direct investment affects economic expansion. For example, a study by Akinlo (2004) found that foreign direct investment has a positive impact on economic growth in Nigeria. To assess if foreign direct investment fosters economic growth, Jyun-Yi and Chih-Chiang (2008) used a threshold regression analysis. Their research demonstrates that FDI alone does not clearly contribute to economic growth based on a sample of 62 nations evaluated between 1975 and 2000. They concluded that the first most significant elements influencing foreign direct investment were GDP and human capital. Foreign direct investment has a favorable and considerable impact on growth when the host nations have higher GDP and human capital. Mehic and Babic- Hodovic (2013) examined the impact of foreign direct investment (FDI) on economic growth in Southeast European transition countries. The empirical study covers seven countries in Southeast Europe and spans the years 1998 to 2007. The estimation model chosen by the authors is the Prais-Winsten regression with panel-adjusted standard errors. The main finding of the study is that FDI has a positive and statistically significant impact on economic growth. The impact of FDI is statistically significant and strong when domestic investment is considered. Çakërri (2019) argues that FDI has a significant impact on the economic growth and development of the host country. In theory, foreign direct investment should promote economic growth in the host country by facilitating knowledge transfer, boosting local investment, and creating employment opportunities. Thus, this link has been discussed by many authors both theoretically and experimentally. A beneficial effect of FDI on GDP has been noted. Alfaro et al. (2004) assert that FDI may boost local businesses’ productivity, transfer technology and information, and foster rivalry in host nations, all of which contribute to higher economic growth. In a similar vein, Lipsey (2004) discovered that FDI may improve local businesses’ productivity and expand the export potential of host nations. According to a study by Borensztein et al., (1998) FD investment is beneficial for economic development, particularly in underdeveloped nations. According to a study by Santangelo (2018), there are different effects depending on the investor's place of origin on FDI in agricultural land in emerging countries, a fact that sometimes- called land grab. Due to institutional pressure from the home country regarding respect for human rights and responsible management of agricultural land, in addition to positive spillover effects, direct land investment by investors from developed countries has a positive impact affect the availability of food by expanding the area used for agricultural production. Lack of investment by firms and governments has led to lower rates of productivity growth and output stagnation in many emerging nations since the agricultural sector has long been disregarded as a source of development and a means of eradicating poverty (Oloyede 2014). Also, to have a comprehensive understanding of the issue, the authors’ empirical scientific research on foreign direct investment, GDP, and agriculture is evaluated (Javorick, 2004; Furtan & Holzman, 2004; Alvaro et al., 2006; Mottaleb, 2007; Falki, 2009; Denisia, 2010; Louzi & Abadi, 2011; Adefabi, 2011; Lipsey & Sjöholm, 2011; Dritsaki, C. & Dritsaki, M., 2012; Amendolagine et al., 2013; Dritsakis & Stamatiou, 2014; Kilic, Bayar & Arica, 2014; Kukaj & Ahmeti, 2016; Epaphra & Mwakalasya, 2017; Siddique et al., 2017; Sertoglu, Ugural, & Bekun, 2017; Bunte et al., 2018). The findings of the many research analyzed have demonstrated a relationship between foreign direct investment, economic growth and agriculture. 68 3. Methodology This study will use a quantitative research design as the method of investigation. Secondary data will be used to conduct the study. GDP and agriculture in Kosovo will be the study's dependent variables. FDI will be the independent variable. The analysis will involve government expenditure, interest rates, and inflation as control variables. Data was collected by the World Bank (WB) and the Kosovo Statistics Service (KAS) to assess the impact of the independent variable on the dependent variable. Primary and secondary data were used in the data gathering process. Data were analyzed using the STATA statistical software. We have adopted general form of multiple regression model: y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + 𝜖 • y = the predicted value of the dependent variable • β0 = the y-intercept (value of y when all other parameters are set to 0) • β1X1 = the regression coefficient (β1) of the first independent variable (X1) (the effect that increasing the value of the independent variable has on the predicted y value) • ΒnXn = the regression coefficient of the last independent variable • 𝜖 = model error 4. Research Results Econometric techniques are used to examine the data. Using panel data regression analysis, the study will examine the relationship between FDI, GDP, and agriculture in Kosovo. 4.2. Descriptive Statistics A summary of descriptive research statistics is shown in Table 1. Depending on the data set displayed, the minimum, maximum, mean, and standard deviation values are displayed. Based on the descriptive statistics presented from Table 3, we can see that the mean GDP value is 22.668 with a std.dev., of 0.148, indicating values that are relatively close to the mean. The minimum and maximum values are 22,399 and 22,965 respectively. A standard deviation of.2 and a mean value of 12.806 indicate that agricultural land values are significantly dispersed. 12.503 and 12.949 are the minimum and highest values, respectively. With a std.dev., of.301 and a mean value of 19.647, the FDI indicates that the values are often near to the mean. 19.113 and 20.098 are the lowest and highest numbers, respectively. Table 1. Descriptive Statistics Variable Mean Std. Dev. Min Max GDP 22.668 .148 22.399 22.965 Agriculture land 12.806 .2 12.503 12.949 FDI 19.647 .301 19.113 20.098 Inflation 2 2.122 -.537 7.336 Int rate 6.934 2.1 4.41 11.427 Gov exp 28.384 3.019 24.92 34.3 Source: calculated by the author 41 and 11.427 are the minimum and maximum values, respectively. Government spending has a mean value of 28.384 and a std.dev. of 3.019, which shows that the values are well dispersed. 24.92 and 34 are the least and highest values. 4.2. Correlation Analysis Table 2 shows a correlation matrix between variables, which is used to test the relationship between variables. According to the correlation results, agriculture land has a 0.701 correlation coefficient and is connected positively with GDP. This suggests that countries with more agricultural land tend to have higher GDP. 69 Table 2. Matrix of correlations Variables (1) (2) (3) (4) (5) (6) (1) GDP 1.000 (2) Agriculture_land 0.701 1.000 (3) FDI -0.048 -0.472 1.000 (4) Inflation -0.135 -0.649 0.646 1.000 (5) Int_rate -0.610 -0.577 -0.183 -0.038 1.000 (6) Gov_exp -0.123 -0.671 0.569 0.498 0.396 1.000 Source: calculated by the author FDI and GDP have a -0.048 correlation coefficient, which is a negative relationship. This suggests that countries with higher FDI tend to have lower GDP, although the correlation is weak. Inflation is negatively correlated with GDP and FDI, with the correlation coefficients being -0.135 and -0.649 respectively. This suggests that higher inflation tends to be associated with lower GDP and less FDI. GDP, agricultural land, and foreign direct investment are all inversely connected with interest rates, with correlation values of -0.610, -0.577, and -0.183, respectively. This indicates that lower GDP, fewer agricultural land, and lower FDI likely to be related to higher interest rates. The correlation coefficients between government expenditure and GDP and inflation are -0.123 and -0.671, respectively. This suggests that higher government expenditure tends to be associated with lower GDP and higher inflation. 4.3. Regression Analysis In the table below (table 3) we can see results from OLSR1 model that examines the relationship between independent variables (Agriculture, FDI, Inflation, Interest Rate and Government Expenditure) and a dependent variable (GDP). The coefficients in the table indicate the estimated impact of the individual independent variables on the dependent variable. Table 3. Summary of econometric models Variable/Model OLSR1 OLSR2 Agriculture 0.984* -3.3 FDI -0.0489 -0.0184 (-0.42) (-0.17) Inflation 0.0335 -0.0381** -1.84 (-3.95) Int_rate -0.00617 -0.0147 (-0.32) (-1.37) Gov_exp 0.0306* -0.022 -2.87 (-1.92) GDP 0.692** -4.61 _cons 10.13 -1.723 -1.74 (-0.34) N 12 12 Mean VIF 3.62 3.62 Hettest 0.8955 0.8955 Source: calculated by the author t statistics in parentheses * p<0.05, ** p<0.01, *** p<0.001 70 The asterisk (*) next to the coefficient for Agriculture and Government Expenditure indicates that these coefficients are statistically significant at the 5% level, suggesting that there is strong evidence to support a relationship between these variables and GDP. The agriculture has a positive impact to GDP, so for every 1% of growth in agriculture, we will have economic growth of 0.984%. Government expenditure have a positive impact in GDP, implying that for every 1% of growth in government expenditure, the GDP will increase for 0.03%. The _cons term represents the intercept term in the regression model and indicates the estimated value of GDP when all independent variables are equal to zero. In this case, the intercept is estimated to be 10.13. In the OLSR2 model, we can consider agriculture as the explanatory variables as well as the controlled variables as GDP, FDI, inflation, interest rates and government spending. GDP coefficient is positive (0.692) and has statistical significance, showing that GDP increases by 1%, agriculture increases by 0.692%. The inflation coefficient is also negative (-0.0381) and statistically significant (-3.95), implying that a 1% increase in inflation corresponds to a 0.038 increase in agriculture. The coefficient of FDI is negative (-0.0184), the coefficient of interest rate is negative (-0.0147), the coefficient of government expenditure is negative (-0.022). However, the t-statistic suggests that this coefficient is not statistically significant. Regarding to the findings of the VIF test, the outcomes have been examined for multicollinearity, as shown in the table (3.62), we consider that the problem of multicollinearity does not appear in the data. From testing for heteroskedasticity with the Breusch Pagan test (P=0.8955), the error term has constant variance, so the data are homoscedastic and the problem of heteroskedasticity is not present. 5. Conclusion and Discussion In summary, this study intends to investigate how FDI affects Kosovo's Economy and agricultural sector. The study looked at the connection between FDI, GDP, and agriculture using a quantitative research approach and regression analysis. The research will expand existing understanding of how FDI influences economic growth and development in developing nations and will give policymakers information on the variables that affect how FDI affects GDP and agriculture. The review of the literature predicts that foreign direct investment will significantly affect the growth and expansion of the host countries’ economies. According to the general theory, FDI promotes technology transfer, increases domestic investment, and creates job opportunities that contribute to the host country’s expanding economy. Correlation matrix shows that there are significant correlations between GDP and several independent variables, including agriculture land, FDI, inflation, interest rate, and government expenditure. To investigate the impact of these independent variables on GDP and agriculture, the OLSR1 and OLSR2 models were developed. The OLSR1 model shows that farmland and government spending have a statistically significant positive effect on GDP. Specifically, a 1% increase in agriculture corresponds to a 0.984% increase in GDP, while a 1% increase in government spending corresponds to a 0.03% increase in GDP. These results suggest that investment in agriculture and public spending can lead to economic growth in the countries studied. The OLSR2 model suggests that GDP and inflation have significant impacts on agriculture. A 1% increase in GDP corresponds to a 0.692% increase in agricultural land area, while a 1% increase in inflation corresponds to an increase in agricultural land area of 0.038%. The negative relationship between inflation and farmland suggests that higher inflation rates may harm agricultural production. The negative coefficients for FDI, interest rate, and government expenditure in the OLSR2 model suggest that these variables have a negative impact on agriculture land, but these coefficients are not statistically significant. Additionally, there appears to be no multicollinearity or heteroskedasticity issues in the data. Hence, these results are in line with and consistent with some earlier investigations, including (Owutuamor & Arene, 2018). The following suggestions can be made in light of the analysis' findings: Encourage investment in agriculture: Given the positive impact of agriculture land on GDP, policymakers should consider promoting investments in agriculture. This could involve providing incentives for farmers and agribusinesses, improving access to credit and infrastructure, and investing in agricultural research and development. Increase government spending: The positive impact of government expenditure on GDP suggests that policymakers should consider increasing public spending in areas such as education, healthcare, and infrastructure. However, care should be taken to ensure that public expenditure is concentrated in sectors that are most likely to contribute to economic growth. Monitor inflation: The negative impact of inflation on agriculture land suggests that policymakers should monitor inflation rates and take measures to control inflation if necessary. This could involve implementing monetary policies such as interest rate adjustments or fiscal policies such as reducing government spending. Encourage foreign investment: While the negative impact of FDI on GDP is weak, policymakers should still consider promoting foreign investment to diversify the economy 71 and create employment opportunities. This could involve providing incentives for foreign investors, improving infrastructure and the business environment, and promoting trade and investment agreements. Continuously monitor and analyze economic trends: Policymakers should continuously monitor and analyze economic trends to make informed decisions. This could involve regularly updating the correlation matrix and regression models, as well as conducting additional research to explore the causal relationships between variables. Overall, these findings suggest that investments in agriculture and government spending could lead to economic growth in Kosovo. 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