Determinants of Foreign Direct Investment: A panel data analysis of the MINT countries
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
One of the most visible signs of the globalization of the world economy is the increase of Foreign Direct Investment (FDI) inflows across countries. This past decade the trend of FDI has shifted from developed countries to emerging economies, which is most notably in the BRICS countries. However, as BRICS reputation has been damaged these past years due to its weak growth outlook in the early 2010s, investors are shifting to the new economic grouping acronym, the MINT (Mexico, Indonesia, Nigeria and Turkey) countries for better future prospects of FDI destination. Since the MINT countries have emerged as a popular destination of FDI, it is necessary to investigate what are the key factors that make these four countries attractive as FDI destinations. Hence, this paper analyzes what are the determinants of inward FDI into the MINT countries during the time period from 1990 to 2014. To be able to answer the research question and demonstrate the effect of the seven independent variables (market size, economic instability, natural resources availability, infrastructure facilities, trade openness, institutional stability and political stability) on FDI as a dependent variable, the study uses a panel data analysis. The data is based on secondary data, which is collected from the World Bank dataset. The empirical finding from the study illustrates that market size, economic instability, infrastructure facilities, trade openness, institutional stability, and political stability are significant as determinants FDI inflows to the MINT countries, meanwhile, natural resources availability appears to be an insignificant determinant of FDI inflows to the MINT countries.
Place, publisher, year, edition, pages
2016. , 56 p.
Foreign Direct Investment, FDI, emerging economies, developing countries, MINT countries, determinants of FDI inflow, panel data analysis
IdentifiersURN: urn:nbn:se:uu:diva-296664OAI: oai:DiVA.org:uu-296664DiVA: diva2:939333
Master Programme in Business and Management