Panel data analysis of the relationships between selected economic variables and capital flows in OECD and G-20 countries

The aim of this thesis is to examine the effects of capital movements on economic growth and real efffective exchange rate (REER) in OECD and G-20 Countries. In the first chapter of the thesis, the types, the causes and consequences of capital flows are discussed. In the second chapter, we investigate the effects of foreign direct investment, portfolio investments and remittance inflows on the REER in OECD countries and the key partners of OECD, consisting of developed countries, over the period of 2002 and 2014 by using Random Effects Model. When the OECD and the key partner countries are classified as developed and developing countries, the capital inflows to the developing countries increase the value of REER; but, they don't have significant effect on the REER for developed countries. In the third chapter, the effects of net capital flows (NKF) on annual per capita GDP growth between 1985 and 2014 in the G-20 countries are examined as a function of GDP per capita (natural logarithm), the share of government consumption in GDP, the share of gross domestic investments in GDP, the openness, the average schooling rate and the share of private credits in GDP as an indicator of financial development, dummy variable for the effects of the 2008 global crisis and interaction term for effect of financial development level of economies on NKF by using Generalized Method of Moments (GMM). The results of the study indicate that NKF has negative effect on economic growth in the G-7 countries and G-20 countries which have current account surplus. However, it has a positive effect on the economic growth of the G-20 countries other than G-7 and G-20 countries experiencing with current account deficits. The overall results of the study have some implications for policies using the capital inflows as a main input to increase the economic growth. Keywords: Capital Movements, Real Exchange Rate, Net Capital Flow, Panel Data Analysis, GMM Estimator