Room: 404

Time: 14:15 - 15:45
Session Chair: Tran Nhu Quan, NIDA Business School

Governance, Competitiveness and Economic Performance in Attracting Foreign Direct Investment Inflow
Md. Ali, National Institute of Development Administration
The underlying purpose of the study are to examine empirically using cross sectional data of 70 FDI receiving countries and implication of global competitiveness and human development indicators as factor affecting foreign direct investment inflow and to examine the governance and economic performance as determinant of FDI inflow and to suggests policy measures to improve FDI inflow. FDI can play a vital role for the economic development of developing countries. The empirical study of 70 FDI receiving country using panel data regression model during 2009-2014 and analysis would suggest the determinants of FDI especially the non-economic factors that affect the growth of FDI. The empirical result from the study would suggest that the countries do have high per capita income and domestic savings and other better domestic economic performances tend to receive more FDI. The non-economic performances of both the regions would suggest that the countries do have better governance in terms of government effectiveness, property rights and better control of corruption, political stability and better regulatory quality can attract more FDI. The countries in SAARC region needs to improve institutional effectiveness, human development and competiveness more than the ASEAN countries in order to receive more FDI.

A Nexus between Economic Variables and USD-INR Exchange Rate
Karthikeyan Parthasarathy, Kongu Engineering College
Mohanasundaram Thangamuthu, Kongu Engineering College
The main aim of this study is to find out the relationship between exchange rate and external economic variables. This study deals with the external factors that influencing the exchange rate of USD-INR. The data of these variables are collected from the official websites of NSE, RBI, PPAC and DIPP. The data have collected from the period January 2004 to December 2015. Eviews and SPSS are the statistical packages used in this study. Descriptive statistics and Jarque-Bera test used to find the mean, median and standard deviation. To meet the forecasting objective ARCH-EGARCH model has been used. Before developing this model normality test, auto correlation test and Heteroskedasticity test are used to test the residuals.