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By: www.sampleassignment.com Global Trade and Markets Assignment 3 Trimester 2, 2009 Submitted By: Due Date: 04/010/2009 Abstract This paper addresses the argument against the foreign direct investment and political constraint. Using regression analysis on four different countries, low correlation, if not, an insignificant relationship between the economic and foreign direct investment was found. This is followed by the discussion on FDI and political risk. Finally, a general non-market framework for political risk assessment is presented. This is followed by discussing relationship between FDI and political risk. Introduction In this paper, we used linear regression model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an independent variable (polconV,cpi & gdp), and the other is considered to be a dependent variable (FDI). Before attempting to fit a linear model to observed data, we first determined whether or not there is a relationship between the variables of interest. (Yale, 1998) With the development of international business, the study of corruption and its effects has received increased concentration recently. International development agencies are concerned that financial aids meant to help economic development and the poor may be wasted by corrupt government officials. (Kwok C, Tadesse S, 2009) not available on the World Bank website. Also, CPI values were available only from 1998-2007 on the Transparency International website for India, USA and Australia. However, we have used whatever data was available to get the best possible regression output. The observations for India were less and thus do not give a very clear picture of testing the hypothesis. For Hypotheses 2, the Upper Critical Values of the Student's-t Distribution have been used to analyse the results (Engineering Statistic Handbook, n.d). Regression Analysis: Regression Analysis is performed so that we can characterize the association of one variable with other variables of interest. The regression model that is used is a simple linear relationship between y and x1 and x2. It is of the form: y = a + b1x1 + b2x2 + e a represents the point which shows the value of y assuming x=0. b1 and b2 partial effects of the corresponding x’sand indicate the degree to which y would change when x changes by one unit. E measures the degree of error in the estimation of the above relationship. The model specification is: FDI = a + b1 (GDP) + b2 (POLCONV) + e a) Australia Coefficients: T – Stat: tells you how much confidence you can have in this estimated relationship. P – Value: The P-Value for GDP and FDI is insignificant as the values are more than 0.01 GDP - The relationship between GDP and FDI is very significant (E-05). PolconV - it is less than 55 thus there is a 55% chance that the relationship between PolconV and FDI is not significant. b) India The above data shows that FDI is not affected to a great extent by political risk in India. There may be other factors that may affect FDI. R Square:This explains that there is 71.3% of variance in y. F – Test: Value 11.209. With Significance= Coefficients: T – Stat: tells you how much confidence you can have in this estimated relationship. P – Value: The P-Value for PolconV is insignificant where as for GDP it is extremely significant. GDP - it is less than 55 thus there is a 55% chance that the relationship between GDP and FDI is not significant. PolconV - it is less than 30 thus there is a 30% chance that the relationship between PolconV and FDI is not significant. c) Mexico To get the full project, please buy the Assignment by using this Link http://sampleassignment.com/ Cost - £29 End
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