The Relationship Between Income, Inflation, And Foreign Direct Investment In Paraguay, Turkey, And China
This is a paper for my International Finance Class. Krayola, I have worked with you in the past and you seem very good on statistics and business math so I wanted to contract with you again.
The paper is almost done. However, I need you to rewrite a prediction, summary, and conclusion for this paper using the attached regression data.
I’m looking at the correlation between GDP and the variables Foreign Direct Investment (FDI) and Inflation. The paper is on how GDP is affected by FDI and inflation
Here is a quick sketch of what I want (this is just a guide):
Prediction:
1) As FDI increases the GDP will increase. GDP and FDI are positively correlated.
2) Most economists think that a small amount inflation is good for the economy (cite source). Too much inflation is bad and deflation is bad. If inflation is gradually increasing my prediction is that GDP will increase because a small amount inflation is a sign of a healthy economy. GDP and Inflation are positively, correlated
3) Inflation and FDI are important components of a strong economy (growing GDP), my prediction is that together FDI and Inflation are statistically significant correlates of GDP
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Results:
I’ve already pulled the regression work for you. It is in the attached “Regression Data File.”
There are about 10 tabs of regression in total. Tabs are
China
-China GDP and Inflation
-China GDP and FDI
-China GDP and FDI+Inflation
Turkey
-Turkey GDP and Inflation
-Turkey GDP and FDI
-Turkey GDP and FDI+Inflation
Paraguay
-Paraguay GDP and Inflation
-Paraguay GDP and FDI
-Paraguay GDP and FDI+Inflation
Look through the tabs. First look at the “Inflation China” tab. I’ve highlighted in yellow the most important data.
For each regression I want you to briefly explain the 1) R2 2) Adjusted R2 3) Significant F 4) Coefficient and 5) P-Values. In the introduction please explain what these values mean in regression
Explain what these values mean
As a guide, here are some notes about what these values mean:
R2 and Adjusted R2: should be above .5%
Significant F: should be below .05
Coefficients: its a sign of impact one variable has on another
P-Value: should be below .05 percent
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Conclusion: summarize results
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Lastly please include the attached screenshots in the paper (The professor requested this).
Also, put the excel regression data into an appendix at the end of the essay
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