The Following data is given for the period 1999-2003 Interest rate Inflation i π 1999 4.7 4.4 2000 4.6 5.4 2001 6.3 5.7 2002 4.8 4.6 2003 2.9 2.4 According to Fisher Equation “a rise in inflation also rises the nominal interest rate by the same amount”. Construct a regression model by determining dependent and independent variables according to this theory. Obtain residuals of the regression. Calculate variance of the residuals and the standard errors of the parameters (note: use the table above for calculations, just write down the final results here). Test significance of the slope parameter (the parameter of the independent variable) at 5% significance level. Is it in line with the proposition?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
- The Following data is given for the period 1999-2003
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Interest rate |
Inflation |
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i |
π |
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1999 |
4.7 |
4.4 |
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2000 |
4.6 |
5.4 |
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2001 |
6.3 |
5.7 |
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2002 |
4.8 |
4.6 |
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2003 |
2.9 |
2.4 |
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- According to Fisher Equation “a rise in inflation also rises the nominal interest rate by the same amount”. Construct a regression model by determining dependent and independent variables according to this theory.
- Obtain residuals of the regression. Calculate variance of the residuals and the standard errors of the parameters (note: use the table above for calculations, just write down the final results here).
- Test significance of the slope parameter (the parameter of the independent variable) at 5% significance level. Is it in line with the proposition?
- Evaluate the overall significance of the model with R2 and F test
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