University | RMIT University (RMIT) |
Subject | Econometrics Assignment |
Econometrics Assignment, RMIT, Singapore: Include a minimum of 5 (five) explanatory variables in the regression equation and provide a scatter plot
QUESTION 1
Please model the drivers of GDPpc using R:
Include a minimum of 5 (five) explanatory variables in the regression equation and provide a scatter plot of your dependent and independent variables (5 scatter plots). (0.5 x 5 marks)
We suggest that you take the natural log of the dependent variable!
When modeling, explain each of your functional form specification choices with respect to:
- The economic or common sense behind the model – why do you pick this variable? (0.5 x 5 marks)
- Multicollinearity – are the independent variables multicollinear? (0.5 x 5 marks)
- Functional form specification- potential nonlinear relationships, eg: log-linear or quadratic relationships. Explain why you use a level or logarithmic form of a variable. (0.5 x 5 marks)
in writing. You will be graded on model accuracy in this section. Pay attention to appropriate degrees of freedom!
Use OLS standard errors.
- (Subtotal: 10 marks) 1 Table [regression output] & Explanations, 6 scatter plots
- Interpret the coefficients on 5 explanatory variables. Describe if the coefficients are elasticities semi-elasticities, or simple level coefficients.
- Interpret the statistical significance of these coefficients using the p-values OR the t-stat.
- Test for heteroscedasticity in R using the Breusch-Pagan test and copy below the results. Interpret the results of the Breusch Pagan test.
1 Table & Explanation - Present the results from a) using HAC robust errors! Did any of the standard errors change significantly?
(3 marks) 1 Table & Explanations
- Explain The Gauss Markov Assumptions (2.5 marks), and whether these are likely to hold in your model? (2.5 marks)
(Subtotal: 5 marks) - Explain the basic concept of an instrumental variable estimation, and when to use it. (2 marks)
What are the criteria for a good instrument? (2 marks)
Can any of the variables in the dataset be in a reverse causal relationship with the dependent variable? If yes, identify please. (2 marks)
What could be used as an instrument to remedy this? (1 mark)
(Subtotal: 7 marks)
- Present a functioning R code reproducing your results below!
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