Include a minimum of 5 (five) explanatory variables in the regression equation and provide a scatter plot of your dependent: Basic Econometrics Research Report Group Assignment, RMIT, Singapore, Singapore

QUESTION 1

Please model the drivers of GDPpc using R:

1. 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 modelling, explain each of your functional form specification choices with respect to:

• 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

A. Interpret the coefficients on 5 explanatory variables. Describe if the coefficients are elasticities or semi-elasticities, or simple level coefficients.

(5 marks)

B. Interpret the statistical significance of these coefficients using the p-values OR the t-stat.

C. Test for heteroscedasticity in R using the Breusch-Pagan test and copy below the results. Interpret the results of the Breusch Pagan test.

D. Present the results from a) using HAC robust errors! Did any of the standard errors change significantly?

E. Explain The Gauss Markov Assumptions (2.5 marks), and whether these are likely to hold in your model? (2.5 marks)

F. 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

G. Present a functioning R code reproducing your results below!

(3 marks)