Potential Nonlinear Relationships – Economics Assignment Help

Assignment Task

Task

What determines life expectancy?

For this home assignment you will be required to model life expectancy worldwide. 

Please use the file: life_expectancy.Rdata. Please read the description at the end of this document to understand the variables.  In this home assignment we are going to model life expectancy at birth (dependent variable). 

QUESTION 1.

Please model the determinants of life expectancy using R: We ask that you create the log of life expectancy at birth for modelling purposes! 

a) Include a minimum of 5 (five) explanatory variables in the regression equation. One of your explanatory variables must be the log of GDP per capita! Please exclude any form of the variable “government expenditure on education”!  Please provide a scatter plot of your dependent and independent variables (5 scatter plots). 

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? 
• Multicollinearity – are the independent variables multicollinear?
• Functional form specification- potential nonlinear relationships, eg: log-linear or quadratic relationships. Explain why you use a linear or logarithmic form of a variable. 

This  part a must have 1 Table [regression output from R ] & Explanations,  5 scatter plots. 

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

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.  This part must have 1 Table & Explanations

d) Present the results from a) using HAC robust errors!  Did any of the standard errors change significantly? This part must have 1 Table & Explanations

e) Re-estimate your model using an instrumental variable (IV) regression instead of OLS.  Please take the log of government expenditure on education as the instrument for the log of GDPpc. All other variables should remain the same in the model.  Present the regression results.  

Interpret the coefficient on log GDPpc. How is it different to that in section a)? 

f) Please determine if the log of government expenditure on education is a good instrument for the logarithm of GDPpc (in question f) or not.  Support your results with a regression output (Hint: between the endogenous variable and the instrument)! 

g) Explain in what situations it is recommended to use an instrumental variable regression, explain its benefits. Name the 3 conditions that must be fulfilled by the instrument in order to obtain unbiased results!  

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