Suppose you want to estimate the causal impact of Honors degree-given to students graduated with a Cumulative Grade Point Average (CGPA) 3.00 or above out of 4.00-on labor market earnings 10 years after graduation. You have access to a large individual-level dataset of individuals graduated on a given year (i.e., on the same year). You observe the labor market earnings (w) of those individuals 10 years after graduation and their CGPAs (x). a) Suppose you run an OLS regression of the natural logarithm of labor market earnings on a dummy variable indicating whether the individual has the award or not (for your entire sample). Can you obtain the causal impact of the award on earnings in this regression? Why? Explain carefully b) Now you are implementing an RDD analysis to estimate the causal effect of an Honors degree on earnings. Which variable is the forcing (or assignment) variable? Plot a reasonable figure assuming linearity c) What are the main assumptions for your RDD to be valid? d) How would you test whether the individuals are randomly distributed around the threshold? [Hint: suppose you also observe a large set of individual-level characteristics]