Problem 1 (a) Obtain time series of real GDP and real consumption for a country of your choice. Provide details. b) Display time-series plots and a scatterplot (put consumption on the vertical axis). (c) Convert your series to growth rates in percent, and again display time series plots. (d) For each series, , provide summary statistics (e.g., mean, standard deviation, range, skewness, kurtosis, ..). (e) Run a simple OLS linear regression in R and interpret its coefficient estimates. (f) Interpret goodness-of-fit metrics for OLS linear regression. (g) Relate R2 with correlation coefficient. Problem 2 Monte Carlo experiment: Consider the following model: Yi = B1+ ByXi + ui You are told that 81 = 25, 82 = 0.5, 02 = 9, and u; ~ N(0, 9). Assume uj ~ N(0, 9), that is, u; are normally distributed with mean 0 and variance 9. Generate 10 sets of 64 observations on u; from the given normal distribution and use the 64 observations on X given in Table 2 , to generate 100 sets of the estimated & coefficients (each set will have the two estimated parameters). Take the averages of each of the estimated & coefficients and relate them to the true values of these coefficients given above. What overall conclusion do you draw