(a) Assume we have the following model: Yt = a + Bxt + Et where the explanatory variable x, is strictly exogenous, and the residual &z is serially correlated (i) What is autocorrelation function in time series? [2 Marks] (ii) Why does the existence of autocorrelation in the residual is a problem? Please provide a detailed answer. [3 Marks] (b) What causes heteroscedasticity? How to mitigate this problem? [4 Marks] (C) How to deal with multicollinearity? [3 Marks] (d) Suppose you have been given the following ordinary least squares (OLS) regression result. Ordinary Least squares Estimation Dependent variable is v 31 observations used for estimation from 1985 to 2015 Regressor Coefficient 7.1681 . 12644 1.2646 .18269 -8.3752 -.99549 .18403 Standard Error 12.8824 .085314 .90206 .37266 4.1019 .64254 .18057 T-Ratio[Prob] .55643[.593) 1.48211.077] 1.4018[.029] .49023[.037] -2.0418[.075] -1.5493[.160] 1.0192[.338] E D R-Squared S.E. of Regression Mean of Dependent variable Residual Sum of squares Akaike Info. Criterion DW-statistic .89772 .037326 .042959 .011146 49.8741 3.0242 R-Bar-Squared .65480 F-stat. EL 19 8) 3.6956[.032] S.D. of Dependent Variable .063530 Equation Log-likelihood 69.8741 Schwarz Bayesian Criterion 36.5521 Where, V = Economic activities K = Capital L = Labour E = Energy consumption T = Trade openness F= Financial development D= Domestic investment (i) Write the regression equation and briefly explain. [3 Marks Which explanatory variables are significant at the 1%, 5% and 10% level? Which variables are insignificant? [3 Marks] (iii) Based on the OLS regression result, interpret the R2 and R2. [4 Marks] (iv) Based on the OLS regression result, interpret Durbin-Watson result. [3 Marks]