Read the R outputs below using cigarette data set and answer questions, where LNC is log consumption; LNP is log price; LNY is log income. > # Run an OLS regression >ols summary (ols) Call: 1m (formula LNC-LNP+LNY) Coefficients: (Intercept) LNP LNY Estimate Std. Error t value Pr(>|t|) 0.9089 4.730 2.43e-05 *** 0.3246 -4.123 0.000168 *** 0.1968 0.876 0.385818 4.2997 -1.3383 0.1724 Signif. codes: 0** 0.001 0.01 0.05 0.11 (a) From the Breusch-Pagan test output below, discuss whether the error term in regression model ols is homoskedastic or heteroskedastic. Clearly write down the null/alternative hypothesis and your conclusion. > bptest (ols) studentized Breusch-Pagan test data: ols BP 6.5936, df = 2, p-value 0.037 (b) If we rejects the null hypothesis of a Breusch-Pagan test, i.e., Assumption 2 turns out to be violated, is the OLS estimator in ols unbiased? consistent? efficient? (c) Suppose we find heteroskedasticity in the regression model, what shall we do to correct it? Clearly write down the steps in details (such as what transformation is needed; what parameters need be estimated).