(d) Test the variables for stationarity. Provide your results for the following variables in the table below (please add rows where necessary): (6) Variable Model Lags ADF test statistic T, IT LRVAT Trend and Intercept Intercept None INF Trend and Intercept Intercept None Statistically significant at the: 10% level (*), 5% level (**), 1% level (***) You can assume that all other variables are non-stationary, integrated of order I(1). (ii) Based on your findings in the table above, comment on the order of integration of the VAT and INF variables, (2) (e) Test for possible cointegration between variables: Estimate the following long-run cointegration equation and use your results to complete the table. (3) VAT= f (HCE, M3) Dependent variable: LRVAT, Variable Coefficient LRHCEL LRM3 CONSTANTt (ii) Evaluate the potential long-run equation. Do the estimated coefficients correspond to your a priori expectations in terms of sign? Explain. (2) (iii) Generate the residual series: RES_VAT. Demonstrate, how you can use the residual series to test if cointegration exists between the variables in the long run model. Provide all details of the test(s) you perform and their criteria