The double-log model is: Ln(Price) = + 1*Ln(sqrft) + 2*Ln(lotsize) + Estimate this model in Gretl and paste the output here. Model 2: OLS, using observations 1-80 Dependent variable: l_price Coefficient Std. Error t-ratio p-value const 5.46295 0.592455 9.221 <0.0001 *** l_sqrft 0.751917 0.0791123 9.504 <0.0001 *** l_lotsize 0.156508 0.0368685 4.245 <0.0001 *** Mean dependent var 12.56503 S.D. dependent var 0.295147 Sum squared resid 2.382482 S.E. of regression 0.175901 R-squared 0.653802 Adjusted R-squared 0.644810 F(2, 77) 72.70805 P-value(F) 1.84e-18 Log-likelihood 27.04027 Akaike criterion 48.08055 Schwarz criterion 40.93447 Hannan-Quinn 45.21548 5. Consider a 2000 square foot house with a 9000 square foot lot. Find its predicted price using both the linear and double-log models. Show your calculations. a) Linear model: Price = 10,307.7 + ... b) Double-log model: Note - use Excel to calculate natural logs. Excel: "=ln(2000)" returns 7.6001; . "=ln(9000)" will return 9.1049 Given a natural log, use the exponent function to find the antilog, e.g. Excel: "=exp(9.1)" returns 8955. l_price = 5.462 +