Class problem set 5 solution

# Class problem set 5 solution - Use data GREENE7_8 for the...

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Use data GREENE7_8 for the following exercise. Consider the following 2 models: Model 1: G = β 0 + β 1 Pg + β 2 ln(Y) + β 3 Pnc + u Model 2: ln(G) = β 0 + β 1 Pg + β 2 ln(Y) + β 3 Pnc + u 1- Estimate both models Model 1: OLS, using observations 1960-1995 (T = 36), Dependent variable: G Coefficient Std. Error t-ratio p-value const 2439.72 97.0238 25.1456 <0.0001 *** Pg 14.8629 2.18229 6.8107 <0.0001 *** Ln(Y) 294.64 11.1949 26.3192 <0.0001 *** Pnc 9.46017 4.80699 1.9680 0.0578 * Mean dependent var 226.0944 S.D. dependent var 50.59182 Sum squared resid 1158.124 S.E. of regression 6.015926 Model 2: OLS, using observations 1960-1995 (T = 36), Dependent variable: ln(G) Coefficient Std. Error t-ratio p-value const 9.26779 0.397036 23.3424 <0.0001 *** Pg 0.0491644 0.00893025 5.5054 <0.0001 *** Ln(Y) 1.63414 0.0458111 35.6713 <0.0001 *** Pnc 0.0681561 0.0196709 3.4648 0.0015 *** Mean dependent var 5.392989 S.D. dependent var 0.248779 Sum squared resid 0.019394 S.E. of regression 0.024618 2- Make a prediction for average G from model 1 when Pg=3, Y=10,000, and Pnc=2. Construct a 95% prediction interval. Interpret the results. Regress G = θ 0 + β 1 (Pg-3) + β 2 (ln(Y) - ln(10000)) + β 3 (Pnc-2) + u, Estimate of intercept for this model is the prediction for G for the given values.

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