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AEB 6184 – Direct Estimation of Cost Functions Elluminate 11 Formulation of the Cobb-Douglas Cost Function Starting with the basic Cobb-Douglas production function formulation min w1 x1 w2 x2 x1 , x2 s.t. Y A0 x1 x2 Forming the Lagrangian L x w1 1 L w1 x1 w2 x2 Y A0 x1 x2 L w 2 x2 Y 0 x1 Y 0 x2 Solving for x1 in terms of x2 Y x w1 w2 Y 1 x2 w2 x2 x1 x2 x1 w1 Substituting this result into the production function and solving for x2 w w A0 2 x2 x2 y 0 Y A0 2 x2 x2 w1 w1 Y A0 w1 x2 w2 Y x2 Y , w1 , w2 A0 1 w1 w 2 Input demands and cost function Y x1 Y , w1 , w2 A0 1 1 w2 w 1 Y w1 x2 Y , w1 , w2 A w 2 0 1 Y w2 C Y , w1 , w2 w1 A w 1 0 1 w Y 2 A 0 w1 w 2 Estimation Defining a two equation system 1 Yt 1t A0 , , Ct w1t A0 1 Yt 2t A0 , , x1t A0 w2t w 1t 1 w Yt 2t A 0 w1t w 2t w2t w 1t Next, we construct an error matrix with 45 rows and 2 columns A , , A , , 11 0 21 0 A , , A , , 12 0 22 0 A0 , , A , , A , , 1N 0 2N 0 Maximum likelihood estimation is then T A0 , , A0 , , min L A0 , , ln A0 , , 2 T The variance matrix for the estimates is given by the Hessian matrix at the optimal value by the Cramer-Rao lower bound. Estimation using the KLEM dataset Parameter A0 Estimate 0.1485 Std. Dev. 0.1756 T-Ratio 0.8456 0.7386 0.8456 0.2868 0.4288 2.5751 1.9722 Exercise Extend the Cobb-Douglas function two four inputs and refit the KLEM data. Implement the same estimation for the Constant Elasticity of Substitution function.