Quadratic Production Function  Estimate a quadratic production function where Q = output; L = labour input; K = capital input. Is the estimated production function “good”? Why or why not?   Cobb-Douglas Production Function (10) Estimate the Cobb-Douglas production function Q ¼ αLβ1Kβ2, where Q = output; L = labour input; K = capital input; and α, β1, and β2 are the parameters to be estimated. For the Cobb-Douglas production function, test whether the coefficients of capital and labour are statistically significant. For Cobb-Douglas production function, determine the percentage of the variation in output that is explained by the regression equation. For Cobb-Douglas production function, determine the labour and capital estimated parameters, and give an economic interpretation of each value. Determine whether this production function exhibits increasing, decreasing, or constant returns to scale. (Ignore the issue of statistical significance.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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  1. Quadratic Production Function 
  1. Estimate a quadratic production function where Q = output; L = labour input; K = capital input.
  2. Is the estimated production function “good”? Why or why not?

 

Cobb-Douglas Production Function (10)

  1. Estimate the Cobb-Douglas production function Q ¼ αLβ1Kβ2, where Q = output; L = labour input; K = capital input; and α, β1, and β2 are the parameters to be estimated.
  2. For the Cobb-Douglas production function, test whether the coefficients of capital and labour are statistically significant.
  • For Cobb-Douglas production function, determine the percentage of the variation in output that is explained by the regression equation.
  1. For Cobb-Douglas production function, determine the labour and capital estimated parameters, and give an economic interpretation of each value.
  2. Determine whether this production function exhibits increasing, decreasing, or constant returns to scale. (Ignore the issue of statistical significance.

 

 

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