21. The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: qi = 16.907 +0.322ki + 2.777li R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5% 4.939971 ☐ Var B 0.216639 0.031857 -0.857446 -0.057229 0.166070/ where q: fitted values of naturals logarithms of output (output express in 1000 tons); ki: natural logarithms of capital output (output express in 1000 tons) li: natural logarithms of labour (labour is in hours) RSS: residual sum of squares 1: firm index Var ẞ: variance - covariance matrix of estimates a. Evaluate the statistical significance of the coefficients.
21. The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: qi = 16.907 +0.322ki + 2.777li R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5% 4.939971 ☐ Var B 0.216639 0.031857 -0.857446 -0.057229 0.166070/ where q: fitted values of naturals logarithms of output (output express in 1000 tons); ki: natural logarithms of capital output (output express in 1000 tons) li: natural logarithms of labour (labour is in hours) RSS: residual sum of squares 1: firm index Var ẞ: variance - covariance matrix of estimates a. Evaluate the statistical significance of the coefficients.
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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Transcribed Image Text:21. The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields:
qi = 16.907 +0.322ki + 2.777li
R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5%
4.939971
☐
Var B 0.216639
0.031857
-0.857446
-0.057229 0.166070/
where q: fitted values of naturals logarithms of output (output express in 1000 tons);
ki: natural logarithms of capital output (output express in 1000 tons)
li: natural logarithms of labour (labour is in hours)
RSS: residual sum of squares
1: firm index
Var ẞ: variance - covariance matrix of estimates
a.
Evaluate the statistical significance of the coefficients.
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