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The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: q₁ = 16.907 + 0.322k₁ + 2.777l₁ R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5%

The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: q₁ = 16.907 + 0.322k₁ + 2.777l₁ R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5%

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter7: Production Economics
Section: Chapter Questions
Problem 8E
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Question 6 The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: = a. 16.907 + 0.322k; + 2.777lį R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5% Var ß = 0.166070 0.031857 0.216639 -0.857446 -0.057229 4.939971/ where : fitted values of naturals logaritrhms of output (output express in 1000 tons); ki: natural logaritrhms of capital output (output express in 1000 tons) li: natural logaritrhms of labour (labour is in hours) RSS: residual sum of squares 1: firm index Var ß: variance covariance matrix of estimates Evaluate the statistical significance of the coefficients. Page 4 of 12 b. A regression on the original regressors, q² and a constant term yields the following statistics: R² = 0.296041 F = 1.177507 coeff of ² has a t-statistic of 2.876 (i) With this information, which test can you implement to deal with the problem omitted variables and why? (ii) Implement the test as stated in b(i) and interpret the results. (iii) What is (are) the consequence(s) of the problem alluded to above on the estimators?
Transcribed Image Text:Question 6 The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: = a. 16.907 + 0.322k; + 2.777lį R² = 0.915 DW = 2.032 RSS = 0.461 Use a = 5% Var ß = 0.166070 0.031857 0.216639 -0.857446 -0.057229 4.939971/ where : fitted values of naturals logaritrhms of output (output express in 1000 tons); ki: natural logaritrhms of capital output (output express in 1000 tons) li: natural logaritrhms of labour (labour is in hours) RSS: residual sum of squares 1: firm index Var ß: variance covariance matrix of estimates Evaluate the statistical significance of the coefficients. Page 4 of 12 b. A regression on the original regressors, q² and a constant term yields the following statistics: R² = 0.296041 F = 1.177507 coeff of ² has a t-statistic of 2.876 (i) With this information, which test can you implement to deal with the problem omitted variables and why? (ii) Implement the test as stated in b(i) and interpret the results. (iii) What is (are) the consequence(s) of the problem alluded to above on the estimators?
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