The document presents the results of estimating a Cobb-Douglas production function for 20 firms. It finds that capital and labor inputs are statistically significant determinants of output. It then notes that running the regression on just output and a constant term yields a lower R-squared and coefficient t-statistic above the critical value. This suggests there may be omitted variables biasing the original regression. Addressing this would make the estimates less reliable.

1. The estimation of a Cobb-Douglas production function for 20 firms of a given industry yields: ql=
16.907+0.322ki+2.777li R2=0.915DW=2.032RSS=0.461Use=5% Var^=0.1660700.031857
0.8574460.2166390.0572294.939971 where qt : 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 l: firm index
Var^: variance - covariance matrix of estimates a. Evaluate the statistical significance of the
coefficients. [10 marks] b. A regression on the original regressors, q^t2 and a constant term yields
the following statistics: R2=0.296041F=1.177507coeffofq^t2hasat-statisticof2.876 (i) With this
information, which test can you implement to deal with the problem omitted variables and why? [2
marks] (ii) Implement the test as stated in b(i) and interpret the results. [15 marks] (iii) What is
(are) the consequence(s) of the problem alluded to above on the estimators? [5 marks]