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What is the value of the OLS estimate of the variance the residuals (the s2) ?  a) .35 b) .34 c) .33 d) .32 e.) .31

What is the value of the OLS estimate of the variance the residuals (the s2) ?  a) .35 b) .34 c) .33 d) .32 e.) .31

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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What is the value of the OLS estimate of the variance the residuals (the s2) ? 

a) .35

b) .34

c) .33

d) .32

e.) .31

The output below is OLS estimation of log output, (Inoutput) as a function of inputs: capital stock (number of units), labour (number of people) and years of managerial experience on a sample of farms. Output is measured in thousands of kilograms. The managerial experience variable is a proxy for the unobserved variable managerial efficiency LnOutput; = bo+ bịCapital; + b2Labour; + b3Manage_Experience; + Ui Some of the information from the output has been hidden. reg Inoutput capital labour manexper Source | SS df MS Number of obs %3D F (3, 71) 15.01 %3D Model | Residual | 3 5.33333333 Prob > F 0.0000 25.000000 R-squared Adj R-squared 71 Total | 41.000000 74 .554054054 Root MSE .59333 Inoutput | Coef. Std. Err. P>|t| [95% Conf. Interval] capital | labour | .0606554 .0257329 2.36 0.021 0093455 .1119653 .0434242 .021624 2.01 0.048 .0003071 .0865414 .0205922 manexper | cons | 1.50 0.138 9097925 .2285037 3.98 0.000 .454169 1.365416
Transcribed Image Text:The output below is OLS estimation of log output, (Inoutput) as a function of inputs: capital stock (number of units), labour (number of people) and years of managerial experience on a sample of farms. Output is measured in thousands of kilograms. The managerial experience variable is a proxy for the unobserved variable managerial efficiency LnOutput; = bo+ bịCapital; + b2Labour; + b3Manage_Experience; + Ui Some of the information from the output has been hidden. reg Inoutput capital labour manexper Source | SS df MS Number of obs %3D F (3, 71) 15.01 %3D Model | Residual | 3 5.33333333 Prob > F 0.0000 25.000000 R-squared Adj R-squared 71 Total | 41.000000 74 .554054054 Root MSE .59333 Inoutput | Coef. Std. Err. P>|t| [95% Conf. Interval] capital | labour | .0606554 .0257329 2.36 0.021 0093455 .1119653 .0434242 .021624 2.01 0.048 .0003071 .0865414 .0205922 manexper | cons | 1.50 0.138 9097925 .2285037 3.98 0.000 .454169 1.365416
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