Model 1: OLS, using observations 1-1000 Dependent variable: Income Coefficient 597.095 р-value <0.0001 Std. Error t-ratio const 6.93618 86.08 *** Experience 21.8751 4.04528 <0.0001 *** Mean dependent var Sum squared resid R-squared F(1, 998) Log-likelihood Schwarz criterion S.D. dependent var S.E. of regression Adjusted R-squared P-value(F) Akaike criterion 607.1195 214.3293 44584757 0.027493 D 8.00e-08 -6771.512 13547.02 13556.84 Hannan-Quinn 13550.75

MATLAB: An Introduction with Applications
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Model 1: OLS, using observations 1-1000
Dependent variable: Income
Coefficient
597.095
Std. Error
6.93618
t-ratio
р-value
const
86.08
<0.0001
***
Experience
<0.0001
21.8751
4.04528
А
***
Mean dependent var
Sum squared resid
R-squared
F(1, 998)
Log-likelihood
Schwarz criterion
S.D. dependent var
S.E. of regression
Adjusted R-squared
P-value(F)
Akaike criterion
607.1195
214.3293
44584757
В
C
0.027493
D
8.00e-08
-6771.512
13547.02
13556.84
Hannan-Quinn
13550.75
Transcribed Image Text:Model 1: OLS, using observations 1-1000 Dependent variable: Income Coefficient 597.095 Std. Error 6.93618 t-ratio р-value const 86.08 <0.0001 *** Experience <0.0001 21.8751 4.04528 А *** Mean dependent var Sum squared resid R-squared F(1, 998) Log-likelihood Schwarz criterion S.D. dependent var S.E. of regression Adjusted R-squared P-value(F) Akaike criterion 607.1195 214.3293 44584757 В C 0.027493 D 8.00e-08 -6771.512 13547.02 13556.84 Hannan-Quinn 13550.75
The attached GRETL outcome details the regression estimate of the relationship between Income (in dollars) and Experience (in years) of 1000 employees on a
firm.
Upon reviewing the attached GRETL outcome, find out the missing values of A, B, C & D.
Show your calculations (where is needed).
Transcribed Image Text:The attached GRETL outcome details the regression estimate of the relationship between Income (in dollars) and Experience (in years) of 1000 employees on a firm. Upon reviewing the attached GRETL outcome, find out the missing values of A, B, C & D. Show your calculations (where is needed).
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