Need Explanation of Quantile Regression
Posted: Fri Sep 21, 2012 11:22 pm
Hi fellows,
I am writing my thesis on "Determinants of Cash holdings in automobile sector" for which i have taken 5 years of data for each company. Our university statistics department says it is Panel data and Quantile regression has to be applied. They applied the Quantile regression in Eviews and give me the following output.
Dependent Variable: CASH
Method: Quantile Regression (Median)
Date: 09/10/12 Time: 11:02
Sample: 1 45
Included observations: 45
Huber Sandwich Standard Errors & Covariance
Sparsity method: Kernel (Epanechnikov) using residuals
Bandwidth method: Hall-Sheather, bw=0.27315
Estimation successfully identifies unique optimal solution
_______________Coefficient___Std. Error______t-Statistic_____Prob.
FMSM___________-1.43E-05____8.07E-06______-1.766801____0.0855
FMSTA___________2.61E-05_____1.01E-05_____2.590602_____0.0136
LEV_____________-0.027711_____0.217789_____-0.127238____0.8994
ATANG__________-0.418138_____0.200929_____-2.081024____0.0444
PROF ____________0.444208_____0.237870______1.867440____0.0698
DIVP_____________0.381644____0.602400______0.633539____0.5303
FGROW__________0.076186_____0.045732______1.665923____0.1042
CCC_____________9.81E-06_____2.19E-05______0.448105____0.6567
Pseudo R-squared____0.503925____Mean dependent var___0.196162
Adjusted R-squared__0.410074____S.D. dependent var_____0.172264
S.E. of regression___0.127943____Objective_____________1.521317
Quantile dependent var____0.147987____Objective (const. only)____3.066711
Sparsity 0.235021
Can somebody please explains me the output completely that what does it mean. how much variability is it explaining? and which variables are significant and why? and what does the following means and in this case what are they saying
> Pseudo R-square
> Mean dep. varaible
> Adjusted R-square
> SD Dependant Var
> S.E of Regression
> Objective
> Quantile Dependant Var
> Objective (const only)
> Sparsity
Please Help me buddies i am in big prob because we have never studied the Quantile regression in the University. Please Help me guys because i have to submit my thesis ASAP.
Regards,
And Love for those who helped me (in advance ;-) )
I am writing my thesis on "Determinants of Cash holdings in automobile sector" for which i have taken 5 years of data for each company. Our university statistics department says it is Panel data and Quantile regression has to be applied. They applied the Quantile regression in Eviews and give me the following output.
Dependent Variable: CASH
Method: Quantile Regression (Median)
Date: 09/10/12 Time: 11:02
Sample: 1 45
Included observations: 45
Huber Sandwich Standard Errors & Covariance
Sparsity method: Kernel (Epanechnikov) using residuals
Bandwidth method: Hall-Sheather, bw=0.27315
Estimation successfully identifies unique optimal solution
_______________Coefficient___Std. Error______t-Statistic_____Prob.
FMSM___________-1.43E-05____8.07E-06______-1.766801____0.0855
FMSTA___________2.61E-05_____1.01E-05_____2.590602_____0.0136
LEV_____________-0.027711_____0.217789_____-0.127238____0.8994
ATANG__________-0.418138_____0.200929_____-2.081024____0.0444
PROF ____________0.444208_____0.237870______1.867440____0.0698
DIVP_____________0.381644____0.602400______0.633539____0.5303
FGROW__________0.076186_____0.045732______1.665923____0.1042
CCC_____________9.81E-06_____2.19E-05______0.448105____0.6567
Pseudo R-squared____0.503925____Mean dependent var___0.196162
Adjusted R-squared__0.410074____S.D. dependent var_____0.172264
S.E. of regression___0.127943____Objective_____________1.521317
Quantile dependent var____0.147987____Objective (const. only)____3.066711
Sparsity 0.235021
Can somebody please explains me the output completely that what does it mean. how much variability is it explaining? and which variables are significant and why? and what does the following means and in this case what are they saying
> Pseudo R-square
> Mean dep. varaible
> Adjusted R-square
> SD Dependant Var
> S.E of Regression
> Objective
> Quantile Dependant Var
> Objective (const only)
> Sparsity
Please Help me buddies i am in big prob because we have never studied the Quantile regression in the University. Please Help me guys because i have to submit my thesis ASAP.
Regards,
And Love for those who helped me (in advance ;-) )