basharat khan mm 113116 section 03 assignment 01

Redundancy

BASHARAT KHANMM113116SECTION 03MAJUISLAMABAD

Redundant Variables TestDependent Variable: LEVEquation: UNTITLEDMethod: Least SquaresSpecification: LEV C ROA TA IH BSDate: 01/05/80 Time: 15:14Redundant Variables: TASample: 1 49Included observations: 49ValuedfProbabilityt-statistic0.586134440.5608VariableCoefficientStd. Errort-StatisticProb. F-statistic0.343553(1, 44)0.5608Likelihood ratio0.38110710.537C61.8212518.960013.2606140.0021ROA-89.9468742.38365-2.1222070.0395Redundant Variables TestTA-0.0002620.000447-0.5861340.5608Equation: UNTITLEDIH-0.2743070.131686-2.0830460.0431Specification: LEV C ROA TA IH BSBS-3.8369112.126817-1.8040630.0781Redundant Variables: BSR-squared0.152454 Mean dependent var18.3898ValuedfProbabilityAdjusted R-squared0.075404 S.D. dependent var17.6989t-statistic1.804063440.0781S.E. of regression17.01853 Akaike info criterion8.602934F-statistic3.254642(1, 44)0.0781Sum squared resid12743.74 Schwarz criterion8.795977Likelihood ratio3.49670210.0615Log likelihood-205.7719 Hannan-Quinn criter.8.676174F-statistic1.978644 Durbin-Watson stat0.994537As the redundacy results are also insignicant so according to the presetProb(F-statistic)0.114415criteria TA and BS are redundant variables and should be excluded

as our intercept is significant which is an indication of ommitted variables.Dependent Variable: LEVtherefore we include all the variables to check the ommitted variable case.Method: Least SquaresDate: 01/05/80 Time: 15:40Redundant Variables TestSample: 1 49Equation: UNTITLEDIncluded observations: 48Specification: LEV C ROA TA IH BS DIV NEDRedundant Variables: DIVVariableCoefficientStd. Errort-StatisticProb.

ValuedfProbabilityC59.3942817.291573.4348680.0014t-statistic0.535671410.5951ROA-116.486947.33888-2.4607020.0182F-statistic0.286943(1, 41)0.5951TA-0.0007370.000416-1.7712460.084Likelihood ratio0.33476310.5629IH-0.7789070.179625-4.3363010.0001BS1.3260632.3487310.5645870.5754DIV-0.034110.063677-0.5356710.5951NED-5.2876231.464342-3.6109220.0008

R-squared0.366008 Mean dependent var18.75Adjusted R-squared0.273229 S.D. dependent var17.70376S.E. of regression15.09261 Akaike info criterion8.400325Sum squared resid9339.26 Schwarz criterion8.673209Log likelihood-194.6078 Hannan-Quinn criter.8.503448as our intercept is again significant.F-statistic3.944931 Durbin-Watson stat1.260622therefore we include log of TA to check its effect on the intercept.Prob(F-statistic)0.003333

By including log of total assets we see that the intercept has becomeDependent Variable: LEVinsignificant.Method: Least SquaresDate: 01/05/80 Time: 15:48Sample: 1 49Included observations: 49

VariableCoefficientStd. Errort-StatisticProb.

C48.5119825.187171.9260590.0606ROA-85.0819241.19503-2.0653440.0448LTA2.9632314.6790990.6332910.5298IH-0.1900510.143725-1.3223220.1929BS-3.7432272.12676-1.7600610.0853

R-squared0.153551 Mean dependent var18.3898Adjusted R-squared0.076602 S.D. dependent var17.6989S.E. of regression17.00751 Akaike info criterion8.601638Sum squared resid12727.24 Schwarz criterion8.794681Log likelihood-205.7401 Hannan-Quinn criter.8.674878F-statistic1.995474 Durbin-Watson stat0.921994Prob(F-statistic)0.111815

Autocorrelation

BASHARAT KHANMM113116SECTION 03MAJUISLAMABAD

Dependent Variable: LEVMethod: Least SquaresDate: 01/05/80 Time: 15:58Sample: 1 49Included observations: 49


C29.518626.3892744.6200270ROA-81.9330343.19325-1.8968940.0643TA-0.000240.000458-0.5244210.6026IH-0.2152790.130712-1.6469630.1065


To check autocorrelation DW is not giving us indication about autocorellationtherefore we need to use DW table as the DW value of 0.87736 lies betweenzero and DL (1.24) which is an indication of positive corellation

Breusch-Godfrey Serial Correlation LM Test:Breusch-Godfrey Serial Correlation LM Test:

F-statistic15.69471 Prob. F(1,44)0.0003Obs*R-squared12.8829 Prob. Chi-Square(1)0.0003

Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 01/05/80 Time: 15:16Sample: 1 49Included observations: 49Presample missing value lagged residuals set to zero.


C-3.110025.602675-0.5550960.5816ROA15.601937.70820.4137540.6811TA0.0002570.0004030.6373310.5272IH0.0312650.1137630.2748280.7847RESID(-1)0.5344120.1348963.9616550.0003

Breusch-Godfrey Serial Correlation LM Test is significant at first lag which shows a caseof serial autocorellation

Breusch-Godfrey Serial Correlation LM Test:

F-statistic8.29554 Prob. F(2,43)0.0009Obs*R-squared13.64236 Prob. Chi-Square(2)0.0011

Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 01/05/80 Time: 15:15Sample: 1 49Included observations: 49Presample missing value lagged residuals set to zero.


C-3.2158945.608627-0.5733830.5694ROA17.6641937.801930.4672830.6427TA0.0002280.0004040.5640810.5756IH0.0337610.1138920.2964330.7683RESID(-1)0.6227070.1633073.8130970.0004RESID(-2)-0.1593170.165774-0.961050.3419

Breusch-Godfrey Serial Correlation LM Test is significant at first lag which shows a caseof serial autocorellation but at second lag there is no autocorellation

As we have no lagged dependent variable included in the equation as an exogenous variable therefore we do not use Durbin "H" Stat for the detection of autocorellation because Durbin "h" stat is used when we have auto regressive term in our equation.

Hetroskedasticity

Dependent Variable: LEVMethod: Least SquaresDate: 01/05/80 Time: 15:33Sample: 1 49Included observations: 49


C29.518626.3892744.6200270ROA-81.9330343.19325-1.8968940.0643TA-0.000240.000458-0.5244210.6026IH-0.2152790.130712-1.6469630.1065


Heteroskedasticity Test: Breusch-Pagan-Godfrey

F-statistic1.019766 Prob. F(3,45)0.3928Obs*R-squared3.11918 Prob. Chi-Square(3)0.3736Scaled explained SS1.314925 Prob. Chi-Square(3)0.7256

As insignificant therfore data is homoskedastic

Heteroskedasticity Test: Harvey



Heteroskedasticity Test: Glejser




Test Equation:Dependent Variable: RESID^2Method: Least SquaresDate: 01/05/80 Time: 15:35Sample: 1 49Included observations: 49


C12.38087167.79080.0737880.9416ROA1656.5222449.7640.6761960.5029ROA^2-8252.0999598.934-0.8596890.3952ROA*TA-0.138830.136499-1.0170750.3154ROA*IH-122.335255.00598-2.2240350.032TA0.098350.0394922.4903630.0171TA^2-5.49E-061.93E-06-2.8513240.0069TA*IH0.0018080.0013611.3281690.1918IH15.725768.7053451.8064490.0786IH^2-0.1382530.099025-1.3961480.1706

As white test is significant which indicants that there is hetroskedastictywhen we include squared and cross product terms in the equation

MulticollinearityLEVROATAIHLEV1-0.18427768710.0384630055-0.1297672958Dependent Variable: LEVROA-0.18427768711-0.0428207624-0.406897188Date: 01/05/80 Time: 15:21TA0.0384630055-0.04282076241-0.3804717059Sample: 1 49IH-0.1297672958-0.406897188-0.38047170591Included observations: 49as per the corellation matrix there is no problem of multicollinerityVariableCoefficientStd. Errort-StatisticProb.

C29.518626.3892744.6200270ROA-81.9330343.19325-1.8968940.0643to check multicollinearity we run the auxilary regressions where there Is a possibility of it, butTA-0.000240.000458-0.5244210.6026we can see that their R SQUARE is not problematic, hence no problem of multicollinearity.IH-0.2152790.130712-1.6469630.1065

R-squared0.089762 Mean dependent var18.3898LEVBSDIVIHTANEDROAAdjusted R-squared0.029079 S.D. dependent var17.6989LEV1-0.1671685592-0.0469223824-0.15014501630.0291193695-0.1750110826-0.1873447554S.E. of regression17.43967 Akaike info criterion8.633479BS-0.16716855921-0.1128552423-0.230990010.10018569050.56637205050.0103844345Sum squared resid13686.39 Schwarz criterion8.787913DIV-0.0469223824-0.11285524231-0.3466039602-0.01963715270.01413136250.6726862964Log likelihood-207.5202 Hannan-Quinn criter.8.692071IH-0.1501450163-0.23099001-0.34660396021-0.3928843351-0.7030333342-0.4110968748F-statistic1.479198 Durbin-Watson stat0.87736TA0.02911936950.1001856905-0.0196371527-0.392884335110.1786060168-0.043473354Prob(F-statistic)0.232927NED-0.17501108260.56637205050.0141313625-0.70303333420.178606016810.1478510139ROA-0.18734475540.01038443450.6726862964-0.4110968748-0.0434733540.14785101391

Auxilary regression between NED and BSDependent Variable: NEDMethod: Least SquaresDate: 01/05/80 Time: 15:35Sample: 1 49Included observations: 48


C-6.290642.282251-2.7563320.0084BS1.3288180.2850964.6609520


Auxilary regression between ROA and DIVDependent Variable: ROAMethod: Least SquaresDate: 01/05/80 Time: 15:38Sample: 1 49Included observations: 49


C0.0336550.0092083.6551250.0006DIV0.0009030.0001466.208640

R-squared0.450596 Mean dependent var0.070633Adjusted R-squared0.438906 S.D. dependent var0.065619S.E. of regression0.049153 Akaike info criterion-3.147818Sum squared resid0.113551 Schwarz criterion-3.070601Log likelihood79.12154 Hannan-Quinn criter.-3.118522F-statistic38.54721 Durbin-Watson stat1.592967Prob(F-statistic)0

Auxilary regression between NED and IHDependent Variable: NEDMethod: Least SquaresDate: 01/05/80 Time: 15:43Sample: 1 49Included observations: 48


C5.9519980.38902615.299740IH-0.0842560.012566-6.7048550

R-squared0.494256 Mean dependent var4.229167Adjusted R-squared0.483261 S.D. dependent var2.815153S.E. of regression2.02366 Akaike info criterion4.288466Sum squared resid188.3792 Schwarz criterion4.366433Log likelihood-100.9232 Hannan-Quinn criter.4.31793F-statistic44.95508 Durbin-Watson stat0.733358Prob(F-statistic)0

Auxilary regression between BS and NEDDependent Variable: BSMethod: Least SquaresDate: 01/05/80 Time: 15:44Sample: 1 49Included observations: 48


C6.8957440.26228426.291120NED0.2414010.0517924.6609520


Auxilary regression between IH and NEDDependent Variable: IHMethod: Least SquaresDate: 01/05/80 Time: 15:45Sample: 1 49Included observations: 48


C45.256624.430710.214330NED-5.8661520.874911-6.7048550


Auxilary regression between DIV and ROADependent Variable: DIVMethod: Least SquaresDate: 01/05/80 Time: 15:47Sample: 1 49Included observations: 49


C5.7016067.7077990.7397190.4631ROA498.734980.329166.208640


Note:to check wether multicollinearity is within tolerable limit or no we should check the variance inflation factor (VIF)

Vif1.0986137691

as the variance inflation factor is less than 5 so we conclude that there is no problemof multicollinearity.

basharat khan mm 113116 section 03 assignment 01

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