Dear Joao Santos Silva ,
I had discussion with my supervisor since he also could not give me much suggestion as he also very new to this model and methodology .I request you to kindly consider if possible
1.inclusion of year and dependent variable Zscore is giving me such results (without year and other dependent variable it is working fine)
2.I am having data till 2019 ,but the results is only till 2014 is it because of the collinearity of variable with my year dummies
Thanking you
Fadi
I had discussion with my supervisor since he also could not give me much suggestion as he also very new to this model and methodology .I request you to kindly consider if possible
1.inclusion of year and dependent variable Zscore is giving me such results (without year and other dependent variable it is working fine)
2.I am having data till 2019 ,but the results is only till 2014 is it because of the collinearity of variable with my year dummies
Code:
qreg Zscore NIM lasset CapitalRatio c.d_MP##c.Boone_Ind i.Year
note: 2019.Year omitted because of collinearity
Iteration 1: WLS sum of weighted deviations = 8.9433852
Iteration 1: sum of abs. weighted deviations = 8.21885
Iteration 2: sum of abs. weighted deviations = 8.21885
Iteration 3: sum of abs. weighted deviations = 8.21885
Iteration 4: sum of abs. weighted deviations = 8.21885
Iteration 5: sum of abs. weighted deviations = 8.21885
Iteration 6: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 7: sum of abs. weighted deviations = 8.21885
Iteration 8: sum of abs. weighted deviations = 8.21885
Iteration 9: sum of abs. weighted deviations = 8.21885
Iteration 10: sum of abs. weighted deviations = 8.21885
Iteration 11: sum of abs. weighted deviations = 8.21885
Iteration 12: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 13: sum of abs. weighted deviations = 8.21885
Iteration 14: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 15: sum of abs. weighted deviations = 8.21885
Iteration 16: sum of abs. weighted deviations = 8.21885
Iteration 17: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 18: sum of abs. weighted deviations = 8.21885
Iteration 19: sum of abs. weighted deviations = 8.21885
Iteration 20: sum of abs. weighted deviations = 8.21885
Iteration 21: sum of abs. weighted deviations = 8.21885
Iteration 22: sum of abs. weighted deviations = 8.21885
Iteration 23: sum of abs. weighted deviations = 8.21885
Iteration 24: sum of abs. weighted deviations = 8.21885
Iteration 25: sum of abs. weighted deviations = 8.21885
Iteration 26: sum of abs. weighted deviations = 8.21885
Iteration 27: sum of abs. weighted deviations = 8.21885
Iteration 28: sum of abs. weighted deviations = 8.21885
Iteration 29: sum of abs. weighted deviations = 8.21885
Iteration 30: sum of abs. weighted deviations = 8.21885
Iteration 31: sum of abs. weighted deviations = 8.21885
Iteration 32: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 33: sum of abs. weighted deviations = 8.21885
Iteration 34: sum of abs. weighted deviations = 8.21885
Iteration 35: sum of abs. weighted deviations = 8.21885
Iteration 36: sum of abs. weighted deviations = 8.21885
Iteration 37: sum of abs. weighted deviations = 8.21885
Iteration 38: sum of abs. weighted deviations = 8.21885
Iteration 39: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 40: sum of abs. weighted deviations = 8.21885
Iteration 41: sum of abs. weighted deviations = 8.21885
note: alternate solutions exist
Iteration 42: sum of abs. weighted deviations = 8.21885
Iteration 43: sum of abs. weighted deviations = 8.21885
Iteration 44: sum of abs. weighted deviations = 8.21885
Iteration 45: sum of abs. weighted deviations = 8.21885
Iteration 46: sum of abs. weighted deviations = 8.21885
Iteration 47: sum of abs. weighted deviations = 8.21885
Iteration 48: sum of abs. weighted deviations = 8.21885
Median regression Number of obs = 647
Raw sum of deviations 191.1734 (about 16.9837)
Min sum of deviations 8.21885 Pseudo R2 = 0.9570
------------------------------------------------------------------------------------
Zscore | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------------+----------------------------------------------------------------
NIM | -1.17e-15 2.72e-16 -4.29 0.000 -1.70e-15 -6.32e-16
lasset | 1.76e-15 1.42e-16 12.37 0.000 1.48e-15 2.03e-15
CapitalRatio | 5.08e-16 2.05e-16 2.48 0.013 1.06e-16 9.10e-16
d_MP | -3.86e-14 4.33e-15 -8.93 0.000 -4.71e-14 -3.01e-14
Boone_Ind | -50.32913 1.03e-13 -4.9e+14 0.000 -50.32913 -50.32913
|
c.d_MP#c.Boone_Ind | 1.49e-13 1.61e-14 9.27 0.000 1.17e-13 1.81e-13
|
Year |
2007 | -.7198463 1.34e-15 -5.4e+14 0.000 -.7198463 -.7198463
2008 | 1.360129 1.73e-15 7.9e+14 0.000 1.360129 1.360129
2009 | 1.15049 1.42e-15 8.1e+14 0.000 1.15049 1.15049
2010 | 2.511705 2.21e-15 1.1e+15 0.000 2.511705 2.511705
2011 | 2.777935 3.17e-15 8.8e+14 0.000 2.777935 2.777935
2012 | 1.720745 1.40e-15 1.2e+15 0.000 1.720745 1.720745
2013 | 1.124593 1.69e-15 6.6e+14 0.000 1.124593 1.124593
2014 | .0187553 2.27e-15 8.2e+12 0.000 .0187553 .0187553
2018 | 4.00e-15 1.12e-14 0.36 0.721 -1.80e-14 2.60e-14
2019 | 0 (omitted)
|
_cons | 28.85743 2.71e-14 1.1e+15 0.000 28.85743 28.85743
------------------------------------------------------------------------------------
.
Code:
qreg assetrisk NIM lasset CapitalRatio c.d_MP##c.Boone_Ind i.Year
note: 2014.Year omitted because of collinearity
Iteration 1: WLS sum of weighted deviations = 85.130146
Iteration 1: sum of abs. weighted deviations = 85.021524
Iteration 2: sum of abs. weighted deviations = 83.294345
Iteration 3: sum of abs. weighted deviations = 83.002368
Iteration 4: sum of abs. weighted deviations = 82.898783
Iteration 5: sum of abs. weighted deviations = 82.869202
Iteration 6: sum of abs. weighted deviations = 82.808319
Iteration 7: sum of abs. weighted deviations = 82.664757
Iteration 8: sum of abs. weighted deviations = 82.640302
Iteration 9: sum of abs. weighted deviations = 82.605172
Iteration 10: sum of abs. weighted deviations = 81.9288
Iteration 11: sum of abs. weighted deviations = 81.916478
Iteration 12: sum of abs. weighted deviations = 81.88787
Iteration 13: sum of abs. weighted deviations = 81.88028
Iteration 14: sum of abs. weighted deviations = 81.866647
Iteration 15: sum of abs. weighted deviations = 81.483306
Iteration 16: sum of abs. weighted deviations = 81.479755
Iteration 17: sum of abs. weighted deviations = 81.47072
Iteration 18: sum of abs. weighted deviations = 81.464368
Iteration 19: sum of abs. weighted deviations = 81.461084
Iteration 20: sum of abs. weighted deviations = 81.458117
Iteration 21: sum of abs. weighted deviations = 81.455509
Iteration 22: sum of abs. weighted deviations = 81.450369
Iteration 23: sum of abs. weighted deviations = 81.446626
Iteration 24: sum of abs. weighted deviations = 81.445369
Iteration 25: sum of abs. weighted deviations = 81.441256
Iteration 26: sum of abs. weighted deviations = 81.440244
Iteration 27: sum of abs. weighted deviations = 81.435765
Iteration 28: sum of abs. weighted deviations = 81.43538
Iteration 29: sum of abs. weighted deviations = 81.434072
Iteration 30: sum of abs. weighted deviations = 81.434065
Iteration 31: sum of abs. weighted deviations = 81.433964
Iteration 32: sum of abs. weighted deviations = 81.433787
Iteration 33: sum of abs. weighted deviations = 81.433305
Iteration 34: sum of abs. weighted deviations = 81.431934
Iteration 35: sum of abs. weighted deviations = 81.429579
Iteration 36: sum of abs. weighted deviations = 81.42879
note: alternate solutions exist
Iteration 37: sum of abs. weighted deviations = 81.428551
Iteration 38: sum of abs. weighted deviations = 81.428527
Iteration 39: sum of abs. weighted deviations = 81.428495
Iteration 40: sum of abs. weighted deviations = 81.428478
note: alternate solutions exist
Iteration 41: sum of abs. weighted deviations = 81.428403
Iteration 42: sum of abs. weighted deviations = 81.428232
Iteration 43: sum of abs. weighted deviations = 81.428096
Iteration 44: sum of abs. weighted deviations = 81.428092
Iteration 45: sum of abs. weighted deviations = 81.428054
Iteration 46: sum of abs. weighted deviations = 81.428033
Iteration 47: sum of abs. weighted deviations = 81.428016
Median regression Number of obs = 523
Raw sum of deviations 81.7715 (about .00442713)
Min sum of deviations 81.42802 Pseudo R2 = 0.0042
------------------------------------------------------------------------------------
assetrisk | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------------+----------------------------------------------------------------
NIM | -.0008234 .0005877 -1.40 0.162 -.0019781 .0003313
lasset | .0007488 .0003506 2.14 0.033 .0000601 .0014376
CapitalRatio | .0044806 .0063272 0.71 0.479 -.00795 .0169113
d_MP | .0081385 .0075849 1.07 0.284 -.0067632 .0230402
Boone_Ind | 1.352781 .1292942 10.46 0.000 1.098765 1.606797
|
c.d_MP#c.Boone_Ind | -.0284459 .0280643 -1.01 0.311 -.0835819 .0266901
|
Year |
2007 | -.0103215 .0022137 -4.66 0.000 -.0146706 -.0059724
2008 | -.003711 .0022256 -1.67 0.096 -.0080835 .0006614
2009 | -.0183742 .0024661 -7.45 0.000 -.0232193 -.0135291
2010 | -.0442307 .0038511 -11.49 0.000 -.0517968 -.0366647
2011 | -.0592462 .0051252 -11.56 0.000 -.0693153 -.0491771
2012 | -.0284731 .0026332 -10.81 0.000 -.0336463 -.0233
2013 | -.0101555 .0021215 -4.79 0.000 -.0143235 -.0059875
2014 | 0 (omitted)
|
_cons | -.3362796 .0338646 -9.93 0.000 -.4028111 -.2697481
-----------------------------------------------------------------------------------
Fadi
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