Sorry if I was not clear, what I would like to see is the estimation results for that model but without the bootstrap.
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Sorry for the inconvenience Joao Santos Silva .I am attaching the result below .
I doubt it because of the inclusion of year and ownership effects in to the model since when i am not inclusing year and ownership effects i am getting the results .Code:xtqreg Zscore MP_callmoneyrate Boone_Ind TotalAsset LiquidityRatio CBT FinFreedom NIM RI Assetcomposit > ionRatiooffixe GDP INF Ratioofnonintrestoperating MPR##C.MP_callmoneyrate owmpr i.Year i.ownership ,qu > antile (.9 ) MM-QR regression results Number of obs = 703 WARNING: some fitted values of the scale function are negative .9 Quantile regression --------------------------------------------------------------------------------------------- | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------------------+---------------------------------------------------------------- MP_callmoneyrate | .0364561 .3934812 0.09 0.926 -.734753 .8076652 Boone_Ind | -38.28719 93.0961 -0.41 0.681 -220.7522 144.1778 TotalAsset | 2.19e-07 1.74e-06 0.13 0.900 -3.19e-06 3.63e-06 LiquidityRatio | -.273911 4.154161 -0.07 0.947 -8.415917 7.868095 CBT | -.7028315 12.08014 -0.06 0.954 -24.37946 22.9738 FinFreedom | .1910914 2.761706 0.07 0.945 -5.221752 5.603935 NIM | .0767332 .5796115 0.13 0.895 -1.059284 1.212751 RII | -.0000458 .0015254 -0.03 0.976 -.0030354 .0029439 AssetcompositionRatiooffixe | .6561622 51.04288 0.01 0.990 -99.38605 100.6984 GDP | .0001923 .1865536 0.00 0.999 -.3654461 .3658307 INF | .0010512 .0117529 0.09 0.929 -.021984 .0240864 Ratioofnonintrestoperating | -.0041564 .3004291 -0.01 0.989 -.5929867 .5846739 | MPR | TMP | .1949845 5.451171 0.04 0.971 -10.48911 10.87908 MP_callmoneyrate | 0 (omitted) | MPR#c.MP_callmoneyrate | TMP | -.028751 .7625445 -0.04 0.970 -1.523311 1.465809 | owmpr | -.0010848 .7993135 -0.00 0.999 -1.56771 1.565541 | Year | 2006 | .697157 10.67525 0.07 0.948 -20.22595 21.62027 2007 | .5418098 10.11538 0.05 0.957 -19.28396 20.36758 2008 | 2.163286 10.19065 0.21 0.832 -17.81001 22.13658 2009 | .0630984 17.13088 0.00 0.997 -33.5128 33.639 2010 | 1.104523 15.92223 0.07 0.945 -30.10247 32.31152 2011 | 1.13731 15.15048 0.08 0.940 -28.55709 30.83171 2012 | .3687874 16.60388 0.02 0.982 -32.17422 32.91179 2013 | 0 17.65253 0.00 1.000 -34.59832 34.59832 2014 | 0 (omitted) 2015 | 0 (empty) 2016 | 0 (empty) 2017 | 0 (empty) 2018 | 0 (empty) 2019 | 0 (empty) | ownership | Private Sector | 0 (omitted) Public Sector | 0 (omitted) ---------------------------------------------------------------------------------------------
Can you please clarify on thisComment
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I believe that the problem with the bootstrap is caused by the fact that you are including the ownership dummies; these are collinear with the fixed effects and therefore are never identified. If you do the bootstrap without those dummies it should work.Comment
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Dear Joao Santos Silva .Thankyou so much for your guidance .I really appreciates .In my case whenever I am using Ownership dummies ,I am getting bootstrap results and when including year dummies the problem arises. So from the suggestions you gave I think problem is with year and not with ownership.
Best regardsComment
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Dear Joao Santos Silva ,I have encountered another problem while running the sqreg command for the same data .my t value and coefficients value are indeterminate or zero and also the p values being 1.can you suggest me what will be the reason since I have explored so many papers but couldn't get an answer.I am attaching my results below
Code:sqreg Zscore C5_Aggregate CBT NIM Ratioofnonintrestoperating AssetcompositionRatiooffixe lGDp lINF lasset CapitalRatio LiquidityRatio RIN ,quantile(.1 .2 .3 .4 .5 . > 6 .7 .8 .9) (fitting base model) Bootstrap replications (20) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 .................... Simultaneous quantile regression Number of obs = 704 bootstrap(20) SEs .10 Pseudo R2 = 0.7350 .20 Pseudo R2 = 0.7163 .30 Pseudo R2 = 0.6826 .40 Pseudo R2 = 0.6049 .50 Pseudo R2 = 0.5182 .60 Pseudo R2 = 0.4586 .70 Pseudo R2 = 0.3824 .80 Pseudo R2 = 0.2284 .90 Pseudo R2 = 0.1249 --------------------------------------------------------------------------------------------- | Bootstrap Zscore | Coef. Std. Err. t P>|t| [95% Conf. Interval] ----------------------------+---------------------------------------------------------------- q10 | C5_Aggregate | -84.06991 .3088986 -272.16 0.000 -84.6764 -83.46342 CBT | -.0700264 .0245242 -2.86 0.004 -.1181772 -.0218756 NIM | -8.87e-17 .0012737 -0.00 1.000 -.0025007 .0025007 Ratioofnonintrestoperating | -5.88e-16 .0007388 -0.00 1.000 -.0014506 .0014506 AssetcompositionRatiooffixe | 5.19e-15 .1389745 0.00 1.000 -.2728622 .2728622 lGDp | -3.00e-16 .0015145 -0.00 1.000 -.0029735 .0029735 lINF | 3.34e-15 .0159021 0.00 1.000 -.0312222 .0312222 lasset | 4.80e-16 .0003017 0.00 1.000 -.0005923 .0005923 CapitalRatio | 1.31e-14 .0155016 0.00 1.000 -.0304358 .0304358 LiquidityRatio | -1.55e-14 .0065052 -0.00 1.000 -.0127723 .0127723 RIN | -1.90e-18 2.49e-06 -0.00 1.000 -4.89e-06 4.89e-06 _cons | 48.80231 .0682307 715.25 0.000 48.66834 48.93627 ----------------------------+---------------------------------------------------------------- q20 | C5_Aggregate | -80.46356 2.0069 -40.09 0.000 -84.40391 -76.52322 CBT | -.0836007 .0145889 -5.73 0.000 -.1122446 -.0549568 NIM | 3.03e-15 .0028106 0.00 1.000 -.0055183 .0055183 Ratioofnonintrestoperating | 5.72e-16 .003285 0.00 1.000 -.0064498 .0064498 AssetcompositionRatiooffixe | 6.09e-15 .4620544 0.00 1.000 -.9071968 .9071968 lGDp | 4.58e-15 .0217288 0.00 1.000 -.0426623 .0426623 lINF | -.270983 .1169679 -2.32 0.021 -.5006376 -.0413285 lasset | 2.32e-16 .0040851 0.00 1.000 -.0080206 .0080206 CapitalRatio | -1.49e-15 .0411056 -0.00 1.000 -.0807066 .0807066 LiquidityRatio | 2.28e-14 .0368838 0.00 1.000 -.0724177 .0724177 RIN | -1.88e-17 .000011 -0.00 1.000 -.0000216 .0000216 _cons | 48.78792 1.273272 38.32 0.000 46.28798 51.28786 ----------------------------+---------------------------------------------------------------- q30 | C5_Aggregate | -79.71946 2.531978 -31.49 0.000 -84.69074 -74.74818 CBT | -.1390461 .0047896 -29.03 0.000 -.1484501 -.1296422 NIM | 4.66e-14 .0039213 0.00 1.000 -.0076991 .0076991 Ratioofnonintrestoperating | -2.00e-14 .001427 -0.00 1.000 -.0028018 .0028018 AssetcompositionRatiooffixe | -2.12e-13 .3563954 -0.00 1.000 -.6997461 .6997461 lGDp | 3.09e-14 .0089871 0.00 1.000 -.0176453 .0176453 lINF | 1.63e-13 .186422 0.00 1.000 -.3660207 .3660207 lasset | 1.50e-14 .0035437 0.00 1.000 -.0069578 .0069578 CapitalRatio | 6.41e-14 .0690111 0.00 1.000 -.1354962 .1354962 LiquidityRatio | -3.00e-13 .039538 -0.00 1.000 -.0776289 .0776289 RIN | 6.27e-17 .0000128 0.00 1.000 -.0000251 .0000251 _cons | 47.45959 .3265006 145.36 0.000 46.81854 48.10064 ----------------------------+---------------------------------------------------------------- q40 | C5_Aggregate | -74.50778 2.216568 -33.61 0.000 -78.85979 -70.15578 CBT | -.1367528 .0138857 -9.85 0.000 -.1640159 -.1094896 NIM | -4.60e-15 .0072866 -0.00 1.000 -.0143065 .0143065 Ratioofnonintrestoperating | 1.99e-15 .0045246 0.00 1.000 -.0088836 .0088836 AssetcompositionRatiooffixe | -1.97e-14 .3910229 -0.00 1.000 -.7677337 .7677337 lGDp | -2.63e-14 .0094849 -0.00 1.000 -.0186226 .0186226 lINF | -.4181048 .1130498 -3.70 0.000 -.6400667 -.196143 lasset | 3.77e-15 .0032475 0.00 1.000 -.0063761 .0063761 CapitalRatio | 3.81e-14 .0722675 0.00 1.000 -.1418898 .1418898 LiquidityRatio | 1.90e-13 .0644728 0.00 1.000 -.1265858 .1265858 RIN | -3.45e-18 .0000234 -0.00 1.000 -.000046 .000046 _cons | 47.46683 .4008328 118.42 0.000 46.67984 48.25383 ----------------------------+---------------------------------------------------------------- q50 | C5_Aggregate | -55.36036 7.657788 -7.23 0.000 -70.39565 -40.32507 CBT | -.1772945 .045087 -3.93 0.000 -.2658181 -.0887708 NIM | -.0077669 .009812 -0.79 0.429 -.0270317 .0114979 Ratioofnonintrestoperating | -.005394 .0069941 -0.77 0.441 -.0191261 .0083382 AssetcompositionRatiooffixe | -.5726174 .8801249 -0.65 0.516 -2.300653 1.155418 lGDp | .0029362 .0255683 0.11 0.909 -.0472646 .053137 lINF | -.4304419 .1838355 -2.34 0.019 -.7913841 -.0694998 lasset | .0061164 .0075952 0.81 0.421 -.008796 .0210288 CapitalRatio | .0503157 .1218698 0.41 0.680 -.1889632 .2895946 LiquidityRatio | .1297658 .0979805 1.32 0.186 -.0626089 .3221405 RIN | .0000537 .0000396 1.36 0.175 -.0000239 .0001314 _cons | 40.42102 3.201784 12.62 0.000 34.13465 46.7074 ----------------------------+---------------------------------------------------------------- q60 | C5_Aggregate | -48.36521 1.814426 -26.66 0.000 -51.92765 -44.80277 CBT | -.2564162 .0125591 -20.42 0.000 -.2810746 -.2317577 NIM | -.0120148 .0119077 -1.01 0.313 -.0353944 .0113648 Ratioofnonintrestoperating | -.0033418 .0086869 -0.38 0.701 -.0203976 .0137141 AssetcompositionRatiooffixe | -.3620643 .7103203 -0.51 0.610 -1.756706 1.032577 lGDp | .0102008 .0228938 0.45 0.656 -.0347489 .0551504 lINF | -.2130288 .1002178 -2.13 0.034 -.4097963 -.0162614 lasset | .0027606 .0051588 0.54 0.593 -.0073682 .0128893 CapitalRatio | .0583577 .1010253 0.58 0.564 -.1399953 .2567106 LiquidityRatio | .0572547 .0654038 0.88 0.382 -.071159 .1856685 RIN | .0000627 .0000358 1.75 0.080 -7.58e-06 .000133 _cons | 37.08885 .5175708 71.66 0.000 36.07265 38.10505 ----------------------------+---------------------------------------------------------------- q70 | C5_Aggregate | -47.16 1.455608 -32.40 0.000 -50.01794 -44.30206 CBT | -.2652941 .0154806 -17.14 0.000 -.2956887 -.2348995 NIM | -.0142069 .0111464 -1.27 0.203 -.0360918 .007678 Ratioofnonintrestoperating | -.0016121 .0113994 -0.14 0.888 -.0239937 .0207695 AssetcompositionRatiooffixe | -.6123469 .4223993 -1.45 0.148 -1.441685 .216991 lGDp | .011946 .0232779 0.51 0.608 -.0337579 .0576498 lINF | -.287864 .0641771 -4.49 0.000 -.4138693 -.1618587 lasset | .0037545 .0053087 0.71 0.480 -.0066685 .0141776 CapitalRatio | .0622714 .0899185 0.69 0.489 -.1142743 .2388172 LiquidityRatio | .1027202 .0999133 1.03 0.304 -.0934493 .2988898 RIN | .0000694 .0000401 1.73 0.084 -9.25e-06 .0001481 _cons | 37.02896 .3769116 98.24 0.000 36.28893 37.76898 ----------------------------+---------------------------------------------------------------- q80 | C5_Aggregate | -41.93194 3.65075 -11.49 0.000 -49.09982 -34.76407 CBT | -.3190534 .0520469 -6.13 0.000 -.4212422 -.2168646 NIM | -.0064871 .0280346 -0.23 0.817 -.0615301 .048556 Ratioofnonintrestoperating | -.0051394 .0221322 -0.23 0.816 -.0485937 .038315 AssetcompositionRatiooffixe | -.8142355 .7711699 -1.06 0.291 -2.328349 .6998781 lGDp | .0290132 .036707 0.79 0.430 -.0430574 .1010837 lINF | -.1473891 .1133744 -1.30 0.194 -.3699881 .0752099 lasset | .0013522 .011443 0.12 0.906 -.0211149 .0238193 CapitalRatio | -.0079554 .1463606 -0.05 0.957 -.2953195 .2794087 LiquidityRatio | .141406 .185304 0.76 0.446 -.2224194 .5052314 RIN | .0001095 .0000882 1.24 0.215 -.0000637 .0002827 _cons | 34.57641 1.498912 23.07 0.000 31.63345 37.51937 ----------------------------+---------------------------------------------------------------- q90 | C5_Aggregate | -33.75532 10.72393 -3.15 0.002 -54.81067 -12.69998 CBT | -.6192229 .1160392 -5.34 0.000 -.8470541 -.3913917 NIM | -1.36e-15 .0213342 -0.00 1.000 -.0418875 .0418875 Ratioofnonintrestoperating | -6.36e-16 .0216777 -0.00 1.000 -.042562 .042562 AssetcompositionRatiooffixe | 2.44e-13 1.351024 0.00 1.000 -2.652597 2.652597 lGDp | -5.89e-16 .0643939 -0.00 1.000 -.1264309 .1264309 lINF | .8147134 .1843811 4.42 0.000 .4526999 1.176727 lasset | -1.76e-15 .0163425 -0.00 1.000 -.0320868 .0320868 CapitalRatio | -1.02e-14 .201794 -0.00 1.000 -.3962019 .3962019 LiquidityRatio | -1.99e-14 .333571 -0.00 1.000 -.6549326 .6549326 RIN | -5.43e-18 .0001676 -0.00 1.000 -.0003291 .0003291 _cons | 28.25899 3.377137 8.37 0.000 21.62833 34.88966 ---------------------------------------------------------------------------------------------Comment
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This looks like a problem with the specification of your model: the variable C5_Aggregate seems to mop up the effect of almost everything else.Comment
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Hi, I am estimating pooled quantile regression and I am using qreg2 to cluster the error terms as I have a panel of firms belonging to different industries. I wanted to ask if I am correct in doing that?
Also, what does R squared in qreg2 represent and is there any way to know which specification to choose out of various specification that we run? I would be really grateful if someone can help me with thisComment
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Dear Jessica Thacker,
If you want to estimate pooled QR that is correct; if you want to include fixed effects, try xtqreg. The R2 is the square of the correlation coefficient between the dependent variable and its fitted values (I guess this is in the help file). You can choose your preferred specification, for example, by using t and F tests.
Best wishes,
JoaoComment
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Dear Joao Santos Silva, thank you for a quick reply.
I would humbly request you to please clarify this further.
(i) Conventionally R squared in OLS is used to determine how well the explanatory variables are able to explain the dependent variable i.e. the proportion of explained variation over total variation. Is the interpretation same for qreg2.
(ii) Could you please elaborate on the preferred specifaction usage? How do we decide that? How to we claim that this is the best specification for our analysis?
(iii) In continuition to (ii), I was checking that for some linear probability models AIC, BIC criterion are used. Do we have to do that we decide on OLS and quantile regressions? Is there any other such criterion that can help determine which model is the best?(I could not find any related material with respect to AIC, BIC for OLS and quantile regression.)
Warm regards,
JessicaComment
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Dear Jessica Thacker,
(i) The R2 only has that interpretation in the linear model when OLS is used, so for quantile regression the interpretation is as I described above (which is also true for OLS). Anyway, the R2 is not a measure of the quality of the model, so do not pay much attention to it.
(ii) You can never claim that. You should think about the problem, and decide on the characteristics the model should have. Then estimate the model and use t tests and F tests to confirm or reject your specification; you can also use the RESET test.
(iii) I am generally not a big fan of AIC/BIC, so I would not recommend those or similar measures.
Best wishes,
JoaoComment
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Joao Santos Silva Thank you!
In sum, there is no check for the quality of the model for quantile regressions, as you replied in (i) that even r2 does not check for quality of the model?
Can I humbly ask you why would you not recomment using AIC/BIC criterion?
Comment
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Dear Jessica Thacker,
What is important is to check the assumptions on which your model and estimator are based; the AIC/BIC/R2 do not do that. Also, some of these assumptions cannot be tested (for example, the validity of instruments), so the most important thing is to think hard about the details of the problem and see if the assumptions are likely to be valid and if the results are sensible. You should make sure you use the right standard errors and you can always do things like the RESET test and test the significance of key regressors, but if you are using "robust" methods, there is not much more to do.
Best wishes,
JoaoComment
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Dear Joao Santos Silva,
I am again encountered with some problem with my quantile regression using xtqreg command .when I am using year effects to the model some years are omitted and for some other years its empty .I don't know what is the reason for the emptiness of year coefficients.
Can you please help me on this
Code:xtqreg Zscore d_MP CBT NIM lasset CapitalRatio ownership#C.d_MP i.Year ,quantile(.1 .2 .3 .4 > .5 .6 .7 .8 .9) MM-QR regression results Number of obs = 645 WARNING: some fitted values of the scale function are negative .1 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0252679 .1988885 0.13 0.899 -.3645464 .4150822 CBT -.433526 .3042344 -1.42 0.154 -1.029814 .1627624 NIM -.0285031 .2866877 -0.10 0.921 -.5904006 .5333944 lasset -.0136292 .1643529 -0.08 0.934 -.335755 .3084967 CapitalRatio -.0016217 .0349172 -0.05 0.963 -.0700583 .0668148 ownership#c.d_MP Private Sector -.018649 .1586822 -0.12 0.906 -.3296604 .2923623 Public Sector -.037345 .2005605 -0.19 0.852 -.4304363 .3557462 Year 2005 0 (empty) 2006 -1.711092 .5820535 -2.94 0.003 -2.851896 -.5702878 2007 -2.394454 .717241 -3.34 0.001 -3.80022 -.988687 2008 .1204783 .5836986 0.21 0.836 -1.02355 1.264506 2009 -.4675054 .6484328 -0.72 0.471 -1.73841 .8033995 2010 .0393039 .493705 0.08 0.937 -.92834 1.006948 2011 -.2161985 .4873486 -0.44 0.657 -1.171384 .7389871 2012 -.0535318 .472872 -0.11 0.910 -.9803438 .8732802 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .2 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0273857 .1201826 0.23 0.820 -.2081679 .2629392 CBT -.4479375 .183847 -2.44 0.015 -.808271 -.0876039 NIM -.0028154 .1729692 -0.02 0.987 -.3418287 .3361979 lasset -.0071404 .0993015 -0.07 0.943 -.2017678 .187487 CapitalRatio -.0027312 .021093 -0.13 0.897 -.0440727 .0386103 ownership#c.d_MP Private Sector -.0185295 .0958905 -0.19 0.847 -.2064714 .1694124 Public Sector -.0311362 .1211856 -0.26 0.797 -.2686556 .2063833 Year 2005 0 (empty) 2006 -1.700872 .3516992 -4.84 0.000 -2.39019 -1.011554 2007 -2.276365 .4312913 -5.28 0.000 -3.12168 -1.43105 2008 .1523941 .3526339 0.43 0.666 -.5387556 .8435438 2009 -.4547487 .391806 -1.16 0.246 -1.222674 .3131769 2010 .0245413 .2983176 0.08 0.934 -.5601504 .6092331 2011 -.2413804 .2944087 -0.82 0.412 -.8184108 .3356501 2012 -.085514 .2856845 -0.30 0.765 -.6454453 .4744174 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .3 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .028203 .1071919 0.26 0.792 -.1818893 .2382953 CBT -.4534991 .1639957 -2.77 0.006 -.7749248 -.1320735 NIM .007098 .1542206 0.05 0.963 -.2951689 .3093648 lasset -.0046362 .0885692 -0.05 0.958 -.1782287 .1689563 CapitalRatio -.0031594 .0188111 -0.17 0.867 -.0400285 .0337098 ownership#c.d_MP Private Sector -.0184833 .0855265 -0.22 0.829 -.1861123 .1491456 Public Sector -.0287401 .1080881 -0.27 0.790 -.2405888 .1831087 Year 2005 0 (empty) 2006 -1.696928 .3136786 -5.41 0.000 -2.311727 -1.082129 2007 -2.230792 .3843006 -5.80 0.000 -2.984008 -1.477577 2008 .164711 .3145301 0.52 0.601 -.4517567 .7811788 2009 -.4498256 .3494501 -1.29 0.198 -1.134735 .235084 2010 .0188442 .2660767 0.07 0.944 -.5026566 .5403449 2011 -.2510985 .262585 -0.96 0.339 -.7657557 .2635587 2012 -.0978565 .2548378 -0.38 0.701 -.5973295 .4016165 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .4 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0288083 .1082639 0.27 0.790 -.183385 .2410017 CBT -.4576183 .1656385 -2.76 0.006 -.7822638 -.1329728 NIM .0144402 .1557646 0.09 0.926 -.2908528 .3197332 lasset -.0027816 .0894556 -0.03 0.975 -.1781113 .1725482 CapitalRatio -.0034765 .0189992 -0.18 0.855 -.0407142 .0337613 ownership#c.d_MP Private Sector -.0184492 .0863819 -0.21 0.831 -.1877545 .1508562 Public Sector -.0269654 .1091695 -0.25 0.805 -.2409337 .1870029 Year 2005 0 (empty) 2006 -1.694007 .3168155 -5.35 0.000 -2.314954 -1.07306 2007 -2.197039 .3881629 -5.66 0.000 -2.957825 -1.436254 2008 .1738335 .3176801 0.55 0.584 -.4488081 .796475 2009 -.4461793 .3529449 -1.26 0.206 -1.137939 .2455799 2010 .0146246 .2687388 0.05 0.957 -.5120937 .5413429 2011 -.2582962 .2652137 -0.97 0.330 -.7781055 .2615132 2012 -.1069979 .2573931 -0.42 0.678 -.6114791 .3974833 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .5 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0295035 .1205212 0.24 0.807 -.2067137 .2657207 CBT -.4623489 .1843884 -2.51 0.012 -.8237436 -.1009543 NIM .0228723 .1734175 0.13 0.895 -.3170198 .3627643 lasset -.0006516 .0995838 -0.01 0.995 -.1958322 .194529 CapitalRatio -.0038407 .0211507 -0.18 0.856 -.0452954 .037614 ownership#c.d_MP Private Sector -.0184099 .0961615 -0.19 0.848 -.206883 .1700631 Public Sector -.0249273 .1215294 -0.21 0.837 -.2631205 .2132659 Year 2005 0 (empty) 2006 -1.690652 .3526857 -4.79 0.000 -2.381904 -.9994009 2007 -2.158276 .4322446 -4.99 0.000 -3.00546 -1.311093 2008 .1843099 .3536482 0.52 0.602 -.5088277 .8774476 2009 -.4419919 .3929058 -1.12 0.261 -1.212073 .3280892 2010 .0097787 .2991644 0.03 0.974 -.5765727 .5961302 2011 -.2665622 .2952437 -0.90 0.367 -.8452292 .3121048 2012 -.1174962 .2865321 -0.41 0.682 -.6790887 .4440963 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .6 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0304792 .1517862 0.20 0.841 -.2670162 .3279746 CBT -.4689882 .2322226 -2.02 0.043 -.924136 -.0138403 NIM .0347065 .2183994 0.16 0.874 -.3933486 .4627615 lasset .0023378 .1254172 0.02 0.985 -.2434754 .2481509 CapitalRatio -.0043518 .0266374 -0.16 0.870 -.0565601 .0478565 ownership#c.d_MP Private Sector -.0183548 .1211073 -0.15 0.880 -.2557207 .2190111 Public Sector -.0220669 .1530559 -0.14 0.885 -.322051 .2779171 Year 2005 0 (empty) 2006 -1.685944 .4441772 -3.80 0.000 -2.556515 -.8153728 2007 -2.103874 .5443367 -3.87 0.000 -3.170754 -1.036993 2008 .1990134 .4453896 0.45 0.655 -.6739341 1.071961 2009 -.4361149 .4948308 -0.88 0.378 -1.405966 .5337357 2010 .0029777 .3767722 0.01 0.994 -.7354822 .7414375 2011 -.2781634 .3718334 -0.75 0.454 -1.006944 .4506168 2012 -.1322302 .3608637 -0.37 0.714 -.8395101 .5750497 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .7 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0316773 .2020114 0.16 0.875 -.3642577 .4276123 CBT -.4771415 .3090652 -1.54 0.123 -1.082898 .1286151 NIM .0492394 .2906418 0.17 0.865 -.5204081 .6188869 lasset .0060088 .1669161 0.04 0.971 -.3211407 .3331583 CapitalRatio -.0049795 .0354509 -0.14 0.888 -.0744621 .0645031 ownership#c.d_MP Private Sector -.0182872 .1611813 -0.11 0.910 -.3341968 .2976224 Public Sector -.0185542 .2037007 -0.09 0.927 -.4178003 .3806918 Year 2005 0 (empty) 2006 -1.680162 .5911511 -2.84 0.004 -2.838797 -.5215272 2007 -2.037065 .7242601 -2.81 0.005 -3.456588 -.617541 2008 .2170699 .5927604 0.37 0.714 -.9447192 1.378859 2009 -.4288977 .6585654 -0.65 0.515 -1.719662 .8618668 2010 -.0053743 .501443 -0.01 0.991 -.9881845 .9774359 2011 -.2924101 .4948641 -0.59 0.555 -1.262326 .6775057 2012 -.1503242 .480268 -0.31 0.754 -1.091632 .7909837 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .8 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0329759 .2630057 0.13 0.900 -.4825058 .5484576 CBT -.4859779 .4023573 -1.21 0.227 -1.274584 .3026279 NIM .0649899 .3784022 0.17 0.864 -.6766648 .8066445 lasset .0099874 .2173093 0.05 0.963 -.4159311 .4359059 CapitalRatio -.0056598 .0461558 -0.12 0.902 -.0961235 .0848039 ownership#c.d_MP Private Sector -.0182139 .2098472 -0.09 0.931 -.4295068 .393079 Public Sector -.0147472 .2652014 -0.06 0.956 -.5345324 .505038 Year 2005 0 (empty) 2006 -1.673896 .7696426 -2.17 0.030 -3.182368 -.1654241 2007 -1.964658 .9429292 -2.08 0.037 -3.812765 -.1165511 2008 .2366392 .7717008 0.31 0.759 -1.275867 1.749145 2009 -.4210759 .8574107 -0.49 0.623 -2.10157 1.259418 2010 -.014426 .652837 -0.02 0.982 -1.293963 1.265111 2011 -.3078504 .6442629 -0.48 0.633 -1.570582 .9548817 2012 -.1699342 .6252211 -0.27 0.786 -1.395345 1.055477 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty) .9 Quantile regression Coef. Std. Err. z P>z [95% Conf. Interval] d_MP .0363263 .4313945 0.08 0.933 -.8091913 .881844 CBT -.5087775 .6598239 -0.77 0.441 -1.802009 .7844536 NIM .1056289 .620763 0.17 0.865 -1.111044 1.322302 lasset .020253 .3564188 0.06 0.955 -.6783151 .7188211 CapitalRatio -.007415 .0757138 -0.10 0.922 -.1558113 .1409813 ownership#c.d_MP Private Sector -.0180248 .344198 -0.05 0.958 -.6926405 .6565909 Public Sector -.0049245 .4349772 -0.01 0.991 -.8574642 .8476151 Year 2005 0 (empty) 2006 -1.657728 1.26242 -1.31 0.189 -4.132026 .8165703 2007 -1.777837 1.547058 -1.15 0.250 -4.810014 1.254341 2008 .2871314 1.265607 0.23 0.821 -2.193412 2.767675 2009 -.4008941 1.406378 -0.29 0.776 -3.157344 2.355555 2010 -.0377811 1.070767 -0.04 0.972 -2.136445 2.060883 2011 -.3476892 1.056669 -0.33 0.742 -2.418723 1.723345 2012 -.2205315 1.025219 -0.22 0.830 -2.229923 1.78886 2013 0 (omitted) 2014 0 (omitted) 2015 0 (empty) 2016 0 (empty) 2017 0 (empty) 2018 0 (empty) 2019 0 (empty)
Comment
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It looks as if there are no observations for those years. Can you show us the results with xtreg?Comment
Comment