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Re: st: Bootstrap: Which standard errors to use?


From   "Supnithadnaporn, Anupit" <[email protected]>
To   [email protected]
Subject   Re: st: Bootstrap: Which standard errors to use?
Date   Mon, 8 Dec 2008 18:34:18 -0500 (EST)

I really appreciate Stas for your elaborative explanation.
My data and model are simpler than your speculation.

Pr(FailEmissionTest) = f(OwnerCharacteristics,VehicleCharacteristics)

Owner characteristics = {Income, Race}
Vehicle characteristics = {Age,Mileage,Type(car,van,truck),ProductionCountry,
			  OtherEmissionControlTechnologies}

tresimp = First test result (1=Fail, 0=Pass)
indlninc = Ln of Individual household income

Vehicle emission test is legally required in some places in order to control
for pollution. However, this might cause more burden to the poor because
they tend to own old vehicles (I control for vehicle age as well). 

In my data, only around 5.37% fail the first emission test.


As you suggested, ...

Thank you
Anupit

. bootstrap _b _se, reps(10000) strata(tresimp) saving("C:\ANUPIT\e1outACIlogitBOOT2Abse
> S.dta", replace): ///
> logit tresimp indlninc `owner' `vehicle', robust
(running logit on estimation sample)


Logistic regression

Number of strata   =         2                  Number of obs      =       465
                                                Replications       =      5070

------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
b            |
    indlninc |  -.2818828    .491087    -0.57   0.566    -1.244396      .68063
       black |   1.184949   .6017671     1.97   0.049     .0055069     2.36439
       other |   .5112052   .7492401     0.68   0.495    -.9572784    1.979689
         age |   .2291411    .088497     2.59   0.010     .0556902    .4025921
       lnodo |   .2668319   .5443578     0.49   0.624    -.8000898    1.333754
       peuro |   .3441804   .9920844     0.35   0.729    -1.600269     2.28863
       pasia |   .1141557   .7469322     0.15   0.879    -1.349805    1.578116
      pother |   .1774283   .7320229     0.24   0.808     -1.25731    1.612167
       displ |  -.0444871   .3925379    -0.11   0.910    -.8138473     .724873
      indefi |   .3926529    .808736     0.49   0.627    -1.192441    1.977746
       indfi |  -.5801308   .8902797    -0.65   0.515    -2.325047    1.164785
      indmfi |  -1.667607   .7216526    -2.31   0.021     -3.08202   -.2531942
        egr1 |  -1.307301    .609217    -2.15   0.032    -2.501345   -.1132581
        tac1 |  -.1766159   .9885491    -0.18   0.858    -2.114137    1.760905
         car |  -1.189119   1.641974    -0.72   0.469    -4.407329    2.029092
         van |  -1.120382   1.712288    -0.65   0.513    -4.476406    2.235641
       _cons |  -3.180481   9.098116    -0.35   0.727    -21.01246     14.6515
-------------+----------------------------------------------------------------
se           |
    indlninc |   .3751495   .1107681     3.39   0.001      .158048    .5922511
       black |   .5377806   .1017104     5.29   0.000     .3384319    .7371293
       other |   .6130217   .1557758     3.94   0.000     .3077068    .9183367
         age |   .0683818   .0153066     4.47   0.000     .0383814    .0983822
       lnodo |   .3736896   .1499676     2.49   0.013     .0797586    .6676207
       peuro |   .8376832   .2292782     3.65   0.000     .3883061     1.28706
       pasia |   .6548303   .1297987     5.04   0.000     .4004296    .9092311
      pother |   .7830163   .2208942     3.54   0.000     .3500715    1.215961
       displ |   .3161949    .082542     3.83   0.000     .1544155    .4779743
      indefi |   .6165853   .1236292     4.99   0.000     .3742765     .858894
       indfi |   .6734173   .1310668     5.14   0.000     .4165312    .9303034
      indmfi |   1.093033   .2006469     5.45   0.000      .699772    1.486293
        egr1 |   .5173223   .0856415     6.04   0.000     .3494679    .6851766
        tac1 |   .7599367   .1663593     4.57   0.000     .4338784    1.085995
         car |   .8430763   .3607768     2.34   0.019     .1359668    1.550186
         van |   .9862894   .3964712     2.49   0.013     .2092202    1.763359
       _cons |   6.637172   1.948067     3.41   0.001     2.819031    10.45531
------------------------------------------------------------------------------
Note: One or more parameters could not be estimated in 4930 bootstrap replicates;
      standard error estimates include only complete replications.


    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         age |       465    6.926882    3.313216          3         20
       lnodo |       465    11.41426    .5641127   8.209309    12.9082
       black |       465     .255914    .4368437          0          1
       other |       465     .144086    .3515552          0          1
      indefi |       465    .2129032    .4098007          0          1
-------------+--------------------------------------------------------
       indfi |       465    .2236559    .4171428          0          1
      indmfi |       465    .2903226    .4544001          0          1
         car |       465    .7225806    .4482074          0          1
         van |       465    .1849462    .3886721          0          1
       peuro |       465    .0666667    .2497125          0          1
-------------+--------------------------------------------------------
       pasia |       465    .2430108    .4293635          0          1
      pother |       465    .1204301    .3258143          0          1
    indlninc |       465    10.82838    .5955187   8.517183   11.51293
     tresimp |       465    .0537634    .2257932          0          1
        egr1 |       465    .7591398    .4280662          0          1
-------------+--------------------------------------------------------
        tac1 |       465    .0688172    .2534157          0          1
       displ |       465    2.936825     1.05423          1        5.9

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