st: bootstrapping

[hsk22@cam.ac.uk]

Dear statalists,

I would like to get confindence interval of my estimates via bootstrapping 
method. I want to run a nested logit model and my dataset has 3 
alternatives such as C:keeping current policy (baseline group), 
A:protection policy (1), B:protection policy (2). I run nested logit model 
and get the results. Then, I would like to bootstrap my estimates of 
coefficients. I set up bootstrapping using bs command as follows. However, 
it did not appear any result. Please check my command and tell me how to 
correct this for bootstrapping. Thanks in advance.


Hanseung Kum


use "F:\Ph.d\fulldatafinal.dta", clear

. gen grp = group(2560)

. sort grp

. by grp: gen policy=_n-1

. label define plab 0 "A" 1 "B" 2 "C"

. label value policy plab

. nlogitgen type = policy(current: 2, protection: 0| 1|)
new variable type is generated with 2 groups
lb_type:
          1 current
          2 protection

. nlogittree policy type

tree structure specified for the nested logit model

        top-->bottom

       type      policy
------------------------
    current           C
 protection           A
                      B

. nlogit choice (policy = asc_a self pop field flood tax) (type = asc_ab 
sexd imp1d factord imp0d fpd marriagd edud rurald logincd), gro

> up(grp) ivc(current=1)
tree structure specified for the nested logit model

        top-->bottom

       type      policy
------------------------
    current           C
 protection           A
                      B

User defined constraint(s):
 1000:  [current]_cons = 1

initial:       log likelihood = -2268.5689
rescale:       log likelihood = -2268.5689
rescale eq:    log likelihood = -2255.7081
Iteration 0:   log likelihood = -2334.7989  (not concave)
Iteration 1:   log likelihood = -2238.8638
Iteration 2:   log likelihood = -2209.5625
Iteration 3:   log likelihood =  -2208.357
Iteration 4:   log likelihood = -2207.7547
Iteration 5:   log likelihood = -2207.5934
Iteration 6:   log likelihood = -2207.5902
Iteration 7:   log likelihood = -2207.5902

Nested logit
Levels             =          2                 Number of obs      = 
7680
Dependent variable =     choice                 LR chi2(17)        = 
1209.715
Log likelihood     = -2207.5902                 Prob > chi2        = 
0.0000

---------------------------------------------------------------------------
---
            |      Coef.   Std. Err.      z    P>|z|     [95% Conf. 
Interval]
-------------+-------------------------------------------------------------
---
policy       |
      asc_a |  -.3044942   .0648184    -4.70   0.000     -.431536 
-.1774525
       self |   .0037827   .0037277     1.01   0.310    -.0035234 
.0110889
        pop |  -.1091335   .0218872    -4.99   0.000    -.1520316 
-.0662354
      field |  -.0086041   .0011962    -7.19   0.000    -.0109487 
-.0062595
      flood |   .0023443   .0088254     0.27   0.791    -.0149532 
.0196418
        tax |   -.207383   .0101394   -20.45   0.000    -.2272558 
-.1875103
-------------+-------------------------------------------------------------
---
type         |
     asc_ab |   1.234788   .7000819     1.76   0.078    -.1373474 
2.606923
       sexd |   .1977326   .0925133     2.14   0.033     .0164098 
.3790554
      imp1d |  -.5137414   .0623688    -8.24   0.000    -.6359819 
-.3915009
    factord |   .3668055   .1024791     3.58   0.000     .1659502 
.5676608
      imp0d |   .3175041   .1090377     2.91   0.004     .1037942 
.531214
        fpd |   .7241194   .1021852     7.09   0.000     .5238402 
.9243986
   marriagd |  -.6216249   .1189533    -5.23   0.000     -.854769 
-.3884807
       edud |   .0849357   .0200909     4.23   0.000     .0455581 
.1243132
     rurald |   .0168562   .0051821     3.25   0.001     .0066995 
.0270129
    logincd |  -.5669557   .2322811    -2.44   0.015    -1.022218 
-.1116931
-------------+-------------------------------------------------------------
---
(IV params)  |
            |
type         |
   /current |          1          .        .       .            . 
.
   /protect |   .6517235   .0615388    10.59   0.000     .5311097 
.7723374
---------------------------------------------------------------------------
---
LR test of homoskedasticity (iv = 1): chi2(1)=   24.04    Prob > chi2 = 
0.0000
---------------------------------------------------------------------------
---

. gen grid = grp

. bs "nlogit choice (policy = asc_a self pop field flood tax) (type = 
asc_ab sexd imp1d factord imp0d fpd marriagd edud rurald logincd),

>  group(grid) ivc(current=1)" "_b[self] _b[pop] _b[field] _b[flood] 
_b[tax]", reps(200) cluster(grp) idcluster(grid)

command:     nlogit choice (policy = asc_a self pop field flood tax) (type 
= asc_ab sexd imp1d factord imp0d fpd marriagd edud rurald lo

> gincd), group(grid) ivc(current=1)
statistics:  _b[self] _b[pop] _b[field] _b[flood] _b[tax]



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