# st: nested logit model: how to interpret insignificant nesting parameter?

 From "Kelchtermans, Stijn" <[email protected]> To <[email protected]> Subject st: nested logit model: how to interpret insignificant nesting parameter? Date Thu, 24 Mar 2005 10:21:56 +0100

```All,

I have estimated a nested logit model explaining schooling choice, with all schooling options in one branch, and the outside option in the (degenerate) second branch. I have estimated the model sequentially because of the computational burden.

Question: the nesting parameter that measure the dissimilarity among the schooling options comes out slighly negative (-.0459305) and insignificant. Does the insignificance imply that the nesting is inappropriate?

The output (the estimates for the lower model were fixed to their first-step estimates):

Nested logit estimates

Levels             =          2                 Number of obs      =   546468

Dependent variable =     chosen                 LR chi2(14)        =  11816.01

Log likelihood     = -7198.8489                 Prob > chi2        =    0.0000

----------------------------------------------------------------------------
|      Coef.   Std. Err.      z    P>|z|     [95% Conf. Int.]
-------------+--------------------------------------------------------------
option       |
LSIZE |   .9400799          .        .       .            .         .
VOCL |  -.6005096          .        .       .            .         .
VOCLmale |   .2947062          .        .       .            .         .
VOCLfor |   .4408798          .        .       .            .         .

[cut]

ctrav |  -5.145888          .        .       .            .         .

-------------+--------------------------------------------------------------
STUDY        |
NONE |   1.169447   .2569964     4.55   0.000     .6657433  1.673151
NONEmale |   .1646824   .1107066     1.49   0.137    -.0522985  .3816633

[cut]

NONEcath |  -.4957498   .1248174    -3.97   0.000    -.7403875   -.2511122

-------------+----------------------------------------------------------------

(incl. value |

parameters) |

STUDY        |

/YES |  -.0459305    .073946    -0.62   0.535    -.1908621     .099001

/NO |          1          .        .       .            .           .

------------------------------------------------------------------------------

LR test of homoskedasticity (iv = 1): chi2(-164)=  -26.94 Prob > chi2 =      .

----------------------------------------------------------------------------

Many thanks,

Stijn Kelchtermans
Katholieke Universiteit Leuven
Belgium
[email protected]

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```