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Antwort: st: Hausman Query


From   Justina Fischer <[email protected]>
To   [email protected]
Subject   Antwort: st: Hausman Query
Date   Wed, 5 Jan 2011 11:22:17 +0100

Hi

I am not an expert on this (any around ?), but I would just do what Stata suggests.
Hausman needs to calculate "[(V_b-V_B)^(-1)]", which, obviously, cannot be done for one of your estimators.

My guess would be that House price causes that problem, or any variable with an extremely small coefficient estimate. Try rescaling....

Justina
[email protected] schrieb: -----

An: "[email protected]" <[email protected]>
Von: "Ross, Andrew" <[email protected]>
Gesendet von: [email protected]
Datum: 05.01.2011 09:50AM
Thema: st: Hausman Query

Hello

I am currently using Stata to investigate new firm formation for 32 Scottish regions over a 10 year period. I was wondering, if you might offer your opinion on a Stata related matter, that I have encountered?

As you can see from the attached output I've run a fixed and random effects model and followed this by the hausman test. However, the hausman highlights a 'note', as you will see from the attached output.

I was wondering, if you could shed any light on this note and what is means? I have asked four other people and they do not know. One suggested it may be a result of over parameterisation given the small size of the panel, but they are not sure.

Many thanks.

Andrew

xtreg Lab_TP Wge_grow Pop_grow Log_unemployed NVQ4_pop House_price LQ_agric LQ_man LQ_b
> s Pop_density Gov_sector Small_bus, fe vce (robust)

Fixed-effects (within) regression               Number of obs      =       320
Group variable: Region                          Number of groups   =        32

R-sq:  within  = 0.2061                         Obs per group: min =        10
between = 0.0019                                        avg =      10.0
overall = 0.0030                                        max =        10

F(11,277)          =      3.10
corr(u_i, Xb)  = -0.9507                        Prob > F           =    0.0006

(Std. Err. adjusted for clustering on Region)
------------------------------------------------------------------------------

-------------+----------------------------------------------------------
-------------+------ Log_unempl~d |   4.109563   4.222209     0.97   0.331     -4.20213    12.42126
NVQ4_pop |  -.0295052   .0431429    -0.68   0.495    -.1144348    .0554243
House_price |   .0000483   .0000121     3.99   0.000     .0000245    .0000722
LQ_agric |   .1687096   .4963323     0.34   0.734    -.8083529    1.145772 Pop_density |   .0236083   .0110802     2.13   0.034     .0017962    .0454204
Gov_sector |  -.0001643   .0309392    -0.01   0.996    -.0610701    .0607415 -------------+----------------------------------------------------------
-------------+------ rho |   .9763121   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. estimates store fixed

. xtreg Lab_TP Wge_grow Pop_grow Log_unemployed NVQ4_pop House_price LQ_agric LQ_man LQ
> _bs Pop_density Gov_sector Small_bus, re vce (robust)

Random-effects GLS regression                   Number of obs      =       320
Group variable: Region                          Number of groups   =        32

R-sq:  within  = 0.1667                         Obs per group: min =        10
between = 0.6091                                        avg =      10.0
overall = 0.4986                                        max =        10

Random effects u_i ~ Gaussian                   Wald chi2(12)      =   3152.08
corr(u_i, X)       = 0 (assumed)                Prob > chi2        =    0.0000

(Std. Err. adjusted for clustering on Region)
------------------------------------------------------------------------------ -------------+----------------------------------------------------------
-------------+------ Log_unempl~d |  -4.643811   2.993296    -1.55   0.121    -10.51056    1.222941
NVQ4_pop |    .008423   .0484623     0.17   0.862    -.0865613    .1034074
House_price |   .0000265   .0000108     2.46   0.014     5.39e-06    .0000476
LQ_agric |   .7014816   .4126435     1.70   0.089    -.1072848    1.510248 Pop_density |   .0023373   .0006452     3.62   0.000     .0010727    .0036018
Gov_sector |  -.0345817    .034529    -1.00   0.317    -.1022574    .0330939 -------------+----------------------------------------------------------
-------------+------ rho |  .40033378   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. estimates store random

. hausman fixed random

Note: the rank of the differenced variance matrix (10) does not equal the number of
coefficients being tested (11); be sure this is what you expect, or there may
be problems computing the test.  Examine the output of your estimators for
anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
-------------+----------------------------------------------------------
-------------+------ Log_unempl~d |    4.109563    -4.643811        8.753374        2.977789
NVQ4_pop |   -.0295052      .008423       -.0379283               .
House_price |    .0000483     .0000265        .0000218        5.53e-06
LQ_agric |    .1687096     .7014816       -.5327721        .2758099 Pop_density |    .0236083     .0023373         .021271        .0110614
Gov_sector |   -.0001643    -.0345817        .0344174               .
Small_bus |    .3920981     .6680098       -.2759117        .3975498
------------------------------------------------------------------------------ Andrew Ross
PhD Candidate
School of Accounting, Economics & Statistics
Napier University Business School
Craiglockhart Campus
Room 1/38
EH14 IDJ
Email: [email protected]







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