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st: RE: Using ivhettest to test for heterogeneity
From
[email protected]
To
[email protected]
Subject
st: RE: Using ivhettest to test for heterogeneity
Date
Mon, 27 Feb 2012 09:37:57 +0100
Dear Mark,
Thank you for explaining me the usage of the two different commands.
Unfortunately, I cannot infer whether the two commands give the same
results from your toy auto example because I miss the -ivhettest-
command below. But kindly have a look at the following example using
my own dataset. There is a marked difference between the results after
calling -imtest, white- and -ivhettest, ivsq nr2-. I would be happy to
know where this difference must likely come from.
. reg COC DRANK LBAGE D_LBAGE LNMV LNBM LNLEV CapInt ROA AssTr LTG LVOL MAFE if FIN==0
Source | SS df MS Number of obs = 98
-------------+------------------------------ F( 12, 85) = 24.23
Model | .156474018 12 .013039502 Prob > F = 0.0000
Residual | .04574489 85 .000538175 R-squared = 0.7738
-------------+------------------------------ Adj R-squared = 0.7418
Total | .202218908 97 .002084731 Root MSE = .0232
------------------------------------------------------------------------------
COC | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
DRANK | -.2832065 .1170839 -2.42 0.018 -.5160006 -.0504123
LBAGE | -.0152769 .0087299 -1.75 0.084 -.0326344 .0020806
D_LBAGE | .032221 .0134307 2.40 0.019 .0055172 .0589248
LNMV | -.0046663 .0022202 -2.10 0.039 -.0090806 -.000252
LNBM | .0030857 .0060793 0.51 0.613 -.0090016 .015173
LNLEV | .0093984 .0140586 0.67 0.506 -.0185538 .0373506
CapInt | -.0209075 .0201706 -1.04 0.303 -.0610121 .0191972
ROA | -.0582245 .0346929 -1.68 0.097 -.1272033 .0107543
AssTr | -.0037709 .0039292 -0.96 0.340 -.0115832 .0040414
LTG | .0009717 .0000776 12.53 0.000 .0008175 .001126
LVOL | -.0011873 .0096773 -0.12 0.903 -.0204284 .0180538
MAFE | .0030178 .0005758 5.24 0.000 .0018729 .0041626
_cons | .2751544 .0723573 3.80 0.000 .1312886 .4190201
------------------------------------------------------------------------------
.
end of do-file
.
. imtest, white
White's test for Ho: homoskedasticity
against Ha: unrestricted heteroskedasticity
chi2(89) = 97.10
Prob > chi2 = 0.2613
Cameron & Trivedi's decomposition of IM-test
---------------------------------------------------
Source | chi2 df p
---------------------+-----------------------------
Heteroskedasticity | 97.10 89 0.2613
Skewness | 17.64 12 0.1272
Kurtosis | 1.82 1 0.1769
---------------------+-----------------------------
Total | 116.56 102 0.1537
---------------------------------------------------
. ivhettest, ivsq nr2
OLS heteroskedasticity test(s) using levels and squares of IVs
Ho: Disturbance is homoskedastic
White/Koenker nR2 test statistic : 58.500 Chi-sq(24) P-value = 0.0001
[email protected] wrote: -----
To: <[email protected]>
From: "Schaffer, Mark E"
Sent by: [email protected]
Date: 02/24/2012 11:51PM
Subject: st: RE: Using ivhettest to test for heterogeneity
Andreas,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> [email protected]
> Sent: 24 February 2012 20:14
> To: [email protected]
> Subject: st: Using ivhettest to test for heterogeneity
>
> Dear Statalist users,
>
> I am concerned with using White's general heteroskedasticity
> test when running an instrumental variables regression. There
> is an option "nr2" which can be used with -ivhettest- after
> the -ivreg2- command that displays the White-Koenker test
> statistic.
This is a test of heteroskedasticity in the IV equation (or "2nd stage"
if you prefer).
> However, when I run the first-stage regression
> manually and use the command "imtest, white", I get a very
> different value for the test statistic.
Because it's a test of heteroskedasticity in the first-stage regression.
> The help file for -ivhettest- claims that this command can
> also be used for OLS regressions.
It can; see the example in the help file. You estimate using OLS
(-regress- or -ivreg2-), then call -ivhettest-.
> But why do the -ivhettest-
> and -imtest- commands yield different test statistics?
They should be the same. Estimate using OLS and -regress-, and then
compare -imtest, white- with -ivhettest, ivsq nr2-. You should get the
same result. Below is an example using the toy auto dataset.
Cheers,
Mark
. reg mpg weight
Source | SS df MS Number of obs =
74
-------------+------------------------------ F( 1, 72) =
134.62
Model | 1591.9902 1 1591.9902 Prob > F =
0.0000
Residual | 851.469256 72 11.8259619 R-squared =
0.6515
-------------+------------------------------ Adj R-squared =
0.6467
Total | 2443.45946 73 33.4720474 Root MSE =
3.4389
------------------------------------------------------------------------
------
mpg | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
weight | -.0060087 .0005179 -11.60 0.000 -.0070411
-.0049763
_cons | 39.44028 1.614003 24.44 0.000 36.22283
42.65774
------------------------------------------------------------------------
------
. imtest, white
White's test for Ho: homoskedasticity
against Ha: unrestricted heteroskedasticity
chi2(2) = 5.89
Prob > chi2 = 0.0526
Cameron & Trivedi's decomposition of IM-test
---------------------------------------------------
Source | chi2 df p
---------------------+-----------------------------
Heteroskedasticity | 5.89 2 0.0526
Skewness | 4.92 1 0.0266
Kurtosis | 1.70 1 0.1919
---------------------+-----------------------------
Total | 12.51 4 0.0139
---------------------------------------------------
> Is the
> -ivhettest- a combined heteroskedasticity test that is
> computed from individual test statistics of the first-stage
> and reduced form regression in the case of 2SLS?
>
> Any help would be greatly appreciated!
>
> Andreas Zweifel
> *
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> * http://www.ats.ucla.edu/stat/stata/
>
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