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From |
andreas.zweifel@uzh.ch |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: RE: Using ivhettest to test for heterogeneity |

Date |
Thu, 1 Mar 2012 10:00:40 +0100 |

Hi As far as I have understood, reducing the degrees of freedom may increase the power of the heterogeneity test if the number of observations is small. With my sample, the opposite is apparently the case because the p-value of the test increases with decreasing degrees of freedom: . reg COC DRANK D_LBAGE LBAGE LNMV LNBM LNLEV CapInt ROA AssTr LTG LVOL MAFE Source | SS df MS Number of obs = 130 -------------+------------------------------ F( 12, 117) = 27.58 Model | .185658991 12 .015471583 Prob > F = 0.0000 Residual | .065629152 117 .000560933 R-squared = 0.7388 -------------+------------------------------ Adj R-squared = 0.7120 Total | .251288143 129 .00194797 Root MSE = .02368 ------------------------------------------------------------------------------ COC | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- DRANK | -.2427198 .101898 -2.38 0.019 -.4445234 -.0409162 D_LBAGE | .0284015 .0117121 2.42 0.017 .0052063 .0515967 LBAGE | -.0145643 .0073708 -1.98 0.051 -.0291619 .0000332 LNMV | -.0015457 .0018037 -0.86 0.393 -.0051178 .0020265 LNBM | .0096937 .0048182 2.01 0.047 .0001514 .019236 LNLEV | .0000791 .0060169 0.01 0.990 -.011837 .0119952 CapInt | -.0261037 .01005 -2.60 0.011 -.0460072 -.0062001 ROA | -.022799 .0294708 -0.77 0.441 -.0811644 .0355663 AssTr | -.0028776 .0033909 -0.85 0.398 -.0095932 .0038379 LTG | .0009762 .0000745 13.10 0.000 .0008286 .0011238 LVOL | .0168072 .0058712 2.86 0.005 .0051796 .0284348 MAFE | .0020086 .0004498 4.47 0.000 .0011178 .0028993 _cons | .2656843 .0619192 4.29 0.000 .1430566 .3883121 ------------------------------------------------------------------------------ . imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(89) = 120.87 Prob > chi2 = 0.0139 Cameron & Trivedi's decomposition of IM-test --------------------------------------------------- Source | chi2 df p ---------------------+----------------------------- Heteroskedasticity | 120.87 89 0.0139 Skewness | 17.08 12 0.1464 Kurtosis | 1.14 1 0.2852 ---------------------+----------------------------- Total | 139.10 102 0.0086 --------------------------------------------------- . ivhettest, ivcp nr2 OLS heteroskedasticity test(s) using levels and cross products of all IVs Ho: Disturbance is homoskedastic White/Koenker nR2 test statistic : 120.871 Chi-sq(89) P-value = 0.0139 . ivhettest, ivsq nr2 OLS heteroskedasticity test(s) using levels and squares of IVs Ho: Disturbance is homoskedastic White/Koenker nR2 test statistic : 39.427 Chi-sq(24) P-value = 0.0246 . ivhettest, nr2 OLS heteroskedasticity test(s) using levels of IVs only Ho: Disturbance is homoskedastic White/Koenker nR2 test statistic : 19.416 Chi-sq(12) P-value = 0.0790 I appreciate your help with interpreting this counterintuitive result. Best, Andreas -----owner-statalist@hsphsun2.harvard.edu wrote: ----- To: statalist@hsphsun2.harvard.edu From: Nick Cox Sent by: owner-statalist@hsphsun2.harvard.edu Date: 02/29/2012 11:01AM Subject: Re: st: RE: RE: Using ivhettest to test for heterogeneity The motivation for power calculations seems to be compromised when the hypotheses being tested are determined by looking at results. I am a great fan of looking at results to see whether I should revise my analysis. But then I don't ever do power calculations and I sit loose to most significance tests. Nick On Wed, Feb 29, 2012 at 9:03 AM, <andreas.zweifel@uzh.ch> wrote: > Yes, I see now that the two commands (-imtest, white- and -ivhettest, ivcp nr2-) > produce equivalent results also for my sample. I think it is a good idea to > reduce the degrees of freedom because I have only 98 observations in my sample. > Maybe I could even drop the -ivsq- option (and hence ignoring also the squares > of the instruments). By calling just -ivhettest, nr2- I could enhance the > power of the test by decreasing the degrees of freedom to 12. > [very big snip] * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: RE: RE: Using ivhettest to test for heterogeneity***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

**RE: st: RE: RE: Using ivhettest to test for heterogeneity***From:*andreas.zweifel@uzh.ch

**RE: st: RE: RE: Using ivhettest to test for heterogeneity***From:*Nick Cox <n.j.cox@durham.ac.uk>

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