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RE: st: RE: Questions on ivprobit (probit model with an endogenousregressor)
Mark,
Thanks a lot! I appreciate your help.
Regards,
Stephen
--
Stephen Owusu-Ansah, PhD, CIA, CBM
---- "Schaffer wrote:
> Stephen,
>
> The output below is messy because of all the line breaks, so I'll reply up here.
>
> - You are right, there is a problem with the syntax, though it probably matters only for appearances. The varlist following the = should have only the EXCLUDED instruments, and should not include instruments that are also exogneous regressors. Thus you have
>
> ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2 aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind_8 grth efin optn (bdin = dual ihol mhol efin size levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind_8 optn vrics_1), first
>
> But it should be
>
> ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2 aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind_8 grth efin optn (bdin = vrics_1), first
>
> I am pretty sure this doesn't matter, though, in terms of results - Stata will (probably?) take care of the collinearities in the varlists in such a way that you will get the same results either way.
>
> - This probably also explains your query about the number of "instrumented variables", though presumably you actually mean "instrumental variables" or just "instruments" ("instrumentED variables" are endogenous regressors).
>
> - In your estimation results, you have a large number of statistically insignificant regressors. This could be a sign of multicollinearity (I'm not sure how you know you don't have this problem). In any case, it may explain why it takes so long for your model to converge.
>
> - The statement at the end
>
> note: 47 failures and 30 successes completely determined
>
> is a common error message in Stata output for limited dependent variable models (logit, probit, etc.). Have a look at the FAQ for the logit case:
>
> http://www.stata.com/support/faqs/stat/logitcd.html
>
> Cheers,
> Mark
>
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]] On Behalf Of
> > [email protected]
> > Sent: Monday, January 07, 2008 1:51 AM
> > To: [email protected]
> > Cc: Schaffer, Mark E
> > Subject: Re: st: RE: Questions on ivprobit (probit model with
> > an endogenous regressor)
> >
> > Hi Mark:
> >
> > Thanks for your prompt response to my questions. I am
> > reposing three of the earlier questions, which you needed
> > more information. I have now provided enough information
> > below to enable you to help me.
> >
> > 1. Is there anything with my syntax below? If yes, how can it
> > be corrected?
> >
> > ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5
> > ind_6 ind_7 ind_8 grth efin optn (bdin = dual ihol mhol fcash
> > size levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind_8
> > optn vrics_1), first
> >
> > 2. Stata increases the number of the instrumented variables
> > in its results than I originally specified in the syntax?
> > Why that? Is it because my model is under-identified?
> >
> > 3. For the fitting of the full model (i.e., probit model with
> > the endogenous regressor), Stata goes through iteration from
> > 1 to 1070, reporting that the intervening iterations (i.e., 1
> > to 1068) are not concave. Why this long iteration? Does it
> > suggest that the model is mis-specified? Or implies that the
> > results are not correct? I DON'T HAVE MULTICOLLINEARITY
> > PROBLEM IN THE DATA.
> >
> > The following are the equations I have been estimating with
> > the ivprobit:
> >
> > BDIN, = F(δ0 + δ1MHOL + δ2BDZE + δ3DUAL + δ4IHOL + δ5SIZE + δ6LEVG
> > + δ7GRTH + + δ17EFIN + δ18OPTN + δ19VRICSt_1)
> > (1)
> >
> > Prob (VRICS = 1) = F(β0 + β1MHOL + β2ACMT + β3IACM + β4BDZE
> > + β5FT_BDIN + β6MDIR + β7DUAL + βb8IHOL + + β14SIZE
> > + β15PERF + β16LEVG + + β26GRTH + β27EFIN + β28OPTN)
> > (2)
> >
> > Equation 2 is the model of interest. FT_BDIN in equation 2
> > is the fitted values of BDIN in equation 1. My sample size
> > is 198 companies (110 experimental and 88 control sub-sample).
> >
> > The syntax and results are as follows:
> >
> > ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5
> > ind_6 ind_7 ind_8 grth efin optn (bdin = dual ihol mhol efin
> > size levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind_8
> > optn vrics_1), first Fitting exogenous probit model
> >
> > Iteration 0: log likelihood = -136.01839
> > .
> > Iteration 6: log likelihood = -103.21347
> >
> > Fitting full model
> >
> > Iteration 0: log likelihood = -507.53953 (not concave)
> > Iteration 1: log likelihood = -507.44146 (not concave)
> > .
> > .
> > Iteration 1061:log likelihood = -467.50251 (backed up)
> > Iteration 1062:log likelihood = -465.17425 Iteration 1063:log
> > likelihood = -462.61643 .
> > .
> > Iteration 1070:log likelihood = -462.0811
> >
> > Probit model with endogenous regressors Number of
> > obs = 198
> >
> > Wald chi2(26) = 392.55
> > Log likelihood = -462.0811
> > Prob > chi2 = 0.0000
> > --------------------------------------------------------------
> > ----------------
> > | Coef. Std. Err. z P>|z|
> > [95% Conf. Interval]
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > vrics |
> > bdin | .535787 .0270656 19.80 0.000
> > .4827393 .5888347
> > mhol | .0082955 .6629267 0.01 0.990
> > -1.291017 1.307608
> > acmt | .0173609 .0293927 0.59 0.555
> > -.0402477 .0749695
> > iacm | -.2845267 .2214701 -1.28 0.199
> > -.7186002 .1495468
> > bdze | .1125746 .0368413 3.06 0.002
> > .040367 .1847823
> > mdir | -.1984201 .0348804 -5.69 0.000
> > -.2667844 -.1300558
> > dual | .3046553 .1763825 1.73 0.084
> > -.041048 .6503587
> > ihol | .5343345 .3381111 1.58 0.114
> > -.1283511 1.19702
> > aud_1 | -.118587 .2618686 -0.45 0.651
> > -.63184 .3946661
> > aud_2 | -.1315854 .1602961 -0.82 0.412
> > -.4457599 .1825892
> > aud_3 | -.2391904 .3023197 -0.79 0.429
> > -.8317261 .3533454
> > aud_4 | -.1764671 .2734199 -0.65 0.519
> > -.7123601 .359426
> > size | -.394326 .085888 -4.59 0.000
> > -.5626634 -.2259885
> > perf | .1184288 .5215651 0.23 0.820
> > -.90382 1.140678
> > levg | -.6340103 .4221428 -1.50 0.133
> > -1.461395 .1933744
> > ind_1 | .638568 .4017463 1.59 0.112
> > -.1488403 1.425976
> > ind_2 | .5798336 .3313281 1.75 0.080
> > -.0695576 1.229225
> > ind_3 | .7170456 .3188755 2.25 0.025
> > .0920611 1.34203
> > ind_4 | .3894297 .3882769 1.00 0.316
> > -.371579 1.150438
> > ind_5 | .7477128 .3261907 2.29 0.022
> > .1083907 1.387035
> > ind_6 | .8033681 .4126983 1.95 0.052
> > -.0055056 1.612242
> > ind_7 | .5320546 .4018902 1.32 0.186
> > -.2556357 1.319745
> > ind_8 | 1.585647 .5801551 2.73 0.006
> > .4485636 2.72273
> > grth | .0025123 .0013356 1.88 0.060
> > -.0001053 .0051299
> > efin | .0080272 .0116433 0.69 0.491
> > -.0147932 .0308476
> > optn | .0069244 .011954 0.58 0.562
> > -.0165049 .0303537
> > _cons | 7.2861 1.909368 3.82 0.000
> > 3.543807 11.02839
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > bdin |
> > mhol | .0378184 1.235286 0.03 0.976
> > -2.383298 2.458935
> > acmt | -.033273 .0544709 -0.61 0.541
> > -.1400339 .073488
> > iacm | .596355 .367546 1.62 0.105
> > -.1240219 1.316732
> > bdze | -.2195357 .0680645 -3.23 0.001
> > -.3529396 -.0861318
> > mdir | .3700483 .0622494 5.94 0.000
> > .2480418 .4920548
> > dual | -.573009 .326602 -1.75 0.079
> > -1.213137 .0671192
> > ihol | -1.012138 .6303383 -1.61 0.108
> > -2.247578 .2233028
> > aud_1 | .14425 .4679218 0.31 0.758
> > -.7728599 1.06136
> > aud_2 | .1355325 .236811 0.57 0.567
> > -.3286086 .5996736
> > aud_3 | .300847 .4963293 0.61 0.544
> > -.6719404 1.273634
> > aud_4 | .2759295 .4846338 0.57 0.569
> > -.6739352 1.225794
> > size | .7537389 .1458796 5.17 0.000
> > .4678201 1.039658
> > perf | -.181126 .9590768 -0.19 0.850
> > -2.060882 1.69863
> > levg | 1.132908 .7862537 1.44 0.150
> > -.4081206 2.673937
> > ind_1 | -1.167724 .744777 -1.57 0.117
> > -2.627461 .2920118
> > ind_2 | -1.046297 .6184434 -1.69 0.091
> > -2.258424 .1658298
> > ind_3 | -1.318878 .590602 -2.23 0.026
> > -2.476436 -.1613189
> > ind_4 | -.7132557 .721654 -0.99 0.323
> > -2.127672 .7011601
> > ind_5 | -1.400158 .6024688 -2.32 0.020
> > -2.580976 -.2193413
> > ind_6 | -1.427494 .7589549 -1.88 0.060
> > -2.915018 .0600307
> > ind_7 | -1.033129 .7444047 -1.39 0.165
> > -2.492135 .4258778
> > ind_8 | -2.996058 1.066981 -2.81 0.005
> > -5.087302 -.9048135
> > grth | -.0046962 .0024757 -1.90 0.058
> > -.0095485 .000156
> > efin | -.0175522 .0208806 -0.84 0.401
> > -.0584774 .0233729
> > optn | -.0136099 .0222878 -0.61 0.541
> > -.0572931 .0300734
> > vrics_1 | .198787 .3208153 0.62 0.536
> > -.4299995 .8275734
> > _cons | -13.92576 3.327674 -4.18 0.000
> > -20.44788 -7.403639
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > /athrho | -3.964625 1.619449 -2.45 0.014
> > -7.138687 -.7905633
> > /lnsigma | .6231125 .050253 12.40 0.000
> > .5246184 .7216065
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > rho | -.9992801 .0023307
> > -.9999987 -.658728
> > sigma | 1.864723 .0937079
> > 1.689814 2.057736
> > --------------------------------------------------------------
> > ----------------
> > Instrumented: bdin
> > Instruments: mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > aud_3 aud_4 size
> > perf levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6
> > ind_7 ind_8 grth
> > efin optn vrics_1*
> > --------------------------------------------------------------
> > ----------------
> > Wald test of exogeneity (/athrho = 0): chi2(1) = 5.99
> > Prob > chi2 = 0.0144
> >
> > *Some of the instrumented variables were not specified in the
> > original syntax.
> >
> > Below is the syntax and results when I used two-step
> > estimator. What does the note at the bottom of the results mean?
> >
> > ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5
> > ind_6 ind_7 ind_8 grth efin optn (bdin = dual ihol mhol efin
> > size levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6 ind_7 ind _8
> > optn vrics_1), twostep first
> >
> > Checking reduced-form model
> > First stage regression
> >
> > Source | SS df MS
> > Number of obs = 198
> > -------------+------------------------------
> > F( 26, 171) = 5.18
> > Model | 542.099097 26 20.8499653
> > Prob > F = 0.0000
> > Residual | 688.483679 171 4.02622035
> > R-squared = 0.4405
> > -------------+------------------------------
> > Adj R-squared = 0.3555
> > Total | 1230.58278 197 6.24661308
> > Root MSE = 2.0065
> > --------------------------------------------------------------
> > ----------------
> > bdin | Coef. Std. Err. t P>|t|
> > [95% Conf. Interval]
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > vrics_1 | .1988048 .3453415 0.58 0.566
> > -.4828765 .8804861
> > mhol | .0378225 1.329227 0.03 0.977
> > -2.585984 2.661629
> > acmt | -.0332726 .0586135 -0.57 0.571
> > -.1489718 .0824266
> > iacm | .5963493 .3955089 1.51 0.133
> > -.1843592 1.377058
> > bdze | -.2195362 .0732413 -3.00 0.003
> > -.3641098 -.0749626
> > mdir | .3700488 .0669836 5.52 0.000
> > .2378275 .50227
> > dual | -.5730081 .3514396 -1.63 0.105
> > -1.266727 .1207105
> > ihol | -1.012142 .6782774 -1.49 0.137
> > -2.351017 .3267326
> > aud_1 | .14425 .5035061 0.29 0.775
> > -.8496378 1.138138
> > aud_2 | .1355322 .2548215 0.53 0.596
> > -.3674686 .638533
> > aud_3 | .3008486 .5340752 0.56 0.574
> > -.7533807 1.355078
> > aud_4 | .2759339 .5214952 0.53 0.597
> > -.7534632 1.305331
> > size | .7537372 .1569757 4.80 0.000
> > .4438776 1.063597
> > perf | -.1811319 1.032013 -0.18 0.861
> > -2.218258 1.855994
> > levg | 1.132905 .8460482 1.34 0.182
> > -.5371384 2.802948
> > ind_1 | -1.167724 .801416 -1.46 0.147
> > -2.749666 .4142183
> > ind_2 | -1.046293 .6654784 -1.57 0.118
> > -2.359903 .2673175
> > ind_3 | -1.318876 .6355171 -2.08 0.039
> > -2.573345 -.0644069
> > ind_4 | -.7132544 .7765309 -0.92 0.360
> > -2.246075 .8195664
> > ind_5 | -1.400157 .6482868 -2.16 0.032
> > -2.679832 -.1204813
> > ind_6 | -1.427492 .8166718 -1.75 0.082
> > -3.039548 .1845637
> > ind_7 | -1.033129 .8010162 -1.29 0.199
> > -2.614282 .5480241
> > ind_8 | -2.996057 1.148121 -2.61 0.010
> > -5.262373 -.7297423
> > grth | -.0046962 .002664 -1.76 0.080
> > -.0099548 .0005623
> > efin | -.0175522 .0224685 -0.78 0.436
> > -.0619036 .0267992
> > optn | -.0136099 .0239828 -0.57 0.571
> > -.0609505 .0337306
> > _cons | -13.92572 3.580775 -3.89 0.000
> > -20.99394 -6.857512
> > --------------------------------------------------------------
> > ----------------
> >
> > Two-step probit with endogenous regressors Number of
> > obs = 198
> >
> > Wald chi2(26) = 0.99
> >
> > Prob > chi2 = 1.0000
> > --------------------------------------------------------------
> > ----------------
> > | Coef. Std. Err. z P>|z|
> > [95% Conf. Interval]
> > -------------+------------------------------------------------
> > ----------
> > -------------+------
> > bdin | 14.12199 24.61414 0.57 0.566
> > -34.12084 62.36482
> > mhol | .2186578 18.79424 0.01 0.991
> > -36.61738 37.05469
> > acmt | .4575839 1.235632 0.37 0.711
> > -1.96421 2.879378
> > iacm | -7.49924 17.15531 -0.44 0.662
> > -41.12302 26.12454
> > bdze | 2.967177 5.363456 0.55 0.580
> > -7.545004 13.47936
> > mdir | -5.22986 9.026449 -0.58 0.562
> > -22.92138 12.46166
> > dual | 8.029926 15.17887 0.53 0.597
> > -21.72012 37.77997
> > ihol | 14.08375 25.45977 0.55 0.580
> > -35.81648 63.98398
> > aud_1 | -3.125751 7.994754 -0.39 0.696
> > -18.79518 12.54368
> > aud_2 | -3.468392 5.087113 -0.68 0.495
> > -13.43895 6.502165
> > aud_3 | -6.304659 10.32934 -0.61 0.542
> > -26.54979 13.94047
> > aud_4 | -4.651355 9.189619 -0.51 0.613
> > -22.66268 13.35997
> > size | -10.39339 19.15959 -0.54 0.587
> > -47.9455 27.15873
> > perf | 3.121618 14.83004 0.21 0.833
> > -25.94473 32.18797
> > levg | -16.71092 31.29799 -0.53 0.593
> > -78.05385 44.63201
> > ind_1 | 16.83106 30.99911 0.54 0.587
> > -43.92608 77.58821
> > ind_2 | 15.28294 28.46859 0.54 0.591
> > -40.51448 71.08035
> > ind_3 | 18.89951 34.12934 0.55 0.580
> > -47.99277 85.79179
> > ind_4 | 10.26438 21.0224 0.49 0.625
> > -30.93877 51.46753
> > ind_5 | 19.70779 36.16063 0.55 0.586
> > -51.16575 90.58132
> > ind_6 | 21.17483 37.29913 0.57 0.570
> > -51.93013 94.27978
> > ind_7 | 14.02357 27.7139 0.51 0.613
> > -40.29468 68.34181
> > ind_8 | 41.79358 75.57157 0.55 0.580
> > -106.324 189.9111
> > grth | .0662178 .1233329 0.54 0.591
> > -.1755102 .3079459
> > efin | .2115723 .5480824 0.39 0.699
> > -.8626495 1.285794
> > optn | .1825097 .4637365 0.39 0.694
> > -.7263971 1.091416
> > _cons | 192.0422 356.4177 0.54 0.590
> > -506.5236 890.6081
> > --------------------------------------------------------------
> > ----------------
> > Instrumented: bdin
> > Instruments: mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > aud_3 aud_4
> > size perf levg ind_1 ind_2 ind_3 ind_4 ind_5
> > ind_6 ind_7
> > ind_8 grth efin optn vrics_1
> > --------------------------------------------------------------
> > ----------------
> > Wald test of exogeneity: chi2(1) = 51.79
> > Prob > chi2 = 0.0000
> >
> > note: 47 failures and 30 successes completely determined.
> >
> > Regards,
> >
> > Stephen
> >
> > ---- "Schaffer wrote:
> > > Stephen,
> > >
> > > > -----Original Message-----
> > > > From: [email protected]
> > > > [mailto:[email protected]] On Behalf Of
> > > > [email protected]
> > > > Sent: 06 January 2008 21:45
> > > > To: [email protected]
> > > > Subject: st: Questions on ivprobit (probit model with an
> > endogenous
> > > > regressor)
> > > >
> > > > Dear colleagues:
> > > >
> > > > I need your help with respect to the following questions about
> > > > ivprobit (command for probit model with an endogenous
> > > > regressor):
> > > >
> > > > 1. Is there anything with my syntax below? If yes, how can it be
> > > > corrected?
> > > >
> > > > ivprobit vrics mhol acmt iacm bdze mdir dual ihol aud_1 aud_2
> > > > aud_3 aud_4 size perf levg ind_1 ind_2 ind_3 ind_4 ind_5
> > > > ind_6 ind_7 ind_8 rev_gwth fcash optns (bdin= dual ihol
> > mhol fcash
> > > > size levg ind_1 ind_2 ind_3 ind_4 ind_5 ind_6
> > > > ind_7 ind_8 optns vrics_1), first
> > >
> > > It's impossible to tell without seeing the actual call to
> > -ivprobit-
> > > and what Stata makes of it. You should post this.
> > >
> > > > 2. The dependent variable, vrics, is a dummy coded 1/0.
> > > > Hence, my use of ivprobit. However, the endogenous
> > regressor, bdin,
> > > > is not. Isn't ivprobit reading the data on bdin as dummy?
> > >
> > > No. It's because you're using the default ML estimator.
> > If you use
> > > the two-step estimator, you'll see that the first-step
> > estimates for
> > > bdin are exactly the same estimates you get if you use -regress-.
> > >
> > > > My question is based on the fact that OLS estimates of the bdin
> > > > equation is different from those returned by ivprobit for the
> > > > first-stage regression. Also, Stata 10 reports iteration for
> > > > "Fitting exogenous probit model".
> > > >
> > > > 3. Stata increases the number of the instrumented
> > variables in its
> > > > results than I originally specified in the syntax? Why
> > that? Is it
> > > > because my model is under-identified?
> > >
> > > Again, it's impossible to tell unless you show us the call to
> > > -ivprobit- and the results.
> > >
> > > > 4. For the fitting of the full model (i.e., probit model with the
> > > > endogenous regressor), Stata goes through iteration from
> > > > 1 to 1070, reporting that the intervening iterations (i.e., 1 to
> > > > 1068) are not concave. Why this long iteration? Does it
> > suggest that
> > > > the model is mis-specified? Or implies that the results are not
> > > > correct?
> > >
> > > You're probably asking a lot of the data, maybe too much.
> > Perhaps you
> > > have some multicollinearity problems. Are many of the coefficients
> > > insignificant?
> > >
> > > > 5. Stata 10 does not report model summary statistics for the
> > > > first-stage regression with bdin as the dependent variable.
> > > > Is there any way of getting these statistics?
> > >
> > > With the ML estimator, the "first-stage regression" isn't really a
> > > first stage, since it's estimated simultaneously with the main
> > > equation. I think this means that you just have to get the
> > stats you
> > > want from the main -ivprobit- results with the ML estimator. You
> > > could switch to the two-step estimator so that the
> > first-stage results
> > > are reproducible with a simple call to -regress-, but this doesn't
> > > seem like a good reason to do this.
> > >
> > > Hope this helps.
> > >
> > > Cheers,
> > > Mark
> > >
> > >
> > > Prof. Mark Schaffer
> > > Director, CERT
> > > Department of Economics
> > > School of Management & Languages
> > > Heriot-Watt University, Edinburgh EH14 4AS tel
> > +44-131-451-3494 / fax
> > > +44-131-451-3296
> > > email: [email protected]
> > > web: http://www.sml.hw.ac.uk/ecomes
> > >
> > > > I look forward to hearing from you. Thanks for your cooperation.
> > > >
> > > > Regards,
> > > >
> > > > Stephen
> > > > --
> > > > Stephen Owusu-Ansah, PhD, CIA, CBM
> > > >
> > > > *
> > > > * For searches and help try:
> > > > * http://www.stata.com/support/faqs/res/findit.html
> > > > * http://www.stata.com/support/statalist/faq
> > > > * http://www.ats.ucla.edu/stat/stata/
> > > >
> > >
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/support/faqs/res/findit.html
> > > * http://www.stata.com/support/statalist/faq
> > > * http://www.ats.ucla.edu/stat/stata/
> >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/