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From |
Suryadipta Roy <sroy2138@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Antwort: Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests |

Date |
Wed, 25 Jan 2012 19:05:31 -0500 |

Andreas, I see the problem. You are right; - condivreg- is not valid for more than one endogenous variable. My first reaction will be similar what has been probably suggested by another subscriber, i.e. to try using powers of x1hat and that of the product of x1hat and x2 to generate additional instruments for testing overidentification in -ivreg2- accompanied by -first- (/-ffirst-) option. If x1 is a limited dependent variable, then you might probably get even more creative by using a non-linear specification (or -rivtest- etc.) along with the usual linear model to generate different values of x1hat, and then interact them with x2 and see whether they retain sufficient independent information to be used as instruments. Or, trying out a log-log model (and/or log linear model) for x1 along with the linear model. Of course, one can check all the specifications checking the adjusted-r square, or the AIC/BIC following the -estat ic- command. Best wishes, Suryadipta. On Wed, Jan 25, 2012 at 5:49 AM, Justina Fischer <JAVFischer@gmx.de> wrote: > Dear Andreas, > > finding suitable instruments (in terms of economic-theoretical coherence with the endogenous) is something this list does not aim at. > > best > > Justina > > > -------- Original-Nachricht -------- >> Datum: Wed, 25 Jan 2012 08:40:54 +0100 >> Von: andreas.zweifel@uzh.ch >> An: statalist@hsphsun2.harvard.edu >> Betreff: Antwort: Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests > >> Hi Suyadipta, >> >> thank you for the suggestion to use -condivreg-. Unfortunately, the >> command works with one endogenous regressor only. However, I have two endogenous >> regressors due to an interaction of the >> original endogenous variable X1 and an exogenous control X2, i.e. my model >> looks like >> >> Y = X1 + X1*X2 + controls + e >> >> I have been recommended to estimate first X1 by instruments Zi (i=1,...n) >> to obtain X1hat, than form interactions X1hat*X2 as instruments to be used >> in the -ivreg2- command which then would be >> >> ivreg2 Y controls (X1 X1*X2 = X1hat X1hat*X2) >> >> (see http://www.stata.com/statalist/archive/2011-08/msg01496.html) >> >> This actually solves the endogeneity problem since the F-statistic of the >> weak instruments test substantially increases compared to the canned 2SLS >> procedure >> >> ivreg2 Y controls (X1 X1*X2 = Zi Zi*X2) >> >> where each basic instrument Zi is interacted with X2 yielding n combined >> instruments. So in total, I have 2*n instruments for 2 endogenous >> regressors. >> >> In the special case of only one basic instrument Z1 (n=1), the first 2SLS >> approach and canned SLS just coincide because the model is exactly >> identified in both cases. However, to test whether >> the instruments are really valid you should have n>1 instruments for one >> endogenous regressor. This yields another problem because in the first 2SLS >> approach there are always two endogenous regressors and two instruments by >> construction. Thus I can see no way how to test for overidentifying >> restrictions with this approach. >> >> I would appreciate any help with respect to a possible solution to that >> problem. >> >> Andreas Zweifel >> >> >> -----owner-statalist@hsphsun2.harvard.edu schrieb: ----- >> An: statalist@hsphsun2.harvard.edu >> Von: Suryadipta Roy >> Gesendet von: owner-statalist@hsphsun2.harvard.edu >> Datum: 24.01.2012 13:20 >> Betreff: Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious >> inference from endogeneity tests >> >> Andreas, >> Along these lines, I would also suggest that you take a look at the >> condivreg command ( - findit condivreg - , the help file and the >> related papers) for detecting weak instruments. The Murray (2006) >> paper cited below is suggesting in those lines. The Stata journal >> references are Mikusheva and Poi (2003), Stata Journal 3: 57–70, and >> Mikusheva and Poi (2006), Stata Journal 6: 335–347. >> >> Best wishes, >> Suryadipta. >> >> On Mon, Jan 23, 2012 at 10:18 AM, Justina Fischer <JAVFischer@gmx.de> >> wrote: >> > Hi Andreas >> > >> > 1) true. This is why you should always consult several test stats (incl. >> t-stats, F-stats, Shea R2, robust-to-weak instr. stats, etc.) to get an >> overall picture. Selecting instruments is a hard and complex business... >> > >> > 2) reduncancy tests make only sense when you have managed to select good >> instruments (it is based on the Sargan/Hansen-J test, if I recall well -> >> consult ivreg2 help file). >> > >> > 3) practice shows it is in most cases to have no of instruments > >> endogenous regressors, but not too many in absolute number. For one endogenous >> regressor, I usually try to find three instruments. You can increase the >> number of instruments artificially by doing some non-linear stuff, e.g. using a >> quadratic term. >> > >> > Best, >> > justina >> > >> > >> > -------- Original-Nachricht -------- >> >> Datum: Mon, 23 Jan 2012 15:59:27 +0100 >> >> Von: andreas.zweifel@uzh.ch >> >> An: statalist@hsphsun2.harvard.edu >> >> Betreff: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious >> inference from endogeneity tests >> > >> >> Hi Justina, >> >> >> >> thank you for the intuitive ideas with respect to the quality of the >> >> instruments. >> >> >> >> So I was wrong with my notion that one should have as many instruments >> as >> >> endogenous variables in the regression. But I can tell you that I have >> >> already tested my model with one endogenous regressor under >> overidentification, >> >> that is with a whole set of instruments. The Sargan test statistic >> using >> >> -ivreg2- (or -ivreg28- in Stata8) is clearly not significant then, so >> the >> >> null that the instruments are exogenous cannot be rejected. However, I >> fear >> >> that this is weak evidence especially for my setting, because >> >> >> >> 1) To my knowlegde, Sargan only allows to test whether the instruments >> are >> >> *jointly* exogenous. It does yield no information about the strength of >> >> one single instrument. >> >> >> >> 2) Using the -redundant- option in -ivreg2-, I get contradictory >> results. >> >> I tried a sensitivity test with a varying number of possibly good >> >> instruments and control variables to find the following: Virtually >> every instrument >> >> candidate yields a more or less significant p-value for the redundancy >> test >> >> if combined with many >> >> other excluded instruments but few control variables. But reducing the >> >> number of instruments or increasing >> >> the number of controls in the regression model, the remaining >> instruments >> >> seem to become more redundant as well. >> >> I don't know what is to be held of an instruments relevance test which >> >> reacts thus sensitively to minor changes in the model specification. >> >> >> >> >> >> Best, >> >> Andreas >> >> >> >> -----owner-statalist@hsphsun2.harvard.edu schrieb: ----- >> >> An: statalist@hsphsun2.harvard.edu >> >> Von: "Justina Fischer" >> >> Gesendet von: owner-statalist@hsphsun2.harvard.edu >> >> Datum: 21.01.2012 01:35 >> >> Betreff: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from >> >> endogeneity tests >> >> >> >> HI Andreas, >> >> >> >> there are no 'right' instrumentsas such: there are only good ones >> (valid, >> >> strong) and bad ones. Imagine ´good´ and ´bad´ being on a >> continuous >> >> scale: most instruments are somwhere on this scale, but rarely at the >> >> extreme. >> >> >> >> now to the Sargan: >> >> "The Sargan test statistic [...] [is] under the null that the error >> term >> >> is uncorrelated with the instruments." >> >> source: http://en.wikipedia.org/wiki/Instrumental_variable >> >> >> >> so you want a p-value > 0.10 >> >> >> >> no rejection is what you want: the null means you have good >> instruments. >> >> >> >> I recommend to use ivreg2 whih allows you to test the redundany of >> >> instruments. >> >> >> >> Best >> >> Justina >> >> >> >> >> >> -------- Original-Nachricht -------- >> >> > Datum: Fri, 20 Jan 2012 21:22:54 +0100 >> >> > Von: andreas.zweifel@uzh.ch >> >> > An: statalist@hsphsun2.harvard.edu >> >> > Betreff: Antwort: Re: Antwort: Re: RE: st: Spurious inference from >> >> endogeneity tests >> >> >> >> > Hi >> >> > >> >> > I think you are quite right, and my intuition also tells me something >> >> > else. Let's assume I have only one endogenous regressor, >> >> > but more than one instrument candidates since there is no theoretical >> >> > foundation for choosing the 'right' instruments for the >> >> > endogenous variable. If I include all of these instruments and the >> >> > -overid- test statistic is still not significant, there is >> >> > likely something wrong with the instruments. This is because theory >> >> claims >> >> > that one instrument should suffice here, and each >> >> > additional instrument included merely increases the standard >> deviation >> >> of >> >> > the IV estimator. As a consequence, the model must >> >> > be overidentified from a theoretical view. However, if the Sargan >> test >> >> > fails to detect overidentification, this can only be >> >> > due to the fact that the selected instruments are quite weak... >> >> > >> >> > Best, >> >> > Andreas >> >> > >> >> > -----owner-statalist@hsphsun2.harvard.edu schrieb: ----- >> >> > An: statalist@hsphsun2.harvard.edu >> >> > Von: "Justina Fischer" >> >> > Gesendet von: owner-statalist@hsphsun2.harvard.edu >> >> > Datum: 19.01.2012 23:22 >> >> > Betreff: Re: Antwort: Re: RE: st: Spurious inference from endogeneity >> >> > tests >> >> > >> >> > nope.. the bias could turn the direction of observed influence - how >> do >> >> > you know then which one is correct (OLS or IV)? >> >> > >> >> > Rule of thumb is: better no instrument (OLS) than weak ones !! >> >> > >> >> > it is sufficient to provide good convincing arguments why you >> selected >> >> the >> >> > instruments; there is no need for theoretical models suggesting the >> >> > instrument explicitly. Let your phantasy work ! >> >> > >> >> > Cheers >> >> > Justina >> >> > >> >> > -------- Original-Nachricht -------- >> >> > > Datum: Thu, 19 Jan 2012 23:00:00 +0100 >> >> > > Von: andreas.zweifel@uzh.ch >> >> > > An: statalist@hsphsun2.harvard.edu >> >> > > Betreff: Antwort: Re: RE: st: Spurious inference from endogeneity >> >> tests >> >> > >> >> > > Thanks for this clarifying remark. >> >> > > >> >> > > In addition, literature always stresses the requirement that >> >> > > IVs should be selected in line with theoretically motivated >> >> > > arguments. But economic theory may sometimes be limited in its >> >> > > capability to yield valid instruments. However, when instruments >> >> > > are therefore weak, I expect the bias of the IV estimator to be >> >> > > similarly large as the OLS estimator. Maybe then it would make >> >> > > sense to prefer one of the two estimators in terms of theory >> >> > > driven expectations as the lesser evil? >> >> > > >> >> > > -----owner-statalist@hsphsun2.harvard.edu schrieb: ----- >> >> > > An: statalist@hsphsun2.harvard.edu >> >> > > Von: Austin Nichols >> >> > > Gesendet von: owner-statalist@hsphsun2.harvard.edu >> >> > > Datum: 18.01.2012 16:37 >> >> > > Betreff: Re: RE: st: Spurious inference from endogeneity tests >> >> > > >> >> > > In re >> >> > > the poster's central question: >> >> > > "I have to conclude from my specification tests that my coefficient >> >> > > estimates from both OLS and 2SLS cannot be interpreted because 2SLS >> >> > > does not succeed in resolving the endogeneity problem?" >> >> > > I would answer yes. Without better instruments, you have learned >> >> > > nothing from 2SLS, including whether OLS is biased or not. The >> overID >> >> > > test is no good if you don't have strong instruments, since its >> >> > > failure to reject the overID restrictions could be due merely to >> the >> >> > > weakness of your excluded instruments. >> >> > > >> >> > > On Tue, Jan 17, 2012 at 6:44 PM, Justina Fischer >> <JAVFischer@gmx.de> >> >> > > wrote: >> >> > > > wow. I am deeply impressed :-) >> >> > > > >> >> > > > Let us hope the authors provide user-written Stata commands >> soon.... >> >> > > > >> >> > > > justina >> >> > > > -------- Original-Nachricht -------- >> >> > > >> Datum: Tue, 17 Jan 2012 18:41:27 -0500 >> >> > > >> Von: Cameron McIntosh <cnm100@hotmail.com> >> >> > > >> An: STATA LIST <statalist@hsphsun2.harvard.edu> >> >> > > >> Betreff: RE: st: Spurious inference from endogeneity tests >> >> > > > >> >> > > >> The following papers will also be helpful: >> >> > > >> Murray, M.P. (2006). Avoiding Invalid Instruments and Coping >> with >> >> > Weak >> >> > > >> Instruments. Journal of Economic Perspectives, 20(4), >> >> > > >> >> >> > > >> >> > >> >> >> 111-132.http://www.eui.eu/Personal/Guiso/Courses/Econometrics/Murray_IV_jep_06.pdf >> >> > > >> >> >> > > >> Chao, J.C., & Swanson, N.R. (2005). Consistent estimation with a >> >> > large >> >> > > >> number of weak instruments. Econometrica, 73(5), >> >> > > >> >> >> > > >> >> > >> >> >> 1673–1692.http://gemini.econ.umd.edu/jrust/econ623/files/chao_swanson_econometrica.pdf >> >> > > >> >> >> > > >> Nevo, A., & Rosen, A.M. (2010). Identification with Imperfect >> >> > > Instruments. >> >> > > >> The Review of Economics and Statistics, Accepted for >> publication. >> >> > > >> >> >> > > >> Kolesár, M., Chetty, R., Friedman, J.N., Glaeser, E.L., & >> Imbens, >> >> > G.W. >> >> > > >> (October 2011). Identification and Inference with Many Invalid >> >> > > Instruments. >> >> > > >> NBER Working Paper No. 17519. http://www.nber.org/papers/w17519 >> >> > > >> >> >> > > >> Cam >> >> > > >> > Date: Wed, 18 Jan 2012 00:06:34 +0100 >> >> > > >> > From: JAVFischer@gmx.de >> >> > > >> > Subject: Re: st: Spurious inference from endogeneity tests >> >> > > >> > To: statalist@hsphsun2.harvard.edu >> >> > > >> > >> >> > > >> > Hi Andreas >> >> > > >> > >> >> > > >> > for judging whether instruments are weak or not I would as >> first >> >> > step >> >> > > >> look into the first stage regression results, look at the Shea >> R2, >> >> > the >> >> > > F-test >> >> > > >> on the instruments, the single estimates....that tells you >> already >> >> a >> >> > > lot. >> >> > > >> Maybe use ivreg2. >> >> > > >> > >> >> > > >> > Maybe you have only one weak instrument in a set of >> instruments >> >> you >> >> > > >> should exclude (so the set is then strong, even though one >> single >> >> > weak >> >> > > >> instrument may bias your results) >> >> > > >> > >> >> > > >> > Best >> >> > > >> > >> >> > > >> > Justina >> >> > > >> > >> >> > > >> > >> >> > > >> > -------- Original-Nachricht -------- >> >> > > >> > > Datum: Tue, 17 Jan 2012 22:12:36 +0100 >> >> > > >> > > Von: andreas.zweifel@uzh.ch >> >> > > >> > > An: statalist@hsphsun2.harvard.edu >> >> > > >> > > Betreff: st: Spurious inference from endogeneity tests >> >> > > >> > >> >> > > >> > > Dear Statausers, >> >> > > >> > > >> >> > > >> > > I am concerned with an endogeneity problem in my sample of >> 126 >> >> > > firms >> >> > > >> when >> >> > > >> > > investigating the relationship between managerial disclosure >> >> and >> >> > > cost >> >> > > >> of >> >> > > >> > > capital effects. After running the ivreg28 command, the >> >> > > Cragg-Donald >> >> > > >> test >> >> > > >> > > F-statistic is 2.27, which indicates that my instruments are >> >> > rather >> >> > > >> weak. >> >> > > >> > > However, my model appears to be correctly identified, >> because >> >> the >> >> > > >> Anderson test >> >> > > >> > > statistic for the first stage equation yields a p-value >> lower >> >> > than >> >> > > >> 0.01 >> >> > > >> > > and the Sargan test statistic is insignificant (p-value = >> >> 0.59). >> >> > > Since >> >> > > >> my >> >> > > >> > > instruments have passed the overidentification test, I run >> the >> >> > > ivendog >> >> > > >> command >> >> > > >> > > which is equivalent to a Hausman test. Again, the test >> >> statistic >> >> > is >> >> > > >> > > insignificant (p-value = 0.48). >> >> > > >> > > >> >> > > >> > > If I compare OLS and 2SLS, I find that only the former >> yields a >> >> > > >> > > significant coefficient of managerial disclosure in the >> model >> >> > > >> regressing cost of >> >> > > >> > > capital on managerial disclosure. Considering the >> specification >> >> > > tests >> >> > > >> above, it >> >> > > >> > > seems unlikely that 2SLS is an improvement over OLS. Thus I >> >> > assume >> >> > > >> that I >> >> > > >> > > can take the OLS estimates for causal inference. Is this >> >> correct? >> >> > > If >> >> > > >> yes, >> >> > > >> > > the point why I should not use 2SLS is likely due to the >> >> weakness >> >> > > of >> >> > > >> the >> >> > > >> > > instruments and the small-sample bias. So I have to conclude >> >> from >> >> > > my >> >> > > >> > > specification tests that my coefficient estimates from both >> OLS >> >> > and >> >> > > >> 2SLS cannot be >> >> > > >> > > interpreted because 2SLS does not succeed in resolving the >> >> > > endogeneity >> >> > > >> > > problem? >> >> > > >> >> > > * >> >> > > * 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/ >> >> > >> >> > -- >> >> > Justina AV Fischer, PhD >> >> > COFIT Fellow >> >> > World Trade Institute >> >> > University of Bern >> >> > >> >> > homepage: http://www.justinaavfischer.de/ >> >> > e-mail: javfischer@gmx.de. justina.fischer@wti.org >> >> > papers: http://ideas.repec.org/e/pfi55.html >> >> > >> >> > >> >> > * >> >> > * 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/ >> >> >> >> -- >> >> Justina AV Fischer, PhD >> >> COFIT Fellow >> >> World Trade Institute >> >> University of Bern >> >> >> >> homepage: http://www.justinaavfischer.de/ >> >> e-mail: javfischer@gmx.de. justina.fischer@wti.org >> >> papers: http://ideas.repec.org/e/pfi55.html >> >> >> >> >> >> * >> >> * 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/ >> > >> > -- >> > Justina AV Fischer, PhD >> > COFIT Fellow >> > World Trade Institute >> > University of Bern >> > >> > homepage: http://www.justinaavfischer.de/ >> > e-mail: javfischer@gmx.de. justina.fischer@wti.org >> > papers: http://ideas.repec.org/e/pfi55.html >> > >> > >> > * >> > * 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/ >> * >> * 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/ > > -- > Justina AV Fischer, PhD > COFIT Fellow > World Trade Institute > University of Bern > > homepage: http://www.justinaavfischer.de/ > e-mail: javfischer@gmx.de. justina.fischer@wti.org > papers: http://ideas.repec.org/e/pfi55.html > > > * > * 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: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**RE: st: Spurious inference from endogeneity tests***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

**References**:**Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

**Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

**Re: RE: st: Spurious inference from endogeneity tests***From:*Austin Nichols <austinnichols@gmail.com>

**st: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**Re: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

**RE: st: Spurious inference from endogeneity tests***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: RE: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

**Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

**Antwort: Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*andreas.zweifel@uzh.ch

**Re: Antwort: Re: Antwort: Re: Antwort: Re: Antwort: Re: RE: st: Spurious inference from endogeneity tests***From:*"Justina Fischer" <JAVFischer@gmx.de>

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