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From |
"Francesco Burchi" <fburchi@uniroma3.it> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
R: st: AW: IV Quantile Regression and Test of Equality |

Date |
Wed, 16 Dec 2009 19:01:00 +0100 |

Thank you Austin, that was great! I finally get my results and I can also run the tests. Just a quick question: if I have my exogenous variable - "education" - which has a coefficient=0.038, s.e.=0.037 and p-value=0.308 at the 0.10 quantile, and the same variable with a coefficient=0.047, s.e.=0.017 and p-value=0.006 at the 0.50 quantile, how comes that the test of equality of coefficients: test [q10]education = [q50]education has a p-value>0.2? I guess my questions are: how is this Wald test calculated and how important it is? Is there another way to compute it? I have seen most of the papers using quantile regression in economics and social science not reporting these tests of equality. Thanks, Francesco. -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Austin Nichols Inviato: mercoledì 16 dicembre 2009 6.51 A: statalist@hsphsun2.harvard.edu Oggetto: Re: st: AW: IV Quantile Regression and Test of Equality and try out this example: clear all use http://fmwww.bc.edu/ec-p/data/wooldridge/card prog tslad, eclass if replay() { syntax [anything] [, *] eret di, `options' } else { syntax [varlist] [, *] loc x `varlist' reg educ `x' nearc?, robust tempvar educ ren educ `educ' predict double educ foreach q in 10 30 50 70 90 { qreg wage `x' educ, q(`q') `options' mat b`q'=e(b) mat colnames b`q'=q`q': mat b=nullmat(b),b`q' } gen e=e(sample) qui count if e eret post b, dep(wage) es(e) obs(`r(N)') eret local cmd "tslad" eret local properties "b" drop educ ren `educ' educ } end unab x: exper* smsa* south mar black reg662-reg669 bs, rep(100): tslad `x' On Tue, Dec 15, 2009 at 8:35 AM, <fburchi@uniroma3.it> wrote: > Dear Martin, > > I am referring to the post: > http://www.stata.com/statalist/archive/2003-09/msg00585.html where this > procedure is suggested. I should add that I am using Stata 10. I try to > re-write the commands used: > > 1) program IVQRestimates > 2) reg endogvar instrument1 instrument2 X1 X2 X3 X4, robust > 3) predict double IVendogvar, xb > 4) sqreg Y IVendogvar X1 X2 X3 X4, quantiles(10,30,50,70,90) > 5) end > 6) bootstrap "IVQRestimates" _b, reps(100) dots > >> <> >> >> " bootstrap "IVQRestimates" _b, reps(100) dots" >> >> This is not your call to -bootstrap- the command "IVQRestimates", is it? >> It >> does not follow the syntax explained in -h bs- (where the command in >> question goes after the colon). > > "IVQRestimates" is just a possible name for the program that I have run. > The final bootstrap on the program should allow to get bootstrapped > standard errors for both the stages. > >> >> " The other problem is that after using this procedure, Stata does not >> recognize the quantiles," >> >> What do you mean by that? -sqreg- does leave behind the coefficient vector >> and the associated varcov, so you can -test- afterwards: > > I am again referring to boostrap of the whole program. Stata displays the > final output calling the variables b_X1 b_2X2 and so on and there seems no > way to recall them in order to run the Wald tests. That is why I wondered > whether there was an alternative procedure to run it or, simply, a way to > compute the test manually. > >> *** >> sysuse auto, clear >> sqreg price weight length foreign, quantile(.25 .5 .75) >> te [q25=q50] >> *** >> >> Since you instructed -bootstrap- to save only the coefficients ("_b"), why >> do you expect that a -test- procedure would be possible afterwards? > > I have just applied the procedure suggested in the previous post on the > same topic. Should I add any other option? > > Thanks again, > Francesco > >> HTH >> Martin > > >> >> -----Ursprüngliche Nachricht----- >> Von: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Francesco >> Burchi >> Gesendet: Dienstag, 15. Dezember 2009 12:42 >> An: statalist@hsphsun2.harvard.edu >> Betreff: st: IV Quantile Regression and Test of Equality >> >> Dear Statalisters, >> >> I am applying instrumental variable quantile regression due to the >> endogeneity of one explanatory variable (endgovar). I am using two >> instrumental variables (instrument1 and instrument2). I have followed the >> procedure already highlighted in previous posts, that is: >> >> program IVQRestimates >> reg endogvar instrument1 instrument2 X1 X2 X3 X4, robust >> predict double IVendogvar, xb >> sqreg Y IVendogvar X1 X2 X3 X4, quantiles(10,30,50,70,90) >> end >> bootstrap "IVQRestimates" _b, reps(100) dots >> >> Unfortunately, Stata gives me the message "insufficient observations to >> compute bootstrap standard errors. no results will be saved" There is >> clearly no problem of total number of observations since they are more >> than >> 6000. I have tried different specifications of the model, but the >> algorithm >> still does not converge. However, when I have included just one of the two >> instrumental variables, it finally produced the results. Do you have any >> explanation of this? I would be really glad to have suggestions on how to >> obtain my results keeping both the instruments. >> >> The other problem is that after using this procedure, Stata does not >> recognize the quantiles, thus I cannot automatically run the Wald tests to >> test the equality of coefficients across different quantiles. Do you have >> any suggestions on this? Or, could you simply tell me how I could compute >> the test by hand? >> >> Thanks, >> Francesco * * 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: AW: IV Quantile Regression and Test of Equality***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**st: Incorporating sample design into logistic regression model***From:*Jamie Burnett <Jamie.Burnett@ipsos.com>

**References**:**Re: st: AW: IV Quantile Regression and Test of Equality***From:*Austin Nichols <austinnichols@gmail.com>

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