Hi

I am not getting a clear figure with coefplot. I think the problem is that the coefficients and confidence intervals of the variables are on different scales.

This is the code:



Code:
eststo clear
    

foreach s in lnsp {

    foreach v in  g mp rra ira {

        eststo `s'_`v', title(`s'_`v'): qui ivreg2 `s'_`v' inv if  event==1 ,robust bw(auto) small                
    }
        

    coefplot `s'_g, bylabel(gt) || `s'_mp, bylabel(mo) || ///
             `s'_rra, bylabel(rn) || ///
             `s'_ira  , bylabel(ir)  ///
             drop(_cons) bycoefs vertical rescale(100)    ///
              yli(0, lp(solid) lc(gray))   /// levels(99 95 90)
             title(event) name(`s', replace)       aspectratio(0, placement(top))                
}
It gives me this figure:


Array

How can I fix the scaling here to have a better figure?

Data example is below

* Example generated by -dataex-. To install: ssc install dataex
clear
input double(date lnsp_g lnsp_mp lnsp_rra lnsp_ira event)
12421 .4692802532253717 .14198951396707926 .10629503389465267 -.9952776840946314 0
12422 .08914587641991911 .10291307764690316 -.3318984640303393 .4418097664912821 0
12423 .03529091803674955 .04109996125757931 .22157609911148768 -.17088358851430918 0
12424 -.40765895173964317 .18539173387332397 -.2448045393640168 .31390102477364756 0
12425 -.7795970204235063 .5142133254770442 -.2705502213848616 1.060767574317742 0
12428 .11401619151197817 .26025975361029197 .46797481801336005 .2597474371801294 0
12429 -.19364316376082868 -.09974189028947933 .0030346989873786256 .057563911711255855 0
12430 .20776474761765673 -.04576813578812988 -.7547986524557153 .5274223146005728 0
12431 .5462456669565521 -.15046456920850204 .2533801960820954 -1.0102612299187559 0
12432 .21740829937344763 -.06713020348587406 .4007314312737229 -.08638537692535131 0
12435 -.0943130556477616 -.05023424709232671 -.1411726291595432 -.08000458637084051 0
12436 -.19579254714728211 .2547532420942886 .004020570122604816 .07535600427065425 0
12437 .011814342583973847 -.0384665223628744 -.004766881421617519 -.017749674613249056 0
12438 -.3952954577303407 .5130418929766485 -.039353952545760684 .03845383502026323 0
12439 .19865771351208128 -.17136365875475335 -.08457641784507519 -.12305880387026846 0
12442 -.184929500582121 -.15172187573763907 -.06425307037898165 -.12207302491143501 0
12443 -.0758445834010617 -.10248966717791674 .21184217753263201 -.28128758179382984 0
12444 .29312350646976615 -.027009516082973306 -.16455620223599166 .3226864723739702 0
12445 .3058560568832407 -.07280011286059818 -.25670945269801493 .8170486473570566 0
12446 -.11894466216942146 .11300240242352899 -.19101730208306744 .49295619750712305 0
12449 .32812852104849366 -.20352284793473885 .3377431878653461 .10539099889690995 0
12450 -.04325627853102798 -.640007449782459 .5350572696211113 -.23958322438683055 0
12451 .08746131982394889 -.04122253568984391 .17343929315802242 .21865536475324454 0
12452 .4434366135967496 -.5976933544288165 -.10846345884968134 -.04674236310928137 1
12453 -.2922161232353835 -1.5241609583330238 .33673559010865706 -.8456219972021835 1
12456 1.1090050486084282 .602494216605681 -.8097711552451052 -.448933729029525 1
12457 -.15259408785790818 -.06398275352762539 .47247001615794915 -.4183412285672805 1
12458 -.05906193891569611 .03847128328568061 -.026657655559586324 .36717136553900076 1
12459 -.016098457679547984 -.4588374177327772 -.3315882108207253 -.06077085160416651 0
12460 .13306199982793476 .12984045540265043 -.24874545326215625 .19019634225854176 0
12463 -.2866019641137818 .10877933212218949 .5059049606559034 -.3281604010069472 0
12464 .23539192752828786 .04470265843669807 -.09761899666576124 .31313018671568393 0
end
format %td date
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