coefplot y-axis labels

[Mukesh Punia]

Dear users I am using Stata 18.5 and trying to plot O-B decomposition results using coefplot

oaxaca outcome (X1: q_mpce_d2 q_mpce_d3 q_mpce_d4 q_mpce_d5)                        ///
(X2:head_edu_d2 head_edu_d3 head_edu_d4)                                                ///
(X3: caste3_d2 caste3_d3) (X4: nssregn_d2 nssregn_d3 nssregn_d4 nssregn_d5 nssregn_d6)    ///
(X5: sex_hh_d1) (X6: religon_d1 religon_d3) (X7: age_hh)                        ///
(X8: size_hh_d1 size_hh_d2) [iw=wt], by(residence_d2) omega ro

est sto m1

After applying oaxaca-blinder decomposition, I am trying to plot the results using coefplot command

coefplot (m1, label(Outcome Variable)), drop(overall:group*) xline(0)                                                               ///
recast(bar) barwidth(.35) base(0) citop ciopts(recast(rcap))                                                                      ///
xtitle("Percent", size(small)) xlabel(-.10 "-10" 0 "0" .10 "10" .20 "20" .30 "30" .40 "40" .50 "50" .60 "60")                    ///
mlabel format(%9.2g) mlabposition(3) mlabsize(tiny) mlabgap(*3) grid(n)                                                        ///
legend(position(3) ring(0)) scheme(cleanplots)                                                                                 ///
ylab(1 "Difference" 2 "Explained" 3 "Unxplained"                                                                              /// 1-3 main    
5 "X1" 6 "X2" 7 "X3" 8 "X4" 9 "X5" 10 "X6" 11 "X7"    12 "X8"                                                                  /// 5-12, factors explained
 14 "X1" 15 "X2" 16 "X3" 17 "X4" 18 "X5" 19 "X6" 20 "X7" 21 "X8"                                                                       /// 14-22, factors unexplained
  22 "Constant", labsize(vsmall))

The outcome of the above command is shown in the figure attached here.


My query is:

How to manage the second (outer) part of the y-axis in the graph, i.e., how to align left, add labels, and rotate its angle?

Thank you!!

[Mukesh Punia]

Ben Jann

[Ben Jann]

Use suboptions within option eqlabels() to affect the rendering of outer labels. Aligning the labels on the left is difficult, see https://repec.sowi.unibe.ch/stata/co...lling.html#h-7

[Mukesh Punia]

thank you, respected Ben Jann, for your response. It worked.

I have two specific queries-

1. Is there a way to "hide or drop outer labels"?
2. I want to combine two graphs/coefplots. Both have the same y-labels but different outcome/dependent variables, so I want to keep y-labels from only one. As shown in the figure attached in post#1. As of now, I did it with gr_edit

[Mukesh Punia]

Dear Andrew Musau Ben Jann can you please explain how to plot only explained part (drop unexplained part) in post #1.

[Hemanshu Kumar]

I think if you just change your drop option to

drop(overall:group* unexplained:*)

you should get what you need.

Also, three suggestions for the future:

• Please do provide a data example with your question, so we can reproduce what you are doing.
• When using a community-contributed command, please mention its source so that others know how to obtain it. In this case, oaxaca is available from net install oaxaca.pkg and coefplot is available from the Stata Journal.
• In my experience, addressing your post to specific individuals is as likely to reduce the chances of getting an answer (since others are less likely to want to answer) as increase them (from the addressees being drawn to the post). Addressing it to specific individuals can also feel burdensome to them. It may be best to avoid this.

[Mukesh Punia]

Dear Hemanshu Kumar , thank you for quick and very useful help and guidelines for a better response.

*Posting with example data:

I have two final small queries:
1) Is there a way to remove the y-axis outer labels (overall, explained, and unexplained)? Currently, I use gr_edit
2) How to convert explained proportion label into a percent (%), e.g in difference (.44), be shown like 44% or 44. I am using STATA 18

Thank you!

clear
input float outcome byte(r_d1 r_d2 ca_d1 ca_d2 ca_d3 q_d1 q_d2 q_d3 q_d4 q_d5) float age
1 1 0 0 0 1 0 0 0 0 1 51
1 1 0 0 1 0 1 0 0 0 0 52
1 1 0 0 1 0 0 0 0 0 1 35
1 1 0 1 0 0 1 0 0 0 0 38
1 1 0 0 1 0 0 0 0 0 1 56
1 1 0 0 1 0 0 0 0 0 1 55
1 1 0 0 0 1 0 0 0 0 1 65
0 1 0 0 1 0 0 1 0 0 0 58
1 1 0 0 0 1 0 0 0 0 1 21
1 1 0 0 1 0 0 0 0 1 0 62
1 1 0 0 0 1 0 0 0 1 0 38
1 1 0 1 0 0 0 0 0 0 1 46
1 1 0 1 0 0 0 0 0 1 0 72
1 1 0 0 1 0 0 0 0 0 1 32
1 1 0 0 0 1 0 0 0 0 1 65
1 1 0 0 1 0 0 0 0 1 0 70
1 1 0 0 0 1 0 0 1 0 0 50
1 1 0 0 1 0 0 0 0 0 1 55
1 1 0 0 1 0 0 0 0 1 0 52
1 1 0 1 0 0 0 0 0 0 1 37
1 1 0 0 1 0 0 0 0 0 1 51
1 1 0 1 0 0 0 0 0 1 0 80
1 1 0 0 1 0 0 0 1 0 0 80
1 1 0 0 1 0 0 0 1 0 0 38
0 1 0 0 1 0 0 0 0 1 0 50
1 1 0 0 1 0 0 0 0 1 0 73
1 1 0 0 0 1 0 0 0 0 1 41
1 1 0 1 0 0 0 1 0 0 0 30
1 1 0 0 0 1 0 0 0 0 1 40
1 1 0 1 0 0 0 0 0 1 0 29
1 1 0 0 0 1 0 0 0 0 1 52
1 1 0 0 1 0 0 0 0 0 1 52
0 1 0 0 1 0 0 0 0 0 1 58
1 1 0 0 0 1 0 0 0 1 0 59
1 1 0 0 0 1 0 0 0 0 1 50
1 1 0 0 0 1 0 0 0 1 0 50
1 1 0 0 0 1 0 0 0 0 1 19
1 1 0 1 0 0 0 0 0 1 0 39
1 1 0 0 1 0 0 0 1 0 0 68
1 1 0 1 0 0 0 0 0 0 1 63
1 1 0 0 1 0 0 0 0 0 1 39
0 1 0 0 1 0 1 0 0 0 0 40
1 1 0 0 1 0 0 0 0 1 0 68
1 1 0 0 0 1 0 0 0 1 0 36
1 1 0 0 1 0 0 0 0 1 0 56
0 1 0 0 0 1 0 0 0 0 1 47
1 1 0 0 0 1 0 0 0 0 1 40
1 1 0 1 0 0 0 0 0 1 0 38
1 1 0 0 1 0 0 0 0 0 1 35
1 1 0 0 0 1 0 0 0 0 1 40
1 1 0 0 0 1 0 0 0 0 1 76
1 1 0 0 1 0 0 0 0 0 1 55
1 1 0 0 1 0 0 0 0 0 1 39
1 1 0 0 0 1 0 0 0 0 1 70
1 1 0 1 0 0 0 0 0 1 0 22
1 1 0 0 0 1 0 0 1 0 0 70
1 1 0 0 1 0 0 1 0 0 0 55
1 1 0 0 1 0 0 0 0 1 0 62
0 1 0 1 0 0 1 0 0 0 0 60
1 1 0 0 0 1 0 0 0 0 1 38
1 1 0 1 0 0 0 0 0 0 1 50
1 1 0 0 1 0 0 0 0 0 1 44
0 1 0 1 0 0 0 1 0 0 0 61
1 1 0 0 0 1 0 0 0 0 1 68
1 1 0 0 0 1 1 0 0 0 0 40
1 1 0 1 0 0 0 0 1 0 0 35
1 1 0 0 1 0 0 0 1 0 0 66
1 1 0 0 1 0 0 1 0 0 0 58
1 1 0 0 0 1 0 0 0 0 1 52
1 1 0 1 0 0 0 0 0 0 1 40
1 1 0 0 1 0 0 1 0 0 0 69
1 1 0 1 0 0 0 0 0 1 0 47
1 1 0 0 1 0 0 0 0 1 0 40
1 1 0 0 1 0 0 0 0 0 1 51
1 1 0 1 0 0 0 0 0 1 0 42
1 1 0 0 1 0 0 0 0 1 0 39
1 1 0 1 0 0 0 0 0 1 0 72
1 1 0 0 0 1 0 0 0 1 0 79
1 1 0 0 1 0 0 0 0 0 1 48
1 1 0 1 0 0 0 1 0 0 0 52
1 1 0 0 1 0 0 0 0 1 0 55
1 1 0 0 1 0 0 0 0 1 0 42
1 1 0 0 0 1 0 0 0 0 1 54
1 1 0 1 0 0 0 0 0 0 1 43
1 1 0 0 1 0 0 0 0 1 0 56
1 1 0 0 0 1 0 0 0 0 1 65
1 1 0 0 0 1 0 0 0 1 0 35
1 1 0 0 1 0 0 1 0 0 0 65
1 1 0 0 1 0 0 0 0 0 1 72
1 1 0 1 0 0 0 0 0 1 0 37
1 1 0 0 0 1 0 0 0 0 1 70
1 1 0 0 0 1 0 0 0 0 1 71
1 1 0 0 1 0 0 0 0 0 1 38
1 1 0 0 1 0 0 0 0 0 1 38
1 1 0 0 1 0 0 0 0 1 0 42
1 1 0 1 0 0 0 0 0 0 1 65
0 1 0 0 1 0 1 0 0 0 0 48
1 1 0 0 0 1 0 0 0 0 1 56
0 1 0 0 0 1 0 0 1 0 0 35
1 1 0 0 1 0 0 0 0 0 1 33
1 1 0 0 1 0 0 1 0 0 0 46
1 1 0 1 0 0 0 0 0 0 1 42
1 1 0 0 1 0 0 0 0 0 1 36
1 1 0 0 0 1 0 0 0 0 1 40
1 1 0 0 1 0 0 0 0 1 0 74
1 1 0 0 1 0 0 1 0 0 0 35
1 1 0 0 1 0 0 0 0 1 0 56
1 1 0 1 0 0 0 0 0 1 0 68
1 1 0 1 0 0 0 0 0 1 0 58
1 1 0 0 1 0 0 0 0 1 0 38
1 1 0 0 0 1 0 0 0 1 0 50
1 1 0 0 0 1 0 0 0 0 1 41
0 0 1 0 1 0 0 0 1 0 0 28
1 0 1 0 0 1 0 0 1 0 0 30
0 0 1 0 1 0 0 1 0 0 0 44
1 0 1 0 1 0 0 0 0 0 1 30
0 0 1 0 0 1 0 0 1 0 0 80
0 0 1 1 0 0 0 1 0 0 0 51
0 0 1 0 1 0 0 1 0 0 0 44
0 0 1 0 1 0 1 0 0 0 0 45
0 0 1 1 0 0 0 1 0 0 0 60
1 0 1 1 0 0 0 0 1 0 0 55
0 0 1 1 0 0 0 0 0 1 0 35
1 0 1 1 0 0 1 0 0 0 0 45
0 0 1 1 0 0 1 0 0 0 0 45
0 0 1 0 1 0 1 0 0 0 0 41
1 0 1 1 0 0 0 0 0 0 1 62
0 0 1 0 1 0 0 0 0 0 1 45
1 0 1 0 0 1 0 0 1 0 0 65
0 0 1 1 0 0 1 0 0 0 0 48
1 0 1 0 0 1 0 0 0 1 0 36
0 0 1 0 1 0 0 0 1 0 0 30
1 0 1 0 1 0 0 0 0 0 1 62
0 0 1 1 0 0 1 0 0 0 0 45
1 0 1 0 1 0 0 0 1 0 0 40
1 0 1 0 1 0 0 0 1 0 0 52
1 0 1 0 0 1 1 0 0 0 0 48
1 0 1 1 0 0 0 0 0 0 1 62
0 0 1 0 1 0 0 0 1 0 0 62
1 0 1 0 1 0 0 1 0 0 0 65
0 0 1 1 0 0 0 0 1 0 0 34
0 0 1 0 1 0 1 0 0 0 0 43
0 0 1 1 0 0 0 1 0 0 0 65
0 0 1 1 0 0 1 0 0 0 0 32
1 0 1 1 0 0 1 0 0 0 0 55
0 0 1 1 0 0 0 0 1 0 0 26
1 0 1 1 0 0 1 0 0 0 0 75
1 0 1 0 0 1 0 0 0 0 1 47
0 0 1 0 0 1 1 0 0 0 0 52
1 0 1 1 0 0 0 0 1 0 0 62
0 0 1 1 0 0 1 0 0 0 0 48
1 0 1 1 0 0 0 0 1 0 0 30
1 0 1 1 0 0 1 0 0 0 0 35
1 0 1 0 1 0 0 1 0 0 0 34
0 0 1 0 1 0 0 1 0 0 0 60
1 0 1 1 0 0 0 1 0 0 0 40
1 0 1 0 1 0 0 1 0 0 0 55
0 0 1 0 0 1 0 1 0 0 0 53
1 0 1 1 0 0 0 0 1 0 0 60
1 0 1 0 1 0 0 0 0 1 0 50
0 0 1 1 0 0 0 1 0 0 0 27
1 0 1 1 0 0 0 0 1 0 0 85
0 0 1 0 1 0 1 0 0 0 0 28
0 0 1 1 0 0 0 1 0 0 0 70
1 0 1 0 0 1 0 0 0 1 0 49
1 0 1 0 0 1 1 0 0 0 0 46
0 0 1 0 1 0 0 0 0 1 0 73
0 0 1 0 1 0 0 1 0 0 0 43
0 0 1 0 1 0 0 0 1 0 0 47
1 0 1 0 0 1 0 0 0 0 1 78
1 0 1 0 1 0 0 0 1 0 0 58
1 0 1 0 1 0 0 1 0 0 0 65
1 0 1 0 1 0 0 1 0 0 0 80
0 0 1 0 1 0 0 0 0 1 0 65
0 0 1 0 1 0 0 0 1 0 0 50
0 0 1 1 0 0 0 0 0 0 1 25
1 0 1 1 0 0 1 0 0 0 0 34
1 0 1 0 1 0 0 0 1 0 0 70
0 0 1 0 0 1 0 0 1 0 0 45
0 0 1 1 0 0 1 0 0 0 0 55
1 0 1 1 0 0 1 0 0 0 0 76
1 0 1 0 1 0 0 0 1 0 0 54
0 0 1 1 0 0 0 1 0 0 0 66
0 0 1 1 0 0 0 1 0 0 0 33
0 0 1 1 0 0 0 1 0 0 0 53
1 0 1 0 0 1 0 1 0 0 0 45
0 0 1 1 0 0 0 1 0 0 0 39
0 0 1 0 0 1 0 0 1 0 0 48
0 0 1 0 1 0 0 1 0 0 0 50
0 0 1 1 0 0 1 0 0 0 0 40
1 0 1 1 0 0 0 0 1 0 0 47
0 0 1 0 1 0 0 0 1 0 0 49
0 0 1 0 1 0 1 0 0 0 0 52
0 0 1 1 0 0 0 0 0 1 0 50
1 0 1 0 0 1 0 0 0 1 0 55
0 0 1 0 1 0 1 0 0 0 0 62
1 0 1 0 1 0 0 0 0 1 0 75
0 0 1 0 0 1 1 0 0 0 0 35
0 0 1 1 0 0 0 1 0 0 0 45
0 0 1 0 0 1 0 0 1 0 0 75
0 0 1 0 1 0 1 0 0 0 0 32
1 0 1 0 0 1 0 0 0 1 0 35
1 0 1 1 0 0 1 0 0 0 0 75
1 0 1 0 0 1 0 0 0 0 1 47
1 0 1 0 0 1 0 0 0 1 0 45
0 0 1 0 1 0 0 0 1 0 0 45
1 0 1 0 1 0 0 0 0 1 0 33
1 0 1 1 0 0 0 0 0 1 0 55
1 0 1 0 0 1 0 0 0 0 1 02
0 0 1 1 0 0 1 0 0 0 0 63
0 0 1 0 1 0 1 0 0 0 0 32
0 0 1 1 0 0 1 0 0 0 0 36
0 0 1 0 0 1 0 0 0 0 1 50
1 0 1 0 1 0 0 0 0 0 1 47
0 0 1 0 1 0 0 0 0 1 0 50
0 0 1 1 0 0 1 0 0 0 0 51
0 0 1 1 0 0 0 0 1 0 0 32
1 0 1 0 1 0 1 0 0 0 0 53
0 0 1 1 0 0 0 1 0 0 0 45
0 0 1 1 0 0 1 0 0 0 0 24
1 0 1 0 1 0 0 0 0 0 1 42
1 0 1 0 1 0 0 1 0 0 0 39
0 0 1 1 0 0 1 0 0 0 0 50
0 0 1 0 1 0 0 0 1 0 0 27
1 0 1 1 0 0 0 0 0 1 0 62
0 0 1 1 0 0 0 0 1 0 0 48
1 0 1 0 1 0 1 0 0 0 0 48
0 0 1 1 0 0 0 0 1 0 0 71
1 0 1 1 0 0 1 0 0 0 0 80
1 0 1 0 1 0 0 1 0 0 0 60
0 0 1 0 1 0 0 0 0 1 0 64
1 0 1 1 0 0 1 0 0 0 0 50
0 0 1 0 0 1 0 0 0 1 0 79
1 0 1 0 1 0 0 1 0 0 0 62
0 0 1 0 1 0 1 0 0 0 0 58
0 0 1 0 0 1 0 1 0 0 0 40
1 0 1 0 0 1 0 0 1 0 0 70
1 0 1 0 1 0 0 0 1 0 0 75
0 0 1 0 1 0 1 0 0 0 0 55
1 0 1 0 1 0 0 1 0 0 0 43
0 0 1 1 0 0 1 0 0 0 0 58
1 0 1 0 1 0 0 0 0 1 0 45
1 0 1 0 0 1 0 1 0 0 0 55
0 0 1 0 1 0 0 0 1 0 0 48
1 0 1 0 1 0 0 0 0 1 0 46
1 0 1 0 1 0 0 1 0 0 0 36
0 0 1 0 1 0 0 1 0 0 0 66
1 0 1 0 0 1 1 0 0 0 0 30
1 0 1 0 1 0 0 0 1 0 0 40
1 0 1 0 1 0 0 1 0 0 0 38
0 0 1 0 1 0 0 1 0 0 0 60
1 0 1 0 1 0 0 1 0 0 0 35
0 0 1 1 0 0 0 0 0 1 0 64
1 0 1 1 0 0 0 0 1 0 0 80
1 0 1 1 0 0 0 1 0 0 0 48
0 0 1 1 0 0 0 1 0 0 0 41
0 0 1 0 0 1 0 1 0 0 0 45
1 0 1 1 0 0 0 1 0 0 0 51
0 0 1 0 1 0 0 0 0 1 0 72
0 0 1 1 0 0 0 0 0 0 1 60
0 0 1 1 0 0 0 0 0 1 0 55
1 0 1 0 0 1 0 0 0 0 1 77
1 0 1 0 0 1 0 1 0 0 0 45
1 0 1 0 1 0 0 0 0 0 1 50
1 0 1 0 1 0 0 0 0 0 1 51
1 0 1 0 0 1 0 0 0 1 0 34
0 0 1 0 1 0 1 0 0 0 0 37
0 0 1 1 0 0 1 0 0 0 0 48
0 0 1 1 0 0 0 0 1 0 0 25
1 0 1 0 0 1 1 0 0 0 0 31
1 0 1 1 0 0 0 0 1 0 0 50
0 0 1 0 0 1 0 1 0 0 0 40
0 0 1 0 1 0 0 1 0 0 0 53
1 0 1 0 1 0 1 0 0 0 0 43
0 0 1 1 0 0 0 1 0 0 0 29
0 0 1 1 0 0 0 0 0 1 0 38
1 0 1 0 1 0 1 0 0 0 0 46
end
label values outcome yesno
label def yesno 0 "no", modify
label def yesno 1 "yes", modify


oaxaca outcome (X1: q_d2 q_d3 q_d4 q_d5) (X2: ca_d2 ca_d3) (X3: age), by(r_d2) omega ro
est sto m1

coefplot (m1, label(Outcome Variable)), drop(overall:group* unexplained:*) xline(0)                              ///
recast(bar) barwidth(.7) base(0) citop ciopts(recast(rcap))                                                     ///
xtitle("Percent", size(small)) xlabel(-.05 "-05" 0 "0" .10 "10" .20 "20" .30 "30" .40 "40" .50 "50" .60 "60")   ///
mlabel format(%9.2g) mlabposition(4)                                                                             ///
ylab(1 "Diff" 2 "Exp" 3 "Unexp" 5 "X1" 6 "X2" 7 "X3" )

 .
oaxaca
c:\ado\plus\o\oaxaca.ado
*! version 4.1.1  24apr2023  Ben Jann

. coefplot
c:\ado\plus\c\coefplot.ado
*! version 1.8.6  22feb2023  Ben Jann

Hope it replicates well and explain my issues.

[Hemanshu Kumar]

Is there a way to remove the y-axis outer labels (overall, explained, and unexplained)?

Use the option noeqlabels

How to convert explained proportion label into a percent (%) e.g in post #1 figure, .41 should appear as 41% or 41.

I think the best approach here might be to extract the relevant portion of the results matrix, and scale the numbers there. You would then also not need to fiddle with the numbers using xlabel().

Here are some bits of code suggestions:

After your oaxaca command, do

matrix C = ( r(table)["b", .] \ r(table)["ll", .] \ r(table)["ul", .] ) * 100

You can now omit the est sto m1 command since we will plot using matrix C directly. Your coefplot command would now start with

coefplot (matrix(C), label(Outcome Variable)), ci((2 3))

followed by all the other options (except xlabel)

[Mukesh Punia]

Thank you!

For showing percent the codes only changes the ci's to percent, neither bar nor labels, i.e., .44 to 44.

oaxaca outcome (X1: q_d2 q_d3 q_d4 q_d5) (X2: ca_d2 ca_d3) (X3: age), by(r_d2) omega ro
matrix C = r(table)["b", .] \ r(table)["ll", .] \ r(table)["ul", .]*100

coefplot (matrix(C), label(Outcome Variable)), ci((2 3)) drop(overall:group* unexplained:*) xline(0)            ///
recast(bar) barwidth(.7) base(0) citop ciopts(recast(rcap))                                                     ///
xtitle("Percent", size(small))                                                                                    ///
mlabel format(%9.2g) mlabposition(4)                                                                             ///
ylab(1 "Diff" 2 "Exp" 3 "Unexp" 5 "X1" 6 "X2" 7 "X3" ) noeqlabels

noeqlabels worked as intended.

[Hemanshu Kumar]

For showing percent the codes only changes the ci's to percent, neither bar nor labels, i.e., .44 to 44.

Yes sorry I made an error in the original code in #8, which I fixed later. In the matrix definition, you need to enclose the portion before the * 100 in brackets, otherwise it only multiplies the last row by 100.

[Mukesh Punia]

Thank you, very much! Dear Himangshu Kumar it worked perfectly well!

oaxaca outcome (X1: q_d2 q_d3 q_d4 q_d5) (X2: ca_d2 ca_d3) (X3: age), by(r_d2) omega ro
matrix C = ( r(table)["b", .] \ r(table)["ll", .] \ r(table)["ul", .] ) * 100

coefplot (matrix(C), label(Outcome Variable)), ci((2 3)) drop(overall:group* unexplained:* ) xline(0)   ///
recast(bar) barwidth(.7) base(0) citop ciopts(recast(rcap))                                                 ///
xtitle("Percent", size(small))                                                                                ///
mlabel format(%9.1f) mlabposition(4)                                                                        ///
ylab(1 "Diff" 2 "Exp"  3 "Unexp" 4 "X1" 5 "X2" 6 "X3" ) noeqlabels

* Can we drop the unexplained % from the overall in the figure?

[Hemanshu Kumar]

* Can we drop the unexplained % from the overall in the figure?

Yes, change the drop option to

drop(overall:group* overall:unexplained unexplained:*)

Incidentally, you have tagged the wrong person in your last post

[Hemanshu Kumar]

* duplicate post; deleted *

[Mukesh Punia]

Thank you!! Hemanshu Kumar for wonderful help and pointing this tagging error alongside codes☺️
Thank you and best regards
Mukesh