coefplot - country label on xaxis instead of numbers

[Renira Corinne Angeles]

Dear Statalist users,

I am trying to produce this graph showing changes in a variable across countries from 1995 to 2010. This is the code I am using with Stata 18. Does anyone have any advice on how to get the ccode (NOR, USA, GBR etc.) labels instead of the numbers on the xaxis?

mean SK_RR_S100 if y==2010, over(ccode)
matrix b88 = e(b)
mean  SK_RR_S100 if y==1995, over(ccode)
mata: assert(st_matrixcolstripe("b88")==st_matrixcolstripe("e(b)"))
quietly estadd matrix b88
coefplot, ci((b b) (b b88)) ciopts(recast(rcap pcarrow)) cionly ///
   vertical sort(, by(ul 2)) rename(^.+@([0-9]+)\..+$ = \1, regex) ///
   xtitle("test") ytitle("Change in sk_rep from 1995 to 2010")

and I get this graph:

[Andrew Musau]

coefplot is from SSC, as you are asked to explain (FAQ Advice #12). To make any such labels readable, you would likely need to flip the axes. Regarding your question, please provide a data example (refer to the referenced FAQ for details).

[Renira Corinne Angeles]

Andrew: thanks for the reminder. For more context: I'm working with an unbalanced panel with N=31 and T=50 (for this graph, the US has no information because they do not have this type of policy (SK_RR_S100). CCODE label consist of three-letter country code.

* Example generated by -dataex-. For more info, type help dataex
clear
input double(ccode y SK_RR_S100)
1 1970                  .
1 1971  .1490314564448123
1 1972 .22108290608978368
1 1973 .26279867213144936
1 1974 .26559960322047965
1 1975 .27233623343570973
1 1976   .288849134851387
1 1977 .32024585695653696
1 1978  .3098841376149818
1 1979 .29505050950637435
1 1980  .2525459889098983
1 1981 .23535648115217472
1 1982 .22859200881318592
1 1983 .24727451252962138
1 1984 .26430078861742246
1 1985  .2635630216411925
1 1986  .2898393015571314
1 1987 .29758726669868457
1 1988  .3024782822466128
1 1989 .29011140696457355
1 1990 .30083486660800224
1 1991  .3102643217799459
1 1992   .322183891069193
1 1993  .3088118989255487
1 1994  .2991224500110392
1 1995 .29728083038094044
1 1996  .3087723761257178
1 1997 .29998280993348986
1 1998 .28912405511100875
1 1999 .28709232149580105
1 2000  .2750577530037783
1 2001  .2743600009142581
1 2002  .2600769658663214
1 2003  .2561624824841846
1 2004  .2601794917614027
1 2005  .2543653187827645
1 2006 .25097259772001806
1 2007 .24675239945893138
1 2008  .2393541427991614
1 2009 .23417023680219776
1 2010 .22833919195653365
1 2011 .22362510655904838
1 2012 .21909540065384062
1 2013 .21325534998857246
1 2014 .21481431323526218
1 2015 .21691779843383077
1 2016 .21751763810695313
1 2017  .2181894004504813
1 2018 .21718236086097298
1 2019 .21552151737556047
1 2020  .2107960207619468
2 1970  .7377818264826091
2 1971  .7425672677788261
2 1972  .7513783095463765
2 1973  .7395600352186933
2 1974  .8678472428049153
2 1975  .8869656218440207
2 1976  .8556651445147881
2 1977  .8651366687203876
2 1978  .8662035600801308
2 1979  .8556457059852272
2 1980  .8671743524129336
2 1981  .8736959616894158
2 1982  .8689310733463569
2 1983  .8646136604855573
2 1984   .875145518032241
2 1985  .8848562938809796
2 1986  .8924320812594145
2 1987   .875964009694303
2 1988   .883257083566614
2 1989   .829311938486311
2 1990  .7996919870025553
2 1991  .7973331104866977
2 1992  .7787053545831498
2 1993  .7659071005308834
2 1994  .7496918034716041
2 1995  .7558863782354146
2 1996   .751670997892195
2 1997  .7412930314616144
2 1998  .7326748171504593
2 1999  .7251447448438763
2 2000  .7218581294916074
2 2001  .8997571119475032
2 2002  .9630914346238543
2 2003  .9586498855803846
2 2004  .9490048870396198
2 2005  .9277326549619026
2 2006  .9217806849589663
2 2007  .9162847504544809
2 2008  .9112955725579135
2 2009  .8849949598880074
2 2010  .8754624028870912
2 2011  .8767336651080851
2 2012  .8674735027287377
2 2013  .8600721196634573
2 2014  .8376151712061853
2 2015 1.0006626769965732
2 2016  .9640131070913923
2 2017  .9678878890787516
2 2018  .9733020495897372
end
label values ccode CCODE
label def CCODE 1 "AUS", modify
label def CCODE 2 "AUT", modify

[Andrew Musau]

Thanks. You can run coefplot with the -nodraw- option, pick up the order of the labels from r(labels) and retrieve the labels from your categorical variable. Using these, redraw the graph. Vertical labels may just work, but otherwise see the -vertical- option to flip the axes.

* Example generated by -dataex-. For more info, type help dataex
clear
input double(ccode y SK_RR_S100)
1 1970                  .
1 1971  .1490314564448123
1 1972 .22108290608978368
1 1973 .26279867213144936
1 1974 .26559960322047965
1 1975 .27233623343570973
1 1976   .288849134851387
1 1977 .32024585695653696
1 1978  .3098841376149818
1 1979 .29505050950637435
1 1980  .2525459889098983
1 1981 .23535648115217472
1 1982 .22859200881318592
1 1983 .24727451252962138
1 1984 .26430078861742246
1 1985  .2635630216411925
1 1986  .2898393015571314
1 1987 .29758726669868457
1 1988  .3024782822466128
1 1989 .29011140696457355
1 1990 .30083486660800224
1 1991  .3102643217799459
1 1992   .322183891069193
1 1993  .3088118989255487
1 1994  .2991224500110392
1 1995 .29728083038094044
1 1996  .3087723761257178
1 1997 .29998280993348986
1 1998 .28912405511100875
1 1999 .28709232149580105
1 2000  .2750577530037783
1 2001  .2743600009142581
1 2002  .2600769658663214
1 2003  .2561624824841846
1 2004  .2601794917614027
1 2005  .2543653187827645
1 2006 .25097259772001806
1 2007 .24675239945893138
1 2008  .2393541427991614
1 2009 .23417023680219776
1 2010 .22833919195653365
1 2011 .22362510655904838
1 2012 .21909540065384062
1 2013 .21325534998857246
1 2014 .21481431323526218
1 2015 .21691779843383077
1 2016 .21751763810695313
1 2017  .2181894004504813
1 2018 .21718236086097298
1 2019 .21552151737556047
1 2020  .2107960207619468
2 1970  .7377818264826091
2 1971  .7425672677788261
2 1972  .7513783095463765
2 1973  .7395600352186933
2 1974  .8678472428049153
2 1975  .8869656218440207
2 1976  .8556651445147881
2 1977  .8651366687203876
2 1978  .8662035600801308
2 1979  .8556457059852272
2 1980  .8671743524129336
2 1981  .8736959616894158
2 1982  .8689310733463569
2 1983  .8646136604855573
2 1984   .875145518032241
2 1985  .8848562938809796
2 1986  .8924320812594145
2 1987   .875964009694303
2 1988   .883257083566614
2 1989   .829311938486311
2 1990  .7996919870025553
2 1991  .7973331104866977
2 1992  .7787053545831498
2 1993  .7659071005308834
2 1994  .7496918034716041
2 1995  .7558863782354146
2 1996   .751670997892195
2 1997  .7412930314616144
2 1998  .7326748171504593
2 1999  .7251447448438763
2 2000  .7218581294916074
2 2001  .8997571119475032
2 2002  .9630914346238543
2 2003  .9586498855803846
2 2004  .9490048870396198
2 2005  .9277326549619026
2 2006  .9217806849589663
2 2007  .9162847504544809
2 2008  .9112955725579135
2 2009  .8849949598880074
2 2010  .8754624028870912
2 2011  .8767336651080851
2 2012  .8674735027287377
2 2013  .8600721196634573
2 2014  .8376151712061853
2 2015 1.0006626769965732
2 2016  .9640131070913923
2 2017  .9678878890787516
2 2018  .9733020495897372
end
label values ccode CCODE
label def CCODE 1 "AUS", modify
label def CCODE 2 "AUT", modify


mean SK_RR_S100 if y==2010, over(ccode)
matrix b88 = e(b)
mean  SK_RR_S100 if y==1995, over(ccode)
mata: assert(st_matrixcolstripe("b88")==st_matrixcolstripe("e(b)"))
quietly estadd matrix b88
coefplot, ci((b b) (b b88)) ciopts(recast(rcap pcarrow)) cionly ///
   vertical sort(, by(ul 2)) rename(^.+@([0-9]+)\..+$ = \1, regex)  ///
   xtitle("test") ytitle("Change in sk_rep from 1995 to 2010") nodraw
  
local order= ustrregexra(ustrregexra(" "+`"`r(labels)'"', "\s[\d+]\s", ""), "[^\d\s]", " ")
local labs
local i 0
foreach num of numlist `order'{
    local ++i
    local lev= "`:lab (ccode) `num''"
    local labs `labs' `i' "`lev'"
}

coefplot, ci((b b) (b b88)) ciopts(recast(rcap pcarrow)) cionly ///
   vertical sort(, by(ul 2)) rename(^.+@([0-9]+)\..+$ = \1, regex)  ///
   xtitle("test") ytitle("Change in sk_rep from 1995 to 2010") xlab(`labs', angle(vertical))

Res.:

[Renira Corinne Angeles]

Excellent! Thanks so much for this.