Problem showing xlabels in a twoway graph

[Diego Malo]

Hello.

I am running a regression country by country, and I would like to show the significance of the coefficients in a twoway graph where each xlabel is a different country. I am running the following code:

encode iso3, gen(iso3_num)
levelsof iso3_num, local(countries)
gen coeff = .
gen sig = .
gen lb = .
gen ub = .

foreach c of local countries {
    
reghdfe identity status_cash if iso3_num == `c' , abs(year group_country) vce(cluster group_country)
 scalar beta = _b[status_cash]
    scalar se = _se[status_cash]
    scalar pval = 1 - ttail(e(df_r), abs(beta / se))  // p-value computation
    
    // Compute confidence intervals
    scalar ci_lower = beta - invttail(e(df_r), 0.025) * se
    scalar ci_upper = beta + invttail(e(df_r), 0.025) * se
    
    replace coeff = beta if iso3_num == `c'
    replace sig = (pval < 0.05) if iso3_num == `c'
    replace lb = ci_lower if iso3_num == `c'
    replace ub = ci_upper if iso3_num == `c'
}
twoway (scatter coeff iso3_num, mcolor(blue)) ///
       (rcap lb ub iso3_num, lcolor(black)), ///
       yline(0, lcolor(red)) ///
       xlabel(, valuelabel angle(90)) ///
       title("Country-Specific Coefficients with Confidence Intervals") ///
       graphregion(margin(10 10 10 10))

However, just the label of three countries appear. I do not think it is a matter of space, as I am writing the labels vertically. But I am not able to find a solution. Any help?

This is an example of my dataset:

* Example generated by -dataex-. For more info, type help dataex
clear
input float(year identity) str3 iso3 float(group_country status_cash) long iso3_num
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 0 "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 85   .04476078 1
2003 . "BWA" 93  .004048369 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 85   .04476078 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 84  .002249904 1
2003 1 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 93  .004048369 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 94 .0010226854 1
2003 0 "BWA" 93  .004048369 1
2003 . "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 1 "BWA" 89  .006098506 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 93  .004048369 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 85   .04476078 1
2003 0 "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 0 "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 0 "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 0 "BWA" 86 .0006186686 1
2003 0 "BWA" 91   .01554987 1
2003 1 "BWA" 93  .004048369 1
2003 1 "BWA" 85   .04476078 1
2003 0 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 85   .04476078 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 94 .0010226854 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 93  .004048369 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 85   .04476078 1
2003 1 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 0 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 85   .04476078 1
2003 . "BWA" 85   .04476078 1
2003 . "BWA" 85   .04476078 1
2003 . "BWA" 91   .01554987 1
2003 1 "BWA" 91   .01554987 1
2003 0 "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
2003 . "BWA" 91   .01554987 1
end
label values iso3_num iso3_num
label def iso3_num 1 "BWA", modify

Thank you!

[Nick Cox]

There is only one country in your example data, so whatever the problem is cannot be explored with that data.

[Chen Samulsion]

Suppose there're 25 countries in your data, just specify the xlabel numlist.

twoway (scatter coeff iso3_num, mcolor(blue)) ///
       (rcap lb ub iso3_num, lcolor(black)), ///
       yline(0, lcolor(red)) ///
       xlabel(1(1)25, valuelabel angle(90)) ///
       title("Country-Specific Coefficients with Confidence Intervals") ///
       graphregion(margin(10 10 10 10))

[Diego Malo]

It works Chen Samulsion . Thank you so much!