I have time series data of an index of employment in Brazilian industries. Part of the data is reproduced below.

What I have: variable "date_2" measuring year-month (200801, 200802, …, 201911, 201912)

What I need: to create a variable "dm": 2008m1, 2008m2, …, 2019m11, 2019m12

However, I've been unable to do it. There is something simple I'm missing.

Could someone help?

Thank you


Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input byte month int year long date_2 double emprego_ind_indice
 1 2008 200801   106
 2 2008 200802 106.3
 3 2008 200803 107.1
 4 2008 200804 108.4
 5 2008 200805 109.2
 6 2008 200806 109.8
 7 2008 200807 110.3
 8 2008 200808 110.8
 9 2008 200809   112
10 2008 200810   112
11 2008 200811 110.5
12 2008 200812 107.5
 1 2009 200901 105.9
 2 2009 200902 104.9
 3 2009 200903 104.4
 4 2009 200904 104.4
 5 2009 200905 104.7
 6 2009 200906 104.7
 7 2009 200907 104.6
 8 2009 200908 105.7
 9 2009 200909 106.5
10 2009 200910 107.1
11 2009 200911 107.3
12 2009 200912 106.3
 1 2010 201001 106.7
 2 2010 201002 107.8
 3 2010 201003 109.5
 4 2010 201004 110.5
 5 2010 201005 111.6
 6 2010 201006 112.1
 7 2010 201007 112.7
 8 2010 201008 113.9
 9 2010 201009 114.5
10 2010 201010 114.6
11 2010 201011 114.1
12 2010 201012 112.6
 1 2011 201101 112.1
 2 2011 201102 112.7
 3 2011 201103 113.2
 4 2011 201104 113.9
 5 2011 201105 114.7
 6 2011 201106 114.8
 7 2011 201107   115
 8 2011 201108 115.4
 9 2011 201109 115.5
10 2011 201110   115
11 2011 201111 113.9
12 2011 201112 112.4
 1 2012 201201 112.5
 2 2012 201202 112.3
 3 2012 201203 112.7
 4 2012 201204 113.1
 5 2012 201205 113.8
 6 2012 201206 113.6
 7 2012 201207 113.8
 8 2012 201208 113.8
 9 2012 201209 114.3
10 2012 201210 114.6
11 2012 201211 114.1
12 2012 201212 112.3
 1 2013 201301 112.1
 2 2013 201302 112.6
 3 2013 201303 113.3
 4 2013 201304 113.9
 5 2013 201305 114.1
 6 2013 201306 114.2
 7 2013 201307 114.7
 8 2013 201308 114.9
 9 2013 201309 115.7
10 2013 201310 115.8
11 2013 201311 115.2
12 2013 201312 113.5
 1 2014 201401 113.6
 2 2014 201402 114.6
 3 2014 201403 114.5
 4 2014 201404 114.5
 5 2014 201405 114.6
 6 2014 201406 113.9
 7 2014 201407 113.5
 8 2014 201408 113.2
 9 2014 201409 112.7
10 2014 201410 112.3
11 2014 201411 111.8
12 2014 201412 110.3
 1 2015 201501 110.1
 2 2015 201502 109.7
 3 2015 201503 109.4
 4 2015 201504 108.8
 5 2015 201505 108.3
 6 2015 201506 107.3
 7 2015 201507 106.2
 8 2015 201508 105.2
 9 2015 201509 104.6
10 2015 201510 103.6
11 2015 201511 102.3
12 2015 201512 100.4
 1 2016 201601  99.3
 2 2016 201602  99.2
 3 2016 201603  99.2
 4 2016 201604  99.3
end