Possibility of merging quarterly data into monthly data

[Hamid muili]

Dear all, I have a quarterly data and some monthly data. I want to convert the quarterly into a monthly format where the new data will only have the Q1(MARCH) Q2(JUNE) Q3(SEPTEMBER) AND Q4( DECEMBER) will only have values while the remaining months will be filled with NA.

For example,

Quarterly
2000q1. 12
2000q2. 14
2000q3. 18
2000q4. 22


New data
Monthly
2000m1 Na
2000m2. Na
2000m3. 12
2000m4. Na
2000m5. Na
2000m6. 14
2000m7. Na 2000m8. Na
20000m9 18
2000m10. Na
2000m11. Na
2000m12. 22

[Hamid muili]

Clyde Schechter , Nick Cox , please is there anyway one could do this for panel data..

[George Ford]

https://www.statalist.org/forums/forum/general-stata-discussion/general/1399385-convert-quarterly-data-to-monthly-quarterly-value-in-second-month-of-quarter-else-null

[Clyde Schechter]

I believe the link shown in #3 is broken; at least I am unable to use it.

Assuming that the date variables in the two data sets are actual Stata quarterly and monthly date variables, not strings that look like quarterly and monthly dates to human eyes, you can do this with:

use monthly_data_set
gen quarterly_date_variable = qofd(dofm(monthly_date_variable))
format quarterly_date_variable %tq
merge 1:1 quarterly_date_variable using quarterly_data_set

Note: Based on your examples in #1, I am assuming that you have single time series in both data sets, not panel data. If you have panel data, then the -merge- command will also require including the name of the panel-id variable.

In the future, when showing data examples, please use the -dataex- command to do so. If you are running version 18, 17, 16 or a fully updated version 15.1 or 14.2, -dataex- is already part of your official Stata installation. If not, run -ssc install dataex- to get it. Either way, run -help dataex- to read the simple instructions for using it. -dataex- will save you time; it is easier and quicker than typing out tables. It includes complete information about aspects of the data that are often critical to answering your question but cannot be seen from tabular displays or screenshots. It also makes it possible for those who want to help you to create a faithful representation of your example to try out their code, which in turn makes it more likely that their answer will actually work in your data.

[Hamid muili]

Thanks a lot, I tried using the Code including cross sectional index but i kept getting cid date cannot uniquely identify.. below Is the data for both monthly and quarterly data


----------------------- copy starting from the next line -----------------------

* Example generated by -dataex-. For more info, type help dataex
clear
input byte cid str14 country str6 quartely double gdp float(date qdate)
1 "Argentina" "2005Q1" 1.300e+11 180 180
1 "Argentina" "2005Q2" 1.300e+11 181 180
1 "Argentina" "2005Q3" 1.300e+11 182 180
1 "Argentina" "2005Q4" 1.400e+11 183 181
1 "Argentina" "2006Q1" 1.400e+11 184 181
1 "Argentina" "2006Q2" 1.400e+11 185 181
1 "Argentina" "2006Q3" 1.400e+11 186 182
1 "Argentina" "2006Q4" 1.500e+11 187 182
1 "Argentina" "2007Q1" 1.500e+11 188 182
1 "Argentina" "2007Q2" 1.500e+11 189 183
1 "Argentina" "2007Q3" 1.600e+11 190 183
1 "Argentina" "2007Q4" 1.600e+11 191 183
1 "Argentina" "2008Q1" 1.600e+11 192 184
1 "Argentina" "2008Q2" 1.600e+11 193 184
1 "Argentina" "2008Q3" 1.600e+11 194 184
1 "Argentina" "2008Q4" 1.600e+11 195 185
1 "Argentina" "2009Q1" 1.500e+11 196 185
1 "Argentina" "2009Q2" 1.500e+11 197 185
1 "Argentina" "2009Q3" 1.500e+11 198 186
1 "Argentina" "2009Q4" 1.600e+11 199 186
1 "Argentina" "2010Q1" 1.600e+11 200 186
1 "Argentina" "2010Q2" 1.700e+11 201 187
1 "Argentina" "2010Q3" 1.700e+11 202 187
1 "Argentina" "2010Q4" 1.700e+11 203 187
1 "Argentina" "2011Q1" 1.800e+11 204 188
1 "Argentina" "2011Q2" 1.800e+11 205 188
1 "Argentina" "2011Q3" 1.800e+11 206 188
1 "Argentina" "2011Q4" 1.800e+11 207 189
1 "Argentina" "2012Q1" 1.800e+11 208 189
1 "Argentina" "2012Q2" 1.700e+11 209 189
1 "Argentina" "2012Q3" 1.800e+11 210 190
1 "Argentina" "2012Q4" 1.800e+11 211 190
1 "Argentina" "2013Q1" 1.800e+11 212 190
1 "Argentina" "2013Q2" 1.800e+11 213 191
1 "Argentina" "2013Q3" 1.800e+11 214 191
1 "Argentina" "2013Q4" 1.800e+11 215 191
1 "Argentina" "2014Q1" 1.800e+11 216 192
1 "Argentina" "2014Q2" 1.800e+11 217 192
1 "Argentina" "2014Q3" 1.700e+11 218 192
1 "Argentina" "2014Q4" 1.800e+11 219 193
1 "Argentina" "2015Q1" 1.800e+11 220 193
1 "Argentina" "2015Q2" 1.800e+11 221 193
1 "Argentina" "2015Q3" 1.800e+11 222 194
1 "Argentina" "2015Q4" 1.800e+11 223 194
1 "Argentina" "2016Q1" 1.800e+11 224 194
1 "Argentina" "2016Q2" 1.800e+11 225 195
1 "Argentina" "2016Q3" 1.800e+11 226 195
1 "Argentina" "2016Q4" 1.800e+11 227 195
1 "Argentina" "2017Q1" 1.800e+11 228 196
1 "Argentina" "2017Q2" 1.800e+11 229 196
1 "Argentina" "2017Q3" 1.800e+11 230 196
1 "Argentina" "2017Q4" 1.800e+11 231 197
1 "Argentina" "2018Q1" 1.800e+11 232 197
1 "Argentina" "2018Q2" 1.800e+11 233 197
1 "Argentina" "2018Q3" 1.800e+11 234 198
1 "Argentina" "2018Q4" 1.700e+11 235 198
1 "Argentina" "2019Q1" 1.700e+11 236 198
1 "Argentina" "2019Q2" 1.700e+11 237 199
1 "Argentina" "2019Q3" 1.700e+11 238 199
1 "Argentina" "2019Q4" 1.700e+11 239 199
1 "Argentina" "2020Q1" 1.600e+11 240 200
1 "Argentina" "2020Q2" 1.400e+11 241 200
1 "Argentina" "2020Q3" 1.600e+11 242 200
1 "Argentina" "2020Q4" 1.600e+11 243 201
1 "Argentina" "2021Q1" 1.700e+11 244 201
1 "Argentina" "2021Q2" 1.700e+11 245 201
1 "Argentina" "2021Q3" 1.700e+11 246 202
1 "Argentina" "2021Q4" 1.800e+11 247 202
1 "Argentina" "2022Q1" 1.800e+11 248 202
2 "Brazil"    "2005Q1" 2.200e+11 180 203
2 "Brazil"    "2005Q2" 2.300e+11 181 203
2 "Brazil"    "2005Q3" 2.300e+11 182 203
2 "Brazil"    "2005Q4" 2.300e+11 183 204
2 "Brazil"    "2006Q1" 2.300e+11 184 204
2 "Brazil"    "2006Q2" 2.300e+11 185 204
2 "Brazil"    "2006Q3" 2.400e+11 186 205
2 "Brazil"    "2006Q4" 2.400e+11 187 205
2 "Brazil"    "2007Q1" 2.400e+11 188 205
2 "Brazil"    "2007Q2" 2.500e+11 189 206
2 "Brazil"    "2007Q3" 2.500e+11 190 206
2 "Brazil"    "2007Q4" 2.500e+11 191 206
2 "Brazil"    "2008Q1" 2.600e+11 192 207
2 "Brazil"    "2008Q2" 2.600e+11 193 207
2 "Brazil"    "2008Q3" 2.700e+11 194 207
2 "Brazil"    "2008Q4" 2.600e+11 195 208
2 "Brazil"    "2009Q1" 2.500e+11 196 208
2 "Brazil"    "2009Q2" 2.600e+11 197 208
2 "Brazil"    "2009Q3" 2.600e+11 198 209
2 "Brazil"    "2009Q4" 2.700e+11 199 209
2 "Brazil"    "2010Q1" 2.800e+11 200 209
2 "Brazil"    "2010Q2" 2.800e+11 201 210
2 "Brazil"    "2010Q3" 2.800e+11 202 210
2 "Brazil"    "2010Q4" 2.900e+11 203 210
2 "Brazil"    "2011Q1" 2.900e+11 204 211
2 "Brazil"    "2011Q2" 2.900e+11 205 211
2 "Brazil"    "2011Q3" 2.900e+11 206 211
2 "Brazil"    "2011Q4" 3.000e+11 207 212
2 "Brazil"    "2012Q1" 2.900e+11 208 212
2 "Brazil"    "2012Q2" 3.000e+11 209 212
2 "Brazil"    "2012Q3" 3.000e+11 210 213
end
format %tq date
format %tq qdate

* Example generated by -dataex-. For more info, type help dataex
clear
input byte cid str14 country str7 months float(mpr_per_annm date qdate)
 6 "Germany"        "2005M1"     2 540 180
11 "Turkey"         "2005M1"    17 540 180
 9 "Saudi Arabia"   "2005M1"  2.25 540 180
 5 "China"          "2005M1"  3.75 540 180
 8 "Mexico"         "2005M1"  8.82 540 180
 2 "Brazil"         "2005M1" 18.25 540 180
12 "United Kingdom" "2005M1"  4.75 540 180
 1 "Argentina"      "2005M1"  2.75 540 180
 7 "Japan"          "2005M1"  14.2 540 180
10 "South AfrIca"   "2005M1"   7.5 540 180
 4 "Chile"          "2005M1"   2.5 540 180
13 "United states"  "2005M1"  2.25 540 180
 3 "Canada"         "2005M1"   2.5 540 180
 3 "Canada"         "2005M2"   2.5 541 180
 1 "Argentina"      "2005M2"  2.75 541 180
 8 "Mexico"         "2005M2"  9.21 541 180
 2 "Brazil"         "2005M2" 18.75 541 180
 5 "China"          "2005M2"     4 541 180
 7 "Japan"          "2005M2"  14.2 541 180
 9 "Saudi Arabia"   "2005M2"   2.5 541 180
 4 "Chile"          "2005M2"  2.75 541 180
11 "Turkey"         "2005M2"  16.5 541 180
13 "United states"  "2005M2"   2.5 541 180
12 "United Kingdom" "2005M2"  4.75 541 180
10 "South AfrIca"   "2005M2"   7.5 541 180
 6 "Germany"        "2005M2"     2 541 180
 7 "Japan"          "2005M3"  14.2 542 180
 9 "Saudi Arabia"   "2005M3"     3 542 180
12 "United Kingdom" "2005M3"  4.75 542 180
 4 "Chile"          "2005M3"  2.75 542 180
 3 "Canada"         "2005M3"   2.5 542 180
 2 "Brazil"         "2005M3" 19.25 542 180
 1 "Argentina"      "2005M3"  2.75 542 180
11 "Turkey"         "2005M3"  15.5 542 180
 6 "Germany"        "2005M3"     2 542 180
 5 "China"          "2005M3"  4.25 542 180
13 "United states"  "2005M3"  2.75 542 180
10 "South AfrIca"   "2005M3"   7.5 542 180
 8 "Mexico"         "2005M3"  9.51 542 180
11 "Turkey"         "2005M4"    15 543 181
 1 "Argentina"      "2005M4"  3.25 543 181
13 "United states"  "2005M4"  2.75 543 181
 5 "China"          "2005M4"  4.25 543 181
 8 "Mexico"         "2005M4"   9.6 543 181
12 "United Kingdom" "2005M4"  4.75 543 181
 3 "Canada"         "2005M4"   2.5 543 181
10 "South AfrIca"   "2005M4"     7 543 181
 9 "Saudi Arabia"   "2005M4"     3 543 181
 4 "Chile"          "2005M4"     3 543 181
 6 "Germany"        "2005M4"     2 543 181
 2 "Brazil"         "2005M4"  19.5 543 181
 7 "Japan"          "2005M4"  14.2 543 181
 7 "Japan"          "2005M5"    14 544 181
 3 "Canada"         "2005M5"   2.5 544 181
10 "South AfrIca"   "2005M5"     7 544 181
13 "United states"  "2005M5"     3 544 181
 1 "Argentina"      "2005M5"  3.75 544 181
 4 "Chile"          "2005M5"  3.25 544 181
11 "Turkey"         "2005M5"  14.5 544 181
 2 "Brazil"         "2005M5" 19.75 544 181
 5 "China"          "2005M5"   4.5 544 181
 8 "Mexico"         "2005M5"  9.75 544 181
 6 "Germany"        "2005M5"     2 544 181
 9 "Saudi Arabia"   "2005M5"     3 544 181
12 "United Kingdom" "2005M5"  4.75 544 181
 3 "Canada"         "2005M6"   2.5 545 181
 9 "Saudi Arabia"   "2005M6"     3 545 181
 4 "Chile"          "2005M6"  3.25 545 181
 8 "Mexico"         "2005M6"  9.76 545 181
 5 "China"          "2005M6"   4.5 545 181
10 "South AfrIca"   "2005M6"     7 545 181
11 "Turkey"         "2005M6" 14.25 545 181
 2 "Brazil"         "2005M6" 19.75 545 181
13 "United states"  "2005M6"  3.25 545 181
 6 "Germany"        "2005M6"     2 545 181
 1 "Argentina"      "2005M6"  4.25 545 181
 7 "Japan"          "2005M6"    14 545 181
12 "United Kingdom" "2005M6"  4.75 545 181
10 "South AfrIca"   "2005M7"     7 546 182
 5 "China"          "2005M7"  4.75 546 182
11 "Turkey"         "2005M7" 14.25 546 182
 9 "Saudi Arabia"   "2005M7"  3.25 546 182
13 "United states"  "2005M7"  3.25 546 182
 3 "Canada"         "2005M7"   2.5 546 182
 2 "Brazil"         "2005M7" 19.75 546 182
 1 "Argentina"      "2005M7"  4.25 546 182
 8 "Mexico"         "2005M7"  9.75 546 182
 6 "Germany"        "2005M7"     2 546 182
 4 "Chile"          "2005M7"   3.5 546 182
12 "United Kingdom" "2005M7"  4.75 546 182
 7 "Japan"          "2005M7"    14 546 182
11 "Turkey"         "2005M8" 14.25 547 182
 2 "Brazil"         "2005M8" 19.75 547 182
 8 "Mexico"         "2005M8"  9.51 547 182
 1 "Argentina"      "2005M8"  4.25 547 182
 9 "Saudi Arabia"   "2005M8"   3.5 547 182
 4 "Chile"          "2005M8"  3.75 547 182
 5 "China"          "2005M8"     5 547 182
 6 "Germany"        "2005M8"     2 547 182
 3 "Canada"         "2005M8"   2.5 547 182
end
format %tm date
format %tq qdate

[Hamid muili]

I observed that the country arrangements has been disrupted so I rearranged them. However, I'm still facing the same problem. Here's the newly adjust monthly data.

* Example generated by -dataex-. For more info, type 
 help dataex
clear
input str14 country str7 months float mpr_per_annm str7 date str6 qdate float(date1 cid)
"Argentina" "2005M1" 2.75 "2005m1" "2005q1" 180 1
"Argentina" "2005M2" 2.75 "2005m2" "2005q1" 180 1
"Argentina" "2005M3" 2.75 "2005m3" "2005q1" 180 1
"Argentina" "2005M4" 3.25 "2005m4" "2005q2" 181 1
"Argentina" "2005M5" 3.75 "2005m5" "2005q2" 181 1
"Argentina" "2005M6" 4.25 "2005m6" "2005q2" 181 1
"Argentina" "2005M7" 4.25 "2005m7" "2005q3" 182 1
"Argentina" "2005M8" 4.25 "2005m8" "2005q3" 182 1
"Argentina" "2005M9" 4.25 "2005m9" "2005q3" 182 1
"Argentina" "2005M10" 4.5 "2005m10" "2005q4" 183 1
"Argentina" "2005M11" 4.5 "2005m11" "2005q4" 183 1
"Argentina" "2005M12" 5 "2005m12" "2005q4" 183 1
"Argentina" "2006M1" 5 "2006m1" "2006q1" 184 1
"Argentina" "2006M2" 5 "2006m2" "2006q1" 184 1
"Argentina" "2006M3" 5 "2006m3" "2006q1" 184 1
"Argentina" "2006M4" 5 "2006m4" "2006q2" 185 1
"Argentina" "2006M5" 5.5 "2006m5" "2006q2" 185 1
"Argentina" "2006M6" 5.75 "2006m6" "2006q2" 185 1
"Argentina" "2006M7" 5.75 "2006m7" "2006q3" 186 1
"Argentina" "2006M8" 5.75 "2006m8" "2006q3" 186 1
"Argentina" "2006M9" 5.75 "2006m9" "2006q3" 186 1
"Argentina" "2006M10" 6 "2006m10" "2006q4" 187 1
"Argentina" "2006M11" 6.25 "2006m11" "2006q4" 187 1
"Argentina" "2006M12" 6.25 "2006m12" "2006q4" 187 1
"Argentina" "2007M1" 6.5 "2007m1" "2007q1" 188 1
"Argentina" "2007M2" 6.75 "2007m2" "2007q1" 188 1
"Argentina" "2007M3" 10.4 "2007m3" "2007q1" 188 1
"Argentina" "2007M4" 10.31 "2007m4" "2007q2" 189 1
"Argentina" "2007M5" 10.33 "2007m5" "2007q2" 189 1
"Argentina" "2007M6" 10.25 "2007m6" "2007q2" 189 1
"Argentina" "2007M7" 10.31 "2007m7" "2007q3" 190 1
"Argentina" "2007M8" 10.5 "2007m8" "2007q3" 190 1
"Argentina" "2007M9" 10.37 "2007m9" "2007q3" 190 1
"Argentina" "2007M10" 10.7 "2007m10" "2007q4" 191 1
"Argentina" "2007M11" 10.65 "2007m11" "2007q4" 191 1
"Argentina" "2007M12" 10.75 "2007m12" "2007q4" 191 1
"Argentina" "2008M1" 11 "2008m1" "2008q1" 192 1
"Argentina" "2008M2" 11.3 "2008m2" "2008q1" 192 1
"Argentina" "2008M3" 11.07 "2008m3" "2008q1" 192 1
"Argentina" "2008M4" 11.52 "2008m4" "2008q2" 193 1
"Argentina" "2008M5" 11.8 "2008m5" "2008q2" 193 1
"Argentina" "2008M6" 11.84 "2008m6" "2008q2" 193 1
"Argentina" "2008M7" 12.2 "2008m7" "2008q3" 194 1
"Argentina" "2008M8" 12.2 "2008m8" "2008q3" 194 1
"Argentina" "2008M9" 12.26 "2008m9" "2008q3" 194 1
"Argentina" "2008M10" 12.48 "2008m10" "2008q4" 195 1
"Argentina" "2008M11" 12.5 "2008m11" "2008q4" 195 1
"Argentina" "2008M12" 12.05 "2008m12" "2008q4" 195 1
"Argentina" "2009M1" 12.5 "2009m1" "2009q1" 196 1
"Argentina" "2009M2" 13.4 "2009m2" "2009q1" 196 1
"Argentina" "2009M3" 14 "2009m3" "2009q1" 196 1
"Argentina" "2009M4" 14.35 "2009m4" "2009q2" 197 1
"Argentina" "2009M5" 14.55 "2009m5" "2009q2" 197 1
"Argentina" "2009M6" 16.25 "2009m6" "2009q2" 197 1
"Argentina" "2009M7" 14.59 "2009m7" "2009q3" 198 1
"Argentina" "2009M8" 15.89 "2009m8" "2009q3" 198 1
"Argentina" "2009M9" 9.75 "2009m9" "2009q3" 198 1
"Argentina" "2009M10" 9.5 "2009m10" "2009q4" 199 1
"Argentina" "2009M11" 9.5 "2009m11" "2009q4" 199 1
"Argentina" "2009M12" 9.5 "2009m12" "2009q4" 199 1
"Argentina" "2010M1" 9.5 "2010m1" "2010q1" 200 1
"Argentina" "2010M2" 9.5 "2010m2" "2010q1" 200 1
"Argentina" "2010M3" 9.5 "2010m3" "2010q1" 200 1
"Argentina" "2010M4" 9.5 "2010m4" "2010q2" 201 1
"Argentina" "2010M5" 9.5 "2010m5" "2010q2" 201 1
"Argentina" "2010M6" 9.5 "2010m6" "2010q2" 201 1
"Argentina" "2010M7" 9.5 "2010m7" "2010q3" 202 1
"Argentina" "2010M8" 9.5 "2010m8" "2010q3" 202 1
"Argentina" "2010M9" 9.5 "2010m9" "2010q3" 202 1
"Argentina" "2010M10" 9.5 "2010m10" "2010q4" 203 1
"Argentina" "2010M11" 9.5 "2010m11" "2010q4" 203 1
"Argentina" "2010M12" 9.5 "2010m12" "2010q4" 203 1
"Argentina" "2011M1" 9.5 "2011m1" "2011q1" 204 1
"Argentina" "2011M2" 9.5 "2011m2" "2011q1" 204 1
"Argentina" "2011M3" 9.5 "2011m3" "2011q1" 204 1
"Argentina" "2011M4" 9.5 "2011m4" "2011q2" 205 1
"Argentina" "2011M5" 9.5 "2011m5" "2011q2" 205 1
"Argentina" "2011M6" 9.5 "2011m6" "2011q2" 205 1
"Argentina" "2011M7" 9.5 "2011m7" "2011q3" 206 1
"Argentina" "2011M8" 9.5 "2011m8" "2011q3" 206 1
"Argentina" "2011M9" 9.5 "2011m9" "2011q3" 206 1
"Argentina" "2011M10" 9.5 "2011m10" "2011q4" 207 1
"Argentina" "2011M11" 9.5 "2011m11" "2011q4" 207 1
"Argentina" "2011M12" 9.5 "2011m12" "2011q4" 207 1
"Argentina" "2012M1" 9.5 "2012m1" "2012q1" 208 1
"Argentina" "2012M2" 9.5 "2012m2" "2012q1" 208 1
"Argentina" "2012M3" 9.5 "2012m3" "2012q1" 208 1
"Argentina" "2012M4" 9.5 "2012m4" "2012q2" 209 1
"Argentina" "2012M5" 9.5 "2012m5" "2012q2" 209 1
"Argentina" "2012M6" 9.5 "2012m6" "2012q2" 209 1
"Argentina" "2012M7" 9.5 "2012m7" "2012q3" 210 1
"Argentina" "2012M8" 9.5 "2012m8" "2012q3" 210 1
"Argentina" "2012M9" 9.5 "2012m9" "2012q3" 210 1
"Argentina" "2012M10" 9.5 "2012m10" "2012q4" 211 1
"Argentina" "2012M11" 9.5 "2012m11" "2012q4" 211 1
"Argentina" "2012M12" 9.5 "2012m12" "2012q4" 211 1
"Argentina" "2013M1" 9.5 "2013m1" "2013q1" 212 1
"Argentina" "2013M2" 9.5 "2013m2" "2013q1" 212 1
"Argentina" "2013M3" 9.5 "2013m3" "2013q1" 212 1
"Argentina" "2013M4" 9.5 "2013m4" "2013q2" 213 1
end
format %tq date1

[Clyde Schechter]

You have a lot of date variables in these data sets, and some of them appear to be wrongly calculated. Anyway, you will get the match you need if you rely on the variable called date in the monthly data set and the variable called date1 in the quarterly data set. When you clear that up, you have another problem: in one of the data sets the variable qdate is a numeric variable and in the other it is a string. -merge- can't work with that either. In this case, the variable qdate plays no role anyway: the information is in date and date1. So the simplest solution is to just drop it.

So

* Example generated by -dataex-. For more info, type help dataex
clear
input byte cid str14 country str6 quartely double gdp float(date qdate)
1 "Argentina" "2005Q1" 1.300e+11 180 180
1 "Argentina" "2005Q2" 1.300e+11 181 180
1 "Argentina" "2005Q3" 1.300e+11 182 180
1 "Argentina" "2005Q4" 1.400e+11 183 181
1 "Argentina" "2006Q1" 1.400e+11 184 181
1 "Argentina" "2006Q2" 1.400e+11 185 181
1 "Argentina" "2006Q3" 1.400e+11 186 182
1 "Argentina" "2006Q4" 1.500e+11 187 182
1 "Argentina" "2007Q1" 1.500e+11 188 182
1 "Argentina" "2007Q2" 1.500e+11 189 183
1 "Argentina" "2007Q3" 1.600e+11 190 183
1 "Argentina" "2007Q4" 1.600e+11 191 183
1 "Argentina" "2008Q1" 1.600e+11 192 184
1 "Argentina" "2008Q2" 1.600e+11 193 184
1 "Argentina" "2008Q3" 1.600e+11 194 184
1 "Argentina" "2008Q4" 1.600e+11 195 185
1 "Argentina" "2009Q1" 1.500e+11 196 185
1 "Argentina" "2009Q2" 1.500e+11 197 185
1 "Argentina" "2009Q3" 1.500e+11 198 186
1 "Argentina" "2009Q4" 1.600e+11 199 186
1 "Argentina" "2010Q1" 1.600e+11 200 186
1 "Argentina" "2010Q2" 1.700e+11 201 187
1 "Argentina" "2010Q3" 1.700e+11 202 187
1 "Argentina" "2010Q4" 1.700e+11 203 187
1 "Argentina" "2011Q1" 1.800e+11 204 188
1 "Argentina" "2011Q2" 1.800e+11 205 188
1 "Argentina" "2011Q3" 1.800e+11 206 188
1 "Argentina" "2011Q4" 1.800e+11 207 189
1 "Argentina" "2012Q1" 1.800e+11 208 189
1 "Argentina" "2012Q2" 1.700e+11 209 189
1 "Argentina" "2012Q3" 1.800e+11 210 190
1 "Argentina" "2012Q4" 1.800e+11 211 190
1 "Argentina" "2013Q1" 1.800e+11 212 190
1 "Argentina" "2013Q2" 1.800e+11 213 191
1 "Argentina" "2013Q3" 1.800e+11 214 191
1 "Argentina" "2013Q4" 1.800e+11 215 191
1 "Argentina" "2014Q1" 1.800e+11 216 192
1 "Argentina" "2014Q2" 1.800e+11 217 192
1 "Argentina" "2014Q3" 1.700e+11 218 192
1 "Argentina" "2014Q4" 1.800e+11 219 193
1 "Argentina" "2015Q1" 1.800e+11 220 193
1 "Argentina" "2015Q2" 1.800e+11 221 193
1 "Argentina" "2015Q3" 1.800e+11 222 194
1 "Argentina" "2015Q4" 1.800e+11 223 194
1 "Argentina" "2016Q1" 1.800e+11 224 194
1 "Argentina" "2016Q2" 1.800e+11 225 195
1 "Argentina" "2016Q3" 1.800e+11 226 195
1 "Argentina" "2016Q4" 1.800e+11 227 195
1 "Argentina" "2017Q1" 1.800e+11 228 196
1 "Argentina" "2017Q2" 1.800e+11 229 196
1 "Argentina" "2017Q3" 1.800e+11 230 196
1 "Argentina" "2017Q4" 1.800e+11 231 197
1 "Argentina" "2018Q1" 1.800e+11 232 197
1 "Argentina" "2018Q2" 1.800e+11 233 197
1 "Argentina" "2018Q3" 1.800e+11 234 198
1 "Argentina" "2018Q4" 1.700e+11 235 198
1 "Argentina" "2019Q1" 1.700e+11 236 198
1 "Argentina" "2019Q2" 1.700e+11 237 199
1 "Argentina" "2019Q3" 1.700e+11 238 199
1 "Argentina" "2019Q4" 1.700e+11 239 199
1 "Argentina" "2020Q1" 1.600e+11 240 200
1 "Argentina" "2020Q2" 1.400e+11 241 200
1 "Argentina" "2020Q3" 1.600e+11 242 200
1 "Argentina" "2020Q4" 1.600e+11 243 201
1 "Argentina" "2021Q1" 1.700e+11 244 201
1 "Argentina" "2021Q2" 1.700e+11 245 201
1 "Argentina" "2021Q3" 1.700e+11 246 202
1 "Argentina" "2021Q4" 1.800e+11 247 202
1 "Argentina" "2022Q1" 1.800e+11 248 202
2 "Brazil"    "2005Q1" 2.200e+11 180 203
2 "Brazil"    "2005Q2" 2.300e+11 181 203
2 "Brazil"    "2005Q3" 2.300e+11 182 203
2 "Brazil"    "2005Q4" 2.300e+11 183 204
2 "Brazil"    "2006Q1" 2.300e+11 184 204
2 "Brazil"    "2006Q2" 2.300e+11 185 204
2 "Brazil"    "2006Q3" 2.400e+11 186 205
2 "Brazil"    "2006Q4" 2.400e+11 187 205
2 "Brazil"    "2007Q1" 2.400e+11 188 205
2 "Brazil"    "2007Q2" 2.500e+11 189 206
2 "Brazil"    "2007Q3" 2.500e+11 190 206
2 "Brazil"    "2007Q4" 2.500e+11 191 206
2 "Brazil"    "2008Q1" 2.600e+11 192 207
2 "Brazil"    "2008Q2" 2.600e+11 193 207
2 "Brazil"    "2008Q3" 2.700e+11 194 207
2 "Brazil"    "2008Q4" 2.600e+11 195 208
2 "Brazil"    "2009Q1" 2.500e+11 196 208
2 "Brazil"    "2009Q2" 2.600e+11 197 208
2 "Brazil"    "2009Q3" 2.600e+11 198 209
2 "Brazil"    "2009Q4" 2.700e+11 199 209
2 "Brazil"    "2010Q1" 2.800e+11 200 209
2 "Brazil"    "2010Q2" 2.800e+11 201 210
2 "Brazil"    "2010Q3" 2.800e+11 202 210
2 "Brazil"    "2010Q4" 2.900e+11 203 210
2 "Brazil"    "2011Q1" 2.900e+11 204 211
2 "Brazil"    "2011Q2" 2.900e+11 205 211
2 "Brazil"    "2011Q3" 2.900e+11 206 211
2 "Brazil"    "2011Q4" 3.000e+11 207 212
2 "Brazil"    "2012Q1" 2.900e+11 208 212
2 "Brazil"    "2012Q2" 3.000e+11 209 212
2 "Brazil"    "2012Q3" 3.000e+11 210 213
end
format %tq date
format %tq qdate
tempfile quarterly
save `quarterly'

* Example generated by -dataex-. For more info, type
 help dataex
clear
input str14 country str7 months float mpr_per_annm str7 date str6 qdate float(date1 cid)
"Argentina" "2005M1" 2.75 "2005m1" "2005q1" 180 1
"Argentina" "2005M2" 2.75 "2005m2" "2005q1" 180 1
"Argentina" "2005M3" 2.75 "2005m3" "2005q1" 180 1
"Argentina" "2005M4" 3.25 "2005m4" "2005q2" 181 1
"Argentina" "2005M5" 3.75 "2005m5" "2005q2" 181 1
"Argentina" "2005M6" 4.25 "2005m6" "2005q2" 181 1
"Argentina" "2005M7" 4.25 "2005m7" "2005q3" 182 1
"Argentina" "2005M8" 4.25 "2005m8" "2005q3" 182 1
"Argentina" "2005M9" 4.25 "2005m9" "2005q3" 182 1
"Argentina" "2005M10" 4.5 "2005m10" "2005q4" 183 1
"Argentina" "2005M11" 4.5 "2005m11" "2005q4" 183 1
"Argentina" "2005M12" 5 "2005m12" "2005q4" 183 1
"Argentina" "2006M1" 5 "2006m1" "2006q1" 184 1
"Argentina" "2006M2" 5 "2006m2" "2006q1" 184 1
"Argentina" "2006M3" 5 "2006m3" "2006q1" 184 1
"Argentina" "2006M4" 5 "2006m4" "2006q2" 185 1
"Argentina" "2006M5" 5.5 "2006m5" "2006q2" 185 1
"Argentina" "2006M6" 5.75 "2006m6" "2006q2" 185 1
"Argentina" "2006M7" 5.75 "2006m7" "2006q3" 186 1
"Argentina" "2006M8" 5.75 "2006m8" "2006q3" 186 1
"Argentina" "2006M9" 5.75 "2006m9" "2006q3" 186 1
"Argentina" "2006M10" 6 "2006m10" "2006q4" 187 1
"Argentina" "2006M11" 6.25 "2006m11" "2006q4" 187 1
"Argentina" "2006M12" 6.25 "2006m12" "2006q4" 187 1
"Argentina" "2007M1" 6.5 "2007m1" "2007q1" 188 1
"Argentina" "2007M2" 6.75 "2007m2" "2007q1" 188 1
"Argentina" "2007M3" 10.4 "2007m3" "2007q1" 188 1
"Argentina" "2007M4" 10.31 "2007m4" "2007q2" 189 1
"Argentina" "2007M5" 10.33 "2007m5" "2007q2" 189 1
"Argentina" "2007M6" 10.25 "2007m6" "2007q2" 189 1
"Argentina" "2007M7" 10.31 "2007m7" "2007q3" 190 1
"Argentina" "2007M8" 10.5 "2007m8" "2007q3" 190 1
"Argentina" "2007M9" 10.37 "2007m9" "2007q3" 190 1
"Argentina" "2007M10" 10.7 "2007m10" "2007q4" 191 1
"Argentina" "2007M11" 10.65 "2007m11" "2007q4" 191 1
"Argentina" "2007M12" 10.75 "2007m12" "2007q4" 191 1
"Argentina" "2008M1" 11 "2008m1" "2008q1" 192 1
"Argentina" "2008M2" 11.3 "2008m2" "2008q1" 192 1
"Argentina" "2008M3" 11.07 "2008m3" "2008q1" 192 1
"Argentina" "2008M4" 11.52 "2008m4" "2008q2" 193 1
"Argentina" "2008M5" 11.8 "2008m5" "2008q2" 193 1
"Argentina" "2008M6" 11.84 "2008m6" "2008q2" 193 1
"Argentina" "2008M7" 12.2 "2008m7" "2008q3" 194 1
"Argentina" "2008M8" 12.2 "2008m8" "2008q3" 194 1
"Argentina" "2008M9" 12.26 "2008m9" "2008q3" 194 1
"Argentina" "2008M10" 12.48 "2008m10" "2008q4" 195 1
"Argentina" "2008M11" 12.5 "2008m11" "2008q4" 195 1
"Argentina" "2008M12" 12.05 "2008m12" "2008q4" 195 1
"Argentina" "2009M1" 12.5 "2009m1" "2009q1" 196 1
"Argentina" "2009M2" 13.4 "2009m2" "2009q1" 196 1
"Argentina" "2009M3" 14 "2009m3" "2009q1" 196 1
"Argentina" "2009M4" 14.35 "2009m4" "2009q2" 197 1
"Argentina" "2009M5" 14.55 "2009m5" "2009q2" 197 1
"Argentina" "2009M6" 16.25 "2009m6" "2009q2" 197 1
"Argentina" "2009M7" 14.59 "2009m7" "2009q3" 198 1
"Argentina" "2009M8" 15.89 "2009m8" "2009q3" 198 1
"Argentina" "2009M9" 9.75 "2009m9" "2009q3" 198 1
"Argentina" "2009M10" 9.5 "2009m10" "2009q4" 199 1
"Argentina" "2009M11" 9.5 "2009m11" "2009q4" 199 1
"Argentina" "2009M12" 9.5 "2009m12" "2009q4" 199 1
"Argentina" "2010M1" 9.5 "2010m1" "2010q1" 200 1
"Argentina" "2010M2" 9.5 "2010m2" "2010q1" 200 1
"Argentina" "2010M3" 9.5 "2010m3" "2010q1" 200 1
"Argentina" "2010M4" 9.5 "2010m4" "2010q2" 201 1
"Argentina" "2010M5" 9.5 "2010m5" "2010q2" 201 1
"Argentina" "2010M6" 9.5 "2010m6" "2010q2" 201 1
"Argentina" "2010M7" 9.5 "2010m7" "2010q3" 202 1
"Argentina" "2010M8" 9.5 "2010m8" "2010q3" 202 1
"Argentina" "2010M9" 9.5 "2010m9" "2010q3" 202 1
"Argentina" "2010M10" 9.5 "2010m10" "2010q4" 203 1
"Argentina" "2010M11" 9.5 "2010m11" "2010q4" 203 1
"Argentina" "2010M12" 9.5 "2010m12" "2010q4" 203 1
"Argentina" "2011M1" 9.5 "2011m1" "2011q1" 204 1
"Argentina" "2011M2" 9.5 "2011m2" "2011q1" 204 1
"Argentina" "2011M3" 9.5 "2011m3" "2011q1" 204 1
"Argentina" "2011M4" 9.5 "2011m4" "2011q2" 205 1
"Argentina" "2011M5" 9.5 "2011m5" "2011q2" 205 1
"Argentina" "2011M6" 9.5 "2011m6" "2011q2" 205 1
"Argentina" "2011M7" 9.5 "2011m7" "2011q3" 206 1
"Argentina" "2011M8" 9.5 "2011m8" "2011q3" 206 1
"Argentina" "2011M9" 9.5 "2011m9" "2011q3" 206 1
"Argentina" "2011M10" 9.5 "2011m10" "2011q4" 207 1
"Argentina" "2011M11" 9.5 "2011m11" "2011q4" 207 1
"Argentina" "2011M12" 9.5 "2011m12" "2011q4" 207 1
"Argentina" "2012M1" 9.5 "2012m1" "2012q1" 208 1
"Argentina" "2012M2" 9.5 "2012m2" "2012q1" 208 1
"Argentina" "2012M3" 9.5 "2012m3" "2012q1" 208 1
"Argentina" "2012M4" 9.5 "2012m4" "2012q2" 209 1
"Argentina" "2012M5" 9.5 "2012m5" "2012q2" 209 1
"Argentina" "2012M6" 9.5 "2012m6" "2012q2" 209 1
"Argentina" "2012M7" 9.5 "2012m7" "2012q3" 210 1
"Argentina" "2012M8" 9.5 "2012m8" "2012q3" 210 1
"Argentina" "2012M9" 9.5 "2012m9" "2012q3" 210 1
"Argentina" "2012M10" 9.5 "2012m10" "2012q4" 211 1
"Argentina" "2012M11" 9.5 "2012m11" "2012q4" 211 1
"Argentina" "2012M12" 9.5 "2012m12" "2012q4" 211 1
"Argentina" "2013M1" 9.5 "2013m1" "2013q1" 212 1
"Argentina" "2013M2" 9.5 "2013m2" "2013q1" 212 1
"Argentina" "2013M3" 9.5 "2013m3" "2013q1" 212 1
"Argentina" "2013M4" 9.5 "2013m4" "2013q2" 213 1
end
format %tq date1
tempfile monthly
save `monthly'


use `quarterly', clear
drop qdate // TYPE MISMATCH TO OTHER DATA SET.
rename date date1    // TO MATCH THE CORRESPONDING VARIABLE IN THE MONTHLY DATASET

merge 1:m cid date1 using `monthly'

[Hamid muili]

After cleaning the dara it looks like this:

* Example generated by -dataex-. For more info, type help dataex
clear
input byte cid str14 country str6 quartely double gdp float date1
1 "Argentina" "2005Q1" 1.300e+11 180
1 "Argentina" "2005Q2" 1.300e+11 181
1 "Argentina" "2005Q3" 1.300e+11 182
1 "Argentina" "2005Q4" 1.400e+11 183
1 "Argentina" "2006Q1" 1.400e+11 184
1 "Argentina" "2006Q2" 1.400e+11 185
1 "Argentina" "2006Q3" 1.400e+11 186
1 "Argentina" "2006Q4" 1.500e+11 187
1 "Argentina" "2007Q1" 1.500e+11 188
1 "Argentina" "2007Q2" 1.500e+11 189
1 "Argentina" "2007Q3" 1.600e+11 190
1 "Argentina" "2007Q4" 1.600e+11 191
1 "Argentina" "2008Q1" 1.600e+11 192
1 "Argentina" "2008Q2" 1.600e+11 193
1 "Argentina" "2008Q3" 1.600e+11 194
1 "Argentina" "2008Q4" 1.600e+11 195
1 "Argentina" "2009Q1" 1.500e+11 196
1 "Argentina" "2009Q2" 1.500e+11 197
1 "Argentina" "2009Q3" 1.500e+11 198
1 "Argentina" "2009Q4" 1.600e+11 199
1 "Argentina" "2010Q1" 1.600e+11 200
1 "Argentina" "2010Q2" 1.700e+11 201
1 "Argentina" "2010Q3" 1.700e+11 202
1 "Argentina" "2010Q4" 1.700e+11 203
1 "Argentina" "2011Q1" 1.800e+11 204
1 "Argentina" "2011Q2" 1.800e+11 205
1 "Argentina" "2011Q3" 1.800e+11 206
1 "Argentina" "2011Q4" 1.800e+11 207
1 "Argentina" "2012Q1" 1.800e+11 208
1 "Argentina" "2012Q2" 1.700e+11 209
1 "Argentina" "2012Q3" 1.800e+11 210
1 "Argentina" "2012Q4" 1.800e+11 211
1 "Argentina" "2013Q1" 1.800e+11 212
1 "Argentina" "2013Q2" 1.800e+11 213
1 "Argentina" "2013Q3" 1.800e+11 214
1 "Argentina" "2013Q4" 1.800e+11 215
1 "Argentina" "2014Q1" 1.800e+11 216
1 "Argentina" "2014Q2" 1.800e+11 217
1 "Argentina" "2014Q3" 1.700e+11 218
1 "Argentina" "2014Q4" 1.800e+11 219
1 "Argentina" "2015Q1" 1.800e+11 220
1 "Argentina" "2015Q2" 1.800e+11 221
1 "Argentina" "2015Q3" 1.800e+11 222
1 "Argentina" "2015Q4" 1.800e+11 223
1 "Argentina" "2016Q1" 1.800e+11 224
1 "Argentina" "2016Q2" 1.800e+11 225
1 "Argentina" "2016Q3" 1.800e+11 226
1 "Argentina" "2016Q4" 1.800e+11 227
1 "Argentina" "2017Q1" 1.800e+11 228
1 "Argentina" "2017Q2" 1.800e+11 229
1 "Argentina" "2017Q3" 1.800e+11 230
1 "Argentina" "2017Q4" 1.800e+11 231
1 "Argentina" "2018Q1" 1.800e+11 232
1 "Argentina" "2018Q2" 1.800e+11 233
1 "Argentina" "2018Q3" 1.800e+11 234
1 "Argentina" "2018Q4" 1.700e+11 235
1 "Argentina" "2019Q1" 1.700e+11 236
1 "Argentina" "2019Q2" 1.700e+11 237
1 "Argentina" "2019Q3" 1.700e+11 238
1 "Argentina" "2019Q4" 1.700e+11 239
1 "Argentina" "2020Q1" 1.600e+11 240
1 "Argentina" "2020Q2" 1.400e+11 241
1 "Argentina" "2020Q3" 1.600e+11 242
1 "Argentina" "2020Q4" 1.600e+11 243
1 "Argentina" "2021Q1" 1.700e+11 244
1 "Argentina" "2021Q2" 1.700e+11 245
1 "Argentina" "2021Q3" 1.700e+11 246
1 "Argentina" "2021Q4" 1.800e+11 247
1 "Argentina" "2022Q1" 1.800e+11 248
2 "Brazil" "2005Q1" 2.200e+11 180
2 "Brazil" "2005Q2" 2.300e+11 181
2 "Brazil" "2005Q3" 2.300e+11 182
2 "Brazil" "2005Q4" 2.300e+11 183
2 "Brazil" "2006Q1" 2.300e+11 184
2 "Brazil" "2006Q2" 2.300e+11 185
2 "Brazil" "2006Q3" 2.400e+11 186
2 "Brazil" "2006Q4" 2.400e+11 187
2 "Brazil" "2007Q1" 2.400e+11 188
2 "Brazil" "2007Q2" 2.500e+11 189
2 "Brazil" "2007Q3" 2.500e+11 190
2 "Brazil" "2007Q4" 2.500e+11 191
2 "Brazil" "2008Q1" 2.600e+11 192
2 "Brazil" "2008Q2" 2.600e+11 193
2 "Brazil" "2008Q3" 2.700e+11 194
2 "Brazil" "2008Q4" 2.600e+11 195
2 "Brazil" "2009Q1" 2.500e+11 196
2 "Brazil" "2009Q2" 2.600e+11 197
2 "Brazil" "2009Q3" 2.600e+11 198
2 "Brazil" "2009Q4" 2.700e+11 199
2 "Brazil" "2010Q1" 2.800e+11 200
2 "Brazil" "2010Q2" 2.800e+11 201
2 "Brazil" "2010Q3" 2.800e+11 202
2 "Brazil" "2010Q4" 2.900e+11 203
2 "Brazil" "2011Q1" 2.900e+11 204
2 "Brazil" "2011Q2" 2.900e+11 205
2 "Brazil" "2011Q3" 2.900e+11 206
2 "Brazil" "2011Q4" 3.000e+11 207
2 "Brazil" "2012Q1" 2.900e+11 208
2 "Brazil" "2012Q2" 3.000e+11 209
2 "Brazil" "2012Q3" 3.000e+11 210
end
format %tq date1

* Example generated by -dataex-. For more info, type help dataex
clear
input str14 country str7 months float mpr_per_annm str6 qdate float(date1 cid)
"Argentina" "2005M1"   2.75 "2005q1" 180 1
"Argentina" "2005M2"   2.75 "2005q1" 180 1
"Argentina" "2005M3"   2.75 "2005q1" 180 1
"Argentina" "2005M4"   3.25 "2005q2" 181 1
"Argentina" "2005M5"   3.75 "2005q2" 181 1
"Argentina" "2005M6"   4.25 "2005q2" 181 1
"Argentina" "2005M7"   4.25 "2005q3" 182 1
"Argentina" "2005M8"   4.25 "2005q3" 182 1
"Argentina" "2005M9"   4.25 "2005q3" 182 1
"Argentina" "2005M10"   4.5 "2005q4" 183 1
"Argentina" "2005M11"   4.5 "2005q4" 183 1
"Argentina" "2005M12"     5 "2005q4" 183 1
"Argentina" "2006M1"      5 "2006q1" 184 1
"Argentina" "2006M2"      5 "2006q1" 184 1
"Argentina" "2006M3"      5 "2006q1" 184 1
"Argentina" "2006M4"      5 "2006q2" 185 1
"Argentina" "2006M5"    5.5 "2006q2" 185 1
"Argentina" "2006M6"   5.75 "2006q2" 185 1
"Argentina" "2006M7"   5.75 "2006q3" 186 1
"Argentina" "2006M8"   5.75 "2006q3" 186 1
"Argentina" "2006M9"   5.75 "2006q3" 186 1
"Argentina" "2006M10"     6 "2006q4" 187 1
"Argentina" "2006M11"  6.25 "2006q4" 187 1
"Argentina" "2006M12"  6.25 "2006q4" 187 1
"Argentina" "2007M1"    6.5 "2007q1" 188 1
"Argentina" "2007M2"   6.75 "2007q1" 188 1
"Argentina" "2007M3"   10.4 "2007q1" 188 1
"Argentina" "2007M4"  10.31 "2007q2" 189 1
"Argentina" "2007M5"  10.33 "2007q2" 189 1
"Argentina" "2007M6"  10.25 "2007q2" 189 1
"Argentina" "2007M7"  10.31 "2007q3" 190 1
"Argentina" "2007M8"   10.5 "2007q3" 190 1
"Argentina" "2007M9"  10.37 "2007q3" 190 1
"Argentina" "2007M10"  10.7 "2007q4" 191 1
"Argentina" "2007M11" 10.65 "2007q4" 191 1
"Argentina" "2007M12" 10.75 "2007q4" 191 1
"Argentina" "2008M1"     11 "2008q1" 192 1
"Argentina" "2008M2"   11.3 "2008q1" 192 1
"Argentina" "2008M3"  11.07 "2008q1" 192 1
"Argentina" "2008M4"  11.52 "2008q2" 193 1
"Argentina" "2008M5"   11.8 "2008q2" 193 1
"Argentina" "2008M6"  11.84 "2008q2" 193 1
"Argentina" "2008M7"   12.2 "2008q3" 194 1
"Argentina" "2008M8"   12.2 "2008q3" 194 1
"Argentina" "2008M9"  12.26 "2008q3" 194 1
"Argentina" "2008M10" 12.48 "2008q4" 195 1
"Argentina" "2008M11"  12.5 "2008q4" 195 1
"Argentina" "2008M12" 12.05 "2008q4" 195 1
"Argentina" "2009M1"   12.5 "2009q1" 196 1
"Argentina" "2009M2"   13.4 "2009q1" 196 1
"Argentina" "2009M3"     14 "2009q1" 196 1
"Argentina" "2009M4"  14.35 "2009q2" 197 1
"Argentina" "2009M5"  14.55 "2009q2" 197 1
"Argentina" "2009M6"  16.25 "2009q2" 197 1
"Argentina" "2009M7"  14.59 "2009q3" 198 1
"Argentina" "2009M8"  15.89 "2009q3" 198 1
"Argentina" "2009M9"   9.75 "2009q3" 198 1
"Argentina" "2009M10"   9.5 "2009q4" 199 1
"Argentina" "2009M11"   9.5 "2009q4" 199 1
"Argentina" "2009M12"   9.5 "2009q4" 199 1
"Argentina" "2010M1"    9.5 "2010q1" 200 1
"Argentina" "2010M2"    9.5 "2010q1" 200 1
"Argentina" "2010M3"    9.5 "2010q1" 200 1
"Argentina" "2010M4"    9.5 "2010q2" 201 1
"Argentina" "2010M5"    9.5 "2010q2" 201 1
"Argentina" "2010M6"    9.5 "2010q2" 201 1
"Argentina" "2010M7"    9.5 "2010q3" 202 1
"Argentina" "2010M8"    9.5 "2010q3" 202 1
"Argentina" "2010M9"    9.5 "2010q3" 202 1
"Argentina" "2010M10"   9.5 "2010q4" 203 1
"Argentina" "2010M11"   9.5 "2010q4" 203 1
"Argentina" "2010M12"   9.5 "2010q4" 203 1
"Argentina" "2011M1"    9.5 "2011q1" 204 1
"Argentina" "2011M2"    9.5 "2011q1" 204 1
"Argentina" "2011M3"    9.5 "2011q1" 204 1
"Argentina" "2011M4"    9.5 "2011q2" 205 1
"Argentina" "2011M5"    9.5 "2011q2" 205 1
"Argentina" "2011M6"    9.5 "2011q2" 205 1
"Argentina" "2011M7"    9.5 "2011q3" 206 1
"Argentina" "2011M8"    9.5 "2011q3" 206 1
"Argentina" "2011M9"    9.5 "2011q3" 206 1
"Argentina" "2011M10"   9.5 "2011q4" 207 1
"Argentina" "2011M11"   9.5 "2011q4" 207 1
"Argentina" "2011M12"   9.5 "2011q4" 207 1
"Argentina" "2012M1"    9.5 "2012q1" 208 1
"Argentina" "2012M2"    9.5 "2012q1" 208 1
"Argentina" "2012M3"    9.5 "2012q1" 208 1
"Argentina" "2012M4"    9.5 "2012q2" 209 1
"Argentina" "2012M5"    9.5 "2012q2" 209 1
"Argentina" "2012M6"    9.5 "2012q2" 209 1
"Argentina" "2012M7"    9.5 "2012q3" 210 1
"Argentina" "2012M8"    9.5 "2012q3" 210 1
"Argentina" "2012M9"    9.5 "2012q3" 210 1
"Argentina" "2012M10"   9.5 "2012q4" 211 1
"Argentina" "2012M11"   9.5 "2012q4" 211 1
"Argentina" "2012M12"   9.5 "2012q4" 211 1
"Argentina" "2013M1"    9.5 "2013q1" 212 1
"Argentina" "2013M2"    9.5 "2013q1" 212 1
"Argentina" "2013M3"    9.5 "2013q1" 212 1
end
format %tq date1

I'm still having issues merging them as it shows that cid and date1 does not uniquely identify the variables.

[Clyde Schechter]

I cannot replicate your problem:

. * Example generated by -dataex-. For more info, type help dataex
. clear

. input byte cid str14 country str6 quartely double gdp float date1

          cid         country   quartely         gdp      date1
  1. 1 "Argentina" "2005Q1" 1.300e+11 180
  2. 1 "Argentina" "2005Q2" 1.300e+11 181
  3. 1 "Argentina" "2005Q3" 1.300e+11 182
  4. 1 "Argentina" "2005Q4" 1.400e+11 183
  5. 1 "Argentina" "2006Q1" 1.400e+11 184
  6. 1 "Argentina" "2006Q2" 1.400e+11 185
  7. 1 "Argentina" "2006Q3" 1.400e+11 186
  8. 1 "Argentina" "2006Q4" 1.500e+11 187
  9. 1 "Argentina" "2007Q1" 1.500e+11 188
 10. 1 "Argentina" "2007Q2" 1.500e+11 189
 11. 1 "Argentina" "2007Q3" 1.600e+11 190
 12. 1 "Argentina" "2007Q4" 1.600e+11 191
 13. 1 "Argentina" "2008Q1" 1.600e+11 192
 14. 1 "Argentina" "2008Q2" 1.600e+11 193
 15. 1 "Argentina" "2008Q3" 1.600e+11 194
 16. 1 "Argentina" "2008Q4" 1.600e+11 195
 17. 1 "Argentina" "2009Q1" 1.500e+11 196
 18. 1 "Argentina" "2009Q2" 1.500e+11 197
 19. 1 "Argentina" "2009Q3" 1.500e+11 198
 20. 1 "Argentina" "2009Q4" 1.600e+11 199
 21. 1 "Argentina" "2010Q1" 1.600e+11 200
 22. 1 "Argentina" "2010Q2" 1.700e+11 201
 23. 1 "Argentina" "2010Q3" 1.700e+11 202
 24. 1 "Argentina" "2010Q4" 1.700e+11 203
 25. 1 "Argentina" "2011Q1" 1.800e+11 204
 26. 1 "Argentina" "2011Q2" 1.800e+11 205
 27. 1 "Argentina" "2011Q3" 1.800e+11 206
 28. 1 "Argentina" "2011Q4" 1.800e+11 207
 29. 1 "Argentina" "2012Q1" 1.800e+11 208
 30. 1 "Argentina" "2012Q2" 1.700e+11 209
 31. 1 "Argentina" "2012Q3" 1.800e+11 210
 32. 1 "Argentina" "2012Q4" 1.800e+11 211
 33. 1 "Argentina" "2013Q1" 1.800e+11 212
 34. 1 "Argentina" "2013Q2" 1.800e+11 213
 35. 1 "Argentina" "2013Q3" 1.800e+11 214
 36. 1 "Argentina" "2013Q4" 1.800e+11 215
 37. 1 "Argentina" "2014Q1" 1.800e+11 216
 38. 1 "Argentina" "2014Q2" 1.800e+11 217
 39. 1 "Argentina" "2014Q3" 1.700e+11 218
 40. 1 "Argentina" "2014Q4" 1.800e+11 219
 41. 1 "Argentina" "2015Q1" 1.800e+11 220
 42. 1 "Argentina" "2015Q2" 1.800e+11 221
 43. 1 "Argentina" "2015Q3" 1.800e+11 222
 44. 1 "Argentina" "2015Q4" 1.800e+11 223
 45. 1 "Argentina" "2016Q1" 1.800e+11 224
 46. 1 "Argentina" "2016Q2" 1.800e+11 225
 47. 1 "Argentina" "2016Q3" 1.800e+11 226
 48. 1 "Argentina" "2016Q4" 1.800e+11 227
 49. 1 "Argentina" "2017Q1" 1.800e+11 228
 50. 1 "Argentina" "2017Q2" 1.800e+11 229
 51. 1 "Argentina" "2017Q3" 1.800e+11 230
 52. 1 "Argentina" "2017Q4" 1.800e+11 231
 53. 1 "Argentina" "2018Q1" 1.800e+11 232
 54. 1 "Argentina" "2018Q2" 1.800e+11 233
 55. 1 "Argentina" "2018Q3" 1.800e+11 234
 56. 1 "Argentina" "2018Q4" 1.700e+11 235
 57. 1 "Argentina" "2019Q1" 1.700e+11 236
 58. 1 "Argentina" "2019Q2" 1.700e+11 237
 59. 1 "Argentina" "2019Q3" 1.700e+11 238
 60. 1 "Argentina" "2019Q4" 1.700e+11 239
 61. 1 "Argentina" "2020Q1" 1.600e+11 240
 62. 1 "Argentina" "2020Q2" 1.400e+11 241
 63. 1 "Argentina" "2020Q3" 1.600e+11 242
 64. 1 "Argentina" "2020Q4" 1.600e+11 243
 65. 1 "Argentina" "2021Q1" 1.700e+11 244
 66. 1 "Argentina" "2021Q2" 1.700e+11 245
 67. 1 "Argentina" "2021Q3" 1.700e+11 246
 68. 1 "Argentina" "2021Q4" 1.800e+11 247
 69. 1 "Argentina" "2022Q1" 1.800e+11 248
 70. 2 "Brazil" "2005Q1" 2.200e+11 180
 71. 2 "Brazil" "2005Q2" 2.300e+11 181
 72. 2 "Brazil" "2005Q3" 2.300e+11 182
 73. 2 "Brazil" "2005Q4" 2.300e+11 183
 74. 2 "Brazil" "2006Q1" 2.300e+11 184
 75. 2 "Brazil" "2006Q2" 2.300e+11 185
 76. 2 "Brazil" "2006Q3" 2.400e+11 186
 77. 2 "Brazil" "2006Q4" 2.400e+11 187
 78. 2 "Brazil" "2007Q1" 2.400e+11 188
 79. 2 "Brazil" "2007Q2" 2.500e+11 189
 80. 2 "Brazil" "2007Q3" 2.500e+11 190
 81. 2 "Brazil" "2007Q4" 2.500e+11 191
 82. 2 "Brazil" "2008Q1" 2.600e+11 192
 83. 2 "Brazil" "2008Q2" 2.600e+11 193
 84. 2 "Brazil" "2008Q3" 2.700e+11 194
 85. 2 "Brazil" "2008Q4" 2.600e+11 195
 86. 2 "Brazil" "2009Q1" 2.500e+11 196
 87. 2 "Brazil" "2009Q2" 2.600e+11 197
 88. 2 "Brazil" "2009Q3" 2.600e+11 198
 89. 2 "Brazil" "2009Q4" 2.700e+11 199
 90. 2 "Brazil" "2010Q1" 2.800e+11 200
 91. 2 "Brazil" "2010Q2" 2.800e+11 201
 92. 2 "Brazil" "2010Q3" 2.800e+11 202
 93. 2 "Brazil" "2010Q4" 2.900e+11 203
 94. 2 "Brazil" "2011Q1" 2.900e+11 204
 95. 2 "Brazil" "2011Q2" 2.900e+11 205
 96. 2 "Brazil" "2011Q3" 2.900e+11 206
 97. 2 "Brazil" "2011Q4" 3.000e+11 207
 98. 2 "Brazil" "2012Q1" 2.900e+11 208
 99. 2 "Brazil" "2012Q2" 3.000e+11 209
100. 2 "Brazil" "2012Q3" 3.000e+11 210
101. end

. format %tq date1

. tempfile dataset1

. save `dataset1'
file C:\Users\clyde\AppData\Local\Temp\ST_2398_000001.tmp saved as .dta format

.
.
.
.
. * Example generated by -dataex-. For more info, type help dataex
. clear

. input str14 country str7 months float mpr_per_annm str6 qdate float(date1 cid)

            country     months  mpr_per~m      qdate      date1        cid
  1. "Argentina" "2005M1"   2.75 "2005q1" 180 1
  2. "Argentina" "2005M2"   2.75 "2005q1" 180 1
  3. "Argentina" "2005M3"   2.75 "2005q1" 180 1
  4. "Argentina" "2005M4"   3.25 "2005q2" 181 1
  5. "Argentina" "2005M5"   3.75 "2005q2" 181 1
  6. "Argentina" "2005M6"   4.25 "2005q2" 181 1
  7. "Argentina" "2005M7"   4.25 "2005q3" 182 1
  8. "Argentina" "2005M8"   4.25 "2005q3" 182 1
  9. "Argentina" "2005M9"   4.25 "2005q3" 182 1
 10. "Argentina" "2005M10"   4.5 "2005q4" 183 1
 11. "Argentina" "2005M11"   4.5 "2005q4" 183 1
 12. "Argentina" "2005M12"     5 "2005q4" 183 1
 13. "Argentina" "2006M1"      5 "2006q1" 184 1
 14. "Argentina" "2006M2"      5 "2006q1" 184 1
 15. "Argentina" "2006M3"      5 "2006q1" 184 1
 16. "Argentina" "2006M4"      5 "2006q2" 185 1
 17. "Argentina" "2006M5"    5.5 "2006q2" 185 1
 18. "Argentina" "2006M6"   5.75 "2006q2" 185 1
 19. "Argentina" "2006M7"   5.75 "2006q3" 186 1
 20. "Argentina" "2006M8"   5.75 "2006q3" 186 1
 21. "Argentina" "2006M9"   5.75 "2006q3" 186 1
 22. "Argentina" "2006M10"     6 "2006q4" 187 1
 23. "Argentina" "2006M11"  6.25 "2006q4" 187 1
 24. "Argentina" "2006M12"  6.25 "2006q4" 187 1
 25. "Argentina" "2007M1"    6.5 "2007q1" 188 1
 26. "Argentina" "2007M2"   6.75 "2007q1" 188 1
 27. "Argentina" "2007M3"   10.4 "2007q1" 188 1
 28. "Argentina" "2007M4"  10.31 "2007q2" 189 1
 29. "Argentina" "2007M5"  10.33 "2007q2" 189 1
 30. "Argentina" "2007M6"  10.25 "2007q2" 189 1
 31. "Argentina" "2007M7"  10.31 "2007q3" 190 1
 32. "Argentina" "2007M8"   10.5 "2007q3" 190 1
 33. "Argentina" "2007M9"  10.37 "2007q3" 190 1
 34. "Argentina" "2007M10"  10.7 "2007q4" 191 1
 35. "Argentina" "2007M11" 10.65 "2007q4" 191 1
 36. "Argentina" "2007M12" 10.75 "2007q4" 191 1
 37. "Argentina" "2008M1"     11 "2008q1" 192 1
 38. "Argentina" "2008M2"   11.3 "2008q1" 192 1
 39. "Argentina" "2008M3"  11.07 "2008q1" 192 1
 40. "Argentina" "2008M4"  11.52 "2008q2" 193 1
 41. "Argentina" "2008M5"   11.8 "2008q2" 193 1
 42. "Argentina" "2008M6"  11.84 "2008q2" 193 1
 43. "Argentina" "2008M7"   12.2 "2008q3" 194 1
 44. "Argentina" "2008M8"   12.2 "2008q3" 194 1
 45. "Argentina" "2008M9"  12.26 "2008q3" 194 1
 46. "Argentina" "2008M10" 12.48 "2008q4" 195 1
 47. "Argentina" "2008M11"  12.5 "2008q4" 195 1
 48. "Argentina" "2008M12" 12.05 "2008q4" 195 1
 49. "Argentina" "2009M1"   12.5 "2009q1" 196 1
 50. "Argentina" "2009M2"   13.4 "2009q1" 196 1
 51. "Argentina" "2009M3"     14 "2009q1" 196 1
 52. "Argentina" "2009M4"  14.35 "2009q2" 197 1
 53. "Argentina" "2009M5"  14.55 "2009q2" 197 1
 54. "Argentina" "2009M6"  16.25 "2009q2" 197 1
 55. "Argentina" "2009M7"  14.59 "2009q3" 198 1
 56. "Argentina" "2009M8"  15.89 "2009q3" 198 1
 57. "Argentina" "2009M9"   9.75 "2009q3" 198 1
 58. "Argentina" "2009M10"   9.5 "2009q4" 199 1
 59. "Argentina" "2009M11"   9.5 "2009q4" 199 1
 60. "Argentina" "2009M12"   9.5 "2009q4" 199 1
 61. "Argentina" "2010M1"    9.5 "2010q1" 200 1
 62. "Argentina" "2010M2"    9.5 "2010q1" 200 1
 63. "Argentina" "2010M3"    9.5 "2010q1" 200 1
 64. "Argentina" "2010M4"    9.5 "2010q2" 201 1
 65. "Argentina" "2010M5"    9.5 "2010q2" 201 1
 66. "Argentina" "2010M6"    9.5 "2010q2" 201 1
 67. "Argentina" "2010M7"    9.5 "2010q3" 202 1
 68. "Argentina" "2010M8"    9.5 "2010q3" 202 1
 69. "Argentina" "2010M9"    9.5 "2010q3" 202 1
 70. "Argentina" "2010M10"   9.5 "2010q4" 203 1
 71. "Argentina" "2010M11"   9.5 "2010q4" 203 1
 72. "Argentina" "2010M12"   9.5 "2010q4" 203 1
 73. "Argentina" "2011M1"    9.5 "2011q1" 204 1
 74. "Argentina" "2011M2"    9.5 "2011q1" 204 1
 75. "Argentina" "2011M3"    9.5 "2011q1" 204 1
 76. "Argentina" "2011M4"    9.5 "2011q2" 205 1
 77. "Argentina" "2011M5"    9.5 "2011q2" 205 1
 78. "Argentina" "2011M6"    9.5 "2011q2" 205 1
 79. "Argentina" "2011M7"    9.5 "2011q3" 206 1
 80. "Argentina" "2011M8"    9.5 "2011q3" 206 1
 81. "Argentina" "2011M9"    9.5 "2011q3" 206 1
 82. "Argentina" "2011M10"   9.5 "2011q4" 207 1
 83. "Argentina" "2011M11"   9.5 "2011q4" 207 1
 84. "Argentina" "2011M12"   9.5 "2011q4" 207 1
 85. "Argentina" "2012M1"    9.5 "2012q1" 208 1
 86. "Argentina" "2012M2"    9.5 "2012q1" 208 1
 87. "Argentina" "2012M3"    9.5 "2012q1" 208 1
 88. "Argentina" "2012M4"    9.5 "2012q2" 209 1
 89. "Argentina" "2012M5"    9.5 "2012q2" 209 1
 90. "Argentina" "2012M6"    9.5 "2012q2" 209 1
 91. "Argentina" "2012M7"    9.5 "2012q3" 210 1
 92. "Argentina" "2012M8"    9.5 "2012q3" 210 1
 93. "Argentina" "2012M9"    9.5 "2012q3" 210 1
 94. "Argentina" "2012M10"   9.5 "2012q4" 211 1
 95. "Argentina" "2012M11"   9.5 "2012q4" 211 1
 96. "Argentina" "2012M12"   9.5 "2012q4" 211 1
 97. "Argentina" "2013M1"    9.5 "2013q1" 212 1
 98. "Argentina" "2013M2"    9.5 "2013q1" 212 1
 99. "Argentina" "2013M3"    9.5 "2013q1" 212 1
100. end

. format %tq date1

. tempfile dataset2

. save `dataset2'
file C:\Users\clyde\AppData\Local\Temp\ST_2398_000002.tmp saved as .dta format

.
. use `dataset1', clear

. merge 1:m cid date1 using `dataset2'
(variable cid was byte, now float to accommodate using data's values)

    Result                      Number of obs
    -----------------------------------------
    Not matched                            67
        from master                        67  (_merge==1)
        from using                          0  (_merge==2)

    Matched                                99  (_merge==3)
    -----------------------------------------

The -merge- works just fine.

Please post back with an example that exhibits your problem.

[Hamid muili]

After formating the data, I tried
use ` dataset1' , clear
The error message showed invalid file specification

[Clyde Schechter]

You shouldn't, in your own code, be referring to `datset1' or `dataset2'. Those were intended, in #9, to be placeholders for the actual names of your first and second data sets. When I write code for example data sets that people provide here, if there is more than one data set involved, I save them in temporary files after reading in the -dataex- output. I then refer to those tempfiles in the code. But when you adapt the code, you should replace those with the actual names of your files.

[Hamid muili]

Thanks so much. I have been able to merge the two dataset.

  * Example generated by -dataex-. For more info, type help dataex
  clear
  input float cid str14 country str6 quartely double gdp float(date1 mpr_per_annm) str7 month byte _merge
  1 "Argentina" "2005Q1" 1.300e+11 180 2.75 "2005m1" 3
  1 "Argentina" "2005Q2" 1.300e+11 181 3.25 "2005m4" 3
  1 "Argentina" "2005Q3" 1.300e+11 182 4.25 "2005m7" 3
  1 "Argentina" "2005Q4" 1.400e+11 183 4.5 "2005m10" 3
  1 "Argentina" "2006Q1" 1.400e+11 184 5 "2006m1" 3
  1 "Argentina" "2006Q2" 1.400e+11 185 5 "2006m4" 3
  1 "Argentina" "2006Q3" 1.400e+11 186 5.75 "2006m7" 3
  1 "Argentina" "2006Q4" 1.500e+11 187 6 "2006m10" 3
  1 "Argentina" "2007Q1" 1.500e+11 188 6.5 "2007m1" 3
  1 "Argentina" "2007Q2" 1.500e+11 189 10.31 "2007m4" 3
  1 "Argentina" "2007Q3" 1.600e+11 190 10.31 "2007m7" 3
  1 "Argentina" "2007Q4" 1.600e+11 191 10.7 "2007m10" 3
  1 "Argentina" "2008Q1" 1.600e+11 192 11 "2008m1" 3
  1 "Argentina" "2008Q2" 1.600e+11 193 11.52 "2008m4" 3
  1 "Argentina" "2008Q3" 1.600e+11 194 12.2 "2008m7" 3
  1 "Argentina" "2008Q4" 1.600e+11 195 12.48 "2008m10" 3
  1 "Argentina" "2009Q1" 1.500e+11 196 12.5 "2009m1" 3
  1 "Argentina" "2009Q2" 1.500e+11 197 14.35 "2009m4" 3
  1 "Argentina" "2009Q3" 1.500e+11 198 14.59 "2009m7" 3
  1 "Argentina" "2009Q4" 1.600e+11 199 9.5 "2009m10" 3
  1 "Argentina" "2010Q1" 1.600e+11 200 9.5 "2010m1" 3
  1 "Argentina" "2010Q2" 1.700e+11 201 9.5 "2010m4" 3
  1 "Argentina" "2010Q3" 1.700e+11 202 9.5 "2010m7" 3
  1 "Argentina" "2010Q4" 1.700e+11 203 9.5 "2010m10" 3
  1 "Argentina" "2011Q1" 1.800e+11 204 9.5 "2011m1" 3
  1 "Argentina" "2011Q2" 1.800e+11 205 9.5 "2011m4" 3
  1 "Argentina" "2011Q3" 1.800e+11 206 9.5 "2011m7" 3
  1 "Argentina" "2011Q4" 1.800e+11 207 9.5 "2011m10" 3
  1 "Argentina" "2012Q1" 1.800e+11 208 9.5 "2012m1" 3
  1 "Argentina" "2012Q2" 1.700e+11 209 9.5 "2012m4" 3
  1 "Argentina" "2012Q3" 1.800e+11 210 9.5 "2012m7" 3
  1 "Argentina" "2012Q4" 1.800e+11 211 9.5 "2012m10" 3
  1 "Argentina" "2013Q1" 1.800e+11 212 9.5 "2013m1" 3
  1 "Argentina" "2013Q2" 1.800e+11 213 9.5 "2013m4" 3
  1 "Argentina" "2013Q3" 1.800e+11 214 9.5 "2013m7" 3
  1 "Argentina" "2013Q4" 1.800e+11 215 9.5 "2013m10" 3
  1 "Argentina" "2014Q1" 1.800e+11 216 25.5201 "2014m1" 3
  1 "Argentina" "2014Q2" 1.800e+11 217 27.7999 "2014m4" 3
  1 "Argentina" "2014Q3" 1.700e+11 218 26.7801 "2014m7" 3
  1 "Argentina" "2014Q4" 1.800e+11 219 26.8599 "2014m10" 3
  1 "Argentina" "2015Q1" 1.800e+11 220 26.56 "2015m1" 3
  1 "Argentina" "2015Q2" 1.800e+11 221 25.9701 "2015m4" 3
  1 "Argentina" "2015Q3" 1.800e+11 222 25.9237 "2015m7" 3
  1 "Argentina" "2015Q4" 1.800e+11 223 28.9307 "2015m10" 3
  1 "Argentina" "2016Q1" 1.800e+11 224 30.7503 "2016m1" 3
  1 "Argentina" "2016Q2" 1.800e+11 225 37.9997 "2016m4" 3
  1 "Argentina" "2016Q3" 1.800e+11 226 30.2498 "2016m7" 3
  1 "Argentina" "2016Q4" 1.800e+11 227 26.7498 "2016m10" 3
  1 "Argentina" "2017Q1" 1.800e+11 228 24.75 "2017m1" 3
  1 "Argentina" "2017Q2" 1.800e+11 229 26.25 "2017m4" 3
  1 "Argentina" "2017Q3" 1.800e+11 230 26.25 "2017m7" 3
  1 "Argentina" "2017Q4" 1.800e+11 231 27.75 "2017m10" 3
  1 "Argentina" "2018Q1" 1.800e+11 232 27.25 "2018m1" 3
  1 "Argentina" "2018Q2" 1.800e+11 233 30.25 "2018m4" 3
  1 "Argentina" "2018Q3" 1.800e+11 234 40 "2018m7" 3
  1 "Argentina" "2018Q4" 1.700e+11 235 68.048 "2018m10" 3
  1 "Argentina" "2019Q1" 1.700e+11 236 53.687 "2019m1" 3
  1 "Argentina" "2019Q2" 1.700e+11 237 73.93 "2019m4" 3
  1 "Argentina" "2019Q3" 1.700e+11 238 60.396 "2019m7" 3
  1 "Argentina" "2019Q4" 1.700e+11 239 68.002 "2019m10" 3
  1 "Argentina" "2020Q1" 1.600e+11 240 50 "2020m1" 3
  1 "Argentina" "2020Q2" 1.400e+11 241 38 "2020m4" 3
  1 "Argentina" "2020Q3" 1.600e+11 242 38 "2020m7" 3
  1 "Argentina" "2020Q4" 1.600e+11 243 36 "2020m10" 3
  1 "Argentina" "2021Q1" 1.700e+11 244 38 "2021m1" 3
  1 "Argentina" "2021Q2" 1.700e+11 245 38 "2021m4" 3
  1 "Argentina" "2021Q3" 1.700e+11 246 38 "2021m7" 3
  1 "Argentina" "2021Q4" 1.800e+11 247 38 "2021m10" 3
  1 "Argentina" "2022Q1" 1.800e+11 248 40 "2022m1" 3
  2 "Brazil" "2005Q1" 2.200e+11 180 18.25 "2005m1" 3
  2 "Brazil" "2005Q2" 2.300e+11 181 19.5 "2005m4" 3
  2 "Brazil" "2005Q3" 2.300e+11 182 19.75 "2005m7" 3
  2 "Brazil" "2005Q4" 2.300e+11 183 19 "2005m10" 3
  2 "Brazil" "2006Q1" 2.300e+11 184 17.25 "2006m1" 3
  2 "Brazil" "2006Q2" 2.300e+11 185 15.75 "2006m4" 3
  2 "Brazil" "2006Q3" 2.400e+11 186 14.75 "2006m7" 3
  2 "Brazil" "2006Q4" 2.400e+11 187 13.75 "2006m10" 3
  2 "Brazil" "2007Q1" 2.400e+11 188 13 "2007m1" 3
  2 "Brazil" "2007Q2" 2.500e+11 189 12.5 "2007m4" 3
  2 "Brazil" "2007Q3" 2.500e+11 190 11.5 "2007m7" 3
  2 "Brazil" "2007Q4" 2.500e+11 191 11.25 "2007m10" 3
  2 "Brazil" "2008Q1" 2.600e+11 192 11.25 "2008m1" 3
  2 "Brazil" "2008Q2" 2.600e+11 193 11.75 "2008m4" 3
  2 "Brazil" "2008Q3" 2.700e+11 194 13 "2008m7" 3
  2 "Brazil" "2008Q4" 2.600e+11 195 13.75 "2008m10" 3
  2 "Brazil" "2009Q1" 2.500e+11 196 12.75 "2009m1" 3
  2 "Brazil" "2009Q2" 2.600e+11 197 10.25 "2009m4" 3
  2 "Brazil" "2009Q3" 2.600e+11 198 8.75 "2009m7" 3
  2 "Brazil" "2009Q4" 2.700e+11 199 8.75 "2009m10" 3
  2 "Brazil" "2010Q1" 2.800e+11 200 8.75 "2010m1" 3
  2 "Brazil" "2010Q2" 2.800e+11 201 9.5 "2010m4" 3
  2 "Brazil" "2010Q3" 2.800e+11 202 10.75 "2010m7" 3
  2 "Brazil" "2010Q4" 2.900e+11 203 10.75 "2010m10" 3
  2 "Brazil" "2011Q1" 2.900e+11 204 11.25 "2011m1" 3
  2 "Brazil" "2011Q2" 2.900e+11 205 12 "2011m4" 3
  2 "Brazil" "2011Q3" 2.900e+11 206 12.5 "2011m7" 3
  2 "Brazil" "2011Q4" 3.000e+11 207 11.5 "2011m10" 3
  2 "Brazil" "2012Q1" 2.900e+11 208 10.5 "2012m1" 3
  2 "Brazil" "2012Q2" 3.000e+11 209 9 "2012m4" 3
  2 "Brazil" "2012Q3" 3.000e+11 210 8 "2012m7" 3
  end
  format %tq date1
  label values _merge _merge
  label def _merge 3 "Matched (3)", modify

However, one last thing to do is to create a gap between the months which will represent the missing months (i.e feb, april such as the months date in the previous data . Just like how the tsfill command does in stata to fill in the missing period.

[Clyde Schechter]

-tsfill- is, indeed, the solution. You just need to get rid of the string date variables and create Stata internal format date variables before you can use it.

 //    CREATE STATA DATE VARIABLES
 gen qdate = quarterly(quartely, "YQ"), after(quartely)
 assert missing(qdate) == missing(quartely)
 format qdate %tq
 drop quartely
 
 gen mdate = monthly(month, "YM"), after(month)
 assert missing(mdate) == missing(month)
 format mdate %tm
 drop month
 
 xtset cid mdate
 tsfill

[Hamid muili]

Thanks it worked much appreciated. Although it filled it with previous values. How do I fill these missing with just empty values (.) Instead of repeating the previous values

[Clyde Schechter]

I cannot reproduce the problem you are having. When I run the code with your example data, the filled-in values have missing values for everything except cid and mdate.

.   * Example generated by -dataex-. For more info, type help dataex
.   clear

.   input float cid str14 country str6 quartely double gdp float(date1 mpr_per_annm) str7 month byte _merge

           cid         country   quartely         gdp      date1  mpr_per~m      month    _merge
  1.   1 "Argentina" "2005Q1" 1.300e+11 180 2.75 "2005m1" 3
  2.   1 "Argentina" "2005Q2" 1.300e+11 181 3.25 "2005m4" 3
  3.   1 "Argentina" "2005Q3" 1.300e+11 182 4.25 "2005m7" 3
  4.   1 "Argentina" "2005Q4" 1.400e+11 183 4.5 "2005m10" 3
  5.   1 "Argentina" "2006Q1" 1.400e+11 184 5 "2006m1" 3
  6.   1 "Argentina" "2006Q2" 1.400e+11 185 5 "2006m4" 3
  7.   1 "Argentina" "2006Q3" 1.400e+11 186 5.75 "2006m7" 3
  8.   1 "Argentina" "2006Q4" 1.500e+11 187 6 "2006m10" 3
  9.   1 "Argentina" "2007Q1" 1.500e+11 188 6.5 "2007m1" 3
 10.   1 "Argentina" "2007Q2" 1.500e+11 189 10.31 "2007m4" 3
 11.   1 "Argentina" "2007Q3" 1.600e+11 190 10.31 "2007m7" 3
 12.   1 "Argentina" "2007Q4" 1.600e+11 191 10.7 "2007m10" 3
 13.   1 "Argentina" "2008Q1" 1.600e+11 192 11 "2008m1" 3
 14.   1 "Argentina" "2008Q2" 1.600e+11 193 11.52 "2008m4" 3
 15.   1 "Argentina" "2008Q3" 1.600e+11 194 12.2 "2008m7" 3
 16.   1 "Argentina" "2008Q4" 1.600e+11 195 12.48 "2008m10" 3
 17.   1 "Argentina" "2009Q1" 1.500e+11 196 12.5 "2009m1" 3
 18.   1 "Argentina" "2009Q2" 1.500e+11 197 14.35 "2009m4" 3
 19.   1 "Argentina" "2009Q3" 1.500e+11 198 14.59 "2009m7" 3
 20.   1 "Argentina" "2009Q4" 1.600e+11 199 9.5 "2009m10" 3
 21.   1 "Argentina" "2010Q1" 1.600e+11 200 9.5 "2010m1" 3
 22.   1 "Argentina" "2010Q2" 1.700e+11 201 9.5 "2010m4" 3
 23.   1 "Argentina" "2010Q3" 1.700e+11 202 9.5 "2010m7" 3
 24.   1 "Argentina" "2010Q4" 1.700e+11 203 9.5 "2010m10" 3
 25.   1 "Argentina" "2011Q1" 1.800e+11 204 9.5 "2011m1" 3
 26.   1 "Argentina" "2011Q2" 1.800e+11 205 9.5 "2011m4" 3
 27.   1 "Argentina" "2011Q3" 1.800e+11 206 9.5 "2011m7" 3
 28.   1 "Argentina" "2011Q4" 1.800e+11 207 9.5 "2011m10" 3
 29.   1 "Argentina" "2012Q1" 1.800e+11 208 9.5 "2012m1" 3
 30.   1 "Argentina" "2012Q2" 1.700e+11 209 9.5 "2012m4" 3
 31.   1 "Argentina" "2012Q3" 1.800e+11 210 9.5 "2012m7" 3
 32.   1 "Argentina" "2012Q4" 1.800e+11 211 9.5 "2012m10" 3
 33.   1 "Argentina" "2013Q1" 1.800e+11 212 9.5 "2013m1" 3
 34.   1 "Argentina" "2013Q2" 1.800e+11 213 9.5 "2013m4" 3
 35.   1 "Argentina" "2013Q3" 1.800e+11 214 9.5 "2013m7" 3
 36.   1 "Argentina" "2013Q4" 1.800e+11 215 9.5 "2013m10" 3
 37.   1 "Argentina" "2014Q1" 1.800e+11 216 25.5201 "2014m1" 3
 38.   1 "Argentina" "2014Q2" 1.800e+11 217 27.7999 "2014m4" 3
 39.   1 "Argentina" "2014Q3" 1.700e+11 218 26.7801 "2014m7" 3
 40.   1 "Argentina" "2014Q4" 1.800e+11 219 26.8599 "2014m10" 3
 41.   1 "Argentina" "2015Q1" 1.800e+11 220 26.56 "2015m1" 3
 42.   1 "Argentina" "2015Q2" 1.800e+11 221 25.9701 "2015m4" 3
 43.   1 "Argentina" "2015Q3" 1.800e+11 222 25.9237 "2015m7" 3
 44.   1 "Argentina" "2015Q4" 1.800e+11 223 28.9307 "2015m10" 3
 45.   1 "Argentina" "2016Q1" 1.800e+11 224 30.7503 "2016m1" 3
 46.   1 "Argentina" "2016Q2" 1.800e+11 225 37.9997 "2016m4" 3
 47.   1 "Argentina" "2016Q3" 1.800e+11 226 30.2498 "2016m7" 3
 48.   1 "Argentina" "2016Q4" 1.800e+11 227 26.7498 "2016m10" 3
 49.   1 "Argentina" "2017Q1" 1.800e+11 228 24.75 "2017m1" 3
 50.   1 "Argentina" "2017Q2" 1.800e+11 229 26.25 "2017m4" 3
 51.   1 "Argentina" "2017Q3" 1.800e+11 230 26.25 "2017m7" 3
 52.   1 "Argentina" "2017Q4" 1.800e+11 231 27.75 "2017m10" 3
 53.   1 "Argentina" "2018Q1" 1.800e+11 232 27.25 "2018m1" 3
 54.   1 "Argentina" "2018Q2" 1.800e+11 233 30.25 "2018m4" 3
 55.   1 "Argentina" "2018Q3" 1.800e+11 234 40 "2018m7" 3
 56.   1 "Argentina" "2018Q4" 1.700e+11 235 68.048 "2018m10" 3
 57.   1 "Argentina" "2019Q1" 1.700e+11 236 53.687 "2019m1" 3
 58.   1 "Argentina" "2019Q2" 1.700e+11 237 73.93 "2019m4" 3
 59.   1 "Argentina" "2019Q3" 1.700e+11 238 60.396 "2019m7" 3
 60.   1 "Argentina" "2019Q4" 1.700e+11 239 68.002 "2019m10" 3
 61.   1 "Argentina" "2020Q1" 1.600e+11 240 50 "2020m1" 3
 62.   1 "Argentina" "2020Q2" 1.400e+11 241 38 "2020m4" 3
 63.   1 "Argentina" "2020Q3" 1.600e+11 242 38 "2020m7" 3
 64.   1 "Argentina" "2020Q4" 1.600e+11 243 36 "2020m10" 3
 65.   1 "Argentina" "2021Q1" 1.700e+11 244 38 "2021m1" 3
 66.   1 "Argentina" "2021Q2" 1.700e+11 245 38 "2021m4" 3
 67.   1 "Argentina" "2021Q3" 1.700e+11 246 38 "2021m7" 3
 68.   1 "Argentina" "2021Q4" 1.800e+11 247 38 "2021m10" 3
 69.   1 "Argentina" "2022Q1" 1.800e+11 248 40 "2022m1" 3
 70.   2 "Brazil" "2005Q1" 2.200e+11 180 18.25 "2005m1" 3
 71.   2 "Brazil" "2005Q2" 2.300e+11 181 19.5 "2005m4" 3
 72.   2 "Brazil" "2005Q3" 2.300e+11 182 19.75 "2005m7" 3
 73.   2 "Brazil" "2005Q4" 2.300e+11 183 19 "2005m10" 3
 74.   2 "Brazil" "2006Q1" 2.300e+11 184 17.25 "2006m1" 3
 75.   2 "Brazil" "2006Q2" 2.300e+11 185 15.75 "2006m4" 3
 76.   2 "Brazil" "2006Q3" 2.400e+11 186 14.75 "2006m7" 3
 77.   2 "Brazil" "2006Q4" 2.400e+11 187 13.75 "2006m10" 3
 78.   2 "Brazil" "2007Q1" 2.400e+11 188 13 "2007m1" 3
 79.   2 "Brazil" "2007Q2" 2.500e+11 189 12.5 "2007m4" 3
 80.   2 "Brazil" "2007Q3" 2.500e+11 190 11.5 "2007m7" 3
 81.   2 "Brazil" "2007Q4" 2.500e+11 191 11.25 "2007m10" 3
 82.   2 "Brazil" "2008Q1" 2.600e+11 192 11.25 "2008m1" 3
 83.   2 "Brazil" "2008Q2" 2.600e+11 193 11.75 "2008m4" 3
 84.   2 "Brazil" "2008Q3" 2.700e+11 194 13 "2008m7" 3
 85.   2 "Brazil" "2008Q4" 2.600e+11 195 13.75 "2008m10" 3
 86.   2 "Brazil" "2009Q1" 2.500e+11 196 12.75 "2009m1" 3
 87.   2 "Brazil" "2009Q2" 2.600e+11 197 10.25 "2009m4" 3
 88.   2 "Brazil" "2009Q3" 2.600e+11 198 8.75 "2009m7" 3
 89.   2 "Brazil" "2009Q4" 2.700e+11 199 8.75 "2009m10" 3
 90.   2 "Brazil" "2010Q1" 2.800e+11 200 8.75 "2010m1" 3
 91.   2 "Brazil" "2010Q2" 2.800e+11 201 9.5 "2010m4" 3
 92.   2 "Brazil" "2010Q3" 2.800e+11 202 10.75 "2010m7" 3
 93.   2 "Brazil" "2010Q4" 2.900e+11 203 10.75 "2010m10" 3
 94.   2 "Brazil" "2011Q1" 2.900e+11 204 11.25 "2011m1" 3
 95.   2 "Brazil" "2011Q2" 2.900e+11 205 12 "2011m4" 3
 96.   2 "Brazil" "2011Q3" 2.900e+11 206 12.5 "2011m7" 3
 97.   2 "Brazil" "2011Q4" 3.000e+11 207 11.5 "2011m10" 3
 98.   2 "Brazil" "2012Q1" 2.900e+11 208 10.5 "2012m1" 3
 99.   2 "Brazil" "2012Q2" 3.000e+11 209 9 "2012m4" 3
100.   2 "Brazil" "2012Q3" 3.000e+11 210 8 "2012m7" 3
101.   end

.   format %tq date1

.   label values _merge _merge

.   label def _merge 3 "Matched (3)", modify

.
.  //    CREATE STATA DATE VARIABLES
.  gen qdate = quarterly(quartely, "YQ"), after(quartely)

.  assert missing(qdate) == missing(quartely)

.  format qdate %tq

.  drop quartely

.  
.  gen mdate = monthly(month, "YM"), after(month)

.  assert missing(mdate) == missing(month)

.  format mdate %tm

.  drop month

.  
.  xtset cid mdate

Panel variable: cid (unbalanced)
 Time variable: mdate, 2005m1 to 2022m1, but with gaps
         Delta: 1 month

.  tsfill

.  
.  list in 1/6, noobs clean

    cid     country    qdate         gdp    date1   mpr_pe~m    mdate        _merge  
      1   Argentina   2005q1   1.300e+11   2005q1       2.75   2005m1   Matched (3)  
      1                    .           .        .          .   2005m2             .  
      1                    .           .        .          .   2005m3             .  
      1   Argentina   2005q2   1.300e+11   2005q2       3.25   2005m4   Matched (3)  
      1                    .           .        .          .   2005m5             .  
      1                    .           .        .          .   2005m6             .

Please post an example that exhibits the problem you are having.