Summing A Financial Data Variable Using Multiple Group Categorisation Variables

[Austin Maloney]

Hi all,

My apologies if this is a very basic question, but I'm been digging around for ages and am still unable to solve it, so thought I'd ask.

I have a dataset of payment data, where I want to merge the sum of payments based on the category of payment and the region the payment was sent to. So I effectively have three variables in play.

1) The amount of the Payment (€)
2) Type of Payment (Categories)
3) Region sent to (Name of Region). (All have been recoded to be numerical)

There are multiple entries for all kinds of payments and regions, and I want to edit to so that I sum all the payments by region and category. So the total of Payment Category Y to Region X, the total of Payment Category Z to Region X, the total of Payment Category Y to Region T etc.

Again, this might be very basic and I might be missing something obvious, but I have looked for ages and been unable to find an answer.

Thanks!

[Clyde Schechter]

As you don't show example data, I am guessing at the names of your variables. But the changes to this code you will need to make should be obvious:

collapse (sum) payment, by(region category)

[Carlo Lazzaro]

Austin:
welcome to this forum.
Do you mean something along the following lines?

. use "https://www.stata-press.com/data/r17/nlswork.dta"
(National Longitudinal Survey of Young Women, 14-24 years old in 1968)

. bysort idcode grade c_city: egen wanted=total(ln_wage)

. list idcode grade c_city ln_wage if idcode<=2

       +------------------------------------+
       | idcode   grade   c_city    ln_wage |
       |------------------------------------|
    1. |      1      12        0   2.462927 |
    2. |      1      12        0   2.536374 |
    3. |      1      12        1   1.777012 |
    4. |      1      12        1   2.551715 |
    5. |      1      12        1   1.778681 |
       |------------------------------------|
    6. |      1      12        1    1.02862 |
    7. |      1      12        1   1.451214 |
    8. |      1      12        1   1.780273 |
    9. |      1      12        1   2.420261 |
   10. |      1      12        1   2.493976 |
       |------------------------------------|
   11. |      1      12        1   2.614172 |
   12. |      1      12        1   1.589977 |
   13. |      2      12        1   1.863417 |
   14. |      2      12        1   1.206198 |
   15. |      2      12        1   1.789367 |
       |------------------------------------|
   16. |      2      12        1   1.726721 |
   17. |      2      12        1   1.726964 |
   18. |      2      12        1   1.832581 |
   19. |      2      12        1    1.84653 |
   20. |      2      12        1    1.68991 |
       |------------------------------------|
   21. |      2      12        1   1.808289 |
   22. |      2      12        1   1.856449 |
   23. |      2      12        1   1.360348 |
   24. |      2      12        1   1.549883 |
       +------------------------------------+

.

[Austin Maloney]

Hi again! This

collapse (sum) payment, by(region category)

solved it. Thank you both for the response and the help, and for the welcome to the forum! Best, Austin