csdid gvar error (unresolved)

[Aditi RSM]

Hello all,

Please note that I have seen the thread on subject 'csdid gvar error' however, the solutions did not address my error the same way. I continue to run into the issue.



An extract of data is pasted below and also attached a snapshot.

import excel "$path\Data Structure.xlsx", sheet("EG Model Data") firstrow clear

rename *, lower


*Setting up event dates

bysort i: gen datenum=_n

bysort i: gen target=datenum if month==eventdate //date of joining programme
egen td = min(target), by(i)

gen dif = datenum-td // difference between any date and joining date

gen TE = td if dif>=0
replace TE = 0 if dif<0
replace TE=0 if dif==.

sort td TE dif


xtset i datenum

csdid yoy, ivar(i) time(month) gvar(TE)

Receive the following error Gvar max value is 18628 and there are no periods available before that treatment
Verify that Gvar is correctly defined
request may not be combined with by
r(190);


I get the error no matter the sample i try. Please advise how to solve the problem.
My sample is made of 7 units. 6 of them receive treatment at different dates and one is a never-treated unit.
We have data on all units until December 2023. However, the starting date of data for each unit differs due to availability.
The treatment dates are:

Oct-17

Mar-18

Aug-18

Dec-22

Jan-23

Oct-23

Hope I have laid out the problem well. Thanks in advance!

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(i treated) int month double(grosslending yoy) int eventdate float(datenum target td dif TE)
3 1 19510            5972000   1.1783695057450303 21093  30 . 82 -52  0
3 1 19936            9865000    4.575021192427239 21093  44 . 82 -38  0
3 1 20940           24195000   -.4591724970382457 21093  77 . 82  -5  0
3 1 19540           30772500    2.638271458973753 21093  31 . 82 -51  0
3 1 18779            5717000    4.378174976481656 21093   6 . 82 -76  0
3 1 19206            1843000   -.5677767354596623 21093  20 . 82 -62  0
3 1 18628            4953500    .3763545429285913 21093   1 . 82 -81  0
3 1 18659            4305000   -.3468365953573054 21093   2 . 82 -80  0
3 1 18687            1360000   -.6747967479674797 21093   3 . 82 -79  0
3 1 19237             765000   -.8238950276243093 21093  21 . 82 -61  0
3 1 19084           12128198   3.7363747485989887 21093  16 . 82 -66  0
3 1 19390            4446000    .3976736875196478 21093  26 . 82 -56  0
3 1 20789           45398000    .5539277768269724 21093  72 . 82 -10  0
3 1 19632           11869500   .14173720661792988 21093  34 . 82 -48  0
3 1 19449           20366000    .6792272025901951 21093  28 . 82 -54  0
3 1 19053            4290000   2.1544117647058822 21093  15 . 82 -67  0
3 1 21001           33286615   .22399018084871303 21093  79 . 82  -3  0
3 1 19783            7276000   -.6623274161735699 21093  39 . 82 -43  0
3 1 20910           27728689    2.038760438356164 21093  76 . 82  -6  0
3 1 21063            4293000   -.5722399362295736 21093  81 . 82  -1  0
3 1 19844           10077000   1.5530782873068154 21093  41 . 82 -41  0
3 1 18840            4264000                    . 21093   8 . 82 -74  0
3 1 19967           19809000    .6072210953346855 21093  45 . 82 -37  0
3 1 20089            7738500   -.3990448085734255 21093  49 . 82 -33  0
3 1 20240           17797500    3.935524126455907 21093  54 . 82 -28  0
3 1 20301           14451000    .4648758236188546 21093  56 . 82 -26  0
3 1 20393           24755000   .28344048112816256 21093  59 . 82 -23  0
3 1 20454           11491000   .48491309685339545 21093  61 . 82 -21  0
3 1 18901            3087000   1.3528963414634148 21093  10 . 82 -72  0
3 1 20636        27195165.06   -.2224087580346319 21093  67 . 82 -15  0
3 1 20698           10036000   -.5894461142911492 21093  69 . 82 -13  0
3 1 20423           29215000   1.4893490115882755 21093  60 . 82 -22  0
3 1 20362           25114000    .8777524393435268 21093  58 . 82 -24  0
3 1 20759           44450500    .7956170470611998 21093  71 . 82 -11  0
3 1 20820           12256800   .06664346009920807 21093  73 . 82  -9  0
3 1 20606           47726000   1.6816125860373647 21093  66 . 82 -16  0
3 1 18748            5865650    .9917317487266553 21093   5 . 82 -77  0
3 1 19114            7425000    .2658443650746294 21093  17 . 82 -65  0
3 1 19267           10396000   2.3676708778749593 21093  22 . 82 -60  0
3 1 18932            5395500    .4330677290836653 21093  11 . 82 -71  0
3 1 20485           18503000     2.74782256431031 21093  62 . 82 -20  0
3 1 20270           34973600   .40659588159588167 21093  55 . 82 -27  0
3 1 20332           24445025   .23403629663284375 21093  57 . 82 -25  0
3 1 20148           13796000    .8960967564595932 21093  51 . 82 -31  0
3 1 18718            2560650    .9431986340352874 21093   4 . 82 -78  0
3 1 19997           13374500   .12679556847381934 21093  46 . 82 -36  0
3 1 20575           44737000   1.4537531942341162 21093  65 . 82 -17  0
3 1 19693        15348180.76    .6081497024308467 21093  36 . 82 -46  0
3 1 19905           24864000   -.1920058493785035 21093  43 . 82 -39  0
3 1 19755           10735000   1.4145299145299144 21093  38 . 82 -44  0
3 1 20728           25495000  .015170821055984662 21093  70 . 82 -12  0
3 1 20879           11534500   .15634085213032578 21093  75 . 82  -7  0
3 1 19875            3606000  -.39618218352310786 21093  42 . 82 -40  0
3 1 20851           25311138    .3679477922499055 21093  74 . 82  -8  0
3 1 19602           12325000    15.11111111111111 21093  33 . 82 -49  0
3 1 20514            9975000   -.2769643374891273 21093  63 . 82 -19  0
3 1 18993             480000   -.9030988190168567 21093  13 . 82 -69  0
3 1 19175            8458000   .11124249471181002 21093  19 . 82 -63  0
3 1 20545            9125000    -.547072225227953 21093  64 . 82 -18  0
3 1 18962            6601490    .3371460401053272 21093  12 . 82 -70  0
3 1 20058           11736000  -.23534911508300482 21093  48 . 82 -34  0
3 1 19328            9544000    .4457342206077719 21093  24 . 82 -58  0
3 1 19145            2741500   -.5204652789924786 21093  18 . 82 -64  0
3 1 19359            7798000   15.245833333333334 21093  25 . 82 -57  0
3 1 19418           21547500   4.0227272727272725 21093  27 . 82 -55  0
3 1 19663           10180000    .7348329925017041 21093  35 . 82 -47  0
3 1 20971           36199000  -.24152453589238565 21093  78 . 82  -4  0
3 1 21032           31851500   1.4030327854322517 21093  80 . 82  -2  0
3 1 19814           14946000  -.26612982421683196 21093  40 . 82 -42  0
3 1 20179           20146700    .3479660109728355 21093  52 . 82 -30  0
3 1 19724           12877000    .6513208515003848 21093  37 . 82 -45  0
3 1 19024            3181000  -.26109175377468063 21093  14 . 82 -68  0
3 1 20209           18232070    .8092755780490226 21093  53 . 82 -29  0
3 1 18871            4344000   1.0423131170662905 21093   9 . 82 -73  0
3 1 18809            7611300    3.614307365868445 21093   7 . 82 -75  0
3 1 19571            1769500 -.039880629408572954 21093  32 . 82 -50  0
3 1 20120            4937000   -.5401024685607825 21093  50 . 82 -32  0
3 1 20667 13254708.879999999   -.0827825839042281 21093  68 . 82 -14  0
3 1 19479            3947000   -.4684175084175084 21093  29 . 82 -53  0
3 1 19298            5868000   .08757297748123438 21093  23 . 82 -59  0
3 1 20028           19288000    .8946954813359529 21093  47 . 82 -35  0
3 1 21275           20589000  -.25748382839159834 21093  88 . 82   6 82
3 1 22980           36827870    -.500089589995458 21093 144 . 82  62 82
3 1 23315           15772260    -.574800640538311 21093 155 . 82  73 82
3 1 23011           19585700   -.4595070593554563 21093 145 . 82  63 82
3 1 22493           89526600   1.2005358371841508 21093 128 . 82  46 82
3 1 21458           32871403   -.1553795555075922 21093  94 . 82  12 82
3 1 22615           73668940     .368085241238014 21093 132 . 82  50 82
3 1 22677           38791100   -.4781442685291468 21093 134 . 82  52 82
3 1 21366           19577280  -.41185728858281323 21093  91 . 82   9 82
3 1 21216           17755000  -.29853015696093954 21093  86 . 82   4 82
3 1 21244           23964630   1.0776479257878537 21093  87 . 82   5 82
3 1 21428           15776920    2.675033775914279 21093  93 . 82  11 82
3 1 22646           36236736   1.9189453313007352 21093 133 . 82  51 82
3 1 21305        44198145.38    .8267470708824138 21093  89 . 82   7 82
3 1 22462           73408000   1.2587666287415744 21093 127 . 82  45 82
3 1 21731           29469100    .5052703950702038 21093 103 . 82  21 82
3 1 21609           35232560   .47019002588397996 21093  99 . 82  17 82
3 1 23042           33634510  -.13293229632570358 21093 146 . 82  64 82
3 1 22889           92772985    .4175297360345689 21093 141 . 82  59 82
end
format %td month
format %tdMon-YY eventdate

[FernandoRios]

Your data is not correctly setup.
First thing first, transform all your "time" variables into month_base dates. See help ym().
Then try your code again

[Aditi RSM]

Update: I fixed the issue (it was due to the mismatch between date variables format). Run into the issue of two many rows and columns against my Stata B/E limits.

For your reference, there 156 time periods per 7 unit. For some units, many cells in the outcome variable are empty in the pre-treatment window.
Please advise a workaround this issue so I can estimate the csdid.

[Aditi RSM]

Thanks FernandoRios i spotted that and seem to have fixed it. Please see update above. Any way to work past the attached issue.

[Aditi RSM]

Is there a way i can constrain the number of parameters pre-estimation.

[FernandoRios]

The matrix and variable limitations are particular to Stata flavor
your best next option is using alternative methods like jwdid