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Available for an HonestDiD package for Sun&Abraham in Stata 18? #27

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YL-CAMS opened this issue Dec 3, 2024 · 1 comment
Open

Available for an HonestDiD package for Sun&Abraham in Stata 18? #27

YL-CAMS opened this issue Dec 3, 2024 · 1 comment

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@YL-CAMS
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YL-CAMS commented Dec 3, 2024

Hi, I met some difficuties when applying honestdid in Sun and Abraham estimation. I could not generate a sensitivity coefplot. Here is the working example for your reference.

Sun and Abraham using command eventstudyinteract

 forvalues l = 0/4 {
     gen L`l'event = K==`l'
 }
 forvalues l = 1/5 {
     gen F`l'event = K==-`l'
 }
 drop F1event

eventstudyinteract ln_sum L*event F*event lnGDP lnpop lnstudent, vce(cluster province) absorb(province year) cohort(treat_year) control_cohort(lastcohort)    
event_plot e(b_iw)#e(V_iw), default_look graph_opt(xtitle("Periods since the event") ///
ytitle("Average causal effect") xlabel(-5(1)4) title("Sun and Abraham (2020)")  ///
name(SA, replace)) stub_lag(L#event) stub_lead(F#event) together 
matrix sat_b = e(b_iw) // storing the estimates for later
matrix sat_v = e(V_iw)

estimates store eventstudyinteract
estimates replay eventstudyinteract
honestdid, post(1/5) pre(6/9) mvec(0(0.5)2) coefplot

However , honestdid generates a coefplot without estimates. And the reported results from eventstudyinteract are different from estimates dir eventstudyinteract:

eventstudyinteract command:

------------------------------------------------------------------------------
             |               Robust
      ln_sum | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     L0event |   .0106074   .0068322     1.55   0.131    -.0033661    .0245809
     L1event |     .03547   .0110083     3.22   0.003     .0129556    .0579844
     L2event |   .0365463   .0151308     2.42   0.022     .0056004    .0674923
     L3event |   .0442416   .0198347     2.23   0.034     .0036751    .0848082
     L4event |   .0769768   .0258086     2.98   0.006     .0241923    .1297614
     F2event |  -.0036461   .0072195    -0.51   0.617    -.0184117    .0111195
     F3event |      .0007   .0064344     0.11   0.914    -.0124599    .0138599
     F4event |  -.0073783   .0173413    -0.43   0.674    -.0428452    .0280886
     F5event |  -.0104371   .0230692    -0.45   0.654     -.057619    .0367447
       lnGDP |  -.0005063   .0084592    -0.06   0.953    -.0178073    .0167946
       lnpop |  -.0448455   .0414904    -1.08   0.289    -.1297028    .0400119
   lnstudent |  -.0427345   .0511465    -0.84   0.410    -.1473409    .0618719
------------------------------------------------------------------------------

estimates replay eventstudyinteract command:

------------------------------------------------------------------------------
             |               Robust
      ln_sum | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    __00000U |          0  (omitted)
    __00000V |   .0174089   .0091639     1.90   0.067    -.0013333    .0361511
    __00000W |  -.0014576   .0083436    -0.17   0.863    -.0185222     .015607
    __00000X |   .0175572   .0068407     2.57   0.016     .0035663     .031548
    __00000Y |          0  (omitted)
    __00000Z |   .0411389    .012254     3.36   0.002     .0160766    .0662011
    __000010 |   .0330809   .0157284     2.10   0.044     .0009126    .0652492
    __000011 |          0  (omitted)
    __000012 |          0  (omitted)
    __000013 |   .0367688   .0152167     2.42   0.022     .0056472    .0678904
    __000014 |          0  (omitted)
    __000015 |          0  (omitted)
    __000016 |          0  (omitted)
    __000017 |   .0445295   .0199571     2.23   0.034     .0037126    .0853463
    __000018 |          0  (omitted)
    __000019 |          0  (omitted)
    __00001A |          0  (omitted)
    __00001B |    .077482   .0259628     2.98   0.006      .024382    .1305819
    __00001C |          0  (omitted)
    __00001D |          0  (omitted)
    __00001E |          0  (omitted)
    __00001F |  -.0164215   .0104065    -1.58   0.125    -.0377053    .0048622
    __00001G |   .0001596   .0085733     0.02   0.985    -.0173749     .017694
    __00001H |   .0059214   .0064786     0.91   0.368    -.0073288    .0191715
    __00001I |          0  (omitted)
    __00001J |          0  (omitted)
    __00001K |   .0014988   .0110473     0.14   0.893    -.0210954    .0240931
    __00001L |  -2.86e-06   .0086694    -0.00   1.000    -.0177337     .017728
    __00001M |          0  (omitted)
    __00001N |          0  (omitted)
    __00001O |  -.0307817   .0152167    -2.02   0.052    -.0619032    .0003399
    __00001P |   .0158392   .0101073     1.57   0.128    -.0048326     .036511
    __00001Q |          0  (omitted)
    __00001R |          0  (omitted)
    __00001S |  -.0419752   .0203078    -2.07   0.048    -.0835094   -.0004409
    __00001T |   .0211257   .0084485     2.50   0.018     .0038465    .0384049
    __00001U |   .1556738   .1001824     1.55   0.131    -.0492221    .3605698
    __00001V |          0  (omitted)
    __00001W |          0  (omitted)
    __00001X |   .3038947   .0934702     3.25   0.003     .1127266    .4950628
    __00001Y |  -.6078498   .4810137    -1.26   0.216    -1.591633    .3759337
    __00001Z |          0  (omitted)
    __000020 |          0  (omitted)
    __000021 |          0  (omitted)
    __000022 |   .2683345   .3078596     0.87   0.391    -.3613091    .8979781
    __000023 |          0  (omitted)
    __000024 |          0  (omitted)
    __000025 |          0  (omitted)
       _cons |   13.68915    1.82066     7.52   0.000      9.96548    17.41282
------------------------------------------------------------------------------

And then I run the command honestdid, and return me a very weird result:

_honestARPConditionalTest(): LP for eta did not converge properly. Not rejecting
_honestARPConditionalTest(): LP for eta did not converge properly. Not rejecting (repeated for many times)

|    M    |   lb   |   ub   |
| ------- | ------ | ------ |
|       . |  0.000 |  0.000 | (Original)
|  0.0000 |  0.000 |  0.000 | (*)
|  0.5000 | -0.017 |  0.017 | (*)
|  1.0000 | -0.033 |  0.033 | (*)
|  1.5000 | -0.050 |  0.050 | (*)
|  2.0000 | -0.066 |  0.066 | (*)
(method = C-LF, Delta = DeltaRM, alpha = 0.050)
(*) CI is open at both endpoints; CI length may not be accurate.
Try expanding the grid using the grid_lb() and grid_ub() options

Could you try to help me fix that? Many thanks!

@jonathandroth
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jonathandroth commented Dec 16, 2024 via email

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