xtevent
Table of contents
Introduction
Installation and options
ssc install xtevent, replace
Take a look at the help file:
help xtevent
Test the command
Let’s try the basic command:
Please make sure that you generate the data using the script given here
xtevent Y, pol(D) p(id) t(t) w(20) cohort(gvar) control_cohort(never_treat)
which shows this output:
No proxy or instruments provided. Implementing OLS estimator
You have specified cohort and control_cohort options. Event-time coefficients will be estimated with the Interaction Weighted Estimator of Sun and Abraham (2021).
warning: variance matrix is nonsymmetric or highly singular.
Linear regression, absorbing indicators Number of obs = 570
Absorbed variable: id No. of categories = 30
F(55, 485) = 4887.00
Prob > F = 0.0000
R-squared = 0.9991
Adj R-squared = 0.9990
Root MSE = 1.3963
------------------------------------------------------------------------------
Y | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
_k_eq_m21 | .1357876 . . . . .
_k_eq_m20 | -.150126 . . . . .
_k_eq_m19 | -.2886362 . . . . .
_k_eq_m18 | 1.001511 . . . . .
_k_eq_m17 | -1.524232 . . . . .
_k_eq_m16 | .4040116 . . . . .
_k_eq_m15 | .0406827 . . . . .
_k_eq_m14 | .1196182 . . . . .
_k_eq_m13 | 1.180311 . . . . .
_k_eq_m12 | .2643562 . . . . .
_k_eq_m11 | -.1566494 . . . . .
_k_eq_m10 | -.1636734 . . . . .
_k_eq_m9 | .378421 . . . . .
_k_eq_m8 | .7320174 . . . . .
_k_eq_m7 | .2677505 . . . . .
_k_eq_m6 | -.0065124 . . . . .
_k_eq_m5 | -.2562236 . . . . .
_k_eq_m4 | .0455235 . . . . .
_k_eq_m3 | .177183 . . . . .
_k_eq_m2 | .2562286 . . . . .
_k_eq_p0 | .0834288 . . . . .
_k_eq_p1 | 8.706174 . . . . .
_k_eq_p2 | 17.65776 . . . . .
_k_eq_p3 | 26.50699 . . . . .
_k_eq_p4 | 35.77882 . . . . .
_k_eq_p5 | 43.81289 . . . . .
_k_eq_p6 | 53.43996 . . . . .
_k_eq_p7 | 69.77442 . . . . .
_k_eq_p8 | 79.86261 . . . . .
_k_eq_p9 | 89.59572 . . . . .
_k_eq_p10 | 99.8721 . . . . .
_k_eq_p11 | 109.2024 . . . . .
_k_eq_p12 | 119.943 . . . . .
_k_eq_p13 | 129.5638 . . . . .
_k_eq_p14 | 140.1471 . . . . .
_k_eq_p15 | 149.8544 . . . . .
_k_eq_p16 | 160.9501 . . . . .
_k_eq_p17 | 0 (omitted)
_k_eq_p18 | 0 (omitted)
_k_eq_p19 | 0 (omitted)
_k_eq_p20 | 0 (omitted)
_k_eq_p21 | 0 (omitted)
|
t |
23 | 1.217965 . . . . .
24 | 2.095903 . . . . .
25 | 3.252631 . . . . .
26 | 4.563759 . . . . .
27 | 6.070876 . . . . .
28 | 7.544779 . . . . .
29 | 8.929311 . . . . .
30 | 10.02112 . . . . .
31 | 10.26208 . . . . .
32 | 11.99903 . . . . .
33 | 12.76723 . . . . .
34 | 13.821 . . . . .
35 | 14.24483 . . . . .
36 | 15.16298 . . . . .
37 | 15.8125 . . . . .
38 | 16.35458 . . . . .
39 | 16.49738 . . . . .
40 | 16.30867 . . . . .
|
_cons | 36.6592 . . . . .
------------------------------------------------------------------------------
The graph can be generated as follows using event_plot command:
matrix xt_b = e(b)
matrix xt_v = e(V)
event_plot xt_b#xt_v, default_look graph_opt(xtitle("Periods since the event") ytitle("Average effect") ///
title("xtevent")) stub_lag(_k_eq_p#) stub_lead(_k_eq_m#) together
