*! version 1 2018-07-27

Title

did_multiplegt -- Library of Estimators in
Difference-in-Difference (DID) designs with multiple groups and periods.

Syntax

did_multiplegt (mode) Y G T D [if] [in]
[, options]

Description

did_multiplegt wraps in a single command all
the DID estimators from de Chaisemartin and D'Haultfoeuille.
Depending on the mode argument, this command can be used to call the following estimators.

did_multiplegt_dyn.
In dyn mode, the command computes
heterogeneity-robust event-study DID estimators
introduced in de Chaisemartin and D'Haultfoeuille (2024a).
Like other recently proposed DID estimators
(csdid, didimputation, ...), these estimators
can be used with a binary and staggered (absorbing)
treatment. But unlike those other estimators,
these estimators can also be used with a non-binary
(discrete or continuous) and non-absorbing
treatment that can increase or decrease multiple times.
These estimators can also be used when lagged
treatments affect the outcome.

did_multiplegt_stat.
In stat mode, the command computes
heterogeneity-robust DID estimators introduced in de Chaisemartin and
D'Haultfoeuille (2020) and de Chaisemartin et al. (2022). These estimators can be used with a
non-binary (discrete or continuous) and non-absorbing treatment. However, they assume
that past treatments do not affect the current outcome.
Finally, these estimators can be used to compute IV-DID estimators, relying on a parallel-trends assumption with respect
to an instrumental variable rather than the treatment.

did_had.
In had mode, the command
computes the DID estimators
introduced in de Chaisemartin and D'Haultfoeuille (2024b).
These estimators can be used in heterogeneous adoption designs (HAD)
with no stayers but some quasi stayers.

did_multiplegt_old.
In old mode, the command computes the DID
estimators introduced in de Chaisemartin and
D'Haultfoeuille (2020). This mode corresponds
to the old version of the did_multiplegt command.
We do not recommend using this mode. The three aforementioned modes are much faster, because
they do not rely on the bootstrap to compute standard errors. Moreover,
they offer more comprehensive and up to date estimation and post-estimation options.

did_multiplegt updates
automatically all the packages above
(on average) every 100 runs of the command.
Self-updates can be stopped by
specifying the command with the no_updates option.

Arguments

mode is the command selector and can be only be dyn, had or old.

Y is the outcome variable.

G is the group variable.

T is the time period variable.

D is the treatment variable.

options is a pass-through
and can include all the options of the
command called with mode. It can
include the no_updates option, which
will apply only for did_multiplegt and
will not be passed onto the mode options.

Example: Estimating the effect of union membership on wages

Loading the worker-year level data from Vella and Verbeek (1998):

bcuse wagepan

Computing DID_M from de Chaisemartin and D'Haultfoeuille (2020):

did_multiplegt (old) lwage nr year union, breps(100) cluster(nr)

did_multiplegt (stat) lwage nr year union, exact_match

Computing 5 dynamic effects and 2 placebos using DID_l from de Chaisemartin and D'Haultfoeuille (2024a):

did_multiplegt (dyn) lwage nr year union, effects(5) placebo(2) graph_off

References

de Chaisemartin, C and D'Haultfoeuille, X (2020). American Economic Review, vol. 110, no. 9.
Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects.

de Chaisemartin, C, D'Haultfoeuille, X, Pasquier, F, Vazquez‐Bare, G (2022).
Difference-in-Differences for Continuous Treatments and Instruments with Stayers.

de Chaisemartin, C and D'Haultfoeuille, X (2024a). Review of Economics and Statistics, 1-45.
Difference-in-Differences Estimators of Intertemporal Treatment Effects.

de Chaisemartin, C and D'Haultfoeuille, X (2024b).
Two-way Fixed Effects and Differences-in-Differences Estimators in Heterogeneous Adoption Designs.

Vella, F. and Verbeek, M. 1998. Journal of Applied Econometrics 13(2), 163–183.
Whose wages do unions raise? a dynamic model of unionism and wage rate determination for young men.

Authors

Clément de Chaisemartin, Economics Department, Sciences Po, France.

Diego Ciccia, Sciences Po, France.

Xavier D'Haultfoeuille, CREST-ENSAE, France.

Felix Knau, Sciences Po, France.

Felix Pasquier, CREST-ENSAE, France.

Mélitine Malézieux, Stockholm School of Economics, Sweden.

Doulo Sow, Sciences Po, France.

Gonzalo Vazquez-Bare, UCSB, USA.

Contact

Mail:
chaisemartin.packages@gmail.com

GitHub:
chaisemartinPackages
or individual packages (did_multiplegt_dyn
| did_multiplegt_stat
| did_had
| did_multiplegt).