Merge pull request #20 from DiegoCiccia/main

Latest updates from de Chaisemartin and D'Haultfoeuille

docs/01_stata.md

@@ -11,6 +11,7 @@ nav_order: 2
 
 Packages are sorted in alphabetical order by name. Some package paths have been split across lines but adding spaces to keep table formatting intact. Just make sure they are in one line with spaces removed when copying them in Stata. To install packages from GitHub, get the `github` package: `net install github, from("https://haghish.github.io/github/")`. Documentation of Stata packages is usually done on internal help files. Some packages do have dedicated websites, PDFs, or GitHub repositories that are identified in the website column. Also check the equivalent [R packages](https://asjadnaqvi.github.io/DiD/docs/02_R/) package that also lists dedicated pages.
 
+
 | Name | Installation | Package by | Reference paper(s) |
 | --- | --- | --- |   --- |
 | bacondecomp | `ssc install bacondecomp, replace`  |   [Andrew Goodman-Bacon](http://goodman-bacon.com/) [<img width="12px" src="https://cdn.jsdelivr.net/npm/simple-icons@v5/icons/twitter.svg" />](https://twitter.com/agoodmanbacon) <br> [Thomas Goldring](https://tgoldring.com/) <br> Austin Nichols [<img width="12px" src="https://cdn.jsdelivr.net/npm/simple-icons@v5/icons/twitter.svg" />](https://twitter.com/AustnNchols) |   [Goodman-Bacon (2021)](https://www.sciencedirect.com/science/article/abs/pii/S0304407621001445) |

docs/code/06_04_did_multiplegt.md

@@ -10,6 +10,22 @@ image: "../../../assets/images/DiD.png"
 # did_multiplegt (Chaisemartin and D'Haultfœuille 2020, 2021)
 {: .no_toc }
 
+## Note
+{: .no_toc}
+
+To estimate event-study/dynamic effects, we strongly recommend using the <ins>much faster</ins> [did_multiplegt_dyn](https://asjadnaqvi.github.io/DiD/docs/code/06_16_did_multiplegt_dyn.md) command. 
+
+In addition to that, did_multiplegt_dyn offers more options than did_multiplegt, among which:
++ **normalized**: estimation of the normalized dynamic effects (de Chaisemartin & D'Haultfoeuille, 2024);
++ **predict_het**: built-in treatment effect heterogeneity analysis;
++ **design** and **date_first_switch**: post-estimation options to analyze the design and timing of the treatment;
++ **by** and **by_path**: estimating dynamic effects within levels of a group-level variable or within treatment paths;
++ **trends_lin**: built-in group-specific linear trends.
+
+Lastly, as of the last release, did_multiplegt_dyn also includes two user-requested features:
++ **only_never_switchers**: restricting the estimators from de Chaisemartin & D'Haultfoeuille (2024) to only compare switchers and never-switchers;
++ integration with **esttab**: here a quick [tutorial](https://github.com/chaisemartinPackages/did_multiplegt_dyn/blob/main/vignettes/vignette_2.md).
+
 ## Table of contents
 {: .no_toc .text-delta }
 
@@ -18,8 +34,6 @@ image: "../../../assets/images/DiD.png"
 
 ---
 
-
-
 ## Installation and options
 
 ```stata
@@ -32,9 +46,6 @@ Take a look at the help file:
 help did_multiplegt
 ```
 
-
-
-
 ## Test the command
 
 Please make sure that you generate the data using the script given [here](https://asjadnaqvi.github.io/DiD/docs/code/06_03_data/) 

docs/code/06_16_did_multiplegt_dyn.md

@@ -0,0 +1,113 @@
+---
+layout: default
+title: did_multiplegt_dyn
+parent: Stata code
+nav_order: 4
+mathjax: true
+image: "../../../assets/images/DiD.png"
+---
+
+# did_multiplegt_dyn (Chaisemartin and D'Haultfœuille 2024)
+{: .no_toc }
+
+## Table of contents
+{: .no_toc .text-delta }
+
+1. TOC
+{:toc}
+
+---
+
+## Installation and options
+
+```stata
+ssc install did_multiplegt_dyn, replace
+```
+
+Take a look at the help file:
+
+```stata
+help did_multiplegt_dyn
+```
+
+## Test the command
+
+Please make sure that you generate the data using the script given [here](https://asjadnaqvi.github.io/DiD/docs/code/06_03_data/) 
+
+Let's try the basic `did_multiplegt_dyn` command:
+
+
+```stata
+did_multiplegt_dyn Y id t D, effects(10) placebo(10) cluster(id)
+```
+
+and we get this output:
+
+```
+--------------------------------------------------------------------------------
+             Estimation of treatment effects: Event-study effects
+--------------------------------------------------------------------------------
+
+             |  Estimate         SE      LB CI      UB CI          N  Switchers 
+-------------+-----------------------------------------------------------------
+    Effect_1 | -.0608394   .3275515  -.7028286   .5811498         78         23 
+    Effect_2 |   8.49767   .3888474   7.735543   9.259797         78         23 
+    Effect_3 |  17.64773   .3877416   16.88777   18.40769         78         23 
+    Effect_4 |   25.9377   .3203208   25.30988   26.56551         78         23 
+    Effect_5 |  34.62362   .3923778   33.85458   35.39267         75         23 
+    Effect_6 |  42.85682   .3893014   42.09381   43.61984         64         19 
+    Effect_7 |  51.93103   .3963844   51.15413   52.70793         64         19 
+    Effect_8 |  60.13327   .3945513   59.35997   60.90658         64         19 
+    Effect_9 |  68.82446   .4118019   68.01735   69.63158         64         19 
+   Effect_10 |  77.30792   .4396869   76.44615   78.16969         64         19 
+--------------------------------------------------------------------------------
+
+
+--------------------------------------------------------------------------------
+               Average cumulative (total) effect per treatment unit
+--------------------------------------------------------------------------------
+
+             |  Estimate         SE      LB CI      UB CI          N     Switch  x Periods 
+-------------+----------------------------------------------------------------------------
+  Av_tot_eff |  36.72796   .2689364   36.20085   37.25506        641        210            
+--------------------------------------------------------------------------------
+Average number of time periods over which a treatment's effect is accumulated = 5.2619048
+
+
+--------------------------------------------------------------------------------
+          Testing the parallel trends and no anticipation assumptions
+--------------------------------------------------------------------------------
+
+             |  Estimate         SE      LB CI      UB CI          N  Switchers 
+-------------+-----------------------------------------------------------------
+   Placebo_1 |  .1308918   .4574125  -.7656203   1.027404         78         23 
+   Placebo_2 | -.0635463   .3403349  -.7305904   .6034978         78         23 
+   Placebo_3 | -.1275425   .3855322  -.8831717   .6280867         78         23 
+   Placebo_4 | -.3848303   .3223237  -1.016573   .2469125         78         23 
+   Placebo_5 | -.4583828   .3389718  -1.122755   .2059897         75         23 
+   Placebo_6 |  -.187576   .4510044  -1.071528   .6963763         64         19 
+   Placebo_7 |  .1194068   .4068627  -.6780295   .9168431         64         19 
+   Placebo_8 |  .0628537   .4251272  -.7703804   .8960877         64         19 
+   Placebo_9 | -.1943702   .4963493  -1.167197   .7784565         64         19 
+  Placebo_10 | -.2936846   .5040208  -1.281547    .694178         64         19 
+--------------------------------------------------------------------------------
+Test of joint nullity of the placebos : p-value = .01289977
+
+
+The development of this package was funded by the European Union (ERC, REALLYCREDIBLE,GA N°101043899).
+
+```
+
+If the **graph_off** option is not specified, the command always returns by default an event-study graph:
+
+<img src="../../../assets/images/did_multiplegt_dyn_stata.png" height="300">
+
+It is also possible to use `event_plot` to produce the event-study graph:
+
+```stata
+event_plot e(estimates)#e(variances), default_look ///
+	graph_opt(xtitle("Periods since the event") ytitle("Average causal effect") ///
+	title("did_multiplegt_dyn") xlabel(-10(1)10)) stub_lag(Effect_#) stub_lead(Placebo_#) together
+```
+
+<img src="../../../assets/images/did_multiplegt_dyn_stata_ep.png" height="300">