/xtevent

Stata package -xtevent-

Primary LanguageStataMIT LicenseMIT

xtevent

GitHub release (latest by date)

Stata package xtevent estimates linear panel event-study models.

Description

xtevent is a Stata package to estimate linear panel event-study models. It includes three commands: xtevent for estimation; xteventplot to create event-study plots and; xteventtest for post-estimation hypotheses testing.

  • Last version: 2.1.1 (12aug2022)
  • Current SSC version: 2.1.0 (1aug2022)

Updates

  • Version 2.1.1 (12aug2022):

    • Fixed bugs present in xtevent 2.1.0.
    • Updates in the help files and other documentation.
    • See here for the complete update list.

  • Version 2.1.0 (1aug2022):

    • Adds diffavg option to xtevent to obtain the difference between the average post-event and pre-event coefficient estimates.
    • Adds textboxoption option to xteventplot to specify characteristics for displaying the p-values of the pre-trend and leveling-off tests.
    • Fixed bugs present in version 2.0.0
    • See here for the complete update list.

  • Version 2.0.0 (24jun2022):

    • Adds impute option for imputing missing values in the policy variable according to several available rules. See the help file to know more about the available imputation rules.
    • The option nonstaggered has been depreciated. The default option is now not to impute missing values or endpoints. You should now choose any of the imputation rules in the impute option. To get results using imputation consistent with staggered adoption, as in version 1.0.0 you should use impute(stag).
    • Now the option trend allows for trend adjustment by either OLS or GMM.
    • Fixed several bugs present in version 1.0.0
    • See here for the complete update list.

Installation

To install version 2.1.0 from SSC:

ssc install xtevent

To update from an older version:

adoupdate xtevent, update

To install the last version in this repository, use the github command:

First, install the github command:

net install github, from("https://haghish.github.io/github/")

Then execute:

cap github uninstall xtevent
github install JMSLab/xtevent

The github command will also install all the necessary dependencies.

If you have an older version and want to update:

github update xtevent

To install using net:

cap ado uninstall xtevent
net install xtevent, from("https://raw.githubusercontent.com/JMSLab/xtevent/master")

To get started

help xtevent

Examples

Using xtevent 2.1.1

xtevent

*setup
webuse nlswork
xtset idcode year

*Estimate a basic event study with clustered standard errors. 
*Impute the policy variable without verifying staggered adoption.
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) cluster(idcode) impute(nuchange)
            
*Omit fixed effects
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) cluster(idcode) impute(nuchange) nofe note

*Adjust the pre-trend by estimating a linear trend by GMM
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(2) cluster(idcode) impute(nuchange) trend(-2, ///
            method(gmm))
      
*FHS estimator with proxy variables
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) vce(cluster idcode) impute(nuchange) ///
            proxy(wks_work)

*reghdfe and two-way clustering
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) impute(nuchange) cluster(idcode year) reghdfe ///
            proxy(wks_work)

xteventplot

*setup
webuse nlswork
xtset idcode year

*Add an extra effect if union equals 1
gen ln_wage2=ln_wage
replace ln_wage2=ln_wage2+0.5 if union==1

*Basic event study with clustered standard errors. 
*Impute policy variable without verifying staggered adoption.
xtevent ln_wage2 age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) cluster(idcode) impute(nuchange) 

* Plot
xteventplot

*Plot smoothest path in confidence region
xteventplot, smpath(line)

*FHS estimator with proxy variables
xtevent ln_wage age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) vce(cluster idcode) impute(nuchange) ///
            proxy(wks_work)

*Dependent variable, proxy variable, and overlay plots
xteventplot, y
xteventplot, proxy
xteventplot, overlay(iv)

xteventtest

*setup
webuse nlswork
xtset idcode year

*Basic event study with clustered standard errors. 
*Impute policy variable without verifying staggered adoption.
xtevent ln_w age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp tenure , ///
            pol(union) w(3) cluster(idcode) impute(nuchange) 

*Test some coefficients to be equal to 0 jointly
xteventtest, coefs(1 2)

*Test that the sum of all pre-event coefficients is equal to 0
xteventtest, allpre cumul

*Test whether the coefficients before the event follow a linear trend
xteventtest, linpretrend

*Tests that the coefficients for the earliest 2 periods before the event are equal to 0
xteventtest, overidpre(2)

Video tutorial:

Our YouTube channel, Linear Panel Event-Study Design, contains a video series discussing xtevent and the accompanying paper, Visualization, Identification, and Estimation in the Panel Event-Study Design.

Citation

Simon Freyaldenhoven, Christian Hansen, Jorge Pérez Pérez, and Jesse M. Shapiro. "Visualization, Identification, and Estimation in the Panel Event-Study Design." NBER Working Paper No. 29170, August 2021.