heckman_lasso

Adaptive post-Lasso Heckman regression

Description

heckman_lasso estimates a post-Lasso Heckman regression where the exclusion restrictions are determined in a data-driven way. Lasso estimations are performed using the built-in Stata command lasso, which requires Stata 16. Post-Lasso Heckman estimation is performed using the built-in Stata command heckman. For general information about adaptive Lasso see Zou (2006).

Installing heckman_lasso

Way 1: Use the Stata module github to install heckman_lasso. Type the following code in Stata:

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

2. github install farbmacher/heckman_lasso
   

Way 2: Copy the heckman_lasso.ado and heckman_lasso.sthlp files into your personal ado folder or the current working directory.

Example

Perform a post-Lasso Heckman regression with y the outcome (ds indicating observations for which y is observed) and x1, x2,... a set of exogenous variables containing both control variables and potential exclusion restrictions

1.  heckman_lasso y x1 x2, seldep(ds) twostep
   

Let z1, z2,... be a set of additional exogenous control variables, which should always be included in the model, then

2.  heckman_lasso y x1 x2 z1 z2, seldep(ds) twostep notpen(z1 z2)
   

References

• Farbmacher, H. (2021): Selection Models with Data-Driven Exclusion Restrictions in Managerial Economics, Discussion Paper.
• Zou H. (2006): The Adaptive Lasso and Its Oracle Properties, Journal of the American Statistical Association 101, 1418-1429.