qte
Quantile Treatment Effects
Provides several methods for computing the Quantile Treatment Effect (QTE) and Quantile Treatment Effect on the Treated (QTT). The main cases covered are (i) Treatment is randomly assigned, (ii) Treatment is as good as randomly assigned after conditioning on some covariates (also called conditional independence or selection on observables) using the methods developed in Firpo (2007) <doi:10.1111/j.1468-0262.2007.00738.x>, (iii) Identification is based on a Difference in Differences assumption (several varieties are available in the package e.g. Athey and Imbens (2006) <doi:10.1111/j.1468-0262.2006.00668.x>, Callaway and Li (2019) <doi:10.3982/QE935>, Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>).
- Version1.3.1
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Firpo (2007)
- Athey and Imbens (2006)
- Callaway and Li (2019)
- Callaway, Li, and Oka (2018)
- Last release09/01/2022
Documentation
Team
Brantly Callaway
MaintainerShow author details
Insights
Last 30 days
This package has been downloaded 351 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 4,328 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was May 02, 2024 with 100 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports8 packages
- Suggests3 packages