000340232 001__ 340232
000340232 005__ 20250206164231.0
000340232 022__ $$a1536-8634
000340232 0247_ $$2doi$$a10.22004/ag.econ.340232
000340232 037__ $$a199-2024-606
000340232 041__ $$aeng
000340232 245__ $$aExploring marginal treatment effects: Flexible estimation using Stata
000340232 260__ $$c2018-01
000340232 269__ $$a2018-01
000340232 336__ $$aJournal Article
000340232 520__ $$aIn settings that exhibit selection on both levels and gains, marginal treatment effects (MTE) allow us to go beyond local average treatment effects and estimate the whole distribution of effects. In this article, I survey the theory behind MTE and introduce the package mtefe, which uses several estimation methods to fit MTE models. This package provides important improvements and flexibility over existing packages such as margte (Brave and Walstrum, 2014, Stata Journal 14: 191–217) and calculates various treatment-effect parameters based on the results. I illustrate the use of the package with examples.
000340232 546__ $$aEnglish
000340232 650__ $$aResearch and Development/Tech Change/Emerging Technologies
000340232 6531_ $$ast0516
000340232 6531_ $$amtefe
000340232 6531_ $$amargte
000340232 6531_ $$aheterogeneity
000340232 6531_ $$amarginal treatment effects
000340232 6531_ $$ainstrumental
000340232 6531_ $$avariables
000340232 700__ $$aAndresen, Martin Eckhoff
000340232 773__ $$j18$$k01$$q118$$o158$$tStata Journal
000340232 8560_ $$fbecke073@umn.edu
000340232 8564_ $$926213ede-6112-46b0-8b96-c9bbb5712a33$$s475685$$uhttps://ageconsearch.umn.edu/record/340232/files/Andresen.pdf
000340232 909CO $$ooai:ageconsearch.umn.edu:340232$$pGLOBAL_SET
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000340232 980__ $$a199