Number of the records: 1
Evaluating (weighted) dynamic treatment effects by double machine learning
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$a 10.1093/ectj/utac018 $2 DOI 035 $a biblio/524304 $2 CREPC2 100 $a 20221107d2022 m y slo 03 ba 101 0-
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$a Evaluating (weighted) dynamic treatment effects by double machine learning $f Hugo Bodory, Martin Huber, Lukáš Laffers 330 $a We consider evaluating the causal effects of dynamic treatments, i.e.. of multiple treatment sequences in various periods, based on double machine learning to control for observed, time-varying covariates in a data-driven way under a selection-on-observables assumption. To this end, we make use of so-called Neyman-orthogonal score functions, which imply the robustness of treatment effect estimation to moderate (local) misspecifications of the dynamic outcome and treatment models. This robustness property permits approximating outcome and treatment models by double machine learning even under high-dimensional covariates. In addition to effect estimation for the total population, we consider weighted estimation that permits assessing dynamic treatment effects in specific subgroups. e.g.. among those treated in the first treatment period. We demonstrate that the estimators are asymptotically normal and root n-consistent under specific regularity conditions and investigate their finite sample properties in a simulation study. Finally, we apply the methods to the Job Corps study. 463 -1
$1 001 umb_un_cat*0314591 $1 011 $a 1368-4221 $1 011 $a 1368-423X $1 200 1 $a The Econometrics Journal $v Vol. 25, no. 3 (2022), pp. 628-648 $1 210 $a Londýn $c Royal Economic Society $d 2022 606 0-
$3 umb_un_auth*0248297 $a strojové učenie $X machine learning 606 0-
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$3 umb_un_auth*0295422 $a Bodory $b Hugo $4 070 $9 34 701 -1
$3 umb_un_auth*0249133 $a Huber $b Martin $4 070 $9 33 701 -1
$3 umb_un_auth*0249128 $a Lafférs $b Lukáš $p UMBFP10 $4 070 $9 33 $f 1986- $T Katedra matematiky 801 $a SK $b BB301 $g AACR2 $9 unimarc sk 856 $u https://academic.oup.com/ectj/article-abstract/25/3/628/6604379 $a Link na zdrojový dokument T85 $x existuji fulltexy
Number of the records: 1