Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Marx, Philip."'
We study the identification and estimation of heterogeneous, intertemporal treatment effects (TE) when potential outcomes depend on past treatments. First, applying a dynamic panel data model to observed outcomes, we show that instrument-based GMM es
Externí odkaz:
http://arxiv.org/abs/2410.19060
Difference-in-differences is a common method for estimating treatment effects, and the parallel trends condition is its main identifying assumption: the trend in mean untreated outcomes is independent of the observed treatment status. In observationa
Externí odkaz:
http://arxiv.org/abs/2207.06564
A much studied issue is the extent to which the confidence scores provided by machine learning algorithms are calibrated to ground truth probabilities. Our starting point is that calibration is seemingly incompatible with class weighting, a technique
Externí odkaz:
http://arxiv.org/abs/2205.04613
Autor:
Marx, Philip
A fundamental question underlying the literature on partial identification is: what can we learn about parameters that are relevant for policy but not necessarily point-identified by the exogenous variation we observe? This paper provides an answer i
Externí odkaz:
http://arxiv.org/abs/2012.02390
Autor:
Caplin, Andrew, Deming, David J., Shangwen Li, Martin, Daniel J., Marx, Philip, Weidmann, Ben, Ye, Kadachi Jiada
Publikováno v:
NBER Working Papers; Oct2024, Issue 33038-33089, Preceding p1-22, 23p
Publikováno v:
Journal of Political Economy Microeconomics. Feb2024, Vol. 2 Issue 1, p129-171. 43p.
Autor:
Marx, Philip1 philiplmarx@gmail.com
Publikováno v:
Journal of Law, Economics & Organization. Mar2022, Vol. 38 Issue 1, p42-91. 50p.
Publikováno v:
NBER Working Papers; Jan2023, Issue 30815-30885, p1-46, 46p