Using Selection on Observed Variables to Assess Bias from Unobservables When Evaluating Swan-Ganz Catheterization

By Joseph G. Altonji, Todd E. Elder, Christopher R. Taber. 2008

144 citations recorded by the source corpus.

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In Economics and Econometrics

Citations in the corpus

The State of Applied Econometrics - Causality and Policy Evaluation (2016, neutral): “Altonji et al. [2008] and Oster [2015] focus on the correlation between the unobserved component in the relation between the outcome and the treatment and observed covariates, and the unobserved component in the relation between the treatment and the observed covariates.”
Sensitivity to Missing Data Assumptions: Theory and an Evaluation of the U.S. Wage Structure (2010, methodology): “These techniques substantially extend the recent econometrics literature on sensitivity analysis (Altonji et al. (2005, 2008), Imbens (2003), Rosenbaum and Rubin (1983), Rosenbaum (2002)), most of which has focused on the sensitivity of scalar treatment effect estimates to confounding influences,…”
Unobservable Selection and Coefficient Stability: Theory and Evidence (2019, background): “I formalize this link through a proportional selection relationship, following Altonji, Elder and Taber (2005). I show that it is necessary to take into account coefficient movements and movements in R-squared values in identifying omitted variable bias.”
Impact of the alternate wetting and drying (AWD) water-saving irrigation technique: Evidence from rice producers in the Philippines (2011, background): “But if the measure is close to 1.0 or less than 1.0, then this means that it takes the same or a smaller shift in unobservables to eliminate the AWD impact and the estimated AWD may impact may simply be due to selection on unobservables (for example, see results in Altonji et al., 2008).”