Identification of Causal Effects Using Instrumental Variables 1 IIiiiiil

Citations in the corpus

Invariant Causal Prediction for Nonlinear Models (2017, neutral): “This follows from an assumption sometimes called autonomy or modularity (Haavelmo, 1944; Aldrich, 1989; Hoover, 1990; Pearl, 2009; Schölkopf et al., 2012).”
Nonparametric Tests for Treatment Effect Heterogeneity With Duration Outcomes (2016, unknown): “Imbens and Angrist (1994) and Angrist et al. (1996). The proposed methodology relies on three main components. First, the tests are based on inverse probability weighted (IPW) estimators, in which the propensity score is estimated by nonparametric methods. We focus on the Series Logit Estimator prop”
Education and Nonmarket Outcomes (2005, unknown): “Arendt (2005) capitalizes on compulsory school reform in Denmark in 1958 and 1975 to study the impact of schooling on self-rated health in the 1990 and 1995 waves of the Danish National Work Environment Cohort Study.”
Managerial Short-Termism and Investment: Evidence from Accelerated Option Vesting* (2019, unknown): “When this condition does not hold, 2SLS estimates equal the LATE plus a bias term that increases with the proportion of firms defying treatment (Angrist, Imbens, and Rubin, 1996).”
Instrumental Variable Estimation of the Causal Effect of Hunger Early in Life on Health Later in Life (2016, unknown): “The size of the complier group and the estimated effect may depend on the severity of the famine (Angrist et al., 1996).”