Semiparametric instrumental variable estimation of treatment response models

By Alberto Abadie. 2003

921 citations recorded by the source corpus.

Subfields: Accounting, Gender Studies, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

In Gender Studies

In Statistics and Probability

Citations in the corpus

Double/De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers (2018, methodology): “(2018b)), using sample selection and variable construction as in Abadie (2003) and Chernozhukov and Hansen (2004). The outcome Y is net financial assets defined as the sum of IRA balances, 401(k) balances, checking accounts, US saving bonds, other interest-earning accounts, stocks, mutual funds, and”
Generalized random forests (2016, methodology): “allows us to estimate a (conditional) local average treatment effect (Abadie, 2003; Imbens and Angrist, 1994). We then use our formalism to derive a forest that is targeted towards estimating causal effects identified via conditional two-stage least squares. Gradient-based labeling (8) yields pseudo”
Efficient Policy Learning (2017, methodology): “1 of Abadie (2003). Suppose moreover that treatment effects are homogenous, meaning that the conditional average treatment effect matches the conditional local average treatment effect (Imbens and Angrist, 1994),(8)”
Threshold Regression with Endogeneity (2017, positive): “Notwithstanding this shortcoming, an objective function for the LATE as in Abadie (2003), which incorporates threshold effects, can be used to estimate the γ and α parameters provided we use the model (14) for compliers.”
Access to 4-Year Public Colleges and Degree Completion (2017, methodology): “Control complier means, computed as suggested by Abadie, Angrist, and Imbens (2002) and Abadie (2003), imply that GSUS enrollment raises peer quality from well below average to slightly above average.”
Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality (2009, background): “considered by Imbens and Rubin (1997) and Abadie (2002, 2003) .1 However, these three papers develop”
Quantile Selection Models with an Application to Understanding Changes in Wage Inequality (2017, methodology): “The Skorohod representation (1) is without loss of generality.”
ESTIMATION IN AN INSTRUMENTAL VARIABLES MODEL WITH TREATMENT EFFECT HETEROGENEITY (2012, methodology): “Therefore, the single constructed instrument is also correlated with the outcome, causing jive to be biased when the number of covariates is large (Ackerberg and Devereux, 2009). In contrast, the ujive estimate of the effect of the covariates is given by a sample average that excludes individual i, ”
Interpretable Almost Matching Exactly With Instrumental Variables (2019, methodology): “Other IV methods in the presence of measured covariates include Bayesian methods (Imbens and Rubin, 1997), semiparametric methods (Abadie, 2003; Tan, 2006; Ogburn et al., 2015), nonparametric methods (Frölich, 2007) and deep learning methods (Hartford et al., 2017), but these methods do not enjoy…”
Education and social capital: empirical evidence from microeconomic analyses (2010, methodology): “Recently there have been efforts to introduce covariates in LATE estimation because instruments may require conditioning on a set of covariates to be valid (e.g. Hirano et al, 2000; Abadie, 2003; Froelich, 2007).”
Breaking Ties: Regression Discontinuity Design Meets Market Design (2019, methodology): “(2017a) compare score-controlled 2SLS estimates with semiparametric instrumental variables estimates based on Abadie (2003). The former are considerably more precise than the latter.”
Doubly robust uniform confidence band for the conditional average treatment effect function (2016, background): “revisit the analyses of Poterba, Venti, and Wise (1995) and Abadie (2003) to examine whether participation in 401(k) pension plans increases household savings. In their example, the vector of covariates Z for the identifying assumption consists of income, age, marital status, and family size, wherea”