Imagen de Portada

An Optimal Transport Approach to Estimating Causal Effects via Nonlinear Difference-in-Differences

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Torous, William, Gunsilius, Florian, Rigollet, Philippe
Formato:	Preprint
Publicado:	2021
Materias:	Methodology Econometrics Statistics Theory
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Efficient Difference-in-Differences Estimation when Outcomes are Missing at Random
por: Testa, Lorenzo, et al.
Publicado: (2025)

Free Discontinuity Regression: With an Application to the Economic Effects of Internet Shutdowns
por: Gunsilius, Florian, et al.
Publicado: (2023)

Fused Extended Two-Way Fixed Effects for Difference-in-Differences With Staggered Adoptions
por: Faletto, Gregory
Publicado: (2023)

Estimation of High-dimensional Nonlinear Vector Autoregressive Models
por: Han, Yuefeng, et al.
Publicado: (2025)

Partial Identification of Causal Effects for Endogenous Continuous Treatments
por: Dalal, Abhinandan, et al.
Publicado: (2025)

Nonlinear Binscatter Methods
por: Cattaneo, Matias D., et al.
Publicado: (2024)

Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference
por: Qu, Zhaonan, et al.
Publicado: (2021)

Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials
por: Oka, Tatsushi, et al.
Publicado: (2024)

Causal Interpretation of Regressions With Ranks
por: Lei, Lihua
Publicado: (2024)

Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects
por: Ghassami, AmirEmad, et al.
Publicado: (2022)

Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
por: Sert, Gözde, et al.
Publicado: (2025)

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference
por: Kato, Masahiro
Publicado: (2025)

The Honest Truth About Causal Trees: Accuracy Limits for Heterogeneous Treatment Effect Estimation
por: Cattaneo, Matias D., et al.
Publicado: (2025)

Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
por: Jin, Jikai, et al.
Publicado: (2024)

Bayesian Model Averaging in Causal Instrumental Variable Models
por: Steiner, Gregor, et al.
Publicado: (2025)

Causal clustering: design of cluster experiments under network interference
por: Viviano, Davide, et al.
Publicado: (2023)

Evaluating Policy Effects under Network Interference without Network Information: A Transfer Learning Approach
por: Hoshino, Tadao
Publicado: (2025)

Optimal Decision Rules Under Partial Identification
por: Yata, Kohei
Publicado: (2021)

Optimal testing in a class of nonregular models
por: Shimizu, Yuya, et al.
Publicado: (2024)

Compound Estimation for Binomials
por: Chen, Yan, et al.
Publicado: (2025)

Optimal estimation for regression discontinuity design with binary outcomes
por: Ishihara, Takuya, et al.
Publicado: (2025)

Robust Estimation and Inference for Categorical Data
por: Welz, Max
Publicado: (2024)

Estimation and Inference for CP Tensor Factor Models
por: Chen, Bin, et al.
Publicado: (2024)

The Local Approach to Causal Inference under Network Interference
por: Auerbach, Eric, et al.
Publicado: (2021)

Bootstrap-Assisted Inference for Generalized Grenander-type Estimators
por: Cattaneo, Matias D., et al.
Publicado: (2023)

Empirical Bayes When Estimation Precision Predicts Parameters
por: Chen, Jiafeng
Publicado: (2022)

Estimating Counterfactual Matrix Means with Short Panel Data
por: Lei, Lihua, et al.
Publicado: (2023)

A General Design-Based Framework and Estimator for Randomized Experiments
por: Harshaw, Christopher, et al.
Publicado: (2022)

Estimation of the complier causal hazard ratio under dependent censoring
por: Crommen, Gilles, et al.
Publicado: (2025)

Estimation and Inference in Boundary Discontinuity Designs: Distance-Based Methods
por: Cattaneo, Matias D., et al.
Publicado: (2025)

Compound Selection Decisions: An Almost SURE Approach
por: Chen, Jiafeng, et al.
Publicado: (2025)

An Adversarial Approach to Structural Estimation
por: Kaji, Tetsuya, et al.
Publicado: (2020)

Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
por: Cattaneo, Matias D., et al.
Publicado: (2022)

Inference for Forecasting Accuracy: Pooled versus Individual Estimators in High-dimensional Panel Data
por: Kutta, Tim, et al.
Publicado: (2025)

A primer on optimal transport for causal inference with observational data
por: Gunsilius, Florian F
Publicado: (2025)

Identification and Debiased Learning of Causal Effects with General Instrumental Variables
por: Chen, Shuyuan, et al.
Publicado: (2025)

Individual Treatment Effect: Prediction Intervals and Sharp Bounds
por: Zhang, Zhehao, et al.
Publicado: (2025)

Joint Quantile Shrinkage: A State-Space Approach toward Non-Crossing Bayesian Quantile Models
por: Kohns, David, et al.
Publicado: (2025)

Semiparametrics via parametrics and contiguity
por: Lee, Adam, et al.
Publicado: (2025)

Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
por: Kato, Masahiro
Publicado: (2025)