Cover Image

Identification of Long-Term Treatment Effects via Temporal Links, Observational, and Experimental Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Obradović, Filip
Format:	Preprint
Published:	2024
Subjects:	Econometrics Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Estimating Effects of Long-Term Treatments
by: Huang, Shan, et al.
Published: (2023)

The Proximal Surrogate Index: Long-Term Treatment Effects under Unobserved Confounding
by: Hung, Ting-Chih, et al.
Published: (2026)

The Bias-Variance Tradeoff in Long-Term Experimentation
by: Ting, Daniel, et al.
Published: (2025)

Nonparametric Point Identification of Treatment Effect Distributions via Rank Stickiness
by: Liang, Tengyuan
Published: (2026)

Nonparametric Treatment Effect Identification in School Choice
by: Chen, Jiafeng
Published: (2021)

Partial Identification of Policy-Relevant Treatment Effects with Instrumental Variables via Optimal Transport
by: Tan, Jiyuan, et al.
Published: (2026)

Identification of Treatment Effects under Limited Exogenous Variation
by: Newey, Whitney K., et al.
Published: (2018)

Bounding Treatment Effects by Pooling Limited Information across Observations
by: Lee, Sokbae, et al.
Published: (2021)

Measuring Diagnostic Test Performance Using Imperfect Reference Tests: A Partial Identification Approach
by: Obradović, Filip
Published: (2022)

Using Experiments to Correct for Selection in Observational Studies
by: Athey, Susan, et al.
Published: (2020)

Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance
by: Bugni, Federico A., et al.
Published: (2024)

Relative Bias Under Imperfect Identification in Observational Causal Inference
by: Huang, Melody, et al.
Published: (2025)

Coupling Designs for Randomized Experiments with Complex Treatments
by: Cytrynbaum, Max, et al.
Published: (2026)

Identification of Average Treatment Effects in Nonparametric Panel Models
by: Athey, Susan, et al.
Published: (2025)

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

Nonparametric Identification and Estimation of Spatial Treatment Effect Boundaries: Evidence from 42 Million Pollution Observations
by: Kikuchi, Tatsuru
Published: (2025)

Treatment Effects in Market Equilibrium
by: Munro, Evan, et al.
Published: (2021)

Treatment Effects with Targeting Instruments
by: Lee, Sokbae, et al.
Published: (2020)

A Unified Framework for Spatial and Temporal Treatment Effect Boundaries: Theory and Identification
by: Kikuchi, Tatsuru
Published: (2025)

Robust Inference for the Direct Average Treatment Effect with Treatment Assignment Interference
by: Cattaneo, Matias D., et al.
Published: (2025)

Estimating Heterogeneous Treatment Effects with Item-Level Outcome Data: Insights from Item Response Theory
by: Gilbert, Joshua B., et al.
Published: (2024)

Heterogeneous Treatment Effects and Causal Mechanisms
by: Fu, Jiawei, et al.
Published: (2024)

(Visualizing) Plausible Treatment Effect Paths
by: Freyaldenhoven, Simon, et al.
Published: (2025)

Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models
by: Davezies, Laurent, et al.
Published: (2021)

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

Identification of Dynamic Panel Logit Models with Fixed Effects
by: Dobronyi, Christopher, et al.
Published: (2021)

Treatment Effect Heterogeneity in Regression Discontinuity Designs
by: Calonico, Sebastian, et al.
Published: (2025)

Estimating Treatment Effects Under Bounded Heterogeneity
by: Kwon, Soonwoo, et al.
Published: (2025)

Identifying Treatment and Spillover Effects Using Exposure Contrasts
by: Leung, Michael P.
Published: (2024)

On the Identifying Power of Generalized Monotonicity for Average Treatment Effects
by: Bai, Yuehao, et al.
Published: (2024)

Inference on Individual Treatment Effects in Nonseparable Triangular Models
by: Ma, Jun, et al.
Published: (2021)

When Do Treatment Changes Identify Causal Effects?
by: Huber, Martin
Published: (2026)

Randomization Inference For the Always-Reporter Average Treatment Effect
by: Chang, Haoge, et al.
Published: (2026)

Data Fusion for Partial Identification of Causal Effects
by: Lanners, Quinn, et al.
Published: (2025)

Identification and Semiparametric Estimation of Conditional Means from Aggregate Data
by: McCartan, Cory, et al.
Published: (2025)

Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
by: Kato, Masahiro, et al.
Published: (2024)

Extracting Mechanisms from Heterogeneous Effects: An Identification Strategy for Mediation Analysis
by: Fu, Jiawei
Published: (2024)

Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
by: Chernozhukov, Victor, et al.
Published: (2024)

Inference on the Distribution of Individual Treatment Effects in Nonseparable Triangular Models
by: Ma, Jun, et al.
Published: (2025)