Global Representation of the Conditional Late Model
A Separability Result
Bibliographic Data
| ID | 21512792 |
|---|---|
| Authors | Yu‐Chang Chen (0000-0003-3851-6902, Department of Economics UC San Diego La Jolla CA USA, corresponding author), Haitian Xie (0000-0003-4284-081X, Department of Economics UC San Diego La Jolla CA USA, corresponding author) |
| Year | 2022 |
| Volume | 84 |
| Issue | 4 |
| Pages | 789-798 |
| Publication date | 2022-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Oxford Bulletin of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0305-9049 • E-ISSN: 1468-0084 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/obes.12476 |
| OpenAlex | W4200509893 |
| Language | EN |
| Citations received | 1 |
| References cited | 12 |
This paper studies the latent index representation of the conditional LATE model, making explicit the role of covariates in treatment selection. We find that if the directions of the monotonicity condition are the same across all values of the conditioning covariate, which is often assumed in the literature, then the treatment choice equation has to satisfy a separability condition between the instrument and the covariate. This global representation result establishes testable restrictions imposed on the way covariates enter the treatment choice equation. We later extend the representation theorem to incorporate multiple ordered levels of treatment
Covariate · Econometrics · Mathematical analysis · Monotonic function · Statistics · Advanced Causal Inference Techniques · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods in Clinical Trials · Artificial Intelligence
Structural Equations, Treatment Effects, and Econometric Policy Evaluation1
Semiparametric instrumental variable estimation of treatment response models
Estimating Marginal Returns to Education
Identification and Estimation of Local Average Treatment Effects
Ordered Discrete-Choice Selection Models and Local Average Treatment Effect Assumptions
Who Benefits from Universal Child Care? Estimating Marginal Returns to Early Child Care Attendance
| Unique citing works | 1 |
|---|---|
| Citations per year | 0.5 |
| Citation span | 2024 - 2024 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |