# Estimating Conditional Average Treatment Effects with Heteroscedasticity by Model Averaging and Matching

arXiv: https://arxiv.org/abs/2304.06960 · HTML: https://mlsanity.com/paper/2304.06960/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2023.

## Built on by (most cited first, 1 of 1)

- [Estimation of conditional average treatment effects on distributed confidential data](https://mlsanity.com/paper/2402.02672/) (2024)

## Abstract (arXiv)

We propose a model averaging approach, combined with a partition and matching method to estimate the conditional average treatment effects under heteroskedastic error settings. The proposed approach has asymptotic optimality and consistency of weights and estimator. Numerical studies show that our method has good finite-sample performances.