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Found 9 papers, 1 papers with code
Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
This representation allows us to introduce an identifying assumption, so-called copula invariance, that restricts the local dependence of the copula with respect to the treatment propensity.
Inference for Interval-Identified Parameters Selected from an Estimated Set
Interval identification of parameters such as average treatment effects, average partial effects and welfare is particularly common when using observational data and experimental data with imperfect compliance due to the endogeneity of individuals' treatment uptake.
Set-Valued Control Functions
The control function approach allows the researcher to identify various causal effects of interest.
Testing Information Ordering for Strategic Agents
A key primitive of a strategic environment is the information available to players.
Policy Learning with Distributional Welfare
In this paper, we explore optimal treatment allocation policies that target distributional welfare.
On Quantile Treatment Effects, Rank Similarity, and Variation of Instrumental Variables
This paper investigates how certain relationship between observed and counterfactual distributions serves as an identifying condition for treatment effects when the treatment is endogenous, and shows that this condition holds in a range of nonparametric models for treatment effects.
Shapes as Product Differentiation: Neural Network Embedding in the Analysis of Markets for Fonts
We then study the causal effects of a merger on the merging firm's creative decisions using the constructed measures in a synthetic control method.
A Computational Approach to Identification of Treatment Effects for Policy Evaluation
For counterfactual policy evaluation, it is important to ensure that treatment parameters are relevant to policies in question.
Optimal Dynamic Treatment Regimes and Partial Welfare Ordering
We propose the notion of sharp partial ordering of counterfactual welfares with respect to dynamic regimes and establish mapping from data to partial ordering via a set of linear programs.
