AI & ML
Logit-based alternatives to two-stage least squares
arXiv stat.TH0 views
arXiv:2312.10333v2 Announce Type: cross Abstract: We propose logit-based IV and augmented logit-based IV estimators that serve as alternatives to the traditionally used 2SLS estimator in the model where both the endogenous treatment variable and the corresponding instrument are binary. Our novel estimators are as easy to compute as the 2SLS estimator but have an advantage over the 2SLS estimator in terms of causal interpretability. In particular, in certain cases where the probability limits of both our estimators and the 2SLS estimator take the form of weighted-average treatment effects, our estimators are guaranteed to yield non-negative weights whereas the 2SLS estimator is not.
Source:https://arxiv.org/abs/2312.10333PreviousComplete Diagrammatic Axiomatisations of Relative EntropyNextAsymmetric conformal prediction with penalized kernel sum-of-squares
Related posts

9 LLMs im Test: Welches KI-Modell hilft bei welchem Teil der Doktorarbeit?
0dev.to AI

How AI Business Solutions Help Companies Make Data-Driven Decisions
0dev.to AI
I migrated off my no-code stack and regretted it. For nine days.
0dev.to WebDev
Why some men check Tea before a first date
0dev.to Security

Turning Visitor Data into Business Insights with People Counting Software
0dev.to Security
How a GPT-5.4 harness scored above GPT-6 Astra and Claude Code on ExtractBench
0dev.to Python