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Using machine learning metrics to provide deeper insights into the performance of choice models
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Beyond Pretrends: A Discordance-Based Sensitivity 分析 (Analysis) for Difference-in-Differences
Beyond Pretrends: A Discordance-Based Sensitivity Analysis for Difference-in-Differences
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Conformal Policy 学习 (Learning) with Distribution-Free Safety Guarantees
Conformal Policy Learning with Distribution-Free Safety Guarantees
👁 209 📚 19
Penalized Maximum Likelihood 推断 (Inference) of Core-Periphery Networks
Penalized Maximum Likelihood Inference of Core-Periphery Networks
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Does p-Hacking Mitigate or Exacerbate the Effects of Publication Bias?
👁 182 📚 29
Off-policy causal estimation in networks
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Causal Non-causal State Space 模型 (Model)s and the 模型 (Model)ling of Financial Bubbles
Causal Non-causal State Space Models and the Modelling of Financial Bubbles
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Efficient tensor bases for pairwise comparisons
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Testing selection on observables in parametric models with refreshment samples
👁 211 📚 8
Across-Design Uncertainty in Short Pricing Panels: Evidence from Simulated Price Trajectories
👁 109 📚 30
A Privacy Budgeting Framework for Online Experimentation
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Don't Drop the Singletons: Efficient 推断 (Inference) for Pairwise Experiments with Independent Attrit...
Don't Drop the Singletons: Efficient Inference for Pairwise Experiments with Independent Attrition
👁 155 📚 21
The Limits of Experimental Design: Covariate Balance Beyond Low Dimension
👁 86 📚 30
Measuring the Arrow of Time: Identification, 估计 (Estimation), and 推断 (Inference) for Directional Str...
Measuring the Arrow of Time: Identification, Estimation, and Inference for Directional Structure in ...
👁 197 📚 29
学习 (Learning) about Treatment Effects in Panels under Unknown Interference
Learning about Treatment Effects in Panels under Unknown Interference
👁 197 📚 30
Bias-robust causal inference for panel data
👁 65 📚 17
A Simple Approximation to the Distribution of the Ridge 回归 (Regression) Estimator
A Simple Approximation to the Distribution of the Ridge Regression Estimator
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Debiased Machine 学习 (Learning): Identification, 估计 (Estimation), and Shape Constraints
Debiased Machine Learning: Identification, Estimation, and Shape Constraints
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Stochastic Potential Choices and Outcomes
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Identifying Treatment and Spillover Effects with Control-Based and Forecast-Based Counterfactuals
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