5 papers · 1 filter
When Predictions Become Regressors: A Split-Sample Correction for Biases in Downstream Inference
Nathan Canen, Ted Enamorado
Prediction-based methods, including Large Language Models (LLMs) and other machine learning techniques, are often used to construct measures of political phenomena that are difficu…
Empirical Challenges with Peers-of-Peers Instruments in the Linear-In-Means Model
Nathan Canen, Shantanu Chadha
In the linear-in-means model, endogeneity arises naturally due to the reflection problem. A common solution is to use Instrumental Variables (IVs) based on higher-order network lin…
Simple Inference on a Simplex-Valued Weight
Nathan Canen, Kyungchul Song
In many applications, the parameter of interest involves a simplex-valued weight which is identified as a solution to an optimization problem. Examples include synthetic control me…
Synthetic Decomposition for Counterfactual Predictions
Nathan Canen, Kyungchul Song
Counterfactual predictions are challenging when the policy variable goes beyond its pre-policy support. However, in many cases, information about the policy of interest is availabl…
A Decomposition Approach to Counterfactual Analysis in Game-Theoretic Models
Nathan Canen, Kyungchul Song
Decomposition methods are often used for producing counterfactual predictions in non-strategic settings. When the outcome of interest arises from a game-theoretic setting where age…