We develop a new class of tree-based models (P-Tree) for analyzing (unbalanced) panel data utilizing global (instead of local) split criteria that incorporate economic guidance to guard against overfitting while preserving interpretability. We grow a P-Tree top-down to split the cross section of...

We investigate the potential for Large Language Models (LLMs) to enhance scientific practice within experimentation by identifying key areas, directions, and implications. First, we discuss how these models can improve experimental design, including improving the elicitation wording, coding...

Researchers using instrumental variables to investigate ordered treatments often recode treatment into an indicator for any exposure. We investigate this estimand under the assumption that the instruments shift compliers from no treatment to some but not from some treatment to more. We show that...

This is an invited chapter for the forthcoming Volume 4 of the Handbook of Industrial Organization. We present empirical models of demand and supply in differentiated products industries with an emphasis on the key ideas arising from the recent applied literature. We start with a discussion of...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...

This paper considers methods for defining aggregate parameters of interest in a difference-in-differences design with a continuous and staggered treatment. It also discusses how aggregation choices often simplify estimation

This paper introduces the concept of a "trimmed aggregate ATT," which is a weighted average of a set of group-time average treatment effect on the treated (ATT) parameters identified in a staggered adoption difference-in-differences (DID) design. The set of identified group-time ATTs that...

This paper examines the econometric causal model and the interpretation of empirical evidence based on thought experiments that was developed by Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two currently popular causal frameworks: the Neyman-Rubin causal model...