Sep 2022,
Accepted,
Journal of American Statistical Association


We partially identify the optimal dynamic regime from observational data, relaxing sequential randomization but instead using IVs. As a first step, we establish the sharp partial ordering of welfares, which summarizes the signs of dynamic treatment effects.



July 2023,

Conditionally Accepted,
Journal of Econometrics


We propose a computational framework to calculate sharp nonparametric bounds (using binary IV that satisfies full independence) on various policy-relevant treatment parameters that are defined as weighted averages of the MTE.


Shapes as Product Differentiation ︎︎︎


with Eric Schulman, Kristen Grauman, Santhosh Ramakrishnan


arxiv ︎︎︎ slides ︎︎︎

Nov 2022

Submitted


Many differentiated products have key attributes that are high-dimensional (e.g., design, text). We consider one of the simplest design products, fonts, and quantify their shapes by constructing neural network embeddings. Using the data from the world's largest online market place for fonts, we study the causal effect of a merger on the merging firm's creative decisions of product differentiation by using the embeddings in a synthetic control method.

*This project is featured in a typography magazine ︎︎︎ and included in the MIT graduate machine learning course ︎︎︎.




Aug 2023

We provide a novel interpretation for rank similarity, which motivates us to relax it in a way that is useful to bound the QTEs using multi-valued IVs. The bounds are easy to calculate in practice and are shown to be informative.


Aug 2023


We propose a class of semiparametric models using copula to point identify and efficiently estimate dynamic treatment effects and dynamic mediator effects under treatment endogeneity.


2023,
Journal of Econometrics,
Vol. 234, pp. 732-757

Treatments are determined by strategic interaction, which poses interesting identification problems.


2021,
Journal of American Statistical Association,
Vol. 116, pp. 192-195

I discuss identification of optimal treatment rules under treatment endogeneity and propose a novel identifying condition.


2021,
Journal of Econometrics,
Vol. 225, pp. 132-147

Time-varying treatment effects are considered in a nonparametric model with treatment endogeneity.


2020,
Quantitative Economics,
Vol. 11, pp. 161-202

Using a control function approach, weak instruments are characterized as a concurvity problem.


2019,
Quantitative Economics,
Vol. 10, pp. 1019-1068

In a set of nonlinear models, we propose reparametrization that facilitates robust inference under weak identification.


© Sukjin Han