Hello!

I am a senior lecturer (assistant professor) in the Department of Economics at the National University of Mongolia and a research fellow at The Economic Institute of the National University of Mongolia. I am also a research affiliate at AI Lab, CyberAgent, Inc in Tokyo, Japan.

My research interests lie at the intersection of econometrics, machine learning and economics.

Previously, I was a research scientist at AI Lab, CyberAgent, Inc. Prior to that, I was a postdoctoral fellow at the Golub Capital Social Impact Lab led by Susan Athey at Stanford Graduate School of Business. I received a PhD in Economics from Boston University, where my main advisor was Hiroaki Kaido. My other advisors were Iván Fernández-Val, Ching-to Albert Ma and Jean-Jacques Forneron.

Here is my CV.

Contact

Email: undral_b@num.edu.mn, undral21@gmail.com

Here are links to my other profiles: Google Scholar, LinkedIn

Software

Distributional Treatment Effects and Regression Adjustment [PyPI] [GitHub]

Working papers

Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks [arxiv] with Tomu Hirata, Tatsushi Oka, Shota Yasui and Shingo Uto

The Heterogeneous Impact of Changes in Default Gift Amounts on Fundraising [preprint] with Susan Athey, Matias Cersosimo, Kristine Koutout and Shanjukta Nath

Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning [arXiv] [slides] with Susan Athey, Vitor Hadad, Sanath Krishnamurthy, Weiwen Leung and Joseph Jay Williams

Identification and Inference for Welfare Gains without Unconfoundedness [arXiv]

Publications

Distributional treatment effects of content promotion: evidence from an ABEMA field experiment [arXiv] with Shota Yasui, Tatsushi Oka, and Yuki Oishi The Japanese Economic Review, 2026

Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials [arXiv] [R code] with Tatsushi Oka, Shota Yasui and Yuta Hayakawa Econometric Reviews, 2026

Beyond the Average: Distributional Causal Inference under Imperfect Compliance [arXiv] [Python code] with Tomu Hirata, Tatsushi Oka and Shota Yasui Neural Information Processing Systems (NeurIPS), 2025

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization with Tomu Hirata, Tatsushi Oka and Shota Yasui [arXiv] [Python/R code] International Conference on Machine Learning (ICML), 2025

Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction [paper] [arXiv] [R code] with Tatsushi Oka and Shota Yasui International Conference on Machine Learning (ICML), 2024

Changing Preferences: An Experiment and Estimation of Market-Incentive Effects on Altruism [paper] [preprint] with Albert Ma and Daniel Wiesen Journal of Health Economics, Volume 92, December 2023, 102808