Joonho (Phil) Hwang

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🏫 PhD student, Seoul National University
CV: Download PDF | Email: jhhwang24@snu.ac.kr

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Hello. My name is Joonho (Phil) Hwang (ν™©μ€€ν˜Έ; ι»ƒδΏŠζ™§), and I am a fifth-year PhD student in economics at Seoul National University, where I am fortunate to be advised by Professor Seojeong Lee. My research interests are in econometrics, with a particular focus on

Working papers

Online Updating for Linear Panel Regressions
joint with Seojeong Lee
πŸ† The Best Third-Year Paper Award in Department of Economics @ SNU
ABS
In this paper, we develop online updating methods for linear panel regression models. Online updating refers to procedures for sequentially updating parameter estimates as new data become available. In practice, the potential size of the dataset or data confidentiality constraints may preclude researchers from storing or accessing the entire dataset. We propose an online updating procedure for widely used linear regression models in panel data, where data expansion can occur through either (1) the arrival of new units or (2) the arrival of additional time periods for existing units. The proposed procedure yields closed-form expressions for updating both the point estimates and associated standard errors in each scenario.

What is online updating? See the example below:
Online Updating Beta Path GIF
presented at: SNU Econometrics Workshop, SETA 2025, University of Sydney, KERIC 2025, SNU Workshop on Recent Advances in Econometrics
On the Failure of the Bracketing Relationship in Staggered Treatment Designs
ABS
It is often for applied researchers to face a dilemma whether to include lagged dependent variables or not. Following Angrist & Pischke (2009), much research relies on a so-called bracketing relationship, treating specifications with and without lagged outcomes as bounds for the true causal effect. In this paper, we demonstrate that this heuristic can break down in staggered two-way fixed effects settings.

Work in progress

Deep Panel Quantile Regression
joint with Chencheng Fang and Gayeon Hong
Synthetic Difference-in-Differences with Missing Post-Treatment Outcomes
joint with Chencheng Fang