no code implementations • 19 Mar 2024 • Yunyun Wang, Tatsushi Oka, Dan Zhu
Macro variables frequently display time-varying distributions, driven by the dynamic and evolving characteristics of economic, social, and environmental factors that consistently reshape the fundamental patterns and relationships governing these variables.
1 code implementation • 8 Jun 2023 • Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
Excellent tail performance is crucial for modern machine learning tasks, such as algorithmic fairness, class imbalance, and risk-sensitive decision making, as it ensures the effective handling of challenging samples within a dataset.
no code implementations • 9 Mar 2023 • Yunyun Wang, Tatsushi Oka, Dan Zhu
Vector autoregression is an essential tool in empirical macroeconomics and finance for understanding the dynamic interdependencies among multivariate time series.
no code implementations • 7 Aug 2022 • Ruofan Xu, Jiti Gao, Tatsushi Oka, Yoon-Jae Whang
We study the estimation of heterogeneous effects of group-level policies, using quantile regression with interactive fixed effects.
no code implementations • 17 Jun 2022 • Difang Huang, Jiti Gao, Tatsushi Oka
We propose a semiparametric method to estimate the average treatment effect under the assumption of unconfoundedness given observational data.