Search Results for author: Tatsushi Oka

Found 6 papers, 2 papers with code

Inflation Target at Risk: A Time-varying Parameter Distributional Regression

no code implementations19 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.


Safe Collaborative Filtering

1 code implementation8 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.

Collaborative Filtering Computational Efficiency +3

Distributional Vector Autoregression: Eliciting Macro and Financial Dependence

no code implementations9 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.

Time Series Time Series Analysis

Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects

no code implementations7 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.

quantile regression

Semiparametric Single-Index Estimation for Average Treatment Effects

no code implementations17 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.


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