RAMuST: A Regime-Aware Multiscale and Mixed-Frequency Transformer for Industry-Level Corporate Income Tax Forecasting

Taewan You

Keywords: Regime aware, Mixed frequency, Transformer, Corporation Income tax, forecasting

TL;DR: we present Regime-aware Multi-scale, a mixed-frequency Transformer-based architecture for industry-level corporation income tax forecasting

Abstract:

We present the Regime-Aware Multiscale Transformer (RAMuST), a mixed-
frequency Transformer-based architecture that couples a multi-scale monthly en-
coder with a yearly regime/shock head and a Transformer decoder for industry-
level corporate income tax forecasting. In mixed-frequency data, monthly
macro–economic and financial indicators are patchified at several temporal scales
and fused through a soft scale gate integrated with economic cycle, trends, volatil-
ity, and seasonality, while yearly regime embeddings and a shock scalar summa-
rize within-year dynamics and transient disturbances. To analyze the model, we
designate the 2021–2024 window—covering the post COVID-19 period—as the
validation interval and focus on the two most volatile Korean industries, Human
health and Real estate activities, for corporate income tax forecasting. As a result of
experiments, the model consistently surpasses recent strong time-series baselines
by at least threefold and up to tenfold.

Submission Number: 32