KoTaP: A Panel Dataset for Corporate Tax Avoidance, Performance, and Governance in Korea

TL;DR

KoTaP is a comprehensive, long-term panel dataset of Korean non-financial firms that links corporate tax avoidance to performance and governance metrics, supporting diverse research and policy applications.

Contribution

This paper introduces KoTaP, a novel, standardized panel dataset capturing Korean firms' tax avoidance, performance, and governance, reflecting unique institutional features and enabling advanced analyses.

Findings

KoTaP includes 12,653 firm-year observations from 1,754 firms.

It links tax avoidance measures with earnings, profitability, stability, growth, and governance indicators.

The dataset supports benchmarking, econometric, deep learning, and policy research.

Abstract

This study introduces the Korean Tax Avoidance Panel (KoTaP), a long-term panel dataset of non-financial firms listed on KOSPI and KOSDAQ between 2011 and 2024. After excluding financial firms, firms with non-December fiscal year ends, capital impairment, and negative pre-tax income, the final dataset consists of 12,653 firm-year observations from 1,754 firms. KoTaP is designed to treat corporate tax avoidance as a predictor variable and link it to multiple domains, including earnings management (accrual- and activity-based), profitability (ROA, ROE, CFO, LOSS), stability (LEV, CUR, SIZE, PPE, AGE, INVREC), growth (GRW, MB, TQ), and governance (BIG4, FORN, OWN). Tax avoidance itself is measured using complementary indicators cash effective tax rate (CETR), GAAP effective tax rate (GETR), and book-tax difference measures (TSTA, TSDA) with adjustments to ensure interpretability. A key strength of KoTaP is its balanced panel structure with standardized variables and its consistency with international literature on the distribution and correlation of core indicators. At the same time, it reflects distinctive institutional features of Korean firms, such as concentrated ownership, high foreign shareholding, and elevated liquidity ratios, providing both international comparability and contextual uniqueness. KoTaP enables applications in benchmarking econometric and deep learning models, external validity checks, and explainable AI analyses. It further supports policy evaluation, audit planning, and investment analysis, making it a critical open resource for accounting, finance, and interdisciplinary research.