Financial metrics for effective tax rate calculations in Johannesburg Stock Exchange (JSE) top 40 South African companies (2004-2024)

This dataset comprises longitudinal financial metrics extracted from the annual financial statements of 22 South African companies listed in the Johannesburg Stock Exchange (JSE) Top 40 Index, spanning 21 years from 2004 to 2024. The data were sourced primarily from the Iress financial database, a reputable platform providing standardised financial reporting for JSE-listed entities, and cross-verified against publicly available company annual financial statements (AFS) accessed via investor relations websites to ensure accuracy and address any gaps.The dataset focuses on key variables essential for calculating Effective Tax Rate (ETR) proxies to assess corporate tax avoidance levels. These include:Income Tax Expense: Total tax expense (current and deferred) as reported in the consolidated statement of comprehensive income, used in GAAP ETR and CFM A calculations.Profit Before Tax: Net profit before taxation from the income statement, serving as the denominator for GAAP ETR and Cash ETR.Taxation Paid: Actual cash outflows for taxes (including corporate income tax, royalties, and settlements) from the cash flow statement, applied in Cash ETR and CFM B.Cash Generated by Operations: Cash inflows from core business activities before interest and taxes, utilised as the denominator for CFM A and CFM B.The sample was purposefully selected from the JSE Top 40 Index, which represents over 80% of the JSE's market capitalisation and spans sectors such as mining (e.g., Anglo American Platinum), banking (e.g., Absa Group), retail (e.g., Shoprite Holdings), telecommunications (e.g., Vodacom Group), and others. Exclusions were applied for non-South African companies (16 excluded), those listed for fewer than 15 years (4 excluded), and sectors like insurance/REITs (2 excluded) to ensure relevance to South African tax jurisdiction and data completeness. Banking companies (6) were analysed separately for non-cash flow measures due to negative operating cash flows distorting CFM proxies. Data cleaning involved truncating ETR values to 0-100% to handle outliers from negative denominators or tax refunds, yielding approximately 400 company-year observations after processing.Data were collected via targeted Iress requests and manual AFS verification. ETR proxies were computed as follows:GAAP ETR: Income tax expense / Profit before tax.Cash ETR: Taxation paid / Profit before tax.CFM A: Income tax expense / Cash generated by operations.CFM B: Taxation paid / Cash generated by operations. Long-run versions were calculated over three-year rolling periods to mitigate short-term volatility. Analyses were performed using Microsoft Excel and IBM SPSS version 30 for descriptive and inferential statistics.