Determinants of tax revenue performance in South Africa for the period 1990-2018

This study investigates the determinants of tax revenue performance in South Africa using time series data from 1990–2018. The study uses Augmented Dickey Fuller and the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests to test stationarity in time series, while Johansen co-integration and error correction models identify long-run and short-run dynamics among variables. The results of the study revealed that Gross Domestic Product (GDP) per capita, foreign direct investment, and trade openness are statistically significant and positively related to tax revenue performance. Unemployment was found to be statistically significant but also negatively correlated with tax revenue performance, while inflation was found to be negative but not statistically significant. The research's diagnostic tests confirmed the validity of the study model, revealing no serial correlation, heteroscedasticity, and a stable and correctly specified model. This study assists policy makers in having a thorough understanding of the determinants of tax revenue performance, and as a result, policymakers may create tax laws that complement the nation's economic environment. Knowing which variables, like GDP per capita, foreign direct investment, and trade openness, have a favourable impact on tax collection allows for more focused policy interventions. Understanding the relationship between tax rates and revenue performance is helpful in determining the ideal tax rates. Based on empirical data, policymakers can modify tax rates to maximise revenue without inhibiting economic growth. The study recommends that the South African government should enhance GDP, encourage foreign direct investment, decrease unemployment, and promote trade openness to enhance tax revenue performance.