The nexus of taxation and economic growth, income inequality and poverty : a macro and micro econometric approach for Zambia

Abstract

Sub-Saharan Africa faces a significant challenge in mobilising tax revenue to finance essential state functions, as many economies in the region fall below the minimum desirable tax-to-GDP ratio of 15%. Despite Zambia's relatively higher tax-to-GDP ratio compared to that of other regions, poverty and income inequality levels remain stubbornly high. This research study addresses this issue by examining the relationships between taxation, economic growth, poverty, and income inequality in Zambia. The study's objectives include investigating the short-term and long-term connections between taxation and economic growth, exploring the direction of causality, and analysing the influence of direct and indirect taxes on poverty and income inequality. Additionally, the study aims to construct a tax revenue forecasting model for Zambia and offer policy recommendations. To achieve these objectives, the researcher employed a combination of macroeconometric and microsimulation models, including vector error-correction models (VECMs), autoregressive distributed lag models (ARDLs), bunching techniques, and MicroZAMOD. This study makes several significant contributions to the literature by utilising a combination of macroeconometric and microsimulation models, incorporating mining sector revenues in the analysis, and providing revenue projections for Zambia. In addition, the study computes poverty and inequality multipliers for every additional 1 billion Kwacha in tax revenue. To unearth the effect of taxation and its redistributive effect on poverty and inequality, this study uses the MicroZAMOD. Furthermore, the study uses the Personal Income Tax (PIT) elasticities from bunching techniques to convert the MicroZAMOD from a static model to a dynamic model. The results reveal that there is evidence of bunching around the first bracket in the PIT. Key findings underscore PIT as a potent instrument for reducing inequality, while the value added tax (VAT) emerges as a significant revenue generator but is inefficient at reducing poverty. Excise taxes and the turnover tax (TOT) have marginal effects on poverty and inequality metrics. Notably, VAT is associated with a 0.45 percentage point increase in the national poverty rate for every billion Kwacha raised, while a 1 billion Kwacha of PIT revenue is associated with an average reduction of 0.68 percentage points in the Gini coefficient. Granger causality analysis suggests that PIT, the corporate income tax (CIT), VAT, changes in the copper price, and mining tax revenue have causal relationships with gross domestic product. (GDP), indicating that lagged values of these variables enhance the model's ability to predict GDP. Additionally, impulse response function and variance decomposition analysis reveal the impact of shocks in these variables on GDP, with VAT notably contributing to GDP growth over time, while negative shocks in mining tax revenue consistently result in GDP decline. In the short run, corporate income tax and personal income tax negatively impact GDP growth, while value-added tax (VAT) and trade openness have positive effects. Conversely, mining tax revenue and government consumption show no significant short-term impact on GDP growth. Long-term analysis reveals that VAT, mining tax revenue, trade openness, and the exchange rate positively influence GDP growth, whereas personal income tax and oil price changes exhibit negative impacts This will be the first study to use these two approaches to model policy impacts in a developing country. Furthermore, this study offers essential insights for policymakers in Zambia and other developing countries by emphasising the importance of balanced taxation policies and targeted investments in key sectors for sustainable development and poverty reduction through the recommendation of empirical policy reform scenarios.