As most developing countries strive to achieve economic growth and development through taxation, they face numerous economic challenges. The debate on the effectiveness of taxes as a tool for promoting growth and development remains inconclusive, as several studies have indicated mixed impacts of tax on economic growth. Against this background, the study investigated the impact of taxation on economic growth in Africa from 2004 to 2013. The study carried out various preliminary tests including descriptive statistics, and stationary tests using Augmented Dickey Fuller (ADF) test, Levin et al. test, Im, Pesaran and Shin W-stat tests. The appropriate fixed and random effect test was employed to determine the fitness of the model using the Hausman test. The study conducted the Hausman-Test to determine the appropriate estimator between Fixed and Random Effect. To confirm the robustness and validity of regression model, some post estimation tests are conducted which were omitted Variable Test, and Heteroscedasticity test. Findings indicated that tax revenue is positively related to GDP and promotes Economic Growth in Africa. It was significant at 5% level. The study concluded that tax revenue has a significant positive relationship with Gross Domestic Product. Therefore, high and weak levels of taxation are favorable to economic growth as upheld by the economic effect of Ibn Khaldun’s theory on taxation, which approves the positive impact that lower tax rate have on work, output and economic performance. However, in the midst of harsh economic conditions such as crashing oil prices, rising exchange rates, drop in Naira value, the governments should be ready to develop a comprehensive tax structure or model that will grow, nurture and sustain its tax economic base so as to drive economic performance.
Key words: Taxation revenue, economic growth, Johansen cointegration test, fixed and random effect, panel data.
Copyright © 2019 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0