Exploring the Co-Movements of Tax-to-GDP in Rwanda: A Wavelet Analysis Approach

Abstract

Clement Uwizeye

This study explores the co-movements of the Tax-to-GDP ratio with various economic indicators in Rwanda using wavelet analysis with monthly data from 2008 to 2023. The descriptive analysis reveals a generally increasing Tax-to-GDP ratio, indicating effective tax policies aligned with industry growth and nominal GDP. However, the Tax-to-GDP declined, coinciding with rising inflation, increasing interest rates, and a contracting service sector. Despite high volatility in inflation and a decreasing trend in interest rates until 2021, the Tax-to-GDP demonstrated resilience. The wavelet coherence analysis (WCA) indicates strong correlations between the Tax-to-GDP ratio and several economic variables during specific periods, particularly between 2008- 2010, 2016-2020, and 2020-2023, while weaker correlations were observed during 2010-2016, similar to robustness check using partial wavelet coherence analysis (PWCA) and Bayesian vector autoregressive model (BVAR). The study highlights the need for policymakers to sustain effective tax strategies, address economic volatility, support the service sector, ensure effective government spending, and refine policies based on periods of high coherence to optimize economic outcomes and ensure sustainable growth.

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