Understanding the interaction between tax revenue performance, the shadow economy, and economic growth is critical for sustainable development in Ethiopia. This study investigates the nexus among tax revenue performance, the shadow economy, and economic growth in Ethiopia over the period 1983 2024 using Vector Error Correction Models (VECM), Dynamic ARDL bounds testing, and Partial Least Squares Structural Equation Modeling (PLS SEM). The analysis focuses on four interrelated ob jectives: (i) identifying the determinants of tax revenue performance, (ii) examining the growth effects of the shadow economy, (iii) analyzing the drivers behind the relative size of the shadow economy , and ( evaluating the conditional role of
taxation in shaping economic growth outcomes. The findings on the determinants of tax revenue performance reveal that GDP per capita exerts a positive but statistically insignificant effect in the short run, consistent with the concept of tax buoyancy, whereby inc reases in income do not immediately translate into higher tax revenue. In the long run, however, GDP per capita positively and significantly affects tax revenue performance (approximately +0.25%), supporting Wagner’s Law, which posits that economic develop ment expands the fiscal capacity of the state. Tax burden reduces compliance and revenue performance in the short run, but its long run positive effect (+0.29%) suggests the presence of a fiscal adjustment mechanism consistent with Laffer Curve intuition. Foreign direct investment (FDI) shows no immediate contribution to tax revenue, yet generates significant long run gains (+0.72%), reflecting the predictions of Endogenous Growth Theory regarding capital accumulation and productivity spillovers. Sectoral c omposition also critically shapes fiscal outcomes. Agricultural value added negatively and significantly affects tax revenue in both the short and long run, reflecting the hard to tax nature of agriculture and the gradual process of structural transformati on toward more taxable sectors. Industrial value added exhibits weak short run effects but a strong negative long run effect (−1.10%), which may indicate excessive tax incentives, profit shifting, tax avoidance practices, or weak industrial tax administrat ion. The shadow economy has no significant direct short run effect on tax performance, although indirect channels, particularly through FDI, appear relevant.
Table of Contents
CHAPTER ONE
INTRODUCTION
1.1 Background of Study
1.2 Statement of the Problem
1.3. Research Objectives
1.3.1. General Objectives
1.3.2 Specific Objective
1.3.3. Research Hypothesis
1.4. Significance of the Study
1.5 Scope and Limitation
1.6 Organizations of the Study
CHAPTER TWO
REVIEW OF RELATED LITERATURE
2.1. Concept and Definition
2.2. Principle of Taxation
2.3. Theoretical Review of Literature
2.3.1. Theories of Taxation
2.3.1.1. Supply Side Taxation Theory
2.3.1.2. Public Choice Taxation Theory
2.3.1.3. Neo-Keynesian Taxation Theory
2.3.1.4. Optimal Taxation Theory
2.4. Review of Theories of Shadow Economy
2.4.1. The Basic Perspectives of Understanding the Shadow Economy
2.4.2. The Economic Dualism Theory of the Shadow Economy
2.4.3. Institutional Theory of the Underground Economy
2.4.4. Rational Choice Theory of the Shadow Economy
2.5. Theories of Economic Growth
2.5.1. The Endogenous Economic Growth Theory
2.5.2. The Institutional Economic Growth Theory
2.5.3. The Supply- Side Economic Growth Theory
2.5.4. The Neo Keynesians Economic Growth Theory
2.5.5. Overall Summary of Theoretical Literature Used in Dynamic Nexus among Tax Revenue Performance, the Shadow Economy, and Economic Growth of Ethiopia (1983–2024)
2.6. Empirical Review of Literature
2.6.1. Empirical Literature Regarding Determinants of Tax Revenue, Shadow Economy and Economic Growth,
2.6.1.1. Determinants of Tax Revenue Performance in Ethiopia
2.6.1.2. The Effect of the Shadow Economy on Ethiopia's Economic Growth
2.6.1.3. Drivers behind the relative size of the shadow economy in Ethiopia;
2.6.2. The conditional role of taxation in shaping economic growth outcomes in Ethiopian
2.7. Empirical Research Gaps
2.8. Conceptual Framework
CHAPTER THREE
RESEARCH METHODOLOGY
INTRODUCTION:
3.1 Description of the Study Area
3.2. Research Philosophy and Paradigm
3.3. Research Design and Approach
3.3.1. Research Design
3.3.2. Research Approach
3.4. Type and Source of Data
3.4.1. Data Accessing Methods
3.4.2. Methods of Data Analysis
3.5. Model Specification
3.5.1. Vector Error Correction Model (VECM)
3.5.1.1. Mathematical Model Specification
3.5.1.2. Econometrics Model Specifications:
3.5.1.2.1. Identify the determinants of tax revenue performance in Ethiopia
3.5.1.2.2. Analyze the drivers behind the relative size of the shadow economy in Ethiopia
3.5.2. Dynamic Autoregressive Distributed Lag (ARDL) Model
3.5.2.1. Mathematical Model Specifications
3.5.2.2. Econometrics Model Specifications:
3.5.2.2.1. Identify the Key Determinants of Tax Revenue Performance of Ethiopian
3.5.3. Evaluate the conditional role of taxation in shaping economic growth outcomes in Ethiopian
3.5.3.1. The Mathematical Model Specification
3.5.3.2. The Econometrics Model Specification
3.5.3.2.1. The Effect of Tax Revenue on Economic Growth is Negatively Moderated on Countries Relative Size of Shadow Economy
3.5.3.2.2. The Effect of Tax Revenue on Economic Growth is positively Moderated on Gross Fixed Capital formation
3.5.3.2.3. The Effect of Tax Revenue on Economic Growth is positively Moderated on Gross Fixed Capital formation
3.6. Data Validity and Reliability
3.7 Ethical Considerations
CHAPTER FOUR
ETHIOPIAN TAX REVENUE PERFORMANCE, THE SHADOW ECONOMY, AND ECONOMIC GROWTH: CHARACTERISTICS AND TREND ANALYSIS
INTRODUCTION
4.1. Ethiopian Tax Revenue Performance, the Shadow Economy, and Economic Growth: Characteristics and Trend Analysis
4.1.1. Ethiopian Tax Revenue Performance Characteristics and Trend Analysis
4.1.1.1. Ethiopian Tax Revenue Performance Characteristics
4.1.1.2. Ethiopian Tax Revenue Performance Trend Analysis
4.1.2. Ethiopian Shadow Economy Characteristics and Trend Analysis
4.1.2.1. The Basic Characteristics of the Shadow Economy in Ethiopia
4.1.2.2. Ethiopian Shadow Economy Trend Analysis
4.1.3. Ethiopian Economic Growth Characteristics and Trend Analysis
4.1.3.1. Ethiopian Economic Growth Characteristics
4.1.3.2. Ethiopian Economic Growth Trend Analysis
4.2. The Interaction between Economic Growth and Unemployment Rate in Ethiopia
4.3. The Interaction between Economic Growth and Tax Revenue Performance in Ethiopia
4.4. The Interaction between Economic Growth and the Size of Shadow Economy in Ethiopia
4.5. The Interaction between Economic Growth and Gini Coefficient in Ethiopia
4.6. The Interaction between Economic Growth and FDI Inflows, in Ethiopia
4.7. The Interaction between Economic Growth and Average Annual Lief Expectancy in Ethiopia
CHAPTER FIVE
IDENTIFYING THE DETERMINANTS OF TAX REVENUE PERFORMANCE IN ETHIOPIA
5.1. Introduction
5.2. Pre Model Estimation Test Results
5.2.1. Descriptive Statistics
5.2.2. Unit Root Tests (Stationarity Check):
5.2.3. Optimal Lag Length Selection
5.2.4. Johansen Cointegration Test
5.3. Vector Error Correction Estimation
5.3.1. Estimation of Long Run
5.3.2. Short Run Dynamics
5.3.3. The Indications of the Constant Term
5.3.4. Residual Diagnostic Tests
5.3.5. Autocorrelation LM Test
5.3.6. Normality test (Jarque-Bera)
5.3.7. Cointegration validity (stability) Test graph
5.3.8. Impulse Response Functions (IRFs)
5.4. Interpretation of Key Findings:
5.6. Discussions of Research Findings
CHAPTER SIX
EXAMINING THE GROWTH EFFECT OF THE SHADOW ECONOMY IN ETHIOPIAN
6.1. Introduction
6.2. Pre Model Estimation Test Results
6.2.1. Descriptive Statistics
6.2.2. Unit Root Tests (Stationarity Check):
6.2.3. Lag Length Selection and Over All Model Goodness of Fit Test
6.2.4: ARDL Model Long Run Estimation
6.2.5: ARDL Short Run Estimation
6.3. Post-Estimation Diagnostic Tests
6.3.1. Serial Correlation (Breusch-Godfrey LM Test)
6.3.2. Heteroskedasticity (Breusch-Pagan-Godfrey or ARCH) Test
6.3.3. Normality Test (Jarque-Bera)
6.3.4. Stability Tests
6.3.4.1. Ramsey RESET
6.3.4.2.1. CUSUM (Cumulative Sum) Test Result
6.3.4.2.1. CUSUM of Squares Test
6.4. Findings of the Study
6.5. Interpretation of Research Findings
6.6. Discussions of Research Findings
CHAPTER SEVEN
ANALYZING THE DRIVERS BEHIND THE RELATIVE SIZE OF SHADOW ECONOMY IN ETHIOPIA
7.1 Introduction
7.2. Model Estimation Tests
7.2.1. Descriptive Statistics
7.2.2. Unit Root Tests (Stationarity Check):
7.2.3. Optimal Lag Length Selection
7.2.4. Johansen Cointegration Test
7.2.5. Vector Error Correction Estimation
7.2.5.1. Estimation of Long Run
7.2.5.2. Short Run Dynamics
7.3. Residual Diagnostic Tests
7.3.1. Autocorrelation LM Test
7.3.2. Jarque-Bera Test
7.3.3. Heteroskedasticity Test
7.3.4. Cointegration validity (stability) Test graph
7.3.5. Impulse Response Functions (IRFs)
7.4. Finding, Interpretations and Discussions
7.4.1. Findings of the Study
7.4.2. Interpretation of the Research Findings
7.4.3. Discussions of Research Findings
CHAPTER EIGHT
EVALUATING THE CONDITIONAL ROLE OF TAXATION IN SHAPING ECONOMIC GROWTH OUTCOMES IN ETHIOPIA
8.1 Introduction
8.2. Moderation Effect of the Shadow Economy (Hypothesis 1)
8.2.1. Pre-Model Estimation Tests
8.2.1.1. Descriptive Statistics
8.2.1.2. Variance Inflation Factor
8.2.1.3. Confirmatory Tetrad Analysis (CTA)
8.2.1.4. Construct Reliability and Validity
8.2.1.5. Discriminant Validity Heterotrait-Monotrait (HTMT) Ratio
8.2.1.6. R² Values
8.2.1.7. Model Fitness
8.2.2. Post-Estimation Diagnostics Test
8.2.2.1. Path Coefficient Matrix
8.2.2.2. Bootstrapping Path Coefficient
8.2.2.3. F² Values
8.2.2.4. Simple Slope Analysis
8.3. Moderation Effect of Gross Fixed Capital Formation (Hypothesis 2)
8.3.1. Pre-Model Estimation Tests
8.3.1.1. Descriptive Statistics
8.3.1.2. Variance Inflation Factor
8.3.1.3. Confirmatory Tetrad Analysis (CTA)
8.3.1.4. Construct Reliability and Validity
8.3.1.5. Discriminant Validity Heterotrait- Monotrait (HTMT) Ratio
8.3.1.6. R² Values
8.3.1.7. Model Fitness
8.3.2. Post-Model Estimation Tests
8.3.2.1. Path Coefficient Matrix
8.3.2.2. Bootstrapping Path Coefficient
8.3.2.3. F² Values
8.3.2.4. Simple Slope Analysis
8.4. Moderating Effect of Government Regulatory Quality Index (GRQI)
8.4.1. Pre-Model Estimation
8.4.1.1. Descriptive Statistics
8.4.1.2. Variance Inflation Factor
8.4.1.3. Confirmatory Tetrad Analysis (CTA)
8.4.1.4. Construct Reliability and Validity
8.4.1.5. Discriminant Validity Heterotrait- Monotrait (HTMT) Ratio
8.4.1.6. R² Values
8.4.1.7. Model Fitness
8.4.2. Post- Model Estimation Tests
8.4.2.1. Path Coefficient Matrix
8.4.2.2. Bootstrapping Path Coefficient
8.4.2.3. F² Values
8.4.2.4. Simple Slope Analysis
8.5. Findings of the Study about Moderation Effect
8.6. Interpretation of Findings of the Study
8.7 Discussions of the Findings
CHAPTER NINE
SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
9.1. Summary of Findings of the Study
9.2. Conclusions
9.3. Policy Recommendations
9.4. Suggestions for Future Research
Research Objectives & Key Themes
This dissertation aims to conduct an empirical analysis of the nexus between tax revenue performance, the shadow economy, and economic growth in Ethiopia over the period 1983-2024. The research identifies the determinants of tax revenue performance, evaluates the growth effects of the shadow economy, and assesses the structural drivers of informality, while also examining the conditional role of taxation in shaping growth outcomes.
- Determinants of tax revenue performance in Ethiopia.
- Economic growth effects of the shadow economy.
- Structural drivers and policy moderators of informality.
- Conditional role of taxation on economic growth.
- Integrated econometric analysis (VECM, ARDL, PLS-SEM).
Excerpt from the Book
1.1 Background of Study
A well-designed and context-sensitive fiscal policy is fundamental to macroeconomic stability, efficient resource allocation, and sustainable economic growth. The management of government revenue and expenditure, makes fiscal policy to contributes to price stability, employment creation, infrastructure development, and long-term structural transformation (Balasoiu et al., 2023). Among the major instruments of fiscal policy, taxation constitutes the principal source of domestic revenue that enables governments to finance public services, strengthen institutions, and support economic development (Carvalho e Costa & Vieira, 2020). In both neoclassical and endogenous growth frameworks, sustainable economic growth depends not only on factor accumulation but also on the state’s capacity to mobilize reliable domestic revenue to finance productive public investment, human capital formation, and technological progress (Barro, 1990; Solow, 1956). Consequently, efficient tax systems are considered indispensable for enhancing fiscal sustainability, promoting investment, and reducing dependence on external financing.
Despite the importance of taxation, domestic revenue mobilization remains a major challenge in many developing economies. While advanced economies generally collect between 25 and 45 percent of GDP in tax revenue, developing countries mobilize only about 10 to 20 percent (Besley & Persson, 2014). Empirical evidence suggests that countries with tax-to-GDP ratios exceedingly approximately 12.75 percent tend to experience more sustainable growth acceleration (Gasper et al., 2016). However, many low-income countries remain below this threshold due to structural constraints such as narrow tax bases, weak tax administration, high informality, corruption, and limited institutional capacity (Danladi, 2020). In addition, the expansion of the digital economy, illicit financial flows, and cross-border tax evasion further complicate domestic revenue mobilization efforts (Agrawal, 2017). Weak governance systems and complex tax structures also reduce taxpayer compliance and public trust in fiscal institutions (Augustine, 2020).
Summary of Chapters
CHAPTER ONE: INTRODUCTION: Outlines the research background, statement of the problem, and objectives regarding fiscal policy in Ethiopia.
CHAPTER TWO: REVIEW OF RELATED LITERATURE: Provides a comprehensive overview of taxation, the shadow economy, and economic growth theories.
CHAPTER THREE: RESEARCH METHODOLOGY: Details the study area, data sources, and the VECM, ARDL, and PLS-SEM econometric models.
CHAPTER FOUR: ETHIOPIAN TAX REVENUE PERFORMANCE, THE SHADOW ECONOMY, AND ECONOMIC GROWTH: CHARACTERISTICS AND TREND ANALYSIS: Analyzes historical trends and current fiscal conditions in Ethiopia.
CHAPTER FIVE: IDENTIFYING THE DETERMINANTS OF TAX REVENUE PERFORMANCE IN ETHIOPIA: Uses VECM to isolate key drivers of national tax performance.
CHAPTER SIX: EXAMINING THE GROWTH EFFECT OF THE SHADOW ECONOMY IN ETHIOPIAN: Investigates the economic impact of the informal sector using the ARDL model.
CHAPTER SEVEN: ANALYZING THE DRIVERS BEHIND THE RELATIVE SIZE OF SHADOW ECONOMY IN ETHIOPIA: Identifies the structural and institutional factors influencing the extent of the shadow economy.
CHAPTER EIGHT: EVALUATING THE CONDITIONAL ROLE OF TAXATION IN SHAPING ECONOMIC GROWTH OUTCOMES IN ETHIOPIA: Utilizes PLS-SEM to analyze the moderation effects of the shadow economy and capital formation.
CHAPTER NINE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS: Synthesizes the findings and provides strategic policy recommendations for fiscal sustainability.
Keywords
Tax burden, shadow economy, tax revenue performance, economic growth, regulatory quality, Ethiopia, fiscal policy, informality, structural transformation, domestic resource mobilization, institutional quality, GDP, econometrics, ARDL, VECM, PLS-SEM.
Frequently Asked Questions
What is the core focus of this dissertation?
The research focuses on the dynamic relationships between tax revenue performance, the shadow economy, and economic growth in Ethiopia over the period 1983–2024.
What are the primary thematic areas covered?
The study examines the determinants of tax revenue, the economic growth effects of the shadow economy, the structural drivers of informality, and the conditional influence of taxation on fiscal outcomes.
What is the overarching research goal?
The goal is to provide an evidence-based framework for strengthening domestic revenue mobilization and sustainable economic growth in a developing economy context.
Which scientific methodologies are employed?
The study uses a triangulation of advanced econometric methods including the Vector Error Correction Model (VECM), Dynamic ARDL bounds testing, and Partial Least Squares Structural Equation Modeling (PLS-SEM).
What does the main body explore?
The main chapters provide historical analysis, econometric estimation of determinants, an assessment of the shadow economy's impact, and moderation analysis testing the influence of institutional quality and investment.
Which key terms characterize the research?
Key terms include tax-to-GDP ratio, shadow economy, fiscal sustainability, structural transformation, institutional quality, and economic growth.
How does the shadow economy interact with tax performance in the Ethiopian context?
The study finds that the shadow economy acts as a destabilizing force in the long run, eroding the tax base and undermining the fiscal contract, despite showing potential for short-term "buffer" effects.
What are the significant policy implications for Ethiopia?
The research emphasizes the necessity of shifting from punitive enforcement to incentive-based formalization strategies, prioritizing administrative digitalization, and strengthening regulatory quality to enhance the productivity of public investment.
- Quote paper
- Cherinet Bariso (Author), 2026, Tax Revenue Performance, Shadow Economy and Growth of Ethiopia, Munich, GRIN Verlag, https://www.grin.com/document/1737318
