The study investigated the effect of the determinants of capacity utilization in Nigeria’s manufacturing sector. The objectives of the study was to determine effect of electricity power consumption, lending interest rate, total labour force, bank credit to manufacturing industries and gross capital formation on average manufacturing capacity utilization rate in Nigeria. The study utilized annual time series data obtained from World Development Indicators (WDI) for the period 1981-2019 with the help of the Auto Regressive Distributive Lag (ARDL) model of estimation.
Table of Contents
1. INTRODUCTION
1.1 Background to the study
1.2. Statement of the Problem
1.3 Objectives of the Study
1.4 Research Questions
1.5 Research Hypotheses
1.6 Significance of the Study
1.7 Scope of the Study
2. LITERATURE REVIEW
2.1. Conceptual Framework
2.1.2 Capacity Utilization
2.1.2.1. Measurement of Capacity Utilization
2.1.3 Electricity Generation Rate in Nigeria
2.1.4 Gross Fixed Capital formation
2.1.5 Lending Interest Rate in Nigeria
2.1.5.1 Management of Interest rate in Nigeria
2.1.6 Imported Goods in Nigeria
2.1.6.1 Growth Rate of Imported Goods in Nigeria
2.1.6.2 Trade Policy Trend - Import control measures
2.1.7. Labour Force and Labour Market in Nigeria
2.1.8 Commercial Bank Credits/Loans to Nigeria Manufacturing Sector
2.1.9 Overview of the Nigerian Manufacturing Sector
2.1.9.1 Contributions of Manufacturing Industries to Growth and Development of Nigeria
2.1.9.2 Determinants of Manufacturing Production in Nigeria
2.1.9.3 Problems of the Manufacturing Sector in Nigeria
2.1.9.4 An Overview of Manufacturing Policies in Nigeria
2.1.9.5 Productivity in the Nigerian Manufacturing Industry
2.1.9.6 Globalization and the manufacturing sector in Nigeria
2.1.9.7 The performance of Nigerian manufacturing firms
2.2 Theoretical Literature Review
2.2.1 The Classical Growth Theory
2.2.2 Keynesian Theory of Economic Growth
2.2.3 Theory of Production
2.2.4 The Neoclassical Growth Theory
2.2.5 The Endogenous Growth Theory
2.2.5.1 The Arrow Model
2.2.5.2 The Levhari-Sheshinski Model
2.2.5.3 The King-Robson Model
2.2.5.4 The Romer Model
2.2.5.5 The Lucas Model
2.2.5.6 Romer’s Model of Technological Change
2.2.6 Structural Change Theory
2.4 Empirical Literature Review
2.5 Summary of Empirical Literature
2.6 Gap in Empirical Literature Review
3. RESEARCH METHODOLOGY
3.1. Research Design
3.2. Theoretical Framework & Model Specification
3.2.1 Definition of Variables
3.3 Estimation Technique
3.3.1 Economic Criteria (Evaluation of apriori test)
3.3.2 Pre-Estimation Test
3.3.2.1 Stepwise Regression Analysis
3.3.2.2 Normality Test
3.3.2.3 Unit Root Test/Test for Stationarity
3.3.2.4 Augmented Dickey Fuller Test
3.3.2.5 Phillips-Perron (PP) Unit Root Tests
3.3.2.6 Cointegration Test
3.3.2.6.1 Autoregressive Distributed Lag Model (ARDL) Approach to Cointegration Testing or Bound Cointegration Testing Approach
3.3.5.6.2 Requirements for the Application of Autoregressive Distributed Lag Model (ARDL) Approach to Cointegration Testing
3.4 Post-Estimation Test
3.4.1. Error Correction Mechanism (ECM)
3.4.3. Breusch–Godfrey Test for Autocorrelation
3.4.4 Breusch–Pagan test for Heteroscadasticity
3.4.5 Stability Test
3.4.5.1 Cumulative Sum and Cumulative Sum of Squares
3.4.5.2 Ramsey Regression Equation Specification Error Test
3.4.6 Statistical Criteria (first order test)
3.4.6.1 The Co-efficient of Determination Test (R2)
3.5 Sources of Data
3.5.1 Description of Data
3.6 Software Application
4. DATA PRESENTATION, ANALYSIS AND DISCUSSION
4.1. Pre-Estimation Test
4.1.1 Descriptive Statistics
4.1.2 Unit Root Test
4.1.2.1 Trend Analysis
4.1.3 Selection of Lag Length Criteria
4.1.4 Cointegration Test
4.2 Dynamic Short Run ARDL Error Correction Model and Discussion
4.3 ARDL Long Run Form For Determinants Of Capacity Utilization In Nigeria’s Manufacturing Sector
4.4 Diagnostic Test/Post Estimation Test
4.4.1 Breusch-Godfrey Serial Correlation LM Test
4.4.2 Breusch-Pagan-Godfrey Heteroskedasticity Test
4.4.3 Stability Test
4.4.3.1 Ramsey Reset Test
4.4.3.2 Cumulative Sum and Cumulative Sum of Squares Test
4.5. Discussion of Findings
4.5.1 Effect of Electricity Power Consumption Per Capita on Average Manufacturing Capacity Utilization in Nigeria
4.5.2 Effect of Consumer Price Index on Average Manufacturing Capacity Utilization in Nigeria
4.5.3 Effect of Total labour Force on Average Manufacturing Capacity Utilization in Nigeria
4.5.4 Effect of Lending Interest Rate on Average Manufacturing Capacity Utilization in Nigeria
4.5.5 Effect of Goods Importation on Average Manufacturing Capacity Utilization in Nigeria
4.5.6 Effect of Gross Fixed Capital Formation on Average Manufacturing Capacity Utilization in Nigeria
4.5.7 Effect of Bank Credit to the Manufacturing Sector on Average Manufacturing Capacity Utilization in Nigeria
5. SUMMARY OF FINDINGS, CONCLUSION & RECOMMENDATIONS
5.1 Summary of Findings
5.2 Conclusion
5.3 Policy Recommendations
5.4 Areas for further Research
Research Objectives and Themes
The primary objective of this research is to investigate the determinants of capacity utilization within the Nigerian manufacturing sector between 1981 and 2019, specifically analyzing how macroeconomic variables influence the sector's performance and productivity.
- Analysis of electricity power consumption's impact on industrial capacity utilization.
- Evaluation of the role of gross fixed capital formation in manufacturing growth.
- Assessment of lending interest rates and their effect on industrial credit and output.
- Investigation of the relationship between goods importation, labor force availability, and bank credit to the manufacturing sector.
Auszug aus dem Buch
2.1.2 Capacity Utilization.
The concept of capacity utilization has no universally accepted meaning. This is due to the fact that different disciplines, such as political economy and organizational development, have diverse perspectives on capacity concerns. Capacity Utilization (CU) and capacity are difficult to define, let alone interpret and quantify consistently and consistently. Understanding capacity use and measuring it is essential for correctly designing a capacity management program, particularly when capacity utilization is controlled by specific constraints (Kirkley, James & Dale 2002). Capacity utilization perception is fundamentally linked to output. CU is frequently mentioned in discussions of applied and theoretical issues at both the macro and microeconomic levels, as its significance for business decision-makers grows. Excess capacity among enterprises, for example, indicates that there are components of monopolistic tendencies within certain industries (Ezu, Gideon, Sarah, Anyeneh, Ogbonnaya, 2019).
Cassel (1937) is credited with the most important work on the economic notion of capacity utilization; he distinguished between excess capacity of fixed elements (short run cost curves) and excess capacity of all factors (long run cost curves). Cassel went on to say that because the absolute technical upper limit of output obtained from fixed factors is unlikely to be within the domain of actual economic operations, capacity output should be defined as the output at which average total costs are at their lowest.
Summary of Chapters
CHAPTER ONE: INTRODUCTION: This chapter provides an overview of the manufacturing sector in Nigeria, identifies the research problem, objectives, and questions, and outlines the significance and scope of the study.
CHAPTER TWO: LITERATURE REVIEW: This chapter covers conceptual, theoretical, and empirical literature regarding capacity utilization, examining various models and historical policy trends in the Nigerian manufacturing sector.
CHAPTER THREE: RESEARCH METHODOLOGY: This chapter describes the research design, model specification, estimation techniques (ARDL), and data sources utilized for the empirical analysis.
CHAPTER FOUR: DATA PRESENTATION, ANALYSIS AND DISCUSSION: This chapter presents the empirical results, including unit root and diagnostic tests, and discusses the findings regarding the impact of various determinants on manufacturing capacity utilization.
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSION & RECOMMENDATIONS: This final chapter synthesizes the study's results, offers conclusions, and provides policy recommendations for enhancing the performance of the Nigerian manufacturing sector.
Keywords
Capacity Utilization, Manufacturing Sector, Nigeria, ARDL, Electricity Power Consumption, Gross Fixed Capital Formation, Lending Interest Rate, Bank Credit, Labor Force, Economic Growth, Inflation, Importation, Industrial Policy, Macroeconomics, Productivity.
Frequently Asked Questions
What is the core focus of this research?
The study investigates the primary determinants of capacity utilization within the Nigerian manufacturing sector, seeking to understand what factors most effectively boost production capabilities.
What are the key themes addressed in the study?
The central themes include the influence of energy supply, interest rates, capital formation, labor force availability, and bank credit on the capacity utilization of manufacturing firms.
What is the primary objective of this dissertation?
The main objective is to empirically determine the effect of specific macroeconomic variables (electricity, interest rate, labor, capital, etc.) on the average manufacturing capacity utilization rate in Nigeria to provide data-driven policy guidance.
Which scientific methodology is applied?
The study utilizes the Auto Regressive Distributive Lag (ARDL) model to perform time series analysis on data spanning from 1981 to 2019, sourced from the World Development Indicators and the Central Bank of Nigeria.
What topics are covered in the main section of the work?
The main body provides a comprehensive literature review of growth theories, a detailed research methodology, and an extensive analysis of data, followed by a discussion on the effect of each determinant on the manufacturing output.
How would you characterize this work using keywords?
Key terms include Capacity Utilization, Manufacturing Sector, Nigeria, ARDL, Electricity Consumption, Capital Formation, and Economic Growth.
How does electricity consumption specifically influence capacity utilization?
The findings indicate that electricity power consumption has a positive and significant relationship with manufacturing capacity utilization in the short run, highlighting it as a critical prerequisite for industrial growth.
What is the role of bank credit in the manufacturing sector?
The study finds that bank credit to the manufacturing sector has a positive relationship with capacity utilization, suggesting that increased access to affordable credit is essential for replacing obsolete machinery and enhancing productive capabilities.
- Arbeit zitieren
- Justin Alugbuo (Autor:in), 2022, Determinants of Capacity Utilization in Nigeria's Manufacturing Sector, München, GRIN Verlag, https://www.grin.com/document/1175869
