Due to the rapid emergence of financial factors as well as the sustainable development goals of energy efficiency, this research focuses on determining whether financial factors can have a major impact on energy efficiency. The growing concern about environmental problems directly related to energy production and consumption includes climate change. The methods that the GCC countries are moving to use to reduce the consumption of energy are through financial factors. This is in line with the sustainable development goals of the UN (United Nation), which is the global organization of which the GCC is a part.
Tests were carried out to see if the dependent variable, Energy intensity can be influenced by different variables of financial factors. The fixed effects model and histograms were used to represent the level of distribution of the skewness and kurtosis as well as the effect of each variable. The results concluded that although it might be possible to have an impact, these economic factors showed a low effect on the size of the impact.
First and foremost, I would like to thank Almighty Allah for giving me the knowledge, strength and ability to complete my thesis. Finally, I would like to deeply thank my family, who have been with me every step of the way and for their constant encouragement on this journey.
Introduction 8
- Background 8
- Problem statement 13
- Aims and objective 13
- Research question 14
- Scope and limitation 14
Energy efficiency and the financial sector must work together to improve the increasing demand for energy sustainability. However, I want to test whether financial factors can affect energy efficiency using different financial instruments. Fintech, Green finance and financial inclusion will be taken into account to see if these factors can have an influence on energy efficiency.
The research will answer the question "Is there a connection between financial technology, green finance, financial inclusion and energy efficiency and sustainability?". This study will test the relationship between financial factors and energy efficiency in GCC countries. By conducting this research, the study will answer whether the three financial factors are related to energy efficiency in the GCC.
This research will test the empirical role of fintech, green finance and financial inclusion on energy efficiency in four of the GCC countries. What is the relationship between fintech, green finance, financial inclusion and energy efficiency in the GCC countries.
Literature review 15
Methodology 16
- Research Design 16
- Hypothesis of the Research 17
- Model Specification 17
- Variables 19
This confirmation was confirmed by the outcomes of the Conference of the Parties to the Paris Agreement in 2016 COP 21. 17 green financing and financial inclusion on energy efficiency and sustainability, as it explains which factors have an impact. The model used to study the effect is a multiple linear regression model, which is a branch of the simple linear regression model.
The multiple linear regression is a simple regression model that estimates the relationship between a quantitative dependent variable and several independent variables using a straight line. The dependent variable will be energy intensity, as the effect of financial factors on energy efficiency was studied. Energy intensity is an indication of how much energy is used to produce one unit of economic output.
GNI gross national income=GDP+(money flowing from abroad - money flowing abroad.
Results and Discussion 20
Results 20
First, the estimated equation calculates a dependent variable and several independent variables to obtain the coefficient and probability of the variable. The ideal shape to look for in the case of normality is a bell-shaped distribution. The extent of conservation of natural resources is a long right tail in positive skewness as it is greater than 1, at 1.113210.
Financial technology is the use of technological innovation that competes with traditional financial techniques in the provision of financial services. The kurtosis data has lighter tails than a normal distribution since it is less than 3, at 2.108327. However, because the data coefficient is larger than the cross-sectional data, it is not possible to test the random effect for this research.
This suggests that a fixed-effect model is more appropriate to account for the results of the available data of this study. In the fixed-effect model, the Durbin-Watson test shows a value of 0.506642, indicating that the autocorrelation is positive. Specifies the percentage of variance in the target field explained by the input or inputs.
Adjusted R-squared can give a more accurate picture of correlation by also considering how many independent variables are added to a given model. The study considered four of the six GCC countries and the years 2001 to 2020 to conduct this analysis. As can be seen in the results section, it was concluded that while it might be possible to influence these several independent variables, R squared = 0.4399 showed a weak or low effect size.
Due to the lack of data for the six GCC countries, this study included only four countries from the periods of 2001 to 2020. As some of the financial factors used in this study are relatively new in the GCC countries, they may have influenced the outcome of the study. However, 0.43% for new and rising factors in finance and energy efficiency can be considered a good lead.
Which may be an opportunity for future studies to test the relationship between financial and energy efficiency tools on what factors can enhance each sector and economic growth. The Impact of Renewable Energy Consumption and Financial Development on CO2 Emissions and Economic Growth in the MENA Region: A Panel Vector Autoregressive (PVAR) Analysis.
Discussion 35
Conclusion and recommendations 35
Recommendation for future research 36
As the GCC countries continue to grow, the aspect of financial technology and efficiency, it may take a few years to identify an effect of these variables on each other. Finally, more financial and energy efficient variables can be considered for future studies. Central banking and the infrastructural power of finance: the case of ECB support for repo and securitization markets.
