A Robust Regression Analysis of Factors Affecting Diesel and Petrol Price

Abstract

Introduction: A lot of factors influence how much crude oil and gasoline prices fluctuate. Various crises, including war and political unrest, the economic and financial crisis, terrorist actions, and natural catastrophes, have had a significant impact on crude oil and gas prices throughout the last several decades. The robust regression analysis approach is beneficial for investigating the influence of the explanatory variable’s diesel and petrol prices. Statistics reveal that some variables, events, and crises have a significant impact on diesel and gasoline prices. To reject the least significant components and proceed to additional regression analysis on the most impacted variables to minimize the number of variables, the ordinary least squares approach was used. The study model explains how these components interact and aids in price forecasting to assist the economy and avoid undesirable scenarios.

Objectives: To identify and understand the key factors influencing the fluctuations in diesel and petrol prices, including supply and demand, crude oil prices, government taxes, and currency exchange rates. To analyse historical and current trends in diesel and petrol prices, enabling predictions about future price movements.

Methods: Robust Regression Analysis for Identify relationships between fuel prices and influencing factors and Correlation Analysis for Measure the degree to which two or more variables. The Trend Charts to use line graphs or bar charts to visualize price changes over time and Forecasting Models to use machine learning algorithms to predict future fuel prices based on historical data.

Results: The following 19 years of gasoline and diesel prices in India served as the foundation for the research project "Forecasting Model for Petrol and Diesel Price" (December 2001–December 2019). To achieve its objectives, this study evaluated secondary data gathered from multiple secondary sources and used a variety of statistical approaches, including trend analysis, regression analysis, and one-way ANOVA. Gasoline shortages are likely to remain, denying fuel to those in most need at any costs, while wealthy countries compete for limited supply.

Conclusions: In summary, the prices of natural gas and crude oil have fluctuated throughout time and will continue to do so. Natural gas and crude oil prices are influenced by a variety of variables, including large environmental disasters, the status of the economy, and the adoption of new technologies. The multiple regression establishes a predictive relationship between variables for both dependent and independent variables. Using data and historical records, the multiple regression technique found and indicated a link between factors that significantly influenced natural gas and crude oil prices.