Unlocking Sustainable Commuting: Exploring the Nexus of Macroeconomic Factors, Environmental Impact, and Daily Travel Patterns

Abstract

This paper examines normality in time series econometrics for a sustainable energy transition. By analysing data from January 1997 to December 2021, this study integrates macroeconomic, environmental, and energy data to gain insights into the potential changes in daily commuting patterns among Slovenians. Various methods, including unit root tests such as the augmented Dickey–Fuller (ADF), Kwiatkowski–Phillips–Schmidt–Shin (KPSS), and Zivot–Andrews (Z-A), as well as other tests, are employed. Additionally, the vector autoregressive (VAR) model, Granger Causality and regression analysis determine the impact. This paper contributes to uncovering valuable information within data from macrovariables using macroeconometric techniques. It also provides insights that can support evidence-based decision-making for sustainable energy transition policies in Slovenia. The results of the normality tests indicate that most macro variables are integrated; there is a need for a careful analysis of integration levels and appropriate testing methods. These findings have implications for policymakers, researchers, and practitioners in economics, the environment, and energy supply. At the same time, this research highlights that gross domestic product, unemployment, inflation, and carbon dioxide positively impact car usage among Slovenians, while gasoline prices and commuters have a negative one. While the recently investigated development of sustainable commuting does not work, the study highlights an innovation: the connection of time series econometrics, which offers a better understanding of future commuting patterns on energy consumption and their causalities.

Keywords

• case study
• commuting
• energy-saving
• environmental impact
• VAR model