Modelling how much extra motorists pay on the road? A cross-sectional study of profit margins of unleaded petrol in Australia

Valadkhani, Abbas; Babacan, Alperhan

doi:10.1016/j.enpol.2014.02.010

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…In this study, hierarchical cluster analysis was performed to check the robustness of the results of the K-means model following Valadkhani et al [29]. The hierarchical clustering algorithm divides objects into groups with similar characteristics that are distinct from each other.…”

Section: Hierarchical Clustering Methodsmentioning

confidence: 99%

“…For instance, Van Meerbeeck [5] and Yilmazkuday and Yilmazkuday [23] found a negative relation between station density and petrol prices. Moreover, Valadkhani and Babacan [29] found that the station density had a negative effect on the variations in the gross margin series in Australia.…”

Section: Kruskal-wallis Rank Sum Testmentioning

confidence: 98%

“…To achieve this, the study used cluster analysis as the best method for grouping cities by their characteristics. Cluster analysis is mostly applied to market segmentation [29]. It lets us create clusters of cities with similar geographic, economic, and demographic features, as well as the same petrol prices [30].…”

Section: Cluster Analysismentioning

confidence: 99%

“…Caltex Australia, for example, measured that the cost of delivery was typically 1.5 to 3.0 CPL higher in regional areas than in capital cities [50]. Pennerstorfer [18] found that distance (a proxy for distribution cost) did not significantly influence petrol prices in Austria, while Valadkhani and Babacan [29] found that the distance between the wholesaler and retailer had a significant positive impact on variations in cross-sectional margins.…”

Section: Supply-side Factorsmentioning

confidence: 99%

“…The daily wholesale petrol prices were obtained from FuelWatch beginning on 1 January 2017 and ending on 31 August 2018. Following Valadkhani and Babacan [29], the distance between retailers and wholesalers was considered a proxy for the transport cost. It was assumed that petrol stations in each city purchased petrol from their nearest wholesaler; therefore, we matched the retail prices of petrol in each city to their nearest wholesalers based on the distance.…”

Section: Datamentioning

confidence: 99%

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What Drives Petrol Price Dispersion across Australian Cities?

Ghazanfari

2022

Energies

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Petrol directly impacts the ability of and extent to which households can engage in day-to-day activities and ultimately directly influences the aggregate economic activity. Petrol price increases can lead to major economic disruption, especially among the most vulnerable, such as low-income families. In Australia, petrol prices differ substantially between metropolitan and regional areas, and regional drivers must pay more for purchasing petrol than those in capital cities. This research explored why retail petrol prices vary from one city to another within and between Australian regions. In this study, clustering methods and panel models will be used to identify factors that cause price differences. The findings revealed that a considerable part of the price differences arose from specific characteristics of cities that influence the demand and supply of petrol, thereby causing variations in price decisions. Petrol prices were substantially influenced by wholesale petrol prices, oil prices, petrol and diesel vehicles, population density, station density, and public transport accessibility. These factors are the main determinants that contribute significantly to price variations between Australian cities. The findings provide critical information for economic agents that interact in this market. From a social welfare perspective, government authorities can consider these factors to improve living standards and consumers’ welfare under price pressure in regional cities.

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Section: Hierarchical Clustering Methodsmentioning

confidence: 99%