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Retail Gasoline Price Cycles: Evidence from Guelph, Ontario Using Bi-Hourly, Station-Specific Retail Price Data

Benjamin Atkinson

Year: 2009
Volume: Volume 30
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No1-4
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Abstract:
This paper uses prices that were directly observed at 27 gasoline stations in Guelph, Ontario, eight times per day for 103 days in late-2005, to examine several basic predictions of a theory of price cycles. It is found that price movements in Guelph are more consistent with the Edgeworth cycle theory than with other dynamic pricing theories. The data also identify some interesting (and somewhat systematic) pricing patterns that have not been identified in previous studies, and which would likely be overlooked with less complete data. These findings are not only of interest to applied economists and policymakers, but also to theoreticians who are interested in refining the theory to make more accurate predictions.



Intra-day Electricity Demand and Temperature

James McCulloch and Katja Ignatieva

Year: 2020
Volume: Volume 41
Number: Number 3
DOI: 10.5547/01956574.41.3.jmcc
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Abstract:
The objective of this paper is to explain the relationship between high frequency electricity demand, intra-day temperature variation and time. Using the Generalised Additive Model (GAM) framework we link high frequency (5-minute) aggregate electricity demand in Australia to the time of the day, time of the year and intra-day temperature. We document a strong relationship between high frequency electricity demand and intra-day temperature. We show a superior model fit when using Daylight Saving Time (DST), or clock time, instead of the standard (solar) time. We introduce the time weighted temperature model that captures instantaneous electricity demand sensitivity to temperature as a function of the human daily activity cycle, by assigning different temperature signal weighting based on the DST time. The results on DST and time weighted temperature modelling are novel in the literature and are important innovations in high frequency electricity demand forecasting.





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