Positions Available: 3 students

Brief Description: The reason for wide variations in the prices of retail gasoline is one of the most widely debated issues in Canada. This focus of this research project is to study the patterns in retail gas price variations in Canada, with a special focus in Alberta. In particular, this project will examine the following key issues, among others: (1) What were the effects of the introduction and removal of the provincial carbon tax on retail gas prices in Alberta (2) Are there certain differences in the trends in retail gasoline price across various Canadian cities and provinces? (3) Are retail gas prices higher typically higher in certain days of the week, and is there a “weekend effect” in the sense that that the retail prices are higher during the weekends compared to the weekdays?

Methods:

This project involves extensive secondary data gathering, cleaning and analysis. We would like to have the student work as a part-timer during fall and winter semester as well since some work needs to be done at that time, especially data collection and preparation.

Secondary data on daily retail and wholesale gasoline prices will be collected from different sources. Principal sources will be Natural Resource Canada, Statistics Canada, Kent Group Limited (https://www.kentgroupltd.com/), GasBuddy (https://www.gasbuddy.com/ ) and some other daily retail gasoline tracking websites.

The principal daily gasoline data source people use is the Kent Group Limited, which posts daily price data on its website. However, this data set lacks information on weekends and statutory holidays, which makes the data set less usable than ideal. And it is for this reason, we plan to hire student Research Assistant to collect and record data from Gasbuddy daily including weekends so that we can calibrate the data and make it continuous.

One important positive side is that the data can be obtained from these sources with no expenses. The only thing we still do not know is whether Gasbuddy keeps weekend data and we can access those. However, irrespective of that, data reported in these sources are often not in the same form. This requires substantial effort to convert different data to a common spreadsheet software [we plan to compile all in Excel]. These data will need to be transformed, corroborated, and synthesized to create a set of consistent workable data for analytical purposes. This is where the students we intend to hire as a research assistant is expected to be highly valuable.

Data reported in these sources are not in the same form or format, neither all are in spreadsheets. This requires substantial effort to convert to a common spreadsheet software [we plan to compile all in MS-Excel]. In addition, they are not in the same units nor are in the same variables nor have the same characteristics. These data will need to be transformed, corroborated, and synthesized to create a set of consistent workable data for analytical purposes.

The other major component is to review literature, prepare a bibliography, write a review on methods, procedures, and results.

Plan of Division of Student Work Hours:

· Data downloading from internet: 40 hours

· Data manipulation, cleaning, transformation: 40 hours

· Preparation of working data file in MS Excel: 40 hours

· Data tabulation and graphing in MS Excel – 50 hours

· Library search and bibliography – 30 hours

· Literature review – 40 hours

The students will be working under the guidance of Subhadip Ghosh