This project is a community collaboration project between Western University and City Studio London, the focus of the project is to analyze the impacts of COVID-19 on marginalized populations in London, specifically the immigrants and the Indigenous populations. In this direction, I chose to dive deeper into their labour market performance since there have been researches published stating that in Canada, the economically disadvantaged population suffer more from COVID-19 (such as a higher unemployment rate) compared to the others. I would like to conduct a similar analysis in London Ontario to further analyze if this holds true in smaller municipalities too.

The data used in this project are directly obtained from Statistics Canada’s open source data tables, some simple data cleaning and pre-processing are performed before analysis, such as removing null values and unifying the units of measure. The main analysis performed are exploratory data visualization, aiming to identify patterns and/or abnormalities. Once a pattern is identified, further analysis will be conducted using both relevant event information and other data sources.

In the analysis, my teammate and I built a simple mathematical model attempt to estimate the monthly employment rate by industry in London. Due to the lack of local disaggregated data, this information was publicly available only to the provincial level and a few metropolitan areas. Please refer to the report for detailed derivation.

The research found that there is a differentiated impact in terms of employment for immigrants and Indigenous populations in London, as they are most represented in industries that are heavily impacted by COVID-19, such as hospitality services and retail. The findings are presented in report form and reported as a presentation to the City Studio staff, please find both the report and slides in the repo.

This is the first comprehensive research I have conducted back in 2020, looking back at it, the data analysis can definitely be improved using R or Python. I think one day I will come back to it and improve on the analysis.

Thank you, hope some of the analysis could be helpful to you :)