Group presentation, your presentation should be around 20-30min total and be handed in with all accompanying code to reproduce your results.
You are tasked with estimating the Cost of the COVID Pandemic. The question is framed in the following way: If the COVID pandemic didn't happen, how much better off would be we now?
You should measure the impact on one to three of a few relevant metrics. These can be economic metrics (loss in GDP, employment/unemlpoyment, consumer spending, income inequality, wealth inequality, etc.) or human metrics (population, deaths, quality-adjusted life-years, humand development index, etc.)
Note that it's impossible to be precise with this sort of question. However, you can get an estimate of the order of magnitude. For instance, if you are measuring the loss in GDP, is it in hundreds of billions, trillions or tens of trillions?
Required parts for this project includes:
- Finding your own data
- A critical literature review
- Data visualizations for important arguments
- At least one statistical test supporting one argument you're making
One rule: No arguments without data or a citation. If you're making a point, it needs to be supported by either data or real research (not some random webpage's clickbait article).
Beyond that, I encourage you to be creative!
You are responsible to find your own datasets. You can (and should!) use open economic data like the one from FRED or the world bank (if they are updated quickly enough to have recent data).
Open COVID data can be found in places like this dataset.
You need a literature review for your presentation. This can be related topics (eg. economic cost of crises in the past) or directly related (COVID health and economic research). You need at least 5 papers cited and reviewed.
This literature should be CRITICAL, if you see bad research it's better to include it and show why you think it's bad.
Similarly, if you cite bad research without questioning its methods, you can expect me to poke holes into your literature review during your presentation.
Important arguments based on data should have supporting data visualizations explaining your argument. Make them pretty!
Just so we're responsible, at least one of your arguments should have a statistical test.
I won't be as strict on this one as on others because of the speculative and difficulty of being precise in this project.