Create a measure of all firms exposed to Covid-19 (Python代写,Machine Learning代写,matplotlib代写,澳洲程序代写)

Your second option is to go find a dataset and build it. You will be judged on whether you competently assemble a database. Please pick a dataset, and explain in a paragraph or two what the potential economic applications of the dataset is. Make sure to answer the following:

• What is the unit of observation of the data?
• What is the purpose of the measure, is it meant to replace an existing measure we have already, or something we cannot measure? What is the application, does it fit into a regression model?
• What are the advantages and disadvantages of the measure relative to existing measures we already have? o Do we have the population or the sample? o Is there a selection bias in the data? A survivorship bias?
• Is there any academic research surrounding the use of this data?

Then, construct the database. Please list all of the tables you create, draw a diagram explaining how these tables connect. Provide me summary statistics that describe quantities in the data. For example, if you decide to put together patents, please tell me how many patents there are?

What would be the extra mile is starting to use the data to tell me something interesting about what’s happening in the world today.

Scrape SEC filings or Hong Kong company filings**

• There are many packages in R and Python to scrape SEC filings o They should be relatively easy to get for Hong Kong as well
• Examples of applications o Create a measure of all firms exposed to Covid-19. Summarize how often, which industries, etc. How many firms mention the Corona virus, Covid-19 or other related terms? What other words do they mention alongside Covid-19? ▪ For example of how to do this, you may try to replicate the measures from firmlevelrisk.com