Resources

This page lists resources and links to outside miscellaneous materials which I found helpful for doing research or programming. 

Programming (Mostly in R)

1. Principles of Econometrics with R

2. Supervised Machine Learning for Text Analysis in R

3. Keyboard Shortcuts in the RStudio IDE

4. Eikon Data API for Python

5. A Comprehensive Collection of R Packages on DID (e.g. TWFE/Goodman-Bacon (2021)/Sun and Abraham (2020)/Callaway and Sant’Anna (2021))  

6. Machine Learning for Factor Investing

7. Include ChatGPT in RStudio 

8. Algorithm for AI-Generated Content Detection (e.g. GPTZero/detect-gpt/ZeroGPT)

Public Data (Useful for Empirical Studies)

1. Data on Coronavirus from Our World in Data 

2. Crowdsourced International Air Trafic Data from OpenSky Network

3. Firm-Level Climate Change Exposure

4. International Comparative Competition Law

5. Text-based Network Industry Classification from Hoberg-Phillips Data Library

6. Open Source Asset Pricing

7. Global Factor Data

8. Common Ownership Data (Backus, Conlon, and Sinkinson 2020)

9. Economic Policy Uncertainty 

10. Financial and Macroeconomic Connectedness 

11. Comprehensive Corporate Ownership Data

12. Financial Disclosure by United States House of Representatives 

13. Financial Disclosure by United States Senate  

14. Toxics Release Inventory (TRI) Program

15. Uppsala Conflict Data Program 

16. Perceived Cost of Capital and Corporate Discount Rates