Learning

Economics and Data Analysis

• Econometrics and Statistics
  • Introduction to Econometrics with R - A comprehensive guide to econometrics using R
  • Mostly Harmless Econometrics - Angrist and Pischke’s practical guide to causal inference
  • Causal Inference: The Mixtape - Scott Cunningham’s guide to causal inference
• Programming for Economics
  • Python for Economists - Quantitative Economics with Python
  • R for Data Science - Hadley Wickham’s guide to data science with R
  • Stata Tutorials - Official Stata learning resources

Research Methods

• Academic Writing
  • Writing Tips for PhD Students - John Cochrane’s writing advice
  • How to Write a Thesis - Raul Pacheco-Vega’s comprehensive guide
  • The Craft of Research - Booth, Colomb, and Williams
• Research Design
  • Field Experiments - J-PAL’s guide to field experiments
  • Natural Experiments - Angrist and Krueger’s paper on natural experiments
  • Survey Design - Pew Research Center’s survey methodology

Online Courses

• Economics
  • MIT OpenCourseWare - Economics
  • Coursera - Econometrics
  • edX - Development Economics
• Data Science
  • DataCamp - Interactive R and Python courses
  • Kaggle Learn - Practical data science tutorials
  • Fast.ai - Practical deep learning

Tools and Resources

• Data Visualization
  • The R Graph Gallery
  • Python Graph Gallery
  • Data Visualization Catalogue
• Research Tools
  • Zotero - Reference management
  • Overleaf - Online LaTeX editor
  • GitHub - Version control and collaboration

Learning Communities

• Economics Stack Exchange
• Cross Validated - Statistics Q&A
• Stack Overflow - Programming Q&A

My Learning Journey

I maintain notes and reflections on my learning process. If you’re interested in any particular topic or have suggestions for resources, feel free to contact me.