Resources for Quantitative Economics

It's become increasingly hard, in pursuing something like quantitative economics, to delineate the boundaries of where economics/econometrics, statistics, and computer science all begin and end; this is of course because there is no clear line to draw. Econometrics today requires the use software tools that can require the same understanding of code and syntax as one would find in computer science. Similarly, computing power and software tools have allowed the analysis of larger and larger datasets, which themselves are improved by the same data and algorithms concepts that are found in technology and computer science.

This is all in addition to the longterm trend of the mathematization of economics in general, where one would be hard-pressed to get through even an undergraduate training without being comfortable with calculus, matrix algebra, and statistics.

In that spirit, this page contains a (by-no-means conclusive) list of resources that could be helpful to any incoming economics students in their studies.

Supplementary Learning Material to Strengthen Your Foundation

  1. The Command Line Crash Course
  2. CS 50

Crash Course in Quantitative Skills:

  1. UToronto's Mathematical Methods for Economic Theory: A Tutorial
  2. Learn SQL The Hardway
  3. Learn Python the Hardway
  4. Swirl Stats: Learn R, in R
  5. Fuqua School of Business Forecasting Notes by Robert Nau
  6. Computational Statistics in Python

General Learning Sites

Some Good Economics Blogs

Non Economics Related Sites

These are a few of my favorite things on the internet: